cytoBandIdeo Chromosome Band (Ideogram) Chromosome Bands Based On ISCN Lengths (for Ideogram) Mapping and Sequencing 
gap Gap Gap Locations Mapping and Sequencing Description This track depicts gaps in the assembly. These gaps - with the exception of intractable heterochromatic gaps - will be closed during the finishing process. Gaps are represented as black boxes in this track. If the relative order and orientation of the contigs on either side of the gap is known, it is a bridged gap and a white line is drawn through the black box representing the gap. This assembly contains the following principal types of gaps: Fragment - gaps between the contigs of a draft clone. (In this context, a contig is a set of overlapping sequence reads.) These are represented by varying numbers of Ns in the assembly. Clone - gaps between bactigs. These are represented by 50,000 Ns in the assembly. 
knownGene Known Genes UCSC Known Genes Based on UniProt, RefSeq, and GenBank mRNA Genes and Gene Predictions Description The UCSC Known Genes track shows known protein-coding genes based on protein data from UniProt (SWISS-PROT and TrEMBL) and mRNA data from the NCBI reference sequences collection (RefSeq) and GenBank. Each Known Gene is represented by an mRNA and a protein. Display Conventions and Configuration This track follows the display conventions for gene prediction tracks with the following color scheme: Black: indicates the gene has a corresponding entry in the Protein Databank (PDB). Dark Blue: indicates the gene has either a corresponding RefSeq mRNA that is "Reviewed" or "Validated" or a corresponding Swiss-Prot protein. Medium Blue: indicates the gene has a corresponding RefSeq mRNA that is not "Reviewed" nor "Validated". Light Blue: everything else. That is, the gene does not have a corresponding Protein Databank entry, RefSeq mRNA, or Swiss-Prot protein, but it has supporting evidence of a GenBank mRNA with a UniProt (TrEMBL) protein. This track contains an optional codon coloring feature that allows users to quickly validate and compare gene predictions. To display codon colors, select the genomic codons option from the Color track by codons pull-down menu. Click here for more information about this feature. Methods This release of UCSC Known Genes was built by a new process, KG II, as described below. UniProt protein sequences (including alternative splicing isoforms) and mRNA sequences from RefSeq and GenBank were aligned against the base genome using BLAT. RefSeq alignments having a base identity level within 0.1% of the best and at least 96% base identity with the genomic sequence were kept. GenBank mRNA alignments having a base identity level within 0.2% of the best and at least 97% base identity with the genomic sequence were kept. Protein alignments having a base identity level within 0.2% of the best and at least 80% base identity with the genomic sequence were kept. Then the genomic mRNA and protein alignments were compared, and protein-mRNA pairings were determined from their overlaps. mRNA CDS data were obtained from RefSeq and GenBank data and supplemented by CDS structures derived from UCSC protein-mRNA BLAT alignments. The initial set of UCSC Known Genes candidates consists of all protein-mRNA pairs with valid mRNA CDS structures. A gene-check program (similar to the one used for the Consensus CDS (CCDS) project) is used to remove questionable candidates, such as those with in-frame stop codons, missing start or stop codons, etc. From each group of gene candidates that share the same CDS structure, the protein-mRNA pair having the best ranking and protein-mRNA alignment score is selected as a UCSC Known Gene. The ranking of a gene candidate depends on its gene-check quality measures. When all else is equal, a preference is given to RefSeq mRNAs and next to MGC mRNAs. Similarly a preference is given to gene candidates represented by Swiss-Prot proteins. The protein-mRNA alignment score is calculated based on protein to mRNA alignment using TBLASTN, plus weighted sub-scores according to the date and length of the mRNA. Credits The UCSC Known Genes track was produced using protein data from UniProt and mRNA data from NCBI RefSeq and GenBank. Data Use Restrictions The UniProt data have the following terms of use, UniProt copyright(c) 2002 - 2004 UniProt consortium: For non-commercial use, all databases and documents in the UniProt FTP directory may be copied and redistributed freely, without advance permission, provided that this copyright statement is reproduced with each copy. For commercial use, all databases and documents in the UniProt FTP directory except the files ftp://ftp.uniprot.org/pub/databases/uniprot/knowledgebase/uniprot_sprot.dat.gz ftp://ftp.uniprot.org/pub/databases/uniprot/knowledgebase/uniprot_sprot.xml.gz may be copied and redistributed freely, without advance permission, provided that this copyright statement is reproduced with each copy. More information for commercial users can be found here. From January 1, 2005, all databases and documents in the UniProt FTP directory may be copied and redistributed freely by all entities, without advance permission, provided that this copyright statement is reproduced with each copy. References Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Wheeler DL. GenBank: update. Nucleic Acids Res. 2004 Jan 1;32(Database issue):D23-6. PMID: 14681350; PMC: PMC308779 Hsu F, Kent WJ, Clawson H, Kuhn RM, Diekhans M, Haussler D. The UCSC Known Genes. Bioinformatics. 2006 May 1;22(9):1036-46. PMID: 16500937 Kent WJ. BLAT - the BLAST-like alignment tool. Genome Res. 2002 Apr;12(4):656-64. PMID: 11932250; PMC: PMC187518 
mrna Rat mRNAs Rat mRNAs from GenBank mRNA and EST Description The mRNA track shows alignments between rat mRNAs in GenBank and the genome. Display Conventions and Configuration This track follows the display conventions for PSL alignment tracks. In dense display mode, the items that are more darkly shaded indicate matches of better quality. The description page for this track has a filter that can be used to change the display mode, alter the color, and include/exclude a subset of items within the track. This may be helpful when many items are shown in the track display, especially when only some are relevant to the current task. To use the filter: Type a term in one or more of the text boxes to filter the mRNA display. For example, to apply the filter to all mRNAs expressed in a specific organ, type the name of the organ in the tissue box. To view the list of valid terms for each text box, consult the table in the Table Browser that corresponds to the factor on which you wish to filter. For example, the "tissue" table contains all the types of tissues that can be entered into the tissue text box. Multiple terms may be entered at once, separated by a space. Wildcards may also be used in the filter. If filtering on more than one value, choose the desired combination logic. If "and" is selected, only mRNAs that match all filter criteria will be highlighted. If "or" is selected, mRNAs that match any one of the filter criteria will be highlighted. Choose the color or display characteristic that should be used to highlight or include/exclude the filtered items. If "exclude" is chosen, the browser will not display mRNAs that match the filter criteria. If "include" is selected, the browser will display only those mRNAs that match the filter criteria. This track may also be configured to display codon coloring, a feature that allows the user to quickly compare mRNAs against the genomic sequence. For more information about this option, go to the Codon and Base Coloring for Alignment Tracks page. Several types of alignment gap may also be colored; for more information, go to the Alignment Insertion/Deletion Display Options page. Methods GenBank rat mRNAs were aligned against the genome using the blat program. When a single mRNA aligned in multiple places, the alignment having the highest base identity was found. Only alignments having a base identity level within 0.5% of the best and at least 96% base identity with the genomic sequence were kept. Credits The mRNA track was produced at UCSC from mRNA sequence data submitted to the international public sequence databases by scientists worldwide. References Benson DA, Cavanaugh M, Clark K, Karsch-Mizrachi I, Lipman DJ, Ostell J, Sayers EW. GenBank. Nucleic Acids Res. 2013 Jan;41(Database issue):D36-42. PMID: 23193287; PMC: PMC3531190 Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Wheeler DL. GenBank: update. Nucleic Acids Res. 2004 Jan 1;32(Database issue):D23-6. PMID: 14681350; PMC: PMC308779 Kent WJ. BLAT - the BLAST-like alignment tool. Genome Res. 2002 Apr;12(4):656-64. PMID: 11932250; PMC: PMC187518 
rmsk RepeatMasker Repeating Elements by RepeatMasker Variation and Repeats Description This track was created by using Arian Smit's RepeatMasker program, which screens DNA sequences for interspersed repeats and low complexity DNA sequences. The program outputs a detailed annotation of the repeats that are present in the query sequence (represented by this track), as well as a modified version of the query sequence in which all the annotated repeats have been masked (generally available on the Downloads page). RepeatMasker uses the Repbase Update library of repeats from the Genetic Information Research Institute (GIRI). Repbase Update is described in Jurka (2000) in the References section below. Some newer assemblies have been made with Dfam, not Repbase. You can find the details for how we make our database data here in our "makeDb/doc/" directory. Display Conventions and Configuration In full display mode, this track displays up to ten different classes of repeats: Short interspersed nuclear elements (SINE), which include ALUs Long interspersed nuclear elements (LINE) Long terminal repeat elements (LTR), which include retroposons DNA repeat elements (DNA) Simple repeats (micro-satellites) Low complexity repeats Satellite repeats RNA repeats (including RNA, tRNA, rRNA, snRNA, scRNA, srpRNA) Other repeats, which includes class RC (Rolling Circle) Unknown The level of color shading in the graphical display reflects the amount of base mismatch, base deletion, and base insertion associated with a repeat element. The higher the combined number of these, the lighter the shading. A "?" at the end of the "Family" or "Class" (for example, DNA?) signifies that the curator was unsure of the classification. At some point in the future, either the "?" will be removed or the classification will be changed. Methods Data are generated using the RepeatMasker -s flag. Additional flags may be used for certain organisms. Repeats are soft-masked. Alignments may extend through repeats, but are not permitted to initiate in them. See the FAQ for more information. Credits Thanks to Arian Smit, Robert Hubley and GIRI for providing the tools and repeat libraries used to generate this track. References Smit AFA, Hubley R, Green P. RepeatMasker Open-3.0. http://www.repeatmasker.org. 1996-2010. Repbase Update is described in: Jurka J. Repbase Update: a database and an electronic journal of repetitive elements. Trends Genet. 2000 Sep;16(9):418-420. PMID: 10973072 For a discussion of repeats in mammalian genomes, see: Smit AF. Interspersed repeats and other mementos of transposable elements in mammalian genomes. Curr Opin Genet Dev. 1999 Dec;9(6):657-63. PMID: 10607616 Smit AF. The origin of interspersed repeats in the human genome. Curr Opin Genet Dev. 1996 Dec;6(6):743-8. PMID: 8994846 
softberryGene Fgenesh++ Genes Fgenesh++ Gene Predictions Genes and Gene Predictions Description Fgenesh++ predictions are based on Softberry's gene-finding software. Methods Fgenesh++ uses both hidden Markov models (HMMs) and protein similarity to find genes in a completely automated manner. For more information, see Solovyev, V.V. (2001) in the References section below. Credits The Fgenesh++ gene predictions were produced by Softberry Inc. Commercial use of these predictions is restricted to viewing in this browser. Please contact Softberry Inc. to make arrangements for further commercial access. References Solovyev, V.V. "Statistical approaches in Eukaryotic gene prediction" in the Handbook of Statistical Genetics (ed. Balding, D. et al.), 83-127. John Wiley & Sons, Ltd. (2001). 
intronEst Spliced ESTs Rat ESTs That Have Been Spliced mRNA and EST Description This track shows alignments between rat expressed sequence tags (ESTs) in GenBank and the genome that show signs of splicing when aligned against the genome. ESTs are single-read sequences, typically about 500 bases in length, that usually represent fragments of transcribed genes. To be considered spliced, an EST must show evidence of at least one canonical intron (i.e., the genomic sequence between EST alignment blocks must be at least 32 bases in length and have GT/AG ends). By requiring splicing, the level of contamination in the EST databases is drastically reduced at the expense of eliminating many genuine 3' ESTs. For a display of all ESTs (including unspliced), see the rat EST track. Display Conventions and Configuration This track follows the display conventions for PSL alignment tracks. In dense display mode, darker shading indicates a larger number of aligned ESTs. The strand information (+/-) indicates the direction of the match between the EST and the matching genomic sequence. It bears no relationship to the direction of transcription of the RNA with which it might be associated. The description page for this track has a filter that can be used to change the display mode, alter the color, and include/exclude a subset of items within the track. This may be helpful when many items are shown in the track display, especially when only some are relevant to the current task. To use the filter: Type a term in one or more of the text boxes to filter the EST display. For example, to apply the filter to all ESTs expressed in a specific organ, type the name of the organ in the tissue box. To view the list of valid terms for each text box, consult the table in the Table Browser that corresponds to the factor on which you wish to filter. For example, the "tissue" table contains all the types of tissues that can be entered into the tissue text box. Multiple terms may be entered at once, separated by a space. Wildcards may also be used in the filter. If filtering on more than one value, choose the desired combination logic. If "and" is selected, only ESTs that match all filter criteria will be highlighted. If "or" is selected, ESTs that match any one of the filter criteria will be highlighted. Choose the color or display characteristic that should be used to highlight or include/exclude the filtered items. If "exclude" is chosen, the browser will not display ESTs that match the filter criteria. If "include" is selected, the browser will display only those ESTs that match the filter criteria. This track may also be configured to display base labeling, a feature that allows the user to display all bases in the aligning sequence or only those that differ from the genomic sequence. For more information about this option, go to the Base Coloring for Alignment Tracks page. Several types of alignment gap may also be colored; for more information, go to the Alignment Insertion/Deletion Display Options page. Methods To make an EST, RNA is isolated from cells and reverse transcribed into cDNA. Typically, the cDNA is cloned into a plasmid vector and a read is taken from the 5' and/or 3' primer. For most — but not all — ESTs, the reverse transcription is primed by an oligo-dT, which hybridizes with the poly-A tail of mature mRNA. The reverse transcriptase may or may not make it to the 5' end of the mRNA, which may or may not be degraded. In general, the 3' ESTs mark the end of transcription reasonably well, but the 5' ESTs may end at any point within the transcript. Some of the newer cap-selected libraries cover transcription start reasonably well. Before the cap-selection techniques emerged, some projects used random rather than poly-A priming in an attempt to retrieve sequence distant from the 3' end. These projects were successful at this, but as a side effect also deposited sequences from unprocessed mRNA and perhaps even genomic sequences into the EST databases. Even outside of the random-primed projects, there is a degree of non-mRNA contamination. Because of this, a single unspliced EST should be viewed with considerable skepticism. To generate this track, rat ESTs from GenBank were aligned against the genome using blat. Note that the maximum intron length allowed by blat is 750,000 bases, which may eliminate some ESTs with very long introns that might otherwise align. When a single EST aligned in multiple places, the alignment having the highest base identity was identified. Only alignments having a base identity level within 0.5% of the best and at least 96% base identity with the genomic sequence are displayed in this track. Credits This track was produced at UCSC from EST sequence data submitted to the international public sequence databases by scientists worldwide. References Benson DA, Cavanaugh M, Clark K, Karsch-Mizrachi I, Lipman DJ, Ostell J, Sayers EW. GenBank. Nucleic Acids Res. 2013 Jan;41(Database issue):D36-42. PMID: 23193287; PMC: PMC3531190 Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Wheeler DL. GenBank: update. Nucleic Acids Res. 2004 Jan 1;32(Database issue):D23-6. PMID: 14681350; PMC: PMC308779 Kent WJ. BLAT - the BLAST-like alignment tool. Genome Res. 2002 Apr;12(4):656-64. PMID: 11932250; PMC: PMC187518 
stsMapRat STS Markers STS Markers on Genetic and Radiation Hybrid Maps Mapping and Sequencing Description This track shows locations of Sequence Tagged Sites (STS) along the rat draft assembly. These markers have been mapped using either genetic (Rat FHH x ACI F2 Intercross Genetic Map, Rat SHRSP x BN F2 Intercross Genetic Map) or radiation hybridization (RH Map 2.2) mapping techniques. Additional data on the individual maps can be found at the following links: NCBI UniSTS (now part of NCBI Probe) Rat Genome Database By default all genetic map markers are shown as blue; only radiation hybrid markers and markers that are neither genetic nor radiation hybrid are shown as black; markers that map to more than one position are shown in lighter colors. Users can choose a color to highlight a subset of markers of interest from the Filter options in STS Markers Track Setting page. Using the Filter The track filter can be used to change the color or include/exclude a set of map data within the track. This is helpful when many items are shown in the track display, especially when only some are relevant to the current task. To use the filter: In the pulldown menu, select the map whose data you would like to highlight or exclude in the display. By default, the "All Genetic" option is selected. Choose the color or display characteristic that will be used to highlight or include/exclude the filtered items. If "exclude" is chosen, the browser will not display data from the map selected in the pulldown list. If "include" is selected, the browser will display only data from the selected map. When you have finished configuring the filter, click the Submit button. 
nscanGene N-SCAN N-SCAN Gene Predictions Genes and Gene Predictions Description This track shows gene predictions using the N-SCAN gene structure prediction software provided by the Computational Genomics Lab at Washington University in St. Louis, MO, USA. Methods N-SCAN combines biological-signal modeling in the target genome sequence along with information from a multiple-genome alignment to generate de novo gene predictions. It extends the TWINSCAN target-informant genome pair to allow for an arbitrary number of informant sequences as well as richer models of sequence evolution. N-SCAN models the phylogenetic relationships between the aligned genome sequences, context-dependent substitution rates, insertions, and deletions. Rat N-SCAN uses human (hg17) as the informant and iterative pseudogene masking. Credits Thanks to Michael Brent's Computational Genomics Group at Washington University St. Louis for providing this data. Special thanks for this implementation of N-SCAN to Aaron Tenney in the Brent lab, and Robert Zimmermann, currently at Max F. Perutz Laboratories in Vienna, Austria. References Gross SS, Brent MR. Using multiple alignments to improve gene prediction. J Comput Biol. 2006 Mar;13(2):379-93. PMID: 16597247 Haas BJ, Delcher AL, Mount SM, Wortman JR, Smith RK Jr, Hannick LI, Maiti R, Ronning CM, Rusch DB, Town CD et al. Improving the Arabidopsis genome annotation using maximal transcript alignment assemblies. Nucleic Acids Res. 2003 Oct 1;31(19):5654-66. PMID: 14500829; PMC: PMC206470 Korf I, Flicek P, Duan D, Brent MR. Integrating genomic homology into gene structure prediction. Bioinformatics. 2001;17 Suppl 1:S140-8. PMID: 11473003 van Baren MJ, Brent MR. Iterative gene prediction and pseudogene removal improves genome annotation. Genome Res. 2006 May;16(5):678-85. PMID: 16651666; PMC: PMC1457044 
xenoRefGene Other RefSeq Non-Rat RefSeq Genes Genes and Gene Predictions Description This track shows known protein-coding and non-protein-coding genes for organisms other than rat, taken from the NCBI RNA reference sequences collection (RefSeq). The data underlying this track are updated weekly. Display Conventions and Configuration This track follows the display conventions for gene prediction tracks. The color shading indicates the level of review the RefSeq record has undergone: predicted (light), provisional (medium), reviewed (dark). The item labels and display colors of features within this track can be configured through the controls at the top of the track description page. Label: By default, items are labeled by gene name. Click the appropriate Label option to display the accession name instead of the gene name, show both the gene and accession names, or turn off the label completely. Codon coloring: This track contains an optional codon coloring feature that allows users to quickly validate and compare gene predictions. To display codon colors, select the genomic codons option from the Color track by codons pull-down menu. For more information about this feature, go to the Coloring Gene Predictions and Annotations by Codon page. Hide non-coding genes: By default, both the protein-coding and non-protein-coding genes are displayed. If you wish to see only the coding genes, click this box. Methods The RNAs were aligned against the rat genome using blat; those with an alignment of less than 15% were discarded. When a single RNA aligned in multiple places, the alignment having the highest base identity was identified. Only alignments having a base identity level within 0.5% of the best and at least 25% base identity with the genomic sequence were kept. Credits This track was produced at UCSC from RNA sequence data generated by scientists worldwide and curated by the NCBI RefSeq project. References Kent WJ. BLAT--the BLAST-like alignment tool. Genome Res. 2002 Apr;12(4):656-64. PMID: 11932250; PMC: PMC187518 Pruitt KD, Brown GR, Hiatt SM, Thibaud-Nissen F, Astashyn A, Ermolaeva O, Farrell CM, Hart J, Landrum MJ, McGarvey KM et al. RefSeq: an update on mammalian reference sequences. Nucleic Acids Res. 2014 Jan;42(Database issue):D756-63. PMID: 24259432; PMC: PMC3965018 Pruitt KD, Tatusova T, Maglott DR. NCBI Reference Sequence (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res. 2005 Jan 1;33(Database issue):D501-4. PMID: 15608248; PMC: PMC539979 
refGene RefSeq Genes RefSeq Genes Genes and Gene Predictions Description The RefSeq Genes track shows known rat protein-coding and non-protein-coding genes taken from the NCBI RNA reference sequences collection (RefSeq). The data underlying this track are updated weekly. Please visit the Feedback for Gene and Reference Sequences (RefSeq) page to make suggestions, submit additions and corrections, or ask for help concerning RefSeq records. For more information on the different gene tracks, see our Genes FAQ. Display Conventions and Configuration This track follows the display conventions for gene prediction tracks. The color shading indicates the level of review the RefSeq record has undergone: predicted (light), provisional (medium), reviewed (dark). The item labels and display colors of features within this track can be configured through the controls at the top of the track description page. Label: By default, items are labeled by gene name. Click the appropriate Label option to display the accession name instead of the gene name, show both the gene and accession names, or turn off the label completely. Codon coloring: This track contains an optional codon coloring feature that allows users to quickly validate and compare gene predictions. To display codon colors, select the genomic codons option from the Color track by codons pull-down menu. For more information about this feature, go to the Coloring Gene Predictions and Annotations by Codon page. Hide non-coding genes: By default, both the protein-coding and non-protein-coding genes are displayed. If you wish to see only the coding genes, click this box. Methods RefSeq RNAs were aligned against the rat genome using BLAT. Those with an alignment of less than 15% were discarded. When a single RNA aligned in multiple places, the alignment having the highest base identity was identified. Only alignments having a base identity level within 0.1% of the best and at least 96% base identity with the genomic sequence were kept. Credits This track was produced at UCSC from RNA sequence data generated by scientists worldwide and curated by the NCBI RefSeq project. References Kent WJ. BLAT - the BLAST-like alignment tool. Genome Res. 2002 Apr;12(4):656-64. PMID: 11932250; PMC: PMC187518 Pruitt KD, Brown GR, Hiatt SM, Thibaud-Nissen F, Astashyn A, Ermolaeva O, Farrell CM, Hart J, Landrum MJ, McGarvey KM et al. RefSeq: an update on mammalian reference sequences. Nucleic Acids Res. 2014 Jan;42(Database issue):D756-63. PMID: 24259432; PMC: PMC3965018 Pruitt KD, Tatusova T, Maglott DR. NCBI Reference Sequence (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res. 2005 Jan 1;33(Database issue):D501-4. PMID: 15608248; PMC: PMC539979 
rgdGene RGD Genes Rat Genome Database Curated Genes Genes and Gene Predictions Description This track shows RefSeq genes curated by the Rat Genome Database (RGD). Coding exons are represented by blocks connected by horizontal lines representing introns. The 5' and 3' untranslated regions (UTRs) are displayed as thinner blocks on the leading and trailing ends of the aligning regions. In full display mode, arrowheads on the connecting intron lines indicate the direction of transcription. Methods The annotation data file, RGD_curated_genes.gff, was downloaded from the RGD website and processed to create this track. Credits Thanks to the RGD for providing this annotation. RGD is funded by grant HL64541 entitled "Rat Genome Database", awarded to Dr. Howard J Jacob, Medical College of Wisconsin, from the National Heart Lung and Blood Institute (NHLBI) of the National Institutes of Health (NIH). 
sgpGene SGP Genes SGP Gene Predictions Using Rat/Human Homology Genes and Gene Predictions Description This track shows gene predictions from the SGP program, developed at the Genome Bioinformatics Laboratory (GBL), which is part of the Grup de Recerca en Informàtica Biomèdica (GRIB) at Institut Municipal d'Investigació Mèdica (IMIM) / Centre de Regulació Genòmica (CRG) in Barcelona. To predict genes in a genomic query, SGP combines geneid predictions with tblastx comparisons of the genomic query against other genomic sequences. Credits Thanks to GRIB for providing these gene predictions. 
ecoresFr1 Fugu Ecores Rat/Fugu Evolutionary Conserved Regions Comparative Genomics Description This track shows Evolutionary Conserved Regions computed by the Exofish program at Genoscope. Each singleton block corresponds to an "ecore"; two blocks connected by a thin line correspond to an "ecotig", a set of colinear ecores in a syntenic region. Methods Genome-wide sequence comparisons were done at the protein-coding level between the genome sequences of rat, Rattus norvegicus, and Fugu (Japanese pufferfish), Takifugu rubripes, to detect evolutionarily conserved regions (ECORES). The sequence versions used in the comparison were Rat (June 2003) and Fugu (August 2002). Credits Thanks to Olivier Jaillon at Genoscope for contributing the data. References Roest Crollius H, Jaillon O, Bernot A, Dasilva C, Bouneau L, Fischer C, Fizames C, Wincker P, Brottier P, Quétier F et al. Estimate of human gene number provided by genome-wide analysis using Tetraodon nigroviridis DNA sequence. Nat Genet. 2000 Jun;25(2):235-8. PMID: 10835645 
ecoresTetraodon Tetraodon Ecores Rat/Tetraodon Evolutionary Conserved Regions Comparative Genomics Description This track shows Evolutionary Conserved Regions computed by the Exofish program at Genoscope. Each singleton block corresponds to an "ecore"; two blocks connected by a thin line correspond to an "ecotig", a set of colinear ecores in a syntenic region. Methods Genome-wide sequence comparisons were done at the protein-coding level between the genome sequences of rat, Rattus norvegicus, and Tetraodon, Tetraodon nigroviridis, to detect evolutionarily conserved regions (ECORES). The sequence versions used in the comparison were Rat (June 2003) and Tetraodon (March 2004). Credits Thanks to Olivier Jaillon at Genoscope for contributing the data. References Roest Crollius H, Jaillon O, Bernot A, Dasilva C, Bouneau L, Fischer C, Fizames C, Wincker P, Brottier P, Quétier F et al. Estimate of human gene number provided by genome-wide analysis using Tetraodon nigroviridis DNA sequence. Nat Genet. 2000 Jun;25(2):235-8. PMID: 10835645 
affyRAE230 Affy RAE230 Alignments of Affymetrix Consensus Sequences from RAE230 Expression and Regulation Description This track shows the location of the consensus sequences used for the selection of probes on the Affymetrix RAE230A and RAE230B chips. Methods Consensus sequences were downloaded from the Affymetrix Product Support and mapped to the genome with blat followed by pslReps using the parameters -minCover=0.3, -minAli=0.95 and -nearTop=0.005. Credits Thanks to Affymetrix for the data underlying this track. 
affyU34A Affy RG-U34A Alignments of Affymetrix Exemplar Sequences from RG-U34A Expression and Regulation Description This track shows the location of the exemplar sequences used for the selection of probes on the Affymetrix RG-U34A chip. Methods Exemplar sequences were downloaded from the Affymetrix Product Support and mapped to the genome with blat followed by pslReps using the parameters -minCover=0.3, -minAli=0.95 and -nearTop=0.005. Credits Thanks to Affymetrix for the data underlying this track. 
gold Assembly Assembly from Fragments Mapping and Sequencing Description This track shows the draft assembly of the rat genome. Instead of a clone-by-clone assembly, the Rat genome assembly is pieced together from Bactig assemblies, which are reassemblies of the reads from sets of overlapping skimmed BAC clones, including mapped whole genome shotgun reads. The assembly process reworks the contigs (splitting some) and selects them under more stringent criteria than are used for the BAC submissions. In dense display mode, this track depicts the path through the draft and finished contigs used to create the assembled sequence. Where gaps exist in the path, spaces are shown between the blocks. 
augustusGene AUGUSTUS AUGUSTUS ab initio gene predictions v3.1 Genes and Gene Predictions Description This track shows ab initio predictions from the program AUGUSTUS (version 3.1). The predictions are based on the genome sequence alone. For more information on the different gene tracks, see our Genes FAQ. Methods Statistical signal models were built for splice sites, branch-point patterns, translation start sites, and the poly-A signal. Furthermore, models were built for the sequence content of protein-coding and non-coding regions as well as for the length distributions of different exon and intron types. Detailed descriptions of most of these different models can be found in Mario Stanke's dissertation. This track shows the most likely gene structure according to a Semi-Markov Conditional Random Field model. Alternative splicing transcripts were obtained with a sampling algorithm (--alternatives-from-sampling=true --sample=100 --minexonintronprob=0.2 --minmeanexonintronprob=0.5 --maxtracks=3 --temperature=2). The different models used by Augustus were trained on a number of different species-specific gene sets, which included 1000-2000 training gene structures. The --species option allows one to choose the species used for training the models. Different training species were used for the --species option when generating these predictions for different groups of assemblies. Assembly Group Training Species Fish zebrafish Birds chicken Human and all other vertebrates human Nematodes caenorhabditis Drosophila fly A. mellifera honeybee1 A. gambiae culex S. cerevisiae saccharomyces This table describes which training species was used for a particular group of assemblies. When available, the closest related training species was used. Credits Thanks to the Stanke lab for providing the AUGUSTUS program. The training for the chicken version was done by Stefanie König and the training for the human and zebrafish versions was done by Mario Stanke. References Stanke M, Diekhans M, Baertsch R, Haussler D. Using native and syntenically mapped cDNA alignments to improve de novo gene finding. Bioinformatics. 2008 Mar 1;24(5):637-44. PMID: 18218656 Stanke M, Waack S. Gene prediction with a hidden Markov model and a new intron submodel. Bioinformatics. 2003 Oct;19 Suppl 2:ii215-25. PMID: 14534192 
bacEndPairs BAC End Pairs BAC End Pairs Mapping and Sequencing Description Bacterial artificial chromosomes (BACs) are a key part of many large-scale sequencing projects. A BAC typically consists of 50 - 300 kb of DNA. During the early phase of a sequencing project, it is common to sequence a single read (approximately 500 bases) off each end of a large number of BACs. Later on in the project, these BAC end reads can be mapped to the genome sequence. This track shows these mappings in cases where both ends could be mapped. These BAC end pairs can be useful for validating the assembly over relatively long ranges. In some cases, the BACs are useful biological reagents. This track can also be used for determining which BAC contains a given gene, useful information for certain wet lab experiments. A valid pair of BAC end sequences must be at least 50 kb but no more than 600 kb away from each other. The orientation of the first BAC end sequence must be "+" and the orientation of the second BAC end sequence must be "-". The scoring scheme used for this annotation assigns 1000 to an alignment when the BAC end pair aligns to only one location in the genome (after filtering). When a BAC end pair or clone aligns to multiple locations, the score is calculated as 1500/(number of alignments). Methods BAC end sequences are placed on the assembled sequence using Jim Kent's blat program. Credits Additional information about the clone, including how it can be obtained, may be found at the NCBI Clone Registry. To view the registry entry for a specific clone, open the details page for the clone and click on its name at the top of the page. 
bactigPos Bactigs Bactigs Mapping and Sequencing Description Instead of clone-by-clone assemblies, the Rat genome assembly is pieced together from Bactig assemblies, which are reassemblies of the reads from sets of overlapping skimmed BAC clones, including mapped whole genome shotgun (WGS) reads. The assembly process reworks the contigs (splitting some) and selects them under more stringent criteria than used for the BAC submissions. Credits Thanks to Paul Havlak at the Baylor College of Medicine Human Genome Sequencing Center for providing the data. 
cytoBand Chromosome Band Chromosome Bands Based On ISCN Lengths Mapping and Sequencing Description The chromosome band track represents the approximate location of bands seen on Giemsa-stained chromosomes under conditions where 400 bands are visible across the entire genome. Methods Data are derived from the ideogram file downloaded from the NCBI ftp site ftp://ftp.ncbi.nih.gov/genomes/R_norvegicus/maps/mapview/. Band lengths are estimated based on relative sizes as defined by the International System for Cytogenetic Nomenclature (ISCN). Credits We would like to thank NCBI for providing this information. 
cpgIsland CpG Islands CpG Islands (Islands < 300 Bases are Light Green) Expression and Regulation Description CpG islands are associated with genes, particularly housekeeping genes, in vertebrates. CpG islands are typically common near transcription start sites, and may be associated with promoter regions. Normally a C (cytosine) base followed immediately by a G (guanine) base (a CpG) is rare in vertebrate DNA because the Cs in such an arrangement tend to be methylated. This methylation helps distinguish the newly synthesized DNA strand from the parent strand, which aids in the final stages of DNA proofreading after duplication. However, over evolutionary time methylated Cs tend to turn into Ts because of spontaneous deamination. The result is that CpGs are relatively rare unless there is selective pressure to keep them or a region is not methylated for some reason, perhaps having to do with the regulation of gene expression. CpG islands are regions where CpGs are present at significantly higher levels than is typical for the genome as a whole. Methods CpG islands are predicted by searching the sequence one base at a time, scoring each dinucleotide (+17 for CG and -1 for others) and identifying maximally scoring segments. Each segment is then evaluated for the following criteria: GC content roughly 50% or greater length greater than 200 ratio greater than 0.6 of observed number of CG dinucleotides to the expected number on the basis of the GC content of the segment The CpG count is the number of CG dinucleotides in the island. The Percentage CpG is the ratio of CpG nucleotide bases (twice the CpG count) to the length. Credits This track was generated using a modification of a program developed by G. Miklem and L. Hillier. 
ECgene ECgene Genes ECgene v1.2 Gene Predictions with Alt-Splicing Genes and Gene Predictions Description ECgene (gene prediction by EST clustering) predicts genes by combining genome-based EST clustering and a transcript assembly procedure in a coherent and consistent fashion. Specifically, ECgene takes alternative splicing events into consideration. The position of splice sites, i.e. exon-intron boundaries, in the genome map is utilized as the critical information in the whole procedure. Sequences that share any splice sites in the genomic alignment are grouped together to define an EST cluster. Transcript assembly, which is based on graph theory, produces gene models and clone evidence, which is essentially identical to sub-clustering according to splice variants. For more detailed information, see the ECgene website. Methods The following is a brief summary of the ECgene algorithm: Genomic alignment of mRNA and ESTs: Input sequences were aligned against the genome using the Blat program developed by Jim Kent. Blat alignments were corrected for valid splice sites, and the SIM4 program was used for suspicious alignments if necessary. Sequences that share more than one splice site were grouped together to define an EST cluster in a similar manner to the genome-based version of the UniGene algorithm. The exon-connectivity in each cluster was represented as a directed acyclic graph (DAG). Distinct paths along exons were obtained by the depth-first-search (DFS) method. They correspond to possible gene models encompassing all alternative splicing events. EST sequences in each cluster were sub-clustered further according to the compatibility of each splice variant with gene structure, and they can be regarded as clone evidence for the corresponding isoform. Gene models without sufficient evidence were discarded at this stage. The presence of polyA tails, detected from careful analysis of genomic alignment of mRNA and EST sequences, was specifically used to determine the gene boundary. Finally, unspliced sequences were added without altering the exon-intron boundaries of existing gene models. Coding potential of gene models: Peptide sequences are only available for those gene models judged to have good coding potential. ORF and CDS are determined based on the number of exons, the ORF length, presence of the start codon (Met), and the CDS length. ORFs (defined as the region between two adjacent stop codons) were classified into four groups: spliced ORFs with Met spliced ORFs without Met single-exon ORFs with Met single-exon ORFs without Met Initially, the first group was searched for the ORF with the longest CDS. Coding sequences were accepted if they were longer than 30 amino acids (93 bp) or they were identical to one of SwissProt proteins excluding fragmented entries. If such an ORF could not be identified in the first group, the other groups were examined sequentially for the presence of an ORF using the same criteria. Genes lacking an apparent ORF were defined as non-coding RNA genes. Credits This algorithm and the predictions for this track were developed by Professor Sanghyuk Lee's Lab of Bioinformatics at Ewha Womans Univeristy, Seoul, KOREA. 
ensGene Ensembl Genes Ensembl Genes Genes and Gene Predictions Description These gene predictions were generated by Ensembl. For more information on the different gene tracks, see our Genes FAQ. Methods For a description of the methods used in Ensembl gene predictions, please refer to Hubbard et al. (2002), also listed in the References section below. Data access Ensembl Gene data can be explored interactively using the Table Browser or the Data Integrator. For local downloads, the genePred format files for rn3 are available in our downloads directory as ensGene.txt.gz or in our genes download directory in GTF format. For programmatic access, the data can be queried from the REST API or directly from our public MySQL servers. Instructions on this method are available on our MySQL help page and on our blog. Previous versions of this track can be found on our archive download server. Credits We would like to thank Ensembl for providing these gene annotations. For more information, please see Ensembl&#39s genome annotation page. References Hubbard T, Barker D, Birney E, Cameron G, Chen Y, Clark L, Cox T, Cuff J, Curwen V, Down T et al. The Ensembl genome database project. Nucleic Acids Res. 2002 Jan 1;30(1):38-41. PMID: 11752248; PMC: PMC99161 
gc5Base GC Percent Percentage GC in 5-Base windows Mapping and Sequencing Description The GC percent track shows the percentage of G (guanine) and C (cytosine) bases in a 5-base windows. High GC content is typically associated with gene-rich areas. This track may be configured in a variety of ways to highlight different aspects of the displayed information. Click the Graph configuration help link for an explanation of the configuration options. Credits The data and presentation of this graph were prepared by Hiram Clawson (&#104;&#105;&#114;a&#109;&#64;&#115;&#111;&#101;.&#117;&#99;&#115;&#99;. &#101;&#100;u). 
geneid Geneid Genes Geneid Gene Predictions Genes and Gene Predictions Description This track shows gene predictions from the geneid program developed by Roderic Guig&oacute;'s Computational Biology of RNA Processing group which is part of the Centre de Regulaci&oacute; Gen&ograve;mica (CRG) in Barcelona, Catalunya, Spain. Methods Geneid is a program to predict genes in anonymous genomic sequences designed with a hierarchical structure. In the first step, splice sites, start and stop codons are predicted and scored along the sequence using Position Weight Arrays (PWAs). Next, exons are built from the sites. Exons are scored as the sum of the scores of the defining sites, plus the the log-likelihood ratio of a Markov Model for coding DNA. Finally, from the set of predicted exons, the gene structure is assembled, maximizing the sum of the scores of the assembled exons. Credits Thanks to Computational Biology of RNA Processing for providing these data. References Blanco E, Parra G, Guig&#243; R. Using geneid to identify genes. Curr Protoc Bioinformatics. 2007 Jun;Chapter 4:Unit 4.3. PMID: 18428791 Parra G, Blanco E, Guig&#243; R. GeneID in Drosophila. Genome Res. 2000 Apr;10(4):511-5. PMID: 10779490; PMC: PMC310871 
genscan Genscan Genes Genscan Gene Predictions Genes and Gene Predictions Description This track shows predictions from the Genscan program written by Chris Burge. The predictions are based on transcriptional, translational and donor/acceptor splicing signals as well as the length and compositional distributions of exons, introns and intergenic regions. For more information on the different gene tracks, see our Genes FAQ. Display Conventions and Configuration This track follows the display conventions for gene prediction tracks. The track description page offers the following filter and configuration options: Color track by codons: Select the genomic codons option to color and label each codon in a zoomed-in display to facilitate validation and comparison of gene predictions. Go to the Coloring Gene Predictions and Annotations by Codon page for more information about this feature. Methods For a description of the Genscan program and the model that underlies it, refer to Burge and Karlin (1997) in the References section below. The splice site models used are described in more detail in Burge (1998) below. Credits Thanks to Chris Burge for providing the Genscan program. References Burge C. Modeling Dependencies in Pre-mRNA Splicing Signals. In: Salzberg S, Searls D, Kasif S, editors. Computational Methods in Molecular Biology. Amsterdam: Elsevier Science; 1998. p. 127-163. Burge C, Karlin S. Prediction of complete gene structures in human genomic DNA. J. Mol. Biol. 1997 Apr 25;268(1):78-94. PMID: 9149143 
gnfAtlas2 GNF Atlas 2 GNF Rat U34A Expression Atlas 2 Expression and Regulation Description This track shows expression data from the GNF Gene Expression Atlas 2. This contains two replicates each of 44 rat tissues run over Affymetrix microarrays. By default, averages of related tissues are shown. Display all tissues by selecting &quot;All Arrays&quot; from the &quot;Combine arrays&quot; menu on the track settings page. As is standard with microarray data red indicates overexpression in the tissue, and green indicates underexpression. You may want to view gene expression with the Gene Sorter as well as the Genome Browser. Credits Thanks to the Genomics Institute of the Novartis Research Foundation (GNF) for the data underlying this track. References Su AI, Wiltshire T, Batalov S, Lapp H, Ching KA, Block D, Zhang J, Soden R, Hayakawa M, Kreiman G et al. A gene atlas of the mouse and human protein-encoding transcriptomes. Proc Natl Acad Sci U S A. 2004 Apr 20;101(16):6062-7. PMID: 15075390; PMC: PMC395923 
mgcFullMrna MGC Genes Mammalian Gene Collection Full ORF mRNAs Genes and Gene Predictions Description This track shows alignments of rat mRNAs from the Mammalian Gene Collection (MGC) having full-length open reading frames (ORFs) to the genome. The goal of the Mammalian Gene Collection is to provide researchers with unrestricted access to sequence-validated full-length protein-coding cDNA clones for human, mouse, and rat genes. Display Conventions and Configuration The track follows the display conventions for gene prediction tracks. An optional codon coloring feature is available for quick validation and comparison of gene predictions. To display codon colors, select the genomic codons option from the Color track by codons pull-down menu. For more information about this feature, go to the Coloring Gene Predictions and Annotations by Codon page. Methods GenBank rat MGC mRNAs identified as having full-length ORFs were aligned against the genome using blat. When a single mRNA aligned in multiple places, the alignment having the highest base identity was found. Only alignments having a base identity level within 1% of the best and at least 95% base identity with the genomic sequence were kept. Credits The rat MGC full-length mRNA track was produced at UCSC from mRNA sequence data submitted to GenBank by the Mammalian Gene Collection project. References Mammalian Gene Collection project references. Kent WJ. BLAT--the BLAST-like alignment tool. Genome Res. 2002 Apr;12(4):656-64. PMID: 11932250; PMC: PMC187518 
microsat Microsatellite Microsatellites - Di-nucleotide and Tri-nucleotide Repeats Variation and Repeats Description This track displays regions that are likely to be useful as microsatellite markers. These are sequences of at least 15 perfect di-nucleotide and tri-nucleotide repeats and tend to be highly polymorphic in the population. Methods The data shown in this track are a subset of the Simple Repeats track, selecting only those repeats of period 2 and 3, with 100% identity and no indels and with at least 15 copies of the repeat. The Simple Repeats track is created using the Tandem Repeats Finder. For more information about this program, see Benson (1999). Credits Tandem Repeats Finder was written by Gary Benson. References Benson G. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 1999 Jan 15;27(2):573-80. PMID: 9862982; PMC: PMC148217 
miRNA miRNA MicroRNAs from miRBase Genes and Gene Predictions Description The miRNA track shows microRNAs from miRBase. Display Conventions and Configuration Mature miRNAs (miRs) are represented by thick blocks. The predicted stem-loop portions of the primary transcripts are indicated by thinner blocks. miRNAs in the sense orientation are shown in black; those in the reverse orientation are colored grey. When a single precursor produces two mature miRs from its 5' and 3' parts, it is displayed twice with the two different positions of the mature miR. To display only those items that exceed a specific unnormalized score, enter a minimum score between 0 and 1000 in the text box at the top of the track description page. Methods Mature and precursor miRNAs from the miRNA Registry were aligned against the genome using blat. The extents of the precursor sequences were not generally known, and were predicted based on base-paired hairpin structure. miRBase is described in Griffiths-Jones, S. et al. (2006). The miRNA Registry is described in Griffiths-Jones, S. (2004) and Weber, M.J. (2005) in the References section below. Credits This track was created by Michel Weber of Laboratoire de Biologie Mol&eacute;culaire Eucaryote, CNRS Universit&eacute; Paul Sabatier (Toulouse, France), Yves Quentin of Laboratoire de Microbiologie et G&eacute;n&eacute;tique Mol&eacute;culaires (Toulouse, France) and Sam Griffiths-Jones of The Wellcome Trust Sanger Institute (Cambridge, UK). References When making use of these data, please cite: Griffiths-Jones S, Grocock RJ, van Dongen S, Bateman A, Enright AJ. miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res. 2006 Jan 1;34(Database issue):D140-4. PMID: 16381832; PMC: PMC1347474 Griffiths-Jones S. The microRNA Registry. Nucleic Acids Res. 2004 Jan 1;32(Database issue):D109-11. PMID: 14681370; PMC: PMC308757 Weber MJ. New human and mouse microRNA genes found by homology search. FEBS J. 2005 Jan;272(1):59-73. PMID: 15634332 The following publication provides guidelines on miRNA annotation: Ambros V, Bartel B, Bartel DP, Burge CB, Carrington JC, Chen X, Dreyfuss G, Eddy SR, Griffiths-Jones S, Marshall M et al. A uniform system for microRNA annotation. RNA. 2003 Mar;9(3):277-9. PMID: 12592000; PMC: PMC1370393 For more information on blat, see Kent WJ. BLAT - the BLAST-like alignment tool. Genome Res. 2002 Apr;12(4):656-64. PMID: 11932250; PMC: PMC187518 
xenoMrna Other mRNAs Non-Rat mRNAs from GenBank mRNA and EST Description This track displays translated blat alignments of vertebrate and invertebrate mRNA in GenBank from organisms other than rat. Display Conventions and Configuration This track follows the display conventions for PSL alignment tracks. In dense display mode, the items that are more darkly shaded indicate matches of better quality. The strand information (+/-) for this track is in two parts. The first + indicates the orientation of the query sequence whose translated protein produced the match (here always 5' to 3', hence +). The second + or - indicates the orientation of the matching translated genomic sequence. Because the two orientations of a DNA sequence give different predicted protein sequences, there are four combinations. ++ is not the same as --, nor is +- the same as -+. The description page for this track has a filter that can be used to change the display mode, alter the color, and include/exclude a subset of items within the track. This may be helpful when many items are shown in the track display, especially when only some are relevant to the current task. To use the filter: Type a term in one or more of the text boxes to filter the mRNA display. For example, to apply the filter to all mRNAs expressed in a specific organ, type the name of the organ in the tissue box. To view the list of valid terms for each text box, consult the table in the Table Browser that corresponds to the factor on which you wish to filter. For example, the &quot;tissue&quot; table contains all the types of tissues that can be entered into the tissue text box. Multiple terms may be entered at once, separated by a space. Wildcards may also be used in the filter. If filtering on more than one value, choose the desired combination logic. If &quot;and&quot; is selected, only mRNAs that match all filter criteria will be highlighted. If &quot;or&quot; is selected, mRNAs that match any one of the filter criteria will be highlighted. Choose the color or display characteristic that should be used to highlight or include/exclude the filtered items. If &quot;exclude&quot; is chosen, the browser will not display mRNAs that match the filter criteria. If &quot;include&quot; is selected, the browser will display only those mRNAs that match the filter criteria. This track may also be configured to display codon coloring, a feature that allows the user to quickly compare mRNAs against the genomic sequence. For more information about this option, go to the Codon and Base Coloring for Alignment Tracks page. Several types of alignment gap may also be colored; for more information, go to the Alignment Insertion/Deletion Display Options page. Methods The mRNAs were aligned against the rat genome using translated blat. When a single mRNA aligned in multiple places, the alignment having the highest base identity was found. Only those alignments having a base identity level within 1% of the best and at least 25% base identity with the genomic sequence were kept. Credits The mRNA track was produced at UCSC from mRNA sequence data submitted to the international public sequence databases by scientists worldwide. References Benson DA, Cavanaugh M, Clark K, Karsch-Mizrachi I, Lipman DJ, Ostell J, Sayers EW. GenBank. Nucleic Acids Res. 2013 Jan;41(Database issue):D36-42. PMID: 23193287; PMC: PMC3531190 Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Wheeler DL. GenBank: update. Nucleic Acids Res. 2004 Jan 1;32(Database issue):D23-6. PMID: 14681350; PMC: PMC308779 Kent WJ. BLAT - the BLAST-like alignment tool. Genome Res. 2002 Apr;12(4):656-64. PMID: 11932250; PMC: PMC187518 
est Rat ESTs Rat ESTs Including Unspliced mRNA and EST Description This track shows alignments between rat expressed sequence tags (ESTs) in GenBank and the genome. ESTs are single-read sequences, typically about 500 bases in length, that usually represent fragments of transcribed genes. Display Conventions and Configuration This track follows the display conventions for PSL alignment tracks. In dense display mode, the items that are more darkly shaded indicate matches of better quality. The strand information (+/-) indicates the direction of the match between the EST and the matching genomic sequence. It bears no relationship to the direction of transcription of the RNA with which it might be associated. The description page for this track has a filter that can be used to change the display mode, alter the color, and include/exclude a subset of items within the track. This may be helpful when many items are shown in the track display, especially when only some are relevant to the current task. To use the filter: Type a term in one or more of the text boxes to filter the EST display. For example, to apply the filter to all ESTs expressed in a specific organ, type the name of the organ in the tissue box. To view the list of valid terms for each text box, consult the table in the Table Browser that corresponds to the factor on which you wish to filter. For example, the &quot;tissue&quot; table contains all the types of tissues that can be entered into the tissue text box. Multiple terms may be entered at once, separated by a space. Wildcards may also be used in the filter. If filtering on more than one value, choose the desired combination logic. If &quot;and&quot; is selected, only ESTs that match all filter criteria will be highlighted. If &quot;or&quot; is selected, ESTs that match any one of the filter criteria will be highlighted. Choose the color or display characteristic that should be used to highlight or include/exclude the filtered items. If &quot;exclude&quot; is chosen, the browser will not display ESTs that match the filter criteria. If &quot;include&quot; is selected, the browser will display only those ESTs that match the filter criteria. This track may also be configured to display base labeling, a feature that allows the user to display all bases in the aligning sequence or only those that differ from the genomic sequence. For more information about this option, go to the Base Coloring for Alignment Tracks page. Several types of alignment gap may also be colored; for more information, go to the Alignment Insertion/Deletion Display Options page. Methods To make an EST, RNA is isolated from cells and reverse transcribed into cDNA. Typically, the cDNA is cloned into a plasmid vector and a read is taken from the 5' and/or 3' primer. For most &mdash; but not all &mdash; ESTs, the reverse transcription is primed by an oligo-dT, which hybridizes with the poly-A tail of mature mRNA. The reverse transcriptase may or may not make it to the 5' end of the mRNA, which may or may not be degraded. In general, the 3' ESTs mark the end of transcription reasonably well, but the 5' ESTs may end at any point within the transcript. Some of the newer cap-selected libraries cover transcription start reasonably well. Before the cap-selection techniques emerged, some projects used random rather than poly-A priming in an attempt to retrieve sequence distant from the 3' end. These projects were successful at this, but as a side effect also deposited sequences from unprocessed mRNA and perhaps even genomic sequences into the EST databases. Even outside of the random-primed projects, there is a degree of non-mRNA contamination. Because of this, a single unspliced EST should be viewed with considerable skepticism. To generate this track, rat ESTs from GenBank were aligned against the genome using blat. Note that the maximum intron length allowed by blat is 750,000 bases, which may eliminate some ESTs with very long introns that might otherwise align. When a single EST aligned in multiple places, the alignment having the highest base identity was identified. Only alignments having a base identity level within 0.5% of the best and at least 96% base identity with the genomic sequence were kept. Credits This track was produced at UCSC from EST sequence data submitted to the international public sequence databases by scientists worldwide. References Benson DA, Cavanaugh M, Clark K, Karsch-Mizrachi I, Lipman DJ, Ostell J, Sayers EW. GenBank. Nucleic Acids Res. 2013 Jan;41(Database issue):D36-42. PMID: 23193287; PMC: PMC3531190 Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Wheeler DL. GenBank: update. Nucleic Acids Res. 2004 Jan 1;32(Database issue):D23-6. PMID: 14681350; PMC: PMC308779 Kent WJ. BLAT - the BLAST-like alignment tool. Genome Res. 2002 Apr;12(4):656-64. PMID: 11932250; PMC: PMC187518 
recombRateRat Recomb Rate Recombination Rate from SHRSPxBN and FHHxACI genetic maps (SHRSPxBN default) Mapping and Sequencing Description The recombination rate track represents calculated sex-averaged rates of recombination based on either the SHRSPxBN F2 intercross or FHHxACI F2 intercross genetic maps. By default, the SHRSPxBN map rates are displayed. Female and male specific recombination rates are not available for either map. Methods The SHRSPxBN and FHHxACI F2 intercross genetic maps were created at the Whitehead Institute For more information on these maps, see RG Steen et. al., &quot;A high-density integrated genetic linkage and radiation hybrid map of the laboratory rat.&quot;, Genome Res., 9(6):AP1-8 (1999). Data for these maps was downloaded from the NCBI ftp site. Each base is assigned the recombination rate calculated by assuming a linear genetic distance across the immediately flanking genetic markers. The recombination rate assigned to each 1 Mb window is the average recombination rate of the bases contained within the window. Using the Filter To view a particular map or gender-specific rate, select the corresponding option from the &quot;Map Distances&quot; pulldown list. By default, the browser displays the SHRSPxBN sex-averaged distances. Credits This track is produced at UCSC and uses data that are freely available for the SHRSPxBN and FHHxACI intercross genetic maps (see above links). Thanks to all who have played a part in the creation of these maps. 
rgdEst RGD EST RGD EST mRNA and EST Description This track shows expressed sequence tags (ESTs) downloaded from the Rat Genome Database (RGD). An EST is a partial sequence of a randomly-chosen cDNA, obtained from the results of a single DNA sequencing reaction. ESTs are used to identify transcribed regions in genomic sequence and to characterize patterns of gene expression in the tissue from which the cDNA was derived. Methods The data used to create this annotation were obtained from the file RGD_EST.gff downloaded from the RGD website. Credits Thanks to the RGD for providing this annotation. RGD is funded by grant HL64541 entitled "Rat Genome Database", awarded to Dr. Howard J Jacob, Medical College of Wisconsin, from the National Heart Lung and Blood Institute (NHLBI) of the National Institutes of Health (NIH). 
rgdQtl RGD QTL Rat Quantitative Trait Locus from RGD Phenotype and Disease Associations Description A quantitative trait locus (QTL) is a polymorphic locus that contains alleles which differentially affect the expression of a continuously distributed phenotypic trait. Usually a QTL is a marker described by statistical association to quantitative variation in the particular phenotypic trait that is thought to be controlled by the cumulative action of alleles at multiple loci. For a comprehensive review of QTL mapping techniques in the rat, see Rapp, J.P. (2000) in the References section below. Credits Thanks to the RGD for providing this annotation. RGD is funded by grant HL64541 entitled "Rat Genome Database", awarded to Dr. Howard J Jacob, Medical College of Wisconsin, from the National Heart Lung and Blood Institute (NHLBI) of the National Institutes of Health (NIH). References Rapp, J.P. Genetic Analysis of Inherited Hypertension in the Rat. Physiol Rev. 2000 Jan;80(1):135-72. PMID: 10617767 
rgdSslp RGD SSLP Rat Genome Database Simple Sequence Length Polymorphisms Variation and Repeats Description Simple sequence-length polymorphisms (SSLPs) are also known as microsatellite DNA. SSLPs consist of 1 - 6 simple nucleotide repeat sequences that are highly polymorphic in repeat length among strains. They are often used as genetic markers for genotyping. Methods The annotation data file, RGD_SSLP.gff, was downloaded from the Rat Genome Database (RGD) website and processed to create this track. Credits Thanks to the RGD for providing this annotation. RGD is funded by grant HL64541 entitled "Rat Genome Database", awarded to Dr. Howard J Jacob, Medical College of Wisconsin, from the National Heart Lung and Blood Institute (NHLBI) of the National Institutes of Health (NIH). 
genomicSuperDups Segmental Dups Duplications of >1000 Bases of Non-RepeatMasked Sequence Variation and Repeats Description This track shows regions detected as putative genomic duplications within the golden path. The following display conventions are used to distinguish levels of similarity: Light to dark gray: 90 - 98% similarity Light to dark yellow: 98 - 99% similarity Light to dark orange: greater than 99% similarity Red: duplications of greater than 98% similarity that lack sufficient Segmental Duplication Database evidence (most likely missed overlaps) For a region to be included in the track, at least 1 Kb of the total sequence (containing at least 500 bp of non-RepeatMasked sequence) had to align and a sequence identity of at least 90% was required. Methods Segmental duplications play an important role in both genomic disease and gene evolution. This track displays an analysis of the global organization of these long-range segments of identity in genomic sequence. Large recent duplications (&gt;= 1 kb and &gt;= 90% identity) were detected by identifying high-copy repeats, removing these repeats from the genomic sequence (&quot;fuguization&quot;) and searching all sequence for similarity. The repeats were then reinserted into the pairwise alignments, the ends of alignments trimmed, and global alignments were generated. For a full description of the &quot;fuguization&quot; detection method, see Bailey et al., 2001. This method has become known as WGAC (whole-genome assembly comparison); for example, see Bailey et al., 2002. Credits These data were provided by Ginger Cheng, Xinwei She, Archana Raja, Tin Louie and Evan Eichler at the University of Washington. References Bailey JA, Gu Z, Clark RA, Reinert K, Samonte RV, Schwartz S, Adams MD, Myers EW, Li PW, Eichler EE. Recent segmental duplications in the human genome. Science. 2002 Aug 9;297(5583):1003-7. PMID: 12169732 Bailey JA, Yavor AM, Massa HF, Trask BJ, Eichler EE. Segmental duplications: organization and impact within the current human genome project assembly. Genome Res. 2001 Jun;11(6):1005-17. PMID: 11381028; PMC: PMC311093 
simpleRepeat Simple Repeats Simple Tandem Repeats by TRF Variation and Repeats Description This track displays simple tandem repeats (possibly imperfect repeats) located by Tandem Repeats Finder (TRF) which is specialized for this purpose. These repeats can occur within coding regions of genes and may be quite polymorphic. Repeat expansions are sometimes associated with specific diseases. Methods For more information about the TRF program, see Benson (1999). Credits TRF was written by Gary Benson. References Benson G. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 1999 Jan 15;27(2):573-80. PMID: 9862982; PMC: PMC148217 
snpMap SNPs Simple Nucleotide Polymorphisms (SNPs) Variation and Repeats Description This track consolidates all the Simple Nucleotide Polymorphisms into a single track. Filtering The SNPs in this track include all known polymorphisms that can be mapped against the current assembly. These include known point mutations (Single Nucleotide Polymorphisms), insertions, deletions, and segmental mutations from the current build of dbSnp, which is shown in the Genome Browser release log. There are three major cases that are not mapped and/or annotated: Submissions that are completely masked as repetitive elements. These are dropped from any further computations. This set of reference SNPs is found in chromosome &quot;rs_chMasked&quot; on the dbSNP ftp site. Submissions that are defined in a cDNA context with extensive splicing. These SNPs are typically annotated on refSeq mRNAs through a separate annotation process. Effort is being made to reverse map these variations back to contig coordinates, but that has not been implemented. For now, you can find this set of variations in &quot;rs_chNotOn&quot; on the dbSNP ftp site. Submissions with excessive hits to the genome. Variations with 3+ hits to the genome are not included in the tracks, but are available in &quot;rs_chMulti&quot; on the dbSNP ftp site. The heuristics for the non-SNP variations (i.e. named elements and STRs) are quite conservative; therefore, some of these are probably lost. This approach was chosen to avoid false annotation of variation in inappropriate locations. Supporting Details Positional information can be found in the annotations section of the Genome Browser downloads page, which is organized by species and assembly. Non-positional information displayed on this page can be found in the shared data section of the same page, where it is split into tables by organism: dbSnpRsHg for Human, dbSnpRsMm for Mouse, and dbSnpRsRn for Rat. Credits Thanks to NIH's dbSNP for providing the public data, which are available from dbSnp at the NCBI. 
tigrGeneIndex TIGR Gene Index Alignment of TIGR Gene Index TCs Against the Rat Genome mRNA and EST Description This track displays alignments of the TIGR Gene Index (TGI) against the rat genome. The TIGR Gene Index is based largely on assemblies of EST sequences in the public databases. See the following page for more information about TIGR Gene Indices. Credits Thanks to Foo Cheung and Razvan Sultana of the The Institute for Genomic Research, for converting these data into a track for the browser. 
chainNetMm7 Mouse Chain/Net Mouse (Aug. 2005 (NCBI35/mm7)), Chain and Net Alignments Comparative Genomics Description This track shows regions of the genome that are alignable to other genomes (&quot;chain&quot; subtracks) or in synteny (&quot;net&quot; subtracks). The alignable parts are shown with thick blocks that look like exons. Non-alignable parts between these are shown like introns. Chain Track The chain track shows alignments of mouse (Aug. 2005 (NCBI35/mm7)) to the rat genome using a gap scoring system that allows longer gaps than traditional affine gap scoring systems. It can also tolerate gaps in both mouse and rat simultaneously. These &quot;double-sided&quot; gaps can be caused by local inversions and overlapping deletions in both species. The chain track displays boxes joined together by either single or double lines. The boxes represent aligning regions. Single lines indicate gaps that are largely due to a deletion in the mouse assembly or an insertion in the rat assembly. Double lines represent more complex gaps that involve substantial sequence in both species. This may result from inversions, overlapping deletions, an abundance of local mutation, or an unsequenced gap in one species. In cases where multiple chains align over a particular region of the rat genome, the chains with single-lined gaps are often due to processed pseudogenes, while chains with double-lined gaps are more often due to paralogs and unprocessed pseudogenes. In the &quot;pack&quot; and &quot;full&quot; display modes, the individual feature names indicate the chromosome, strand, and location (in thousands) of the match for each matching alignment. Net Track The net track shows the best mouse/rat chain for every part of the rat genome. It is useful for finding syntenic regions, possibly orthologs, and for studying genome rearrangement. The mouse sequence used in this annotation is from the Aug. 2005 (NCBI35/mm7) assembly. Display Conventions and Configuration Chain Track By default, the chains to chromosome-based assemblies are colored based on which chromosome they map to in the aligning organism. To turn off the coloring, check the &quot;off&quot; button next to: Color track based on chromosome. To display only the chains of one chromosome in the aligning organism, enter the name of that chromosome (e.g. chr4) in box next to: Filter by chromosome. Net Track In full display mode, the top-level (level 1) chains are the largest, highest-scoring chains that span this region. In many cases gaps exist in the top-level chain. When possible, these are filled in by other chains that are displayed at level 2. The gaps in level 2 chains may be filled by level 3 chains and so forth. In the graphical display, the boxes represent ungapped alignments; the lines represent gaps. Click on a box to view detailed information about the chain as a whole; click on a line to display information about the gap. The detailed information is useful in determining the cause of the gap or, for lower level chains, the genomic rearrangement. Individual items in the display are categorized as one of four types (other than gap): Top - the best, longest match. Displayed on level 1. Syn - line-ups on the same chromosome as the gap in the level above it. Inv - a line-up on the same chromosome as the gap above it, but in the opposite orientation. NonSyn - a match to a chromosome different from the gap in the level above. Methods Chain track Transposons that have been inserted since the mouse/rat split were removed from the assemblies. The abbreviated genomes were aligned with lastz, and the transposons were added back in. The resulting alignments were converted into axt format using the lavToAxt program. The axt alignments were fed into axtChain, which organizes all alignments between a single mouse chromosome and a single rat chromosome into a group and creates a kd-tree out of the gapless subsections (blocks) of the alignments. A dynamic program was then run over the kd-trees to find the maximally scoring chains of these blocks. The following matrix was used: &nbsp;ACGT A91-114-31-123 C-114100-125-31 G-31-125100-114 T-123-31-11491 Chains scoring below a minimum score of &quot;3000&quot; were discarded; the remaining chains are displayed in this track. The linear gap matrix used with axtChain: -linearGap=medium tableSize 11 smallSize 111 position 1 2 3 11 111 2111 12111 32111 72111 152111 252111 qGap 350 425 450 600 900 2900 22900 57900 117900 217900 317900 tGap 350 425 450 600 900 2900 22900 57900 117900 217900 317900 bothGap 750 825 850 1000 1300 3300 23300 58300 118300 218300 318300 Net track Chains were derived from lastz alignments, using the methods described on the chain tracks description pages, and sorted with the highest-scoring chains in the genome ranked first. The program chainNet was then used to place the chains one at a time, trimming them as necessary to fit into sections not already covered by a higher-scoring chain. During this process, a natural hierarchy emerged in which a chain that filled a gap in a higher-scoring chain was placed underneath that chain. The program netSyntenic was used to fill in information about the relationship between higher- and lower-level chains, such as whether a lower-level chain was syntenic or inverted relative to the higher-level chain. The program netClass was then used to fill in how much of the gaps and chains contained Ns (sequencing gaps) in one or both species and how much was filled with transposons inserted before and after the two organisms diverged. Credits Lastz (previously known as blastz) was developed at Pennsylvania State University by Minmei Hou, Scott Schwartz, Zheng Zhang, and Webb Miller with advice from Ross Hardison. Lineage-specific repeats were identified by Arian Smit and his RepeatMasker program. The axtChain program was developed at the University of California at Santa Cruz by Jim Kent with advice from Webb Miller and David Haussler. The browser display and database storage of the chains and nets were created by Robert Baertsch and Jim Kent. The chainNet, netSyntenic, and netClass programs were developed at the University of California Santa Cruz by Jim Kent. References Harris, R.S. (2007) Improved pairwise alignment of genomic DNA Ph.D. Thesis, The Pennsylvania State University Chiaromonte F, Yap VB, Miller W. Scoring pairwise genomic sequence alignments. Pac Symp Biocomput. 2002:115-26. PMID: 11928468 Kent WJ, Baertsch R, Hinrichs A, Miller W, Haussler D. Evolution's cauldron: duplication, deletion, and rearrangement in the mouse and human genomes. Proc Natl Acad Sci U S A. 2003 Sep 30;100(20):11484-9. PMID: 14500911; PMC: PMC208784 Schwartz S, Kent WJ, Smit A, Zhang Z, Baertsch R, Hardison RC, Haussler D, Miller W. Human-mouse alignments with BLASTZ. Genome Res. 2003 Jan;13(1):103-7. PMID: 12529312; PMC: PMC430961 
chainNetMm7Viewnet Net Mouse (Aug. 2005 (NCBI35/mm7)), Chain and Net Alignments Comparative Genomics 
netMm7 Mouse Net Mouse (Aug. 2005 (NCBI35/mm7)) Alignment Net Comparative Genomics Description This track shows regions of the genome that are alignable to other genomes (&quot;chain&quot; subtracks) or in synteny (&quot;net&quot; subtracks). The alignable parts are shown with thick blocks that look like exons. Non-alignable parts between these are shown like introns. Chain Track The chain track shows alignments of mouse (Aug. 2005 (NCBI35/mm7)) to the rat genome using a gap scoring system that allows longer gaps than traditional affine gap scoring systems. It can also tolerate gaps in both mouse and rat simultaneously. These &quot;double-sided&quot; gaps can be caused by local inversions and overlapping deletions in both species. The chain track displays boxes joined together by either single or double lines. The boxes represent aligning regions. Single lines indicate gaps that are largely due to a deletion in the mouse assembly or an insertion in the rat assembly. Double lines represent more complex gaps that involve substantial sequence in both species. This may result from inversions, overlapping deletions, an abundance of local mutation, or an unsequenced gap in one species. In cases where multiple chains align over a particular region of the rat genome, the chains with single-lined gaps are often due to processed pseudogenes, while chains with double-lined gaps are more often due to paralogs and unprocessed pseudogenes. In the &quot;pack&quot; and &quot;full&quot; display modes, the individual feature names indicate the chromosome, strand, and location (in thousands) of the match for each matching alignment. Net Track The net track shows the best mouse/rat chain for every part of the rat genome. It is useful for finding syntenic regions, possibly orthologs, and for studying genome rearrangement. The mouse sequence used in this annotation is from the Aug. 2005 (NCBI35/mm7) assembly. Display Conventions and Configuration Chain Track By default, the chains to chromosome-based assemblies are colored based on which chromosome they map to in the aligning organism. To turn off the coloring, check the &quot;off&quot; button next to: Color track based on chromosome. To display only the chains of one chromosome in the aligning organism, enter the name of that chromosome (e.g. chr4) in box next to: Filter by chromosome. Net Track In full display mode, the top-level (level 1) chains are the largest, highest-scoring chains that span this region. In many cases gaps exist in the top-level chain. When possible, these are filled in by other chains that are displayed at level 2. The gaps in level 2 chains may be filled by level 3 chains and so forth. In the graphical display, the boxes represent ungapped alignments; the lines represent gaps. Click on a box to view detailed information about the chain as a whole; click on a line to display information about the gap. The detailed information is useful in determining the cause of the gap or, for lower level chains, the genomic rearrangement. Individual items in the display are categorized as one of four types (other than gap): Top - the best, longest match. Displayed on level 1. Syn - line-ups on the same chromosome as the gap in the level above it. Inv - a line-up on the same chromosome as the gap above it, but in the opposite orientation. NonSyn - a match to a chromosome different from the gap in the level above. Methods Chain track Transposons that have been inserted since the mouse/rat split were removed from the assemblies. The abbreviated genomes were aligned with lastz, and the transposons were added back in. The resulting alignments were converted into axt format using the lavToAxt program. The axt alignments were fed into axtChain, which organizes all alignments between a single mouse chromosome and a single rat chromosome into a group and creates a kd-tree out of the gapless subsections (blocks) of the alignments. A dynamic program was then run over the kd-trees to find the maximally scoring chains of these blocks. The following matrix was used: &nbsp;ACGT A91-114-31-123 C-114100-125-31 G-31-125100-114 T-123-31-11491 Chains scoring below a minimum score of &quot;3000&quot; were discarded; the remaining chains are displayed in this track. The linear gap matrix used with axtChain: -linearGap=medium tableSize 11 smallSize 111 position 1 2 3 11 111 2111 12111 32111 72111 152111 252111 qGap 350 425 450 600 900 2900 22900 57900 117900 217900 317900 tGap 350 425 450 600 900 2900 22900 57900 117900 217900 317900 bothGap 750 825 850 1000 1300 3300 23300 58300 118300 218300 318300 Net track Chains were derived from lastz alignments, using the methods described on the chain tracks description pages, and sorted with the highest-scoring chains in the genome ranked first. The program chainNet was then used to place the chains one at a time, trimming them as necessary to fit into sections not already covered by a higher-scoring chain. During this process, a natural hierarchy emerged in which a chain that filled a gap in a higher-scoring chain was placed underneath that chain. The program netSyntenic was used to fill in information about the relationship between higher- and lower-level chains, such as whether a lower-level chain was syntenic or inverted relative to the higher-level chain. The program netClass was then used to fill in how much of the gaps and chains contained Ns (sequencing gaps) in one or both species and how much was filled with transposons inserted before and after the two organisms diverged. Credits Lastz (previously known as blastz) was developed at Pennsylvania State University by Minmei Hou, Scott Schwartz, Zheng Zhang, and Webb Miller with advice from Ross Hardison. Lineage-specific repeats were identified by Arian Smit and his RepeatMasker program. The axtChain program was developed at the University of California at Santa Cruz by Jim Kent with advice from Webb Miller and David Haussler. The browser display and database storage of the chains and nets were created by Robert Baertsch and Jim Kent. The chainNet, netSyntenic, and netClass programs were developed at the University of California Santa Cruz by Jim Kent. References Harris, R.S. (2007) Improved pairwise alignment of genomic DNA Ph.D. Thesis, The Pennsylvania State University Chiaromonte F, Yap VB, Miller W. Scoring pairwise genomic sequence alignments. Pac Symp Biocomput. 2002:115-26. PMID: 11928468 Kent WJ, Baertsch R, Hinrichs A, Miller W, Haussler D. Evolution's cauldron: duplication, deletion, and rearrangement in the mouse and human genomes. Proc Natl Acad Sci U S A. 2003 Sep 30;100(20):11484-9. PMID: 14500911; PMC: PMC208784 Schwartz S, Kent WJ, Smit A, Zhang Z, Baertsch R, Hardison RC, Haussler D, Miller W. Human-mouse alignments with BLASTZ. Genome Res. 2003 Jan;13(1):103-7. PMID: 12529312; PMC: PMC430961 
chainNetMm7Viewchain Chain Mouse (Aug. 2005 (NCBI35/mm7)), Chain and Net Alignments Comparative Genomics 
chainMm7 Mouse Chain Mouse (Aug. 2005 (NCBI35/mm7)) Chained Alignments Comparative Genomics Description This track shows regions of the genome that are alignable to other genomes (&quot;chain&quot; subtracks) or in synteny (&quot;net&quot; subtracks). The alignable parts are shown with thick blocks that look like exons. Non-alignable parts between these are shown like introns. Chain Track The chain track shows alignments of mouse (Aug. 2005 (NCBI35/mm7)) to the rat genome using a gap scoring system that allows longer gaps than traditional affine gap scoring systems. It can also tolerate gaps in both mouse and rat simultaneously. These &quot;double-sided&quot; gaps can be caused by local inversions and overlapping deletions in both species. The chain track displays boxes joined together by either single or double lines. The boxes represent aligning regions. Single lines indicate gaps that are largely due to a deletion in the mouse assembly or an insertion in the rat assembly. Double lines represent more complex gaps that involve substantial sequence in both species. This may result from inversions, overlapping deletions, an abundance of local mutation, or an unsequenced gap in one species. In cases where multiple chains align over a particular region of the rat genome, the chains with single-lined gaps are often due to processed pseudogenes, while chains with double-lined gaps are more often due to paralogs and unprocessed pseudogenes. In the &quot;pack&quot; and &quot;full&quot; display modes, the individual feature names indicate the chromosome, strand, and location (in thousands) of the match for each matching alignment. Net Track The net track shows the best mouse/rat chain for every part of the rat genome. It is useful for finding syntenic regions, possibly orthologs, and for studying genome rearrangement. The mouse sequence used in this annotation is from the Aug. 2005 (NCBI35/mm7) assembly. Display Conventions and Configuration Chain Track By default, the chains to chromosome-based assemblies are colored based on which chromosome they map to in the aligning organism. To turn off the coloring, check the &quot;off&quot; button next to: Color track based on chromosome. To display only the chains of one chromosome in the aligning organism, enter the name of that chromosome (e.g. chr4) in box next to: Filter by chromosome. Net Track In full display mode, the top-level (level 1) chains are the largest, highest-scoring chains that span this region. In many cases gaps exist in the top-level chain. When possible, these are filled in by other chains that are displayed at level 2. The gaps in level 2 chains may be filled by level 3 chains and so forth. In the graphical display, the boxes represent ungapped alignments; the lines represent gaps. Click on a box to view detailed information about the chain as a whole; click on a line to display information about the gap. The detailed information is useful in determining the cause of the gap or, for lower level chains, the genomic rearrangement. Individual items in the display are categorized as one of four types (other than gap): Top - the best, longest match. Displayed on level 1. Syn - line-ups on the same chromosome as the gap in the level above it. Inv - a line-up on the same chromosome as the gap above it, but in the opposite orientation. NonSyn - a match to a chromosome different from the gap in the level above. Methods Chain track Transposons that have been inserted since the mouse/rat split were removed from the assemblies. The abbreviated genomes were aligned with lastz, and the transposons were added back in. The resulting alignments were converted into axt format using the lavToAxt program. The axt alignments were fed into axtChain, which organizes all alignments between a single mouse chromosome and a single rat chromosome into a group and creates a kd-tree out of the gapless subsections (blocks) of the alignments. A dynamic program was then run over the kd-trees to find the maximally scoring chains of these blocks. The following matrix was used: &nbsp;ACGT A91-114-31-123 C-114100-125-31 G-31-125100-114 T-123-31-11491 Chains scoring below a minimum score of &quot;3000&quot; were discarded; the remaining chains are displayed in this track. The linear gap matrix used with axtChain: -linearGap=medium tableSize 11 smallSize 111 position 1 2 3 11 111 2111 12111 32111 72111 152111 252111 qGap 350 425 450 600 900 2900 22900 57900 117900 217900 317900 tGap 350 425 450 600 900 2900 22900 57900 117900 217900 317900 bothGap 750 825 850 1000 1300 3300 23300 58300 118300 218300 318300 Net track Chains were derived from lastz alignments, using the methods described on the chain tracks description pages, and sorted with the highest-scoring chains in the genome ranked first. The program chainNet was then used to place the chains one at a time, trimming them as necessary to fit into sections not already covered by a higher-scoring chain. During this process, a natural hierarchy emerged in which a chain that filled a gap in a higher-scoring chain was placed underneath that chain. The program netSyntenic was used to fill in information about the relationship between higher- and lower-level chains, such as whether a lower-level chain was syntenic or inverted relative to the higher-level chain. The program netClass was then used to fill in how much of the gaps and chains contained Ns (sequencing gaps) in one or both species and how much was filled with transposons inserted before and after the two organisms diverged. Credits Lastz (previously known as blastz) was developed at Pennsylvania State University by Minmei Hou, Scott Schwartz, Zheng Zhang, and Webb Miller with advice from Ross Hardison. Lineage-specific repeats were identified by Arian Smit and his RepeatMasker program. The axtChain program was developed at the University of California at Santa Cruz by Jim Kent with advice from Webb Miller and David Haussler. The browser display and database storage of the chains and nets were created by Robert Baertsch and Jim Kent. The chainNet, netSyntenic, and netClass programs were developed at the University of California Santa Cruz by Jim Kent. References Harris, R.S. (2007) Improved pairwise alignment of genomic DNA Ph.D. Thesis, The Pennsylvania State University Chiaromonte F, Yap VB, Miller W. Scoring pairwise genomic sequence alignments. Pac Symp Biocomput. 2002:115-26. PMID: 11928468 Kent WJ, Baertsch R, Hinrichs A, Miller W, Haussler D. Evolution's cauldron: duplication, deletion, and rearrangement in the mouse and human genomes. Proc Natl Acad Sci U S A. 2003 Sep 30;100(20):11484-9. PMID: 14500911; PMC: PMC208784 Schwartz S, Kent WJ, Smit A, Zhang Z, Baertsch R, Hardison RC, Haussler D, Miller W. Human-mouse alignments with BLASTZ. Genome Res. 2003 Jan;13(1):103-7. PMID: 12529312; PMC: PMC430961 
chainNetHg18 Human Chain/Net Human (Mar. 2006 (NCBI36/hg18)), Chain and Net Alignments Comparative Genomics Description This track shows regions of the genome that are alignable to other genomes (&quot;chain&quot; subtracks) or in synteny (&quot;net&quot; subtracks). The alignable parts are shown with thick blocks that look like exons. Non-alignable parts between these are shown like introns. Chain Track The chain track shows alignments of human (Mar. 2006 (NCBI36/hg18)) to the rat genome using a gap scoring system that allows longer gaps than traditional affine gap scoring systems. It can also tolerate gaps in both human and rat simultaneously. These &quot;double-sided&quot; gaps can be caused by local inversions and overlapping deletions in both species. The chain track displays boxes joined together by either single or double lines. The boxes represent aligning regions. Single lines indicate gaps that are largely due to a deletion in the human assembly or an insertion in the rat assembly. Double lines represent more complex gaps that involve substantial sequence in both species. This may result from inversions, overlapping deletions, an abundance of local mutation, or an unsequenced gap in one species. In cases where multiple chains align over a particular region of the rat genome, the chains with single-lined gaps are often due to processed pseudogenes, while chains with double-lined gaps are more often due to paralogs and unprocessed pseudogenes. In the &quot;pack&quot; and &quot;full&quot; display modes, the individual feature names indicate the chromosome, strand, and location (in thousands) of the match for each matching alignment. Net Track The net track shows the best human/rat chain for every part of the rat genome. It is useful for finding syntenic regions, possibly orthologs, and for studying genome rearrangement. The human sequence used in this annotation is from the Mar. 2006 (NCBI36/hg18) assembly. Display Conventions and Configuration Chain Track By default, the chains to chromosome-based assemblies are colored based on which chromosome they map to in the aligning organism. To turn off the coloring, check the &quot;off&quot; button next to: Color track based on chromosome. To display only the chains of one chromosome in the aligning organism, enter the name of that chromosome (e.g. chr4) in box next to: Filter by chromosome. Net Track In full display mode, the top-level (level 1) chains are the largest, highest-scoring chains that span this region. In many cases gaps exist in the top-level chain. When possible, these are filled in by other chains that are displayed at level 2. The gaps in level 2 chains may be filled by level 3 chains and so forth. In the graphical display, the boxes represent ungapped alignments; the lines represent gaps. Click on a box to view detailed information about the chain as a whole; click on a line to display information about the gap. The detailed information is useful in determining the cause of the gap or, for lower level chains, the genomic rearrangement. Individual items in the display are categorized as one of four types (other than gap): Top - the best, longest match. Displayed on level 1. Syn - line-ups on the same chromosome as the gap in the level above it. Inv - a line-up on the same chromosome as the gap above it, but in the opposite orientation. NonSyn - a match to a chromosome different from the gap in the level above. Methods Chain track Transposons that have been inserted since the human/rat split were removed from the assemblies. The abbreviated genomes were aligned with lastz, and the transposons were added back in. The resulting alignments were converted into axt format using the lavToAxt program. The axt alignments were fed into axtChain, which organizes all alignments between a single human chromosome and a single rat chromosome into a group and creates a kd-tree out of the gapless subsections (blocks) of the alignments. A dynamic program was then run over the kd-trees to find the maximally scoring chains of these blocks. The following matrix was used: &nbsp;ACGT A91-114-31-123 C-114100-125-31 G-31-125100-114 T-123-31-11491 Chains scoring below a minimum score of &quot;1000&quot; were discarded; the remaining chains are displayed in this track. The linear gap matrix used with axtChain: -linearGap=medium tableSize 11 smallSize 111 position 1 2 3 11 111 2111 12111 32111 72111 152111 252111 qGap 350 425 450 600 900 2900 22900 57900 117900 217900 317900 tGap 350 425 450 600 900 2900 22900 57900 117900 217900 317900 bothGap 750 825 850 1000 1300 3300 23300 58300 118300 218300 318300 Net track Chains were derived from lastz alignments, using the methods described on the chain tracks description pages, and sorted with the highest-scoring chains in the genome ranked first. The program chainNet was then used to place the chains one at a time, trimming them as necessary to fit into sections not already covered by a higher-scoring chain. During this process, a natural hierarchy emerged in which a chain that filled a gap in a higher-scoring chain was placed underneath that chain. The program netSyntenic was used to fill in information about the relationship between higher- and lower-level chains, such as whether a lower-level chain was syntenic or inverted relative to the higher-level chain. The program netClass was then used to fill in how much of the gaps and chains contained Ns (sequencing gaps) in one or both species and how much was filled with transposons inserted before and after the two organisms diverged. Credits Lastz (previously known as blastz) was developed at Pennsylvania State University by Minmei Hou, Scott Schwartz, Zheng Zhang, and Webb Miller with advice from Ross Hardison. Lineage-specific repeats were identified by Arian Smit and his RepeatMasker program. The axtChain program was developed at the University of California at Santa Cruz by Jim Kent with advice from Webb Miller and David Haussler. The browser display and database storage of the chains and nets were created by Robert Baertsch and Jim Kent. The chainNet, netSyntenic, and netClass programs were developed at the University of California Santa Cruz by Jim Kent. References Harris, R.S. (2007) Improved pairwise alignment of genomic DNA Ph.D. Thesis, The Pennsylvania State University Chiaromonte F, Yap VB, Miller W. Scoring pairwise genomic sequence alignments. Pac Symp Biocomput. 2002:115-26. PMID: 11928468 Kent WJ, Baertsch R, Hinrichs A, Miller W, Haussler D. Evolution's cauldron: duplication, deletion, and rearrangement in the mouse and human genomes. Proc Natl Acad Sci U S A. 2003 Sep 30;100(20):11484-9. PMID: 14500911; PMC: PMC208784 Schwartz S, Kent WJ, Smit A, Zhang Z, Baertsch R, Hardison RC, Haussler D, Miller W. Human-mouse alignments with BLASTZ. Genome Res. 2003 Jan;13(1):103-7. PMID: 12529312; PMC: PMC430961 
chainNetHg18Viewnet Net Human (Mar. 2006 (NCBI36/hg18)), Chain and Net Alignments Comparative Genomics 
netHg18 Human Net Human (Mar. 2006 (NCBI36/hg18)) Alignment net Comparative Genomics Description This track shows regions of the genome that are alignable to other genomes (&quot;chain&quot; subtracks) or in synteny (&quot;net&quot; subtracks). The alignable parts are shown with thick blocks that look like exons. Non-alignable parts between these are shown like introns. Chain Track The chain track shows alignments of human (Mar. 2006 (NCBI36/hg18)) to the rat genome using a gap scoring system that allows longer gaps than traditional affine gap scoring systems. It can also tolerate gaps in both human and rat simultaneously. These &quot;double-sided&quot; gaps can be caused by local inversions and overlapping deletions in both species. The chain track displays boxes joined together by either single or double lines. The boxes represent aligning regions. Single lines indicate gaps that are largely due to a deletion in the human assembly or an insertion in the rat assembly. Double lines represent more complex gaps that involve substantial sequence in both species. This may result from inversions, overlapping deletions, an abundance of local mutation, or an unsequenced gap in one species. In cases where multiple chains align over a particular region of the rat genome, the chains with single-lined gaps are often due to processed pseudogenes, while chains with double-lined gaps are more often due to paralogs and unprocessed pseudogenes. In the &quot;pack&quot; and &quot;full&quot; display modes, the individual feature names indicate the chromosome, strand, and location (in thousands) of the match for each matching alignment. Net Track The net track shows the best human/rat chain for every part of the rat genome. It is useful for finding syntenic regions, possibly orthologs, and for studying genome rearrangement. The human sequence used in this annotation is from the Mar. 2006 (NCBI36/hg18) assembly. Display Conventions and Configuration Chain Track By default, the chains to chromosome-based assemblies are colored based on which chromosome they map to in the aligning organism. To turn off the coloring, check the &quot;off&quot; button next to: Color track based on chromosome. To display only the chains of one chromosome in the aligning organism, enter the name of that chromosome (e.g. chr4) in box next to: Filter by chromosome. Net Track In full display mode, the top-level (level 1) chains are the largest, highest-scoring chains that span this region. In many cases gaps exist in the top-level chain. When possible, these are filled in by other chains that are displayed at level 2. The gaps in level 2 chains may be filled by level 3 chains and so forth. In the graphical display, the boxes represent ungapped alignments; the lines represent gaps. Click on a box to view detailed information about the chain as a whole; click on a line to display information about the gap. The detailed information is useful in determining the cause of the gap or, for lower level chains, the genomic rearrangement. Individual items in the display are categorized as one of four types (other than gap): Top - the best, longest match. Displayed on level 1. Syn - line-ups on the same chromosome as the gap in the level above it. Inv - a line-up on the same chromosome as the gap above it, but in the opposite orientation. NonSyn - a match to a chromosome different from the gap in the level above. Methods Chain track Transposons that have been inserted since the human/rat split were removed from the assemblies. The abbreviated genomes were aligned with lastz, and the transposons were added back in. The resulting alignments were converted into axt format using the lavToAxt program. The axt alignments were fed into axtChain, which organizes all alignments between a single human chromosome and a single rat chromosome into a group and creates a kd-tree out of the gapless subsections (blocks) of the alignments. A dynamic program was then run over the kd-trees to find the maximally scoring chains of these blocks. The following matrix was used: &nbsp;ACGT A91-114-31-123 C-114100-125-31 G-31-125100-114 T-123-31-11491 Chains scoring below a minimum score of &quot;1000&quot; were discarded; the remaining chains are displayed in this track. The linear gap matrix used with axtChain: -linearGap=medium tableSize 11 smallSize 111 position 1 2 3 11 111 2111 12111 32111 72111 152111 252111 qGap 350 425 450 600 900 2900 22900 57900 117900 217900 317900 tGap 350 425 450 600 900 2900 22900 57900 117900 217900 317900 bothGap 750 825 850 1000 1300 3300 23300 58300 118300 218300 318300 Net track Chains were derived from lastz alignments, using the methods described on the chain tracks description pages, and sorted with the highest-scoring chains in the genome ranked first. The program chainNet was then used to place the chains one at a time, trimming them as necessary to fit into sections not already covered by a higher-scoring chain. During this process, a natural hierarchy emerged in which a chain that filled a gap in a higher-scoring chain was placed underneath that chain. The program netSyntenic was used to fill in information about the relationship between higher- and lower-level chains, such as whether a lower-level chain was syntenic or inverted relative to the higher-level chain. The program netClass was then used to fill in how much of the gaps and chains contained Ns (sequencing gaps) in one or both species and how much was filled with transposons inserted before and after the two organisms diverged. Credits Lastz (previously known as blastz) was developed at Pennsylvania State University by Minmei Hou, Scott Schwartz, Zheng Zhang, and Webb Miller with advice from Ross Hardison. Lineage-specific repeats were identified by Arian Smit and his RepeatMasker program. The axtChain program was developed at the University of California at Santa Cruz by Jim Kent with advice from Webb Miller and David Haussler. The browser display and database storage of the chains and nets were created by Robert Baertsch and Jim Kent. The chainNet, netSyntenic, and netClass programs were developed at the University of California Santa Cruz by Jim Kent. References Harris, R.S. (2007) Improved pairwise alignment of genomic DNA Ph.D. Thesis, The Pennsylvania State University Chiaromonte F, Yap VB, Miller W. Scoring pairwise genomic sequence alignments. Pac Symp Biocomput. 2002:115-26. PMID: 11928468 Kent WJ, Baertsch R, Hinrichs A, Miller W, Haussler D. Evolution's cauldron: duplication, deletion, and rearrangement in the mouse and human genomes. Proc Natl Acad Sci U S A. 2003 Sep 30;100(20):11484-9. PMID: 14500911; PMC: PMC208784 Schwartz S, Kent WJ, Smit A, Zhang Z, Baertsch R, Hardison RC, Haussler D, Miller W. Human-mouse alignments with BLASTZ. Genome Res. 2003 Jan;13(1):103-7. PMID: 12529312; PMC: PMC430961 
chainNetHg18Viewchain Chain Human (Mar. 2006 (NCBI36/hg18)), Chain and Net Alignments Comparative Genomics 
chainHg18 Human Chain Human (Mar. 2006 (NCBI36/hg18)) Chained Alignments Comparative Genomics Description This track shows regions of the genome that are alignable to other genomes (&quot;chain&quot; subtracks) or in synteny (&quot;net&quot; subtracks). The alignable parts are shown with thick blocks that look like exons. Non-alignable parts between these are shown like introns. Chain Track The chain track shows alignments of human (Mar. 2006 (NCBI36/hg18)) to the rat genome using a gap scoring system that allows longer gaps than traditional affine gap scoring systems. It can also tolerate gaps in both human and rat simultaneously. These &quot;double-sided&quot; gaps can be caused by local inversions and overlapping deletions in both species. The chain track displays boxes joined together by either single or double lines. The boxes represent aligning regions. Single lines indicate gaps that are largely due to a deletion in the human assembly or an insertion in the rat assembly. Double lines represent more complex gaps that involve substantial sequence in both species. This may result from inversions, overlapping deletions, an abundance of local mutation, or an unsequenced gap in one species. In cases where multiple chains align over a particular region of the rat genome, the chains with single-lined gaps are often due to processed pseudogenes, while chains with double-lined gaps are more often due to paralogs and unprocessed pseudogenes. In the &quot;pack&quot; and &quot;full&quot; display modes, the individual feature names indicate the chromosome, strand, and location (in thousands) of the match for each matching alignment. Net Track The net track shows the best human/rat chain for every part of the rat genome. It is useful for finding syntenic regions, possibly orthologs, and for studying genome rearrangement. The human sequence used in this annotation is from the Mar. 2006 (NCBI36/hg18) assembly. Display Conventions and Configuration Chain Track By default, the chains to chromosome-based assemblies are colored based on which chromosome they map to in the aligning organism. To turn off the coloring, check the &quot;off&quot; button next to: Color track based on chromosome. To display only the chains of one chromosome in the aligning organism, enter the name of that chromosome (e.g. chr4) in box next to: Filter by chromosome. Net Track In full display mode, the top-level (level 1) chains are the largest, highest-scoring chains that span this region. In many cases gaps exist in the top-level chain. When possible, these are filled in by other chains that are displayed at level 2. The gaps in level 2 chains may be filled by level 3 chains and so forth. In the graphical display, the boxes represent ungapped alignments; the lines represent gaps. Click on a box to view detailed information about the chain as a whole; click on a line to display information about the gap. The detailed information is useful in determining the cause of the gap or, for lower level chains, the genomic rearrangement. Individual items in the display are categorized as one of four types (other than gap): Top - the best, longest match. Displayed on level 1. Syn - line-ups on the same chromosome as the gap in the level above it. Inv - a line-up on the same chromosome as the gap above it, but in the opposite orientation. NonSyn - a match to a chromosome different from the gap in the level above. Methods Chain track Transposons that have been inserted since the human/rat split were removed from the assemblies. The abbreviated genomes were aligned with lastz, and the transposons were added back in. The resulting alignments were converted into axt format using the lavToAxt program. The axt alignments were fed into axtChain, which organizes all alignments between a single human chromosome and a single rat chromosome into a group and creates a kd-tree out of the gapless subsections (blocks) of the alignments. A dynamic program was then run over the kd-trees to find the maximally scoring chains of these blocks. The following matrix was used: &nbsp;ACGT A91-114-31-123 C-114100-125-31 G-31-125100-114 T-123-31-11491 Chains scoring below a minimum score of &quot;1000&quot; were discarded; the remaining chains are displayed in this track. The linear gap matrix used with axtChain: -linearGap=medium tableSize 11 smallSize 111 position 1 2 3 11 111 2111 12111 32111 72111 152111 252111 qGap 350 425 450 600 900 2900 22900 57900 117900 217900 317900 tGap 350 425 450 600 900 2900 22900 57900 117900 217900 317900 bothGap 750 825 850 1000 1300 3300 23300 58300 118300 218300 318300 Net track Chains were derived from lastz alignments, using the methods described on the chain tracks description pages, and sorted with the highest-scoring chains in the genome ranked first. The program chainNet was then used to place the chains one at a time, trimming them as necessary to fit into sections not already covered by a higher-scoring chain. During this process, a natural hierarchy emerged in which a chain that filled a gap in a higher-scoring chain was placed underneath that chain. The program netSyntenic was used to fill in information about the relationship between higher- and lower-level chains, such as whether a lower-level chain was syntenic or inverted relative to the higher-level chain. The program netClass was then used to fill in how much of the gaps and chains contained Ns (sequencing gaps) in one or both species and how much was filled with transposons inserted before and after the two organisms diverged. Credits Lastz (previously known as blastz) was developed at Pennsylvania State University by Minmei Hou, Scott Schwartz, Zheng Zhang, and Webb Miller with advice from Ross Hardison. Lineage-specific repeats were identified by Arian Smit and his RepeatMasker program. The axtChain program was developed at the University of California at Santa Cruz by Jim Kent with advice from Webb Miller and David Haussler. The browser display and database storage of the chains and nets were created by Robert Baertsch and Jim Kent. The chainNet, netSyntenic, and netClass programs were developed at the University of California Santa Cruz by Jim Kent. References Harris, R.S. (2007) Improved pairwise alignment of genomic DNA Ph.D. Thesis, The Pennsylvania State University Chiaromonte F, Yap VB, Miller W. Scoring pairwise genomic sequence alignments. Pac Symp Biocomput. 2002:115-26. PMID: 11928468 Kent WJ, Baertsch R, Hinrichs A, Miller W, Haussler D. Evolution's cauldron: duplication, deletion, and rearrangement in the mouse and human genomes. Proc Natl Acad Sci U S A. 2003 Sep 30;100(20):11484-9. PMID: 14500911; PMC: PMC208784 Schwartz S, Kent WJ, Smit A, Zhang Z, Baertsch R, Hardison RC, Haussler D, Miller W. Human-mouse alignments with BLASTZ. Genome Res. 2003 Jan;13(1):103-7. PMID: 12529312; PMC: PMC430961 
chainNetCanFam2 Dog Chain/Net Dog (May 2005 (Broad/canFam2)), Chain and Net Alignments Comparative Genomics Description This track shows regions of the genome that are alignable to other genomes (&quot;chain&quot; subtracks) or in synteny (&quot;net&quot; subtracks). The alignable parts are shown with thick blocks that look like exons. Non-alignable parts between these are shown like introns. Chain Track The chain track shows alignments of dog (May 2005 (Broad/canFam2)) to the rat genome using a gap scoring system that allows longer gaps than traditional affine gap scoring systems. It can also tolerate gaps in both dog and rat simultaneously. These &quot;double-sided&quot; gaps can be caused by local inversions and overlapping deletions in both species. The chain track displays boxes joined together by either single or double lines. The boxes represent aligning regions. Single lines indicate gaps that are largely due to a deletion in the dog assembly or an insertion in the rat assembly. Double lines represent more complex gaps that involve substantial sequence in both species. This may result from inversions, overlapping deletions, an abundance of local mutation, or an unsequenced gap in one species. In cases where multiple chains align over a particular region of the rat genome, the chains with single-lined gaps are often due to processed pseudogenes, while chains with double-lined gaps are more often due to paralogs and unprocessed pseudogenes. In the &quot;pack&quot; and &quot;full&quot; display modes, the individual feature names indicate the chromosome, strand, and location (in thousands) of the match for each matching alignment. Net Track The net track shows the best dog/rat chain for every part of the rat genome. It is useful for finding syntenic regions, possibly orthologs, and for studying genome rearrangement. The dog sequence used in this annotation is from the May 2005 (Broad/canFam2) assembly. Display Conventions and Configuration Chain Track By default, the chains to chromosome-based assemblies are colored based on which chromosome they map to in the aligning organism. To turn off the coloring, check the &quot;off&quot; button next to: Color track based on chromosome. To display only the chains of one chromosome in the aligning organism, enter the name of that chromosome (e.g. chr4) in box next to: Filter by chromosome. Net Track In full display mode, the top-level (level 1) chains are the largest, highest-scoring chains that span this region. In many cases gaps exist in the top-level chain. When possible, these are filled in by other chains that are displayed at level 2. The gaps in level 2 chains may be filled by level 3 chains and so forth. In the graphical display, the boxes represent ungapped alignments; the lines represent gaps. Click on a box to view detailed information about the chain as a whole; click on a line to display information about the gap. The detailed information is useful in determining the cause of the gap or, for lower level chains, the genomic rearrangement. Individual items in the display are categorized as one of four types (other than gap): Top - the best, longest match. Displayed on level 1. Syn - line-ups on the same chromosome as the gap in the level above it. Inv - a line-up on the same chromosome as the gap above it, but in the opposite orientation. NonSyn - a match to a chromosome different from the gap in the level above. Methods Chain track Transposons that have been inserted since the dog/rat split were removed from the assemblies. The abbreviated genomes were aligned with lastz, and the transposons were added back in. The resulting alignments were converted into axt format using the lavToAxt program. The axt alignments were fed into axtChain, which organizes all alignments between a single dog chromosome and a single rat chromosome into a group and creates a kd-tree out of the gapless subsections (blocks) of the alignments. A dynamic program was then run over the kd-trees to find the maximally scoring chains of these blocks. The following matrix was used: &nbsp;ACGT A91-114-31-123 C-114100-125-31 G-31-125100-114 T-123-31-11491 Chains scoring below a minimum score of &quot;1000&quot; were discarded; the remaining chains are displayed in this track. The linear gap matrix used with axtChain: -linearGap=loose tablesize 11 smallSize 111 position 1 2 3 11 111 2111 12111 32111 72111 152111 252111 qGap 325 360 400 450 600 1100 3600 7600 15600 31600 56600 tGap 325 360 400 450 600 1100 3600 7600 15600 31600 56600 bothGap 625 660 700 750 900 1400 4000 8000 16000 32000 57000 Net track Chains were derived from lastz alignments, using the methods described on the chain tracks description pages, and sorted with the highest-scoring chains in the genome ranked first. The program chainNet was then used to place the chains one at a time, trimming them as necessary to fit into sections not already covered by a higher-scoring chain. During this process, a natural hierarchy emerged in which a chain that filled a gap in a higher-scoring chain was placed underneath that chain. The program netSyntenic was used to fill in information about the relationship between higher- and lower-level chains, such as whether a lower-level chain was syntenic or inverted relative to the higher-level chain. The program netClass was then used to fill in how much of the gaps and chains contained Ns (sequencing gaps) in one or both species and how much was filled with transposons inserted before and after the two organisms diverged. Credits Lastz (previously known as blastz) was developed at Pennsylvania State University by Minmei Hou, Scott Schwartz, Zheng Zhang, and Webb Miller with advice from Ross Hardison. Lineage-specific repeats were identified by Arian Smit and his RepeatMasker program. The axtChain program was developed at the University of California at Santa Cruz by Jim Kent with advice from Webb Miller and David Haussler. The browser display and database storage of the chains and nets were created by Robert Baertsch and Jim Kent. The chainNet, netSyntenic, and netClass programs were developed at the University of California Santa Cruz by Jim Kent. References Harris, R.S. (2007) Improved pairwise alignment of genomic DNA Ph.D. Thesis, The Pennsylvania State University Chiaromonte F, Yap VB, Miller W. Scoring pairwise genomic sequence alignments. Pac Symp Biocomput. 2002:115-26. PMID: 11928468 Kent WJ, Baertsch R, Hinrichs A, Miller W, Haussler D. Evolution's cauldron: duplication, deletion, and rearrangement in the mouse and human genomes. Proc Natl Acad Sci U S A. 2003 Sep 30;100(20):11484-9. PMID: 14500911; PMC: PMC208784 Schwartz S, Kent WJ, Smit A, Zhang Z, Baertsch R, Hardison RC, Haussler D, Miller W. Human-mouse alignments with BLASTZ. Genome Res. 2003 Jan;13(1):103-7. PMID: 12529312; PMC: PMC430961 
chainNetCanFam2Viewnet Net Dog (May 2005 (Broad/canFam2)), Chain and Net Alignments Comparative Genomics 
netCanFam2 Dog Net Dog (May 2005 (Broad/canFam2)) Alignment Net Comparative Genomics Description This track shows regions of the genome that are alignable to other genomes (&quot;chain&quot; subtracks) or in synteny (&quot;net&quot; subtracks). The alignable parts are shown with thick blocks that look like exons. Non-alignable parts between these are shown like introns. Chain Track The chain track shows alignments of dog (May 2005 (Broad/canFam2)) to the rat genome using a gap scoring system that allows longer gaps than traditional affine gap scoring systems. It can also tolerate gaps in both dog and rat simultaneously. These &quot;double-sided&quot; gaps can be caused by local inversions and overlapping deletions in both species. The chain track displays boxes joined together by either single or double lines. The boxes represent aligning regions. Single lines indicate gaps that are largely due to a deletion in the dog assembly or an insertion in the rat assembly. Double lines represent more complex gaps that involve substantial sequence in both species. This may result from inversions, overlapping deletions, an abundance of local mutation, or an unsequenced gap in one species. In cases where multiple chains align over a particular region of the rat genome, the chains with single-lined gaps are often due to processed pseudogenes, while chains with double-lined gaps are more often due to paralogs and unprocessed pseudogenes. In the &quot;pack&quot; and &quot;full&quot; display modes, the individual feature names indicate the chromosome, strand, and location (in thousands) of the match for each matching alignment. Net Track The net track shows the best dog/rat chain for every part of the rat genome. It is useful for finding syntenic regions, possibly orthologs, and for studying genome rearrangement. The dog sequence used in this annotation is from the May 2005 (Broad/canFam2) assembly. Display Conventions and Configuration Chain Track By default, the chains to chromosome-based assemblies are colored based on which chromosome they map to in the aligning organism. To turn off the coloring, check the &quot;off&quot; button next to: Color track based on chromosome. To display only the chains of one chromosome in the aligning organism, enter the name of that chromosome (e.g. chr4) in box next to: Filter by chromosome. Net Track In full display mode, the top-level (level 1) chains are the largest, highest-scoring chains that span this region. In many cases gaps exist in the top-level chain. When possible, these are filled in by other chains that are displayed at level 2. The gaps in level 2 chains may be filled by level 3 chains and so forth. In the graphical display, the boxes represent ungapped alignments; the lines represent gaps. Click on a box to view detailed information about the chain as a whole; click on a line to display information about the gap. The detailed information is useful in determining the cause of the gap or, for lower level chains, the genomic rearrangement. Individual items in the display are categorized as one of four types (other than gap): Top - the best, longest match. Displayed on level 1. Syn - line-ups on the same chromosome as the gap in the level above it. Inv - a line-up on the same chromosome as the gap above it, but in the opposite orientation. NonSyn - a match to a chromosome different from the gap in the level above. Methods Chain track Transposons that have been inserted since the dog/rat split were removed from the assemblies. The abbreviated genomes were aligned with lastz, and the transposons were added back in. The resulting alignments were converted into axt format using the lavToAxt program. The axt alignments were fed into axtChain, which organizes all alignments between a single dog chromosome and a single rat chromosome into a group and creates a kd-tree out of the gapless subsections (blocks) of the alignments. A dynamic program was then run over the kd-trees to find the maximally scoring chains of these blocks. The following matrix was used: &nbsp;ACGT A91-114-31-123 C-114100-125-31 G-31-125100-114 T-123-31-11491 Chains scoring below a minimum score of &quot;1000&quot; were discarded; the remaining chains are displayed in this track. The linear gap matrix used with axtChain: -linearGap=loose tablesize 11 smallSize 111 position 1 2 3 11 111 2111 12111 32111 72111 152111 252111 qGap 325 360 400 450 600 1100 3600 7600 15600 31600 56600 tGap 325 360 400 450 600 1100 3600 7600 15600 31600 56600 bothGap 625 660 700 750 900 1400 4000 8000 16000 32000 57000 Net track Chains were derived from lastz alignments, using the methods described on the chain tracks description pages, and sorted with the highest-scoring chains in the genome ranked first. The program chainNet was then used to place the chains one at a time, trimming them as necessary to fit into sections not already covered by a higher-scoring chain. During this process, a natural hierarchy emerged in which a chain that filled a gap in a higher-scoring chain was placed underneath that chain. The program netSyntenic was used to fill in information about the relationship between higher- and lower-level chains, such as whether a lower-level chain was syntenic or inverted relative to the higher-level chain. The program netClass was then used to fill in how much of the gaps and chains contained Ns (sequencing gaps) in one or both species and how much was filled with transposons inserted before and after the two organisms diverged. Credits Lastz (previously known as blastz) was developed at Pennsylvania State University by Minmei Hou, Scott Schwartz, Zheng Zhang, and Webb Miller with advice from Ross Hardison. Lineage-specific repeats were identified by Arian Smit and his RepeatMasker program. The axtChain program was developed at the University of California at Santa Cruz by Jim Kent with advice from Webb Miller and David Haussler. The browser display and database storage of the chains and nets were created by Robert Baertsch and Jim Kent. The chainNet, netSyntenic, and netClass programs were developed at the University of California Santa Cruz by Jim Kent. References Harris, R.S. (2007) Improved pairwise alignment of genomic DNA Ph.D. Thesis, The Pennsylvania State University Chiaromonte F, Yap VB, Miller W. Scoring pairwise genomic sequence alignments. Pac Symp Biocomput. 2002:115-26. PMID: 11928468 Kent WJ, Baertsch R, Hinrichs A, Miller W, Haussler D. Evolution's cauldron: duplication, deletion, and rearrangement in the mouse and human genomes. Proc Natl Acad Sci U S A. 2003 Sep 30;100(20):11484-9. PMID: 14500911; PMC: PMC208784 Schwartz S, Kent WJ, Smit A, Zhang Z, Baertsch R, Hardison RC, Haussler D, Miller W. Human-mouse alignments with BLASTZ. Genome Res. 2003 Jan;13(1):103-7. PMID: 12529312; PMC: PMC430961 
chainNetCanFam2Viewchain Chain Dog (May 2005 (Broad/canFam2)), Chain and Net Alignments Comparative Genomics 
chainCanFam2 Dog Chain Dog (May 2005 (Broad/canFam2)) Chained Alignments Comparative Genomics Description This track shows regions of the genome that are alignable to other genomes (&quot;chain&quot; subtracks) or in synteny (&quot;net&quot; subtracks). The alignable parts are shown with thick blocks that look like exons. Non-alignable parts between these are shown like introns. Chain Track The chain track shows alignments of dog (May 2005 (Broad/canFam2)) to the rat genome using a gap scoring system that allows longer gaps than traditional affine gap scoring systems. It can also tolerate gaps in both dog and rat simultaneously. These &quot;double-sided&quot; gaps can be caused by local inversions and overlapping deletions in both species. The chain track displays boxes joined together by either single or double lines. The boxes represent aligning regions. Single lines indicate gaps that are largely due to a deletion in the dog assembly or an insertion in the rat assembly. Double lines represent more complex gaps that involve substantial sequence in both species. This may result from inversions, overlapping deletions, an abundance of local mutation, or an unsequenced gap in one species. In cases where multiple chains align over a particular region of the rat genome, the chains with single-lined gaps are often due to processed pseudogenes, while chains with double-lined gaps are more often due to paralogs and unprocessed pseudogenes. In the &quot;pack&quot; and &quot;full&quot; display modes, the individual feature names indicate the chromosome, strand, and location (in thousands) of the match for each matching alignment. Net Track The net track shows the best dog/rat chain for every part of the rat genome. It is useful for finding syntenic regions, possibly orthologs, and for studying genome rearrangement. The dog sequence used in this annotation is from the May 2005 (Broad/canFam2) assembly. Display Conventions and Configuration Chain Track By default, the chains to chromosome-based assemblies are colored based on which chromosome they map to in the aligning organism. To turn off the coloring, check the &quot;off&quot; button next to: Color track based on chromosome. To display only the chains of one chromosome in the aligning organism, enter the name of that chromosome (e.g. chr4) in box next to: Filter by chromosome. Net Track In full display mode, the top-level (level 1) chains are the largest, highest-scoring chains that span this region. In many cases gaps exist in the top-level chain. When possible, these are filled in by other chains that are displayed at level 2. The gaps in level 2 chains may be filled by level 3 chains and so forth. In the graphical display, the boxes represent ungapped alignments; the lines represent gaps. Click on a box to view detailed information about the chain as a whole; click on a line to display information about the gap. The detailed information is useful in determining the cause of the gap or, for lower level chains, the genomic rearrangement. Individual items in the display are categorized as one of four types (other than gap): Top - the best, longest match. Displayed on level 1. Syn - line-ups on the same chromosome as the gap in the level above it. Inv - a line-up on the same chromosome as the gap above it, but in the opposite orientation. NonSyn - a match to a chromosome different from the gap in the level above. Methods Chain track Transposons that have been inserted since the dog/rat split were removed from the assemblies. The abbreviated genomes were aligned with lastz, and the transposons were added back in. The resulting alignments were converted into axt format using the lavToAxt program. The axt alignments were fed into axtChain, which organizes all alignments between a single dog chromosome and a single rat chromosome into a group and creates a kd-tree out of the gapless subsections (blocks) of the alignments. A dynamic program was then run over the kd-trees to find the maximally scoring chains of these blocks. The following matrix was used: &nbsp;ACGT A91-114-31-123 C-114100-125-31 G-31-125100-114 T-123-31-11491 Chains scoring below a minimum score of &quot;1000&quot; were discarded; the remaining chains are displayed in this track. The linear gap matrix used with axtChain: -linearGap=loose tablesize 11 smallSize 111 position 1 2 3 11 111 2111 12111 32111 72111 152111 252111 qGap 325 360 400 450 600 1100 3600 7600 15600 31600 56600 tGap 325 360 400 450 600 1100 3600 7600 15600 31600 56600 bothGap 625 660 700 750 900 1400 4000 8000 16000 32000 57000 Net track Chains were derived from lastz alignments, using the methods described on the chain tracks description pages, and sorted with the highest-scoring chains in the genome ranked first. The program chainNet was then used to place the chains one at a time, trimming them as necessary to fit into sections not already covered by a higher-scoring chain. During this process, a natural hierarchy emerged in which a chain that filled a gap in a higher-scoring chain was placed underneath that chain. The program netSyntenic was used to fill in information about the relationship between higher- and lower-level chains, such as whether a lower-level chain was syntenic or inverted relative to the higher-level chain. The program netClass was then used to fill in how much of the gaps and chains contained Ns (sequencing gaps) in one or both species and how much was filled with transposons inserted before and after the two organisms diverged. Credits Lastz (previously known as blastz) was developed at Pennsylvania State University by Minmei Hou, Scott Schwartz, Zheng Zhang, and Webb Miller with advice from Ross Hardison. Lineage-specific repeats were identified by Arian Smit and his RepeatMasker program. The axtChain program was developed at the University of California at Santa Cruz by Jim Kent with advice from Webb Miller and David Haussler. The browser display and database storage of the chains and nets were created by Robert Baertsch and Jim Kent. The chainNet, netSyntenic, and netClass programs were developed at the University of California Santa Cruz by Jim Kent. References Harris, R.S. (2007) Improved pairwise alignment of genomic DNA Ph.D. Thesis, The Pennsylvania State University Chiaromonte F, Yap VB, Miller W. Scoring pairwise genomic sequence alignments. Pac Symp Biocomput. 2002:115-26. PMID: 11928468 Kent WJ, Baertsch R, Hinrichs A, Miller W, Haussler D. Evolution's cauldron: duplication, deletion, and rearrangement in the mouse and human genomes. Proc Natl Acad Sci U S A. 2003 Sep 30;100(20):11484-9. PMID: 14500911; PMC: PMC208784 Schwartz S, Kent WJ, Smit A, Zhang Z, Baertsch R, Hardison RC, Haussler D, Miller W. Human-mouse alignments with BLASTZ. Genome Res. 2003 Jan;13(1):103-7. PMID: 12529312; PMC: PMC430961