cpgIslandExt 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 other 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. The unmasked version of the track displays potential CpG islands that exist in repeat regions and would otherwise not be visible in the repeat masked version. By default, only the masked version of the track is displayed. To view the unmasked version, change the visibility settings in the track controls at the top of this page. Methods CpG islands were 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 was then evaluated for the following criteria: GC content of 50% or greater length greater than 200 bp ratio greater than 0.6 of observed number of CG dinucleotides to the expected number on the basis of the number of Gs and Cs in the segment The entire genome sequence, masking areas included, was used for the construction of the track Unmasked CpG. The track CpG Islands is constructed on the sequence after all masked sequence is removed. 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. The ratio of observed to expected CpG is calculated according to the formula (cited in Gardiner-Garden et al. (1987)): Obs/Exp CpG = Number of CpG * N / (Number of C * Number of G) where N = length of sequence. The calculation of the track data is performed by the following command sequence: twoBitToFa assembly.2bit stdout | maskOutFa stdin hard stdout \ | cpg_lh /dev/stdin 2&gt; cpg_lh.err \ | awk '{&dollar;2 = &dollar;2 - 1; width = &dollar;3 - &dollar;2; printf("%s\t%d\t%s\t%s %s\t%s\t%s\t%0.0f\t%0.1f\t%s\t%s\n", &dollar;1, &dollar;2, &dollar;3, &dollar;5, &dollar;6, width, &dollar;6, width*&dollar;7*0.01, 100.0*2*&dollar;6/width, &dollar;7, &dollar;9);}' \ | sort -k1,1 -k2,2n &gt; cpgIsland.bed The unmasked track data is constructed from twoBitToFa -noMask output for the twoBitToFa command. Data access CpG islands and its associated tables can be explored interactively using the REST API, the Table Browser or the Data Integrator. All the tables can also be queried directly from our public MySQL servers, with more information available on our help page as well as on our blog. The source for the cpg_lh program can be obtained from src/utils/cpgIslandExt/. The cpg_lh program binary can be obtained from: http://hgdownload.soe.ucsc.edu/admin/exe/linux.x86_64/cpg_lh (choose "save file") Credits This track was generated using a modification of a program developed by G. Miklem and L. Hillier (unpublished). References Gardiner-Garden M, Frommer M. CpG islands in vertebrate genomes. J Mol Biol. 1987 Jul 20;196(2):261-82. PMID: 3656447 
cpgIslandSuper 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 other 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. The unmasked version of the track displays potential CpG islands that exist in repeat regions and would otherwise not be visible in the repeat masked version. By default, only the masked version of the track is displayed. To view the unmasked version, change the visibility settings in the track controls at the top of this page. Methods CpG islands were 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 was then evaluated for the following criteria: GC content of 50% or greater length greater than 200 bp ratio greater than 0.6 of observed number of CG dinucleotides to the expected number on the basis of the number of Gs and Cs in the segment The entire genome sequence, masking areas included, was used for the construction of the track Unmasked CpG. The track CpG Islands is constructed on the sequence after all masked sequence is removed. 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. The ratio of observed to expected CpG is calculated according to the formula (cited in Gardiner-Garden et al. (1987)): Obs/Exp CpG = Number of CpG * N / (Number of C * Number of G) where N = length of sequence. The calculation of the track data is performed by the following command sequence: twoBitToFa assembly.2bit stdout | maskOutFa stdin hard stdout \ | cpg_lh /dev/stdin 2&gt; cpg_lh.err \ | awk '{&dollar;2 = &dollar;2 - 1; width = &dollar;3 - &dollar;2; printf("%s\t%d\t%s\t%s %s\t%s\t%s\t%0.0f\t%0.1f\t%s\t%s\n", &dollar;1, &dollar;2, &dollar;3, &dollar;5, &dollar;6, width, &dollar;6, width*&dollar;7*0.01, 100.0*2*&dollar;6/width, &dollar;7, &dollar;9);}' \ | sort -k1,1 -k2,2n &gt; cpgIsland.bed The unmasked track data is constructed from twoBitToFa -noMask output for the twoBitToFa command. Data access CpG islands and its associated tables can be explored interactively using the REST API, the Table Browser or the Data Integrator. All the tables can also be queried directly from our public MySQL servers, with more information available on our help page as well as on our blog. The source for the cpg_lh program can be obtained from src/utils/cpgIslandExt/. The cpg_lh program binary can be obtained from: http://hgdownload.soe.ucsc.edu/admin/exe/linux.x86_64/cpg_lh (choose "save file") Credits This track was generated using a modification of a program developed by G. Miklem and L. Hillier (unpublished). References Gardiner-Garden M, Frommer M. CpG islands in vertebrate genomes. J Mol Biol. 1987 Jul 20;196(2):261-82. PMID: 3656447 
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 &quot;makeDb/doc/&quot; directory. When analyzing the data tables of this track, keep in mind that Repbase is not the same as the Repeatmasker sequence database and that the repeat names in the Repeatmasker output are not the same as the sequence names in the Repeatmasker database. Concretely, you can find a name such as "L1PA4" in the Repeatmasker output and this track, but there is not necessarily a single sequence "L1PA4" in the Repeatmasker database. This is because Repeatmasker creates annotations by joining matches to partial pieces of the database together so there is no 1:1 relationship between its sequence database and the annotations. To learn more, you can read the Repeatmasker paper, its source code or reach out to the Repeatmasker authors, your local expert on transposable elements or us. 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 &quot;?&quot; at the end of the &quot;Family&quot; or &quot;Class&quot; (for example, DNA?) signifies that the curator was unsure of the classification. At some point in the future, either the &quot;?&quot; 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 
refGene RefSeq Genes RefSeq Genes Genes and Gene Predictions Description The RefSeq Genes track shows known gorilla 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 gorilla 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 
cpgIslandExtUnmasked Unmasked CpG CpG Islands on All Sequence (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 other 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. The unmasked version of the track displays potential CpG islands that exist in repeat regions and would otherwise not be visible in the repeat masked version. By default, only the masked version of the track is displayed. To view the unmasked version, change the visibility settings in the track controls at the top of this page. Methods CpG islands were 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 was then evaluated for the following criteria: GC content of 50% or greater length greater than 200 bp ratio greater than 0.6 of observed number of CG dinucleotides to the expected number on the basis of the number of Gs and Cs in the segment The entire genome sequence, masking areas included, was used for the construction of the track Unmasked CpG. The track CpG Islands is constructed on the sequence after all masked sequence is removed. 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. The ratio of observed to expected CpG is calculated according to the formula (cited in Gardiner-Garden et al. (1987)): Obs/Exp CpG = Number of CpG * N / (Number of C * Number of G) where N = length of sequence. The calculation of the track data is performed by the following command sequence: twoBitToFa assembly.2bit stdout | maskOutFa stdin hard stdout \ | cpg_lh /dev/stdin 2&gt; cpg_lh.err \ | awk '{&dollar;2 = &dollar;2 - 1; width = &dollar;3 - &dollar;2; printf("%s\t%d\t%s\t%s %s\t%s\t%s\t%0.0f\t%0.1f\t%s\t%s\n", &dollar;1, &dollar;2, &dollar;3, &dollar;5, &dollar;6, width, &dollar;6, width*&dollar;7*0.01, 100.0*2*&dollar;6/width, &dollar;7, &dollar;9);}' \ | sort -k1,1 -k2,2n &gt; cpgIsland.bed The unmasked track data is constructed from twoBitToFa -noMask output for the twoBitToFa command. Data access CpG islands and its associated tables can be explored interactively using the REST API, the Table Browser or the Data Integrator. All the tables can also be queried directly from our public MySQL servers, with more information available on our help page as well as on our blog. The source for the cpg_lh program can be obtained from src/utils/cpgIslandExt/. The cpg_lh program binary can be obtained from: http://hgdownload.soe.ucsc.edu/admin/exe/linux.x86_64/cpg_lh (choose "save file") Credits This track was generated using a modification of a program developed by G. Miklem and L. Hillier (unpublished). References Gardiner-Garden M, Frommer M. CpG islands in vertebrate genomes. J Mol Biol. 1987 Jul 20;196(2):261-82. PMID: 3656447 
gold Assembly Assembly from Fragments Mapping and Sequencing Description This track shows the sequences used in the Dec 2014 gorilla genome assembly. Genome assembly procedures are covered in the NCBI assembly documentation. NCBI also provides specific information about this assembly. The definition of this assembly is from the AGP file delivered with the sequence. The NCBI document AGP Specification describes the format of the AGP file. In dense mode, this track depicts the contigs that make up the currently viewed scaffold. Contig boundaries are distinguished by the use of alternating gold and brown coloration. Where gaps exist between contigs, spaces are shown between the gold and brown blocks. The relative order and orientation of the contigs within a scaffold is always known; therefore, a line is drawn in the graphical display to bridge the blocks. Component types found in this track (with counts of that type in parentheses): W - whole genome shotgun (170,086) 
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 K&ouml;nig 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 
cytoBandIdeo Chromosome Band (Ideogram) Ideogram for Orientation Mapping and Sequencing 
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 gorGor4 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 
evaSnpContainer EVA SNP Short Genetic Variants from European Variant Archive Variation and Repeats Description These tracks contain mappings of single nucleotide variants and small insertions and deletions (indels) from the European Variation Archive (EVA) for the gorilla gorGor4 genome. The dbSNP database at NCBI no longer hosts non-human variants. Interpreting and Configuring the Graphical Display Variants are shown as single tick marks at most zoom levels. When viewing the track at or near base-level resolution, the displayed width of the SNP variant corresponds to the width of the variant in the reference sequence. Insertions are indicated by a single tick mark displayed between two nucleotides, single nucleotide polymorphisms are displayed as the width of a single base, and multiple nucleotide variants are represented by a block that spans two or more bases. The display is set to automatically collapse to dense visibility when there are more than 100k variants in the window. When the window size is more than 250k bp, the display is switched to density graph mode. Searching, details, and filtering Navigation to an individual variant can be accomplished by typing or copying the variant identifier (rsID) or the genomic coordinates into the Position/Search box on the Browser. A click on an item in the graphical display displays a page with data about that variant. Data fields include the Reference and Alternate Alleles, the class of the variant as reported by EVA, the source of the data, the amino acid change, if any, and the functional class as determined by UCSC's Variant Annotation Integrator. Variants can be filtered using the track controls to show subsets of the data by either EVA Sequence Ontology (SO) term, UCSC-generated functional effect, or by color, which bins the UCSC functional effects into general classes. Mouse-over Mousing over an item shows the ucscClass, which is the consequence according to the Variant Annotation Integrator, and the aaChange when one is available, which is the change in amino acid in HGVS.p terms. Items may have multiple ucscClasses, which will all be shown in the mouse-over in a comma-separated list. Likewise, multiple HGVS.p terms may be shown for each rsID separated by spaces describing all possible AA changes. Multiple items may appear due to different variant predictions on multiple gene transcripts. For all organisms the gene models used were the NCBI RefSeq curated when available, if not then ensembl genes, or finally UCSC mappings of RefSeq if neither of the previous models was possible. Track colors Variants are colored according to the most potentially deleterious functional effect prediction according to the Variant Annotation Integrator. Specific bins can be seen in the Methods section below. Color Variant Type Protein-altering variants and splice site variants Synonymous codon variants Non-coding transcript or Untranslated Region (UTR) variants Intergenic and intronic variants Sequence ontology (SO) Variants are classified by EVA into one of the following sequence ontology terms: substitution &mdash; A single nucleotide in the reference is replaced by another, alternate allele deletion &mdash; One or more nucleotides is deleted. The representation in the database is to display one additional nucleotide in both the Reference field (Ref) and the Alternate Allele field (Alt). E.g. a variant that is a deletion of an A maybe be represented as Ref = GA and Alt = G. insertion &mdash; One or more nucleotides is inserted. The representation in the database is to display one additional nucleotide in both the Reference field (Ref) and the Alternate Allele field (Alt). E.g. a variant that is an insertion of a T maybe be represented as Ref = G and Alt = GT delins &mdash; Similar to tandemRepeat, in that the runs of Ref and Alt Alleles are of different length, except that there is more than one type of nucleotide, e.g., Ref = CCAAAAACAAAAACA, Alt = ACAAAAAC. multipleNucleotideVariant &mdash; More than one nucleotide is substituted by an equal number of different nucleotides, e.g., Ref = AA, Alt = GC. sequence alteration &mdash; A parent term meant to signify a deviation from another sequence. Can be assigned to variants that have not been characterized yet. Methods Data were downloaded from the European Variation Archive EVA current_ids.vcf.gz files corresponding to the proper assembly. Chromosome names were converted to UCSC-style and the variants passed through the Variant Annotation Integrator to predict consequence. For every organism the NCBI RefSeq curated models were used when available, followed by ensembl genes, and finally UCSC mapping of RefSeq when neither of the previous models were possible. Variants were then colored according to their predicted consequence in the following fashion: Protein-altering variants and splice site variants - exon_loss_variant, frameshift_variant, inframe_deletion, inframe_insertion, initiator_codon_variant, missense_variant, splice_acceptor_variant, splice_donor_variant, splice_region_variant, stop_gained, stop_lost, coding_sequence_variant, transcript_ablation Synonymous codon variants - synonymous_variant, stop_retained_variant Non-coding transcript or Untranslated Region (UTR) variants - 5_prime_UTR_variant, 3_prime_UTR_variant, complex_transcript_variant, non_coding_transcript_exon_variant Intergenic and intronic variants - upstream_gene_variant, downstream_gene_variant, intron_variant, intergenic_variant, NMD_transcript_variant, no_sequence_alteration Sequence Ontology (&quot;SO:&quot;) terms were converted to the variant classes, then the files were converted to BED, and then bigBed format. No functional annotations were provided by the EVA (e.g., missense, nonsense, etc). These were computed using UCSC's Variant Annotation Integrator (Hinrichs, et al., 2016). Amino-acid substitutions for missense variants are based on RefSeq alignments of mRNA transcripts, which do not always match the amino acids predicted from translating the genomic sequence. Therefore, in some instances, the variant and the genomic nucleotide and associated amino acid may be reversed. E.g., a Pro &gt; Arg change from the perspective of the mRNA would be Arg &gt; Pro from the persepective the genomic sequence. Also, in bosTau9, galGal5, rheMac8, danRer10 and danRer11 the mitochondrial sequence was removed or renamed to match UCSC. For complete documentation of the processing of these tracks, see the makedoc corresponding to the version of interest. For example, the EVA Release 6 MakeDoc. Data Access Note: It is not recommeneded to use LiftOver to convert SNPs between assemblies, and more information about how to convert SNPs between assemblies can be found on the following FAQ entry. The data can be explored interactively with the Table Browser, or the Data Integrator. For automated analysis, the data may be queried from our REST API. Please refer to our mailing list archives for questions, or our Data Access FAQ for more information. For automated download and analysis, this annotation is stored in a bigBed file that can be downloaded from our download server. Use the corresponding version number for the track of interest, e.g. evaSnp6.bb. Individual regions or the whole genome annotation can be obtained using our tool bigBedToBed which can be compiled from the source code or downloaded as a precompiled binary for your system. Instructions for downloading source code and binaries can be found here. The tool can also be used to obtain only features within a given range, e.g. bigBedToBed https://hgdownload.soe.ucsc.edu/gbdb/gorGor4/bbi/evaSnp6.bb -chrom=chr21 -start=0 -end=100000000 stdout Credits This track was produced from the European Variation Archive release data. Consequences were predicted using UCSC's Variant Annotation Integrator and NCBI's RefSeq as well as ensembl gene models. References Cezard T, Cunningham F, Hunt SE, Koylass B, Kumar N, Saunders G, Shen A, Silva AF, Tsukanov K, Venkataraman S et al. The European Variation Archive: a FAIR resource of genomic variation for all species. Nucleic Acids Res. 2021 Oct 28:gkab960. doi:10.1093/nar/gkab960. Epub ahead of print. PMID: 34718739. PMID: PMC8728205. Hinrichs AS, Raney BJ, Speir ML, Rhead B, Casper J, Karolchik D, Kuhn RM, Rosenbloom KR, Zweig AS, Haussler D, Kent WJ. UCSC Data Integrator and Variant Annotation Integrator. Bioinformatics. 2016 May 1;32(9):1430-2. PMID: 26740527; PMC: PMC4848401 
evaSnp6 EVA SNP Release 6 Short Genetic Variants from European Variant Archive Release 6 Variation and Repeats Description These tracks contain mappings of single nucleotide variants and small insertions and deletions (indels) from the European Variation Archive (EVA) for the gorilla gorGor4 genome. The dbSNP database at NCBI no longer hosts non-human variants. Interpreting and Configuring the Graphical Display Variants are shown as single tick marks at most zoom levels. When viewing the track at or near base-level resolution, the displayed width of the SNP variant corresponds to the width of the variant in the reference sequence. Insertions are indicated by a single tick mark displayed between two nucleotides, single nucleotide polymorphisms are displayed as the width of a single base, and multiple nucleotide variants are represented by a block that spans two or more bases. The display is set to automatically collapse to dense visibility when there are more than 100k variants in the window. When the window size is more than 250k bp, the display is switched to density graph mode. Searching, details, and filtering Navigation to an individual variant can be accomplished by typing or copying the variant identifier (rsID) or the genomic coordinates into the Position/Search box on the Browser. A click on an item in the graphical display displays a page with data about that variant. Data fields include the Reference and Alternate Alleles, the class of the variant as reported by EVA, the source of the data, the amino acid change, if any, and the functional class as determined by UCSC's Variant Annotation Integrator. Variants can be filtered using the track controls to show subsets of the data by either EVA Sequence Ontology (SO) term, UCSC-generated functional effect, or by color, which bins the UCSC functional effects into general classes. Mouse-over Mousing over an item shows the ucscClass, which is the consequence according to the Variant Annotation Integrator, and the aaChange when one is available, which is the change in amino acid in HGVS.p terms. Items may have multiple ucscClasses, which will all be shown in the mouse-over in a comma-separated list. Likewise, multiple HGVS.p terms may be shown for each rsID separated by spaces describing all possible AA changes. Multiple items may appear due to different variant predictions on multiple gene transcripts. For all organisms the gene models used were the NCBI RefSeq curated when available, if not then ensembl genes, or finally UCSC mappings of RefSeq if neither of the previous models was possible. Track colors Variants are colored according to the most potentially deleterious functional effect prediction according to the Variant Annotation Integrator. Specific bins can be seen in the Methods section below. Color Variant Type Protein-altering variants and splice site variants Synonymous codon variants Non-coding transcript or Untranslated Region (UTR) variants Intergenic and intronic variants Sequence ontology (SO) Variants are classified by EVA into one of the following sequence ontology terms: substitution &mdash; A single nucleotide in the reference is replaced by another, alternate allele deletion &mdash; One or more nucleotides is deleted. The representation in the database is to display one additional nucleotide in both the Reference field (Ref) and the Alternate Allele field (Alt). E.g. a variant that is a deletion of an A maybe be represented as Ref = GA and Alt = G. insertion &mdash; One or more nucleotides is inserted. The representation in the database is to display one additional nucleotide in both the Reference field (Ref) and the Alternate Allele field (Alt). E.g. a variant that is an insertion of a T maybe be represented as Ref = G and Alt = GT delins &mdash; Similar to tandemRepeat, in that the runs of Ref and Alt Alleles are of different length, except that there is more than one type of nucleotide, e.g., Ref = CCAAAAACAAAAACA, Alt = ACAAAAAC. multipleNucleotideVariant &mdash; More than one nucleotide is substituted by an equal number of different nucleotides, e.g., Ref = AA, Alt = GC. sequence alteration &mdash; A parent term meant to signify a deviation from another sequence. Can be assigned to variants that have not been characterized yet. Methods Data were downloaded from the European Variation Archive EVA current_ids.vcf.gz files corresponding to the proper assembly. Chromosome names were converted to UCSC-style and the variants passed through the Variant Annotation Integrator to predict consequence. For every organism the NCBI RefSeq curated models were used when available, followed by ensembl genes, and finally UCSC mapping of RefSeq when neither of the previous models were possible. Variants were then colored according to their predicted consequence in the following fashion: Protein-altering variants and splice site variants - exon_loss_variant, frameshift_variant, inframe_deletion, inframe_insertion, initiator_codon_variant, missense_variant, splice_acceptor_variant, splice_donor_variant, splice_region_variant, stop_gained, stop_lost, coding_sequence_variant, transcript_ablation Synonymous codon variants - synonymous_variant, stop_retained_variant Non-coding transcript or Untranslated Region (UTR) variants - 5_prime_UTR_variant, 3_prime_UTR_variant, complex_transcript_variant, non_coding_transcript_exon_variant Intergenic and intronic variants - upstream_gene_variant, downstream_gene_variant, intron_variant, intergenic_variant, NMD_transcript_variant, no_sequence_alteration Sequence Ontology (&quot;SO:&quot;) terms were converted to the variant classes, then the files were converted to BED, and then bigBed format. No functional annotations were provided by the EVA (e.g., missense, nonsense, etc). These were computed using UCSC's Variant Annotation Integrator (Hinrichs, et al., 2016). Amino-acid substitutions for missense variants are based on RefSeq alignments of mRNA transcripts, which do not always match the amino acids predicted from translating the genomic sequence. Therefore, in some instances, the variant and the genomic nucleotide and associated amino acid may be reversed. E.g., a Pro &gt; Arg change from the perspective of the mRNA would be Arg &gt; Pro from the persepective the genomic sequence. Also, in bosTau9, galGal5, rheMac8, danRer10 and danRer11 the mitochondrial sequence was removed or renamed to match UCSC. For complete documentation of the processing of these tracks, see the makedoc corresponding to the version of interest. For example, the EVA Release 6 MakeDoc. Data Access Note: It is not recommeneded to use LiftOver to convert SNPs between assemblies, and more information about how to convert SNPs between assemblies can be found on the following FAQ entry. The data can be explored interactively with the Table Browser, or the Data Integrator. For automated analysis, the data may be queried from our REST API. Please refer to our mailing list archives for questions, or our Data Access FAQ for more information. For automated download and analysis, this annotation is stored in a bigBed file that can be downloaded from our download server. Use the corresponding version number for the track of interest, e.g. evaSnp6.bb. Individual regions or the whole genome annotation can be obtained using our tool bigBedToBed which can be compiled from the source code or downloaded as a precompiled binary for your system. Instructions for downloading source code and binaries can be found here. The tool can also be used to obtain only features within a given range, e.g. bigBedToBed https://hgdownload.soe.ucsc.edu/gbdb/gorGor4/bbi/evaSnp6.bb -chrom=chr21 -start=0 -end=100000000 stdout Credits This track was produced from the European Variation Archive release data. Consequences were predicted using UCSC's Variant Annotation Integrator and NCBI's RefSeq as well as ensembl gene models. References Cezard T, Cunningham F, Hunt SE, Koylass B, Kumar N, Saunders G, Shen A, Silva AF, Tsukanov K, Venkataraman S et al. The European Variation Archive: a FAIR resource of genomic variation for all species. Nucleic Acids Res. 2021 Oct 28:gkab960. doi:10.1093/nar/gkab960. Epub ahead of print. PMID: 34718739. PMID: PMC8728205. Hinrichs AS, Raney BJ, Speir ML, Rhead B, Casper J, Karolchik D, Kuhn RM, Rosenbloom KR, Zweig AS, Haussler D, Kent WJ. UCSC Data Integrator and Variant Annotation Integrator. Bioinformatics. 2016 May 1;32(9):1430-2. PMID: 26740527; PMC: PMC4848401 
evaSnp5 EVA SNP Release 5 Short Genetic Variants from European Variant Archive Release 5 Variation and Repeats Description This track contains mappings of single nucleotide variants and small insertions and deletions (indels) from the European Variation Archive (EVA) Release 5 for the gorilla gorGor4 genome. The dbSNP database at NCBI no longer hosts non-human variants. Interpreting and Configuring the Graphical Display Variants are shown as single tick marks at most zoom levels. When viewing the track at or near base-level resolution, the displayed width of the SNP variant corresponds to the width of the variant in the reference sequence. Insertions are indicated by a single tick mark displayed between two nucleotides, single nucleotide polymorphisms are displayed as the width of a single base, and multiple nucleotide variants are represented by a block that spans two or more bases. The display is set to automatically collapse to dense visibility when there are more than 100k variants in the window. When the window size is more than 250k bp, the display is switched to density graph mode. Searching, details, and filtering Navigation to an individual variant can be accomplished by typing or copying the variant identifier (rsID) or the genomic coordinates into the Position/Search box on the Browser. A click on an item in the graphical display displays a page with data about that variant. Data fields include the Reference and Alternate Alleles, the class of the variant as reported by EVA, the source of the data, the amino acid change, if any, and the functional class as determined by UCSC's Variant Annotation Integrator. Variants can be filtered using the track controls to show subsets of the data by either EVA Sequence Ontology (SO) term, UCSC-generated functional effect, or by color, which bins the UCSC functional effects into general classes. Mouse-over Mousing over an item shows the ucscClass, which is the consequence according to the Variant Annotation Integrator, and the aaChange when one is available, which is the change in amino acid in HGVS.p terms. Items may have multiple ucscClasses, which will all be shown in the mouse-over in a comma-separated list. Likewise, multiple HGVS.p terms may be shown for each rsID separated by spaces describing all possible AA changes. Multiple items may appear due to different variant predictions on multiple gene transcripts. For all organisms the gene models used were the NCBI RefSeq curated when available, if not then ensembl genes, or finally UCSC mappings of RefSeq if neither of the previous models was possible. Track colors Variants are colored according to the most potentially deleterious functional effect prediction according to the Variant Annotation Integrator. Specific bins can be seen in the Methods section below. Color Variant Type Protein-altering variants and splice site variants Synonymous codon variants Non-coding transcript or Untranslated Region (UTR) variants Intergenic and intronic variants Sequence ontology (SO) Variants are classified by EVA into one of the following sequence ontology terms: substitution &mdash; A single nucleotide in the reference is replaced by another, alternate allele deletion &mdash; One or more nucleotides is deleted. The representation in the database is to display one additional nucleotide in both the Reference field (Ref) and the Alternate Allele field (Alt). E.g. a variant that is a deletion of an A maybe be represented as Ref = GA and Alt = G. insertion &mdash; One or more nucleotides is inserted. The representation in the database is to display one additional nucleotide in both the Reference field (Ref) and the Alternate Allele field (Alt). E.g. a variant that is an insertion of a T maybe be represented as Ref = G and Alt = GT delins &mdash; Similar to tandemRepeat, in that the runs of Ref and Alt Alleles are of different length, except that there is more than one type of nucleotide, e.g., Ref = CCAAAAACAAAAACA, Alt = ACAAAAAC. multipleNucleotideVariant &mdash; More than one nucleotide is substituted by an equal number of different nucleotides, e.g., Ref = AA, Alt = GC. sequence alteration &mdash; A parent term meant to signify a deviation from another sequence. Can be assigned to variants that have not been characterized yet. Methods Data were downloaded from the European Variation Archive EVA release 5 (2023-9-7) current_ids.vcf.gz files corresponding to the proper assembly. Chromosome names were converted to UCSC-style and the variants passed through the Variant Annotation Integrator to predict consequence. For every organism the NCBI RefSeq curated models were used when available, followed by ensembl genes, and finally UCSC mapping of RefSeq when neither of the previous models were possible. Variants were then colored according to their predicted consequence in the following fashion: Protein-altering variants and splice site variants - exon_loss_variant, frameshift_variant, inframe_deletion, inframe_insertion, initiator_codon_variant, missense_variant, splice_acceptor_variant, splice_donor_variant, splice_region_variant, stop_gained, stop_lost, coding_sequence_variant, transcript_ablation Synonymous codon variants - synonymous_variant, stop_retained_variant Non-coding transcript or Untranslated Region (UTR) variants - 5_prime_UTR_variant, 3_prime_UTR_variant, complex_transcript_variant, non_coding_transcript_exon_variant Intergenic and intronic variants - upstream_gene_variant, downstream_gene_variant, intron_variant, intergenic_variant, NMD_transcript_variant, no_sequence_alteration Sequence Ontology (&quot;SO:&quot;) terms were converted to the variant classes, then the files were converted to BED, and then bigBed format. No functional annotations were provided by the EVA (e.g., missense, nonsense, etc). These were computed using UCSC's Variant Annotation Integrator (Hinrichs, et al., 2016). Amino-acid substitutions for missense variants are based on RefSeq alignments of mRNA transcripts, which do not always match the amino acids predicted from translating the genomic sequence. Therefore, in some instances, the variant and the genomic nucleotide and associated amino acid may be reversed. E.g., a Pro &gt; Arg change from the perspective of the mRNA would be Arg &gt; Pro from the persepective the genomic sequence. Also, in bosTau9, galGal5, rheMac8, danRer10 and danRer11 the mitochondrial sequence was removed or renamed to match UCSC. For complete documentation of the processing of these tracks, read the EVA Release 5 MakeDoc. Data Access Note: It is not recommeneded to use LiftOver to convert SNPs between assemblies, and more information about how to convert SNPs between assemblies can be found on the following FAQ entry. The data can be explored interactively with the Table Browser, or the Data Integrator. For automated analysis, the data may be queried from our REST API. Please refer to our mailing list archives for questions, or our Data Access FAQ for more information. For automated download and analysis, this annotation is stored in a bigBed file that can be downloaded from our download server. The file for this track is called evaSnp5.bb. Individual regions or the whole genome annotation can be obtained using our tool bigBedToBed which can be compiled from the source code or downloaded as a precompiled binary for your system. Instructions for downloading source code and binaries can be found here. The tool can also be used to obtain only features within a given range, e.g. bigBedToBed https://hgdownload.soe.ucsc.edu/gbdb/gorGor4/bbi/evaSnp5.bb -chrom=chr21 -start=0 -end=100000000 stdout Credits This track was produced from the European Variation Archive release 5 data. Consequences were predicted using UCSC's Variant Annotation Integrator and NCBI's RefSeq as well as ensembl gene models. References Cezard T, Cunningham F, Hunt SE, Koylass B, Kumar N, Saunders G, Shen A, Silva AF, Tsukanov K, Venkataraman S et al. The European Variation Archive: a FAIR resource of genomic variation for all species. Nucleic Acids Res. 2021 Oct 28:gkab960. doi:10.1093/nar/gkab960. Epub ahead of print. PMID: 34718739. PMID: PMC8728205. Hinrichs AS, Raney BJ, Speir ML, Rhead B, Casper J, Karolchik D, Kuhn RM, Rosenbloom KR, Zweig AS, Haussler D, Kent WJ. UCSC Data Integrator and Variant Annotation Integrator. Bioinformatics. 2016 May 1;32(9):1430-2. PMID: 26740527; PMC: PMC4848401 
evaSnp4 EVA SNP Release 4 Short Genetic Variants from European Variant Archive Release 4 Variation and Repeats Description This track contains mappings of single nucleotide variants and small insertions and deletions (indels) from the European Variation Archive (EVA) Release 4 for the gorilla gorGor4 genome. The dbSNP database at NCBI no longer hosts non-human variants. Interpreting and Configuring the Graphical Display Variants are shown as single tick marks at most zoom levels. When viewing the track at or near base-level resolution, the displayed width of the SNP variant corresponds to the width of the variant in the reference sequence. Insertions are indicated by a single tick mark displayed between two nucleotides, single nucleotide polymorphisms are displayed as the width of a single base, and multiple nucleotide variants are represented by a block that spans two or more bases. The display is set to automatically collapse to dense visibility when there are more than 100k variants in the window. When the window size is more than 250k bp, the display is switched to density graph mode. Searching, details, and filtering Navigation to an individual variant can be accomplished by typing or copying the variant identifier (rsID) or the genomic coordinates into the Position/Search box on the Browser. A click on an item in the graphical display displays a page with data about that variant. Data fields include the Reference and Alternate Alleles, the class of the variant as reported by EVA, the source of the data, the amino acid change, if any, and the functional class as determined by UCSC's Variant Annotation Integrator. Variants can be filtered using the track controls to show subsets of the data by either EVA Sequence Ontology (SO) term, UCSC-generated functional effect, or by color, which bins the UCSC functional effects into general classes. Mouse-over Mousing over an item shows the ucscClass, which is the consequence according to the Variant Annotation Integrator, and the aaChange when one is available, which is the change in amino acid in HGVS.p terms. Items may have multiple ucscClasses, which will all be shown in the mouse-over in a comma-separated list. Likewise, multiple HGVS.p terms may be shown for each rsID separated by spaces describing all possible AA changes. Multiple items may appear due to different variant predictions on multiple gene transcripts. For all organisms the gene models used were the NCBI RefSeq curated when available, if not then ensembl genes, or finally UCSC mappings of RefSeq if neither of the previous models was possible. Track colors Variants are colored according to the most potentially deleterious functional effect prediction according to the Variant Annotation Integrator. Specific bins can be seen in the Methods section below. Color Variant Type Protein-altering variants and splice site variants Synonymous codon variants Non-coding transcript or Untranslated Region (UTR) variants Intergenic and intronic variants Sequence ontology (SO) Variants are classified by EVA into one of the following sequence ontology terms: substitution &mdash; A single nucleotide in the reference is replaced by another, alternate allele deletion &mdash; One or more nucleotides is deleted. The representation in the database is to display one additional nucleotide in both the Reference field (Ref) and the Alternate Allele field (Alt). E.g. a variant that is a deletion of an A maybe be represented as Ref = GA and Alt = G. insertion &mdash; One or more nucleotides is inserted. The representation in the database is to display one additional nucleotide in both the Reference field (Ref) and the Alternate Allele field (Alt). E.g. a variant that is an insertion of a T maybe be represented as Ref = G and Alt = GT delins &mdash; Similar to tandemRepeat, in that the runs of Ref and Alt Alleles are of different length, except that there is more than one type of nucleotide, e.g., Ref = CCAAAAACAAAAACA, Alt = ACAAAAAC. multipleNucleotideVariant &mdash; More than one nucleotide is substituted by an equal number of different nucleotides, e.g., Ref = AA, Alt = GC. sequence alteration &mdash; A parent term meant to signify a deviation from another sequence. Can be assigned to variants that have not been characterized yet. Methods Data were downloaded from the European Variation Archive EVA release 4 (2022-11-21) current_ids.vcf.gz files corresponding to the proper assembly. Chromosome names were converted to UCSC-style and the variants passed through the Variant Annotation Integrator to predict consequence. For every organism the NCBI RefSeq curated models were used when available, followed by ensembl genes, and finally UCSC mapping of RefSeq when neither of the previous models were possible. Variants were then colored according to their predicted consequence in the following fashion: Protein-altering variants and splice site variants - exon_loss_variant, frameshift_variant, inframe_deletion, inframe_insertion, initiator_codon_variant, missense_variant, splice_acceptor_variant, splice_donor_variant, splice_region_variant, stop_gained, stop_lost, coding_sequence_variant, transcript_ablation Synonymous codon variants - synonymous_variant, stop_retained_variant Non-coding transcript or Untranslated Region (UTR) variants - 5_prime_UTR_variant, 3_prime_UTR_variant, complex_transcript_variant, non_coding_transcript_exon_variant Intergenic and intronic variants - upstream_gene_variant, downstream_gene_variant, intron_variant, intergenic_variant, NMD_transcript_variant, no_sequence_alteration Sequence Ontology (&quot;SO:&quot;) terms were converted to the variant classes, then the files were converted to BED, and then bigBed format. No functional annotations were provided by the EVA (e.g., missense, nonsense, etc). These were computed using UCSC's Variant Annotation Integrator (Hinrichs, et al., 2016). Amino-acid substitutions for missense variants are based on RefSeq alignments of mRNA transcripts, which do not always match the amino acids predicted from translating the genomic sequence. Therefore, in some instances, the variant and the genomic nucleotide and associated amino acid may be reversed. E.g., a Pro &gt; Arg change from the perspective of the mRNA would be Arg &gt; Pro from the persepective the genomic sequence. Also, in bosTau9, galGal5, rheMac8, danRer10 and danRer11 the mitochondrial sequence was removed or renamed to match UCSC. For complete documentation of the processing of these tracks, read the EVA Release 4 MakeDoc. Data Access Note: It is not recommeneded to use LiftOver to convert SNPs between assemblies, and more information about how to convert SNPs between assemblies can be found on the following FAQ entry. The data can be explored interactively with the Table Browser, or the Data Integrator. For automated analysis, the data may be queried from our REST API. Please refer to our mailing list archives for questions, or our Data Access FAQ for more information. For automated download and analysis, this annotation is stored in a bigBed file that can be downloaded from our download server. The file for this track is called evaSnp4.bb. Individual regions or the whole genome annotation can be obtained using our tool bigBedToBed which can be compiled from the source code or downloaded as a precompiled binary for your system. Instructions for downloading source code and binaries can be found here. The tool can also be used to obtain only features within a given range, e.g. bigBedToBed https://hgdownload.soe.ucsc.edu/gbdb/gorGor4/bbi/evaSnp4.bb -chrom=chr21 -start=0 -end=100000000 stdout Credits This track was produced from the European Variation Archive release 4 data. Consequences were predicted using UCSC's Variant Annotation Integrator and NCBI's RefSeq as well as ensembl gene models. References Cezard T, Cunningham F, Hunt SE, Koylass B, Kumar N, Saunders G, Shen A, Silva AF, Tsukanov K, Venkataraman S et al. The European Variation Archive: a FAIR resource of genomic variation for all species. Nucleic Acids Res. 2021 Oct 28:gkab960. doi:10.1093/nar/gkab960. Epub ahead of print. PMID: 34718739. PMID: PMC8728205. Hinrichs AS, Raney BJ, Speir ML, Rhead B, Casper J, Karolchik D, Kuhn RM, Rosenbloom KR, Zweig AS, Haussler D, Kent WJ. UCSC Data Integrator and Variant Annotation Integrator. Bioinformatics. 2016 May 1;32(9):1430-2. PMID: 26740527; PMC: PMC4848401 
gap Gap Gap Locations Mapping and Sequencing Description This track shows the gaps in the Dec 2014 gorilla genome assembly. Genome assembly procedures are covered in the NCBI assembly documentation. NCBI also provides specific information about this assembly. The definition of the gaps in this assembly is from the AGP file delivered with the sequence. The NCBI document AGP Specification describes the format of the AGP file. 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 supported by read pair data, 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: centromere - gaps for centromeres are included when they can be reasonably localized (count: 19; size range: 99,581 - 3,000,000 bases) scaffold - gaps between scaffolds in chromosome assemblies (count: 129,375; size range: 10 - 178,037 bases) 
gc5BaseBw GC Percent GC Percent in 5-Base Windows Mapping and Sequencing Description The GC percent track shows the percentage of G (guanine) and C (cytosine) bases in 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 apsects of the displayed information. Click the &quot;Graph configuration help&quot; link for an explanation of the configuration options. Credits The data and presentation of this graph were prepared by Hiram Clawson. 
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 
mrna Gorilla mRNAs Gorilla mRNAs from GenBank mRNA and EST Description The mRNA track shows alignments between gorilla 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 &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 GenBank gorilla 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 
ucscToINSDC INSDC Accession at INSDC - International Nucleotide Sequence Database Collaboration Mapping and Sequencing Description This track associates UCSC Genome Browser chromosome names to accession names from the International Nucleotide Sequence Database Collaboration (INSDC). The data were downloaded from the NCBI assembly database. Credits The data for this track was prepared by Hiram Clawson. 
nestedRepeats Interrupted Rpts Fragments of Interrupted Repeats Joined by RepeatMasker ID Variation and Repeats Description This track shows joined fragments of interrupted repeats extracted from the output of the RepeatMasker program which screens DNA sequences for interspersed repeats and low complexity DNA sequences using 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. The detailed annotations from RepeatMasker are in the RepeatMasker track. This track shows fragments of original repeat insertions which have been interrupted by insertions of younger repeats or through local rearrangements. The fragments are joined using the ID column of RepeatMasker output. Display Conventions and Configuration In pack or full mode, each interrupted repeat is displayed as boxes (fragments) joined by horizontal lines, labeled with the repeat name. If all fragments are on the same strand, arrows are added to the horizontal line to indicate the strand. In dense or squish mode, labels and arrows are omitted and in dense mode, all items are collapsed to fit on a single row. Items are shaded according to the average identity score of their fragments. Usually, the shade of an item is similar to the shades of its fragments unless some fragments are much more diverged than others. The score displayed above is the average identity score, clipped to a range of 50% - 100% and then mapped to the range 0 - 1000 for shading in the browser. Methods UCSC has used the most current versions of the RepeatMasker software and repeat libraries available to generate these data. Note that these versions may be newer than those that are publicly available on the Internet. Data are generated using the RepeatMasker -s flag. Additional flags may be used for certain organisms. 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 
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 
xenoRefGene Other RefSeq Non-Gorilla RefSeq Genes Genes and Gene Predictions Description This track shows known protein-coding and non-protein-coding genes for organisms other than gorilla, 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 gorilla 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 
ucscToRefSeq RefSeq Acc RefSeq Accession Mapping and Sequencing Description This track associates UCSC Genome Browser chromosome names to accession identifiers from the NCBI Reference Sequence Database (RefSeq). The data were downloaded from the NCBI assembly database. Credits The data for this track was prepared by Hiram Clawson. 
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 
windowmaskerSdust WM + SDust Genomic Intervals Masked by WindowMasker + SDust Variation and Repeats Description This track depicts masked sequence as determined by WindowMasker. The WindowMasker tool is included in the NCBI C++ toolkit. The source code for the entire toolkit is available from the NCBI FTP site. Methods To create this track, WindowMasker was run with the following parameters: windowmasker -mk_counts true -input gorGor4.fa -output wm_counts windowmasker -ustat wm_counts -sdust true -input gorGor4.fa -output repeats.bed The repeats.bed (BED3) file was loaded into the &quot;windowmaskerSdust&quot; table for this track. References Morgulis A, Gertz EM, Sch&auml;ffer AA, Agarwala R. WindowMasker: window-based masker for sequenced genomes. Bioinformatics. 2006 Jan 15;22(2):134-41. PMID: 16287941 
chainNetHg38 Human Chain/Net Human (Dec. 2013 (GRCh38/hg38)), 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 (Dec. 2013 (GRCh38/hg38)) to the gorilla 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 gorilla 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 gorilla 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 gorilla 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/gorilla chain for every part of the gorilla 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 Dec. 2013 (GRCh38/hg38) 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/gorilla 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 gorilla 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 A90-330-236-356 C-330100-318-236 G-236-318100-330 T-356-236-33090 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 
chainNetHg38Viewnet Net Human (Dec. 2013 (GRCh38/hg38)), Chain and Net Alignments Comparative Genomics 
netHg38 Human Net Human (Dec. 2013 (GRCh38/hg38)) 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 (Dec. 2013 (GRCh38/hg38)) to the gorilla 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 gorilla 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 gorilla 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 gorilla 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/gorilla chain for every part of the gorilla 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 Dec. 2013 (GRCh38/hg38) 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/gorilla 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 gorilla 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 A90-330-236-356 C-330100-318-236 G-236-318100-330 T-356-236-33090 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 
chainNetHg38Viewchain Chain Human (Dec. 2013 (GRCh38/hg38)), Chain and Net Alignments Comparative Genomics 
chainHg38 Human Chain Human (Dec. 2013 (GRCh38/hg38)) 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 (Dec. 2013 (GRCh38/hg38)) to the gorilla 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 gorilla 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 gorilla 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 gorilla 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/gorilla chain for every part of the gorilla 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 Dec. 2013 (GRCh38/hg38) 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/gorilla 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 gorilla 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 A90-330-236-356 C-330100-318-236 G-236-318100-330 T-356-236-33090 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