intronEst Spliced ESTs C. briggsae ESTs That Have Been Spliced mRNA and EST Description This track shows alignments between C. briggsae 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. one that is at least 32 bases in length and has 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 C. briggsae 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. 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. 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, C. briggsae 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, 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 
gold Assembly Assembly from Fragments Mapping and Sequencing Description This track shows the draft assembly of the C. briggsae genome. To quote from the WormBase README: "This sequence version makes minor modifications to the original Cb1 (cb25.agp8) sequence assembly and uses a genetic map to align the contigs along chromosomes. The Cb1 assembly was produced for the C. briggsae strain AF16 from 2.05 million whole genome shotgun (WGS) reads, of which 88.2% were in read pairs. The sequence reads were generated at Washington University School of Medicine's Genome Sequencing Center and the Sanger Centre (Hinxton, UK). The Phusion (Mullikin, J) assembler was used to assemble the WGS reads into contigs based on overlap information, and then into supercontigs using read pair information to cross gaps. These supercontigs were assembled into mapped ultracontigs based on FPC fingerprint mapping (generated at Washington University School of Medicine's Genome Sequencing Center), with material from previously finished clones used to bridge gaps. Using the sequence data to identify SNPs between AF16 and HK104 and to distribute primers along major ultracontigs, a genetic map (Ray Miller, Washington University School of Medicine) was constructed using recombinant inbred lines (Scott E. Baird, Wright State University) which yielded 6 chromosomes. The genetic mapping data along with underlying read pairing data were used to break several misassemblies in ultracontigs and to order and orient the sequences along the C. briggsae chromosomes to create the Cb3 release." In dense mode, this track depicts the ultracontigs that make up the currently viewed chromosome. Ultracontig boundaries are distinguished by the use of alternating gold and brown coloration. There are 100 base gaps between ultracontigs. All components within this track are of fragment type "W": Whole Genome Shotgun contig. Credits The Jan. 2007 Caenorhabditis briggsae draft assembly produced by the Washington University School of Medicine GSC with the following data usage policy. 
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 
est C. briggsae ESTs C. briggsae ESTs Including Unspliced mRNA and EST Description This track shows alignments between C. briggsae 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 "tissue" table contains all the types of tissues that can be entered into the tissue text box. 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. 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, C. briggsae 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, 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 
mrna C. briggsae mRNAs C. briggsae mRNAs from GenBank mRNA and EST Description The mRNA track shows alignments between C. briggsae 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. 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. Methods GenBank C. briggsae 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, 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 
gap Gap Gap Locations Mapping and Sequencing Description This track depicts gaps in the assembly. Gaps are represented as black boxes in this track. All these gaps are arbitrary 100 base pair gaps between ultracontigs. The relative order and orientation of the ultracontigs is not known on this artifical chrUn assembly. None of these gaps are bridged. This assembly contains the following principal types of gaps: clone - gaps between the Whole Genome Shotgun ultracontigs contig - gaps between the Whole Genome Shotgun ultracontigs Credits The Jan. 2007 Caenorhabditis briggsae draft assembly produced by the Washington University School of Medicine GSC with the following data usage policy. 
gc5Base 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 "Graph configuration help" link for an explanation of the configuration options. Credits The data and presentation of this graph were prepared by Hiram Clawson. 
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 
xenoMrna Other mRNAs Non-C. briggsae mRNAs from GenBank mRNA and EST Description This track displays translated blat alignments of vertebrate and invertebrate mRNA in GenBank from organisms other than C. briggsae. 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 "tissue" table contains all the types of tissues that can be entered into the tissue text box. 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. Methods The mRNAs were aligned against the C. briggsae 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, 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 
xenoRefGene Other RefSeq Non-C. briggsae RefSeq Genes Genes and Gene Predictions Description This track shows known protein-coding and non-protein-coding genes for organisms other than C. briggsae, 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 C. briggsae 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 
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 
tRNAs tRNA Genes Transfer RNA Genes Identified with tRNAscan-SE Genes and Gene Predictions Description This track displays tRNA genes predicted by using tRNAscan-SE v.1.23. tRNAscan-SE is an integrated program that uses tRNAscan (Fichant) and an A/B box motif detection algorithm (Pavesi) as pre-filters to obtain an initial list of tRNA candidates. The program then filters these candidates with a covariance model-based search program COVE (Eddy) to obtain a highly specific set of primary sequence and secondary structure predictions that represent 99-100% of true tRNAs with a false positive rate of fewer than 1 per 15 gigabases. Detailed tRNA annotations for eukaryotes, bacteria, and archaea are available at Genomic tRNA Database (GtRNAdb). What does the tRNAscan-SE score mean? Anything with a score above 20 bits is likely to be derived from a tRNA, although this does not indicate whether the tRNA gene still encodes a functional tRNA molecule (i.e. tRNA-derived SINES probably do not function in the ribosome in translation). Vertebrate tRNAs with scores of >60.0 (bits) are likely to encode functional tRNA genes, and those with scores below ~45 have sequence or structural features that indicate they probably are no longer involved in translation. tRNAs with scores between 45-60 bits are in the "grey" zone, and may or may not have all the required features to be functional. In these cases, tRNAs should be inspected carefully for loss of specific primary or secondary structure features (usually in alignments with other genes of the same isotype), in order to make a better educated guess. These rough score range guides are not exact, nor are they based on specific biochemical studies of atypical tRNA features, so please treat them accordingly. Please note that tRNA genes marked as "Pseudo" are low scoring predictions that are mostly pseudogenes or tRNA-derived elements. These genes do not usually fold into a typical cloverleaf tRNA secondary structure and the provided images of the predicted secondary structures may appear rotated. Credits Both tRNAscan-SE and GtRNAdb are maintained by the Lowe Lab at UCSC. Cove-predicted tRNA secondary structures were rendered by NAVIEW (c) 1988 Robert E. Bruccoleri. References When making use of these data, please cite the following articles: Chan PP, Lowe TM. GtRNAdb: a database of transfer RNA genes detected in genomic sequence. Nucleic Acids Res. 2009 Jan;37(Database issue):D93-7. PMID: 18984615; PMC: PMC2686519 Eddy SR, Durbin R. RNA sequence analysis using covariance models. Nucleic Acids Res. 1994 Jun 11;22(11):2079-88. PMID: 8029015; PMC: PMC308124 Fichant GA, Burks C. Identifying potential tRNA genes in genomic DNA sequences. J Mol Biol. 1991 Aug 5;220(3):659-71. PMID: 1870126 Lowe TM, Eddy SR. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 1997 Mar 1;25(5):955-64. PMID: 9023104; PMC: PMC146525 Pavesi A, Conterio F, Bolchi A, Dieci G, Ottonello S. Identification of new eukaryotic tRNA genes in genomic DNA databases by a multistep weight matrix analysis of transcriptional control regions. Nucleic Acids Res. 1994 Apr 11;22(7):1247-56. PMID: 8165140; PMC: PMC523650 
uniprot UniProt UniProt SwissProt/TrEMBL Protein Annotations Genes and Gene Predictions Description This track shows protein sequences and annotations on them from the UniProt/SwissProt database, mapped to genomic coordinates. UniProt/SwissProt data has been curated from scientific publications by the UniProt staff, UniProt/TrEMBL data has been predicted by various computational algorithms. The annotations are divided into multiple subtracks, based on their "feature type" in UniProt. The first two subtracks below - one for SwissProt, one for TrEMBL - show the alignments of protein sequences to the genome, all other tracks below are the protein annotations mapped through these alignments to the genome. Track Name Description UCSC Alignment, SwissProt = curated protein sequences Protein sequences from SwissProt mapped to the genome. All other tracks are (start,end) SwissProt annotations on these sequences mapped through this alignment. Even protein sequences without a single curated annotation (splice isoforms) are visible in this track. Each UniProt protein has one main isoform, which is colored in dark. Alternative isoforms are sequences that do not have annotations on them and are colored in light-blue. They can be hidden with the TrEMBL/Isoform filter (see below). UCSC Alignment, TrEMBL = predicted protein sequences Protein sequences from TrEMBL mapped to the genome. All other tracks below are (start,end) TrEMBL annotations mapped to the genome using this track. This track is hidden by default. To show it, click its checkbox on the track configuration page. UniProt Signal Peptides Regions found in proteins destined to be secreted, generally cleaved from mature protein. UniProt Extracellular Domains Protein domains with the comment "Extracellular". UniProt Transmembrane Domains Protein domains of the type "Transmembrane". UniProt Cytoplasmic Domains Protein domains with the comment "Cytoplasmic". UniProt Polypeptide Chains Polypeptide chain in mature protein after post-processing. UniProt Regions of Interest Regions that have been experimentally defined, such as the role of a region in mediating protein-protein interactions or some other biological process. UniProt Domains Protein domains, zinc finger regions and topological domains. UniProt Disulfide Bonds Disulfide bonds. UniProt Amino Acid Modifications Glycosylation sites, modified residues and lipid moiety-binding regions. UniProt Amino Acid Mutations Mutagenesis sites and sequence variants. UniProt Protein Primary/Secondary Structure Annotations Beta strands, helices, coiled-coil regions and turns. UniProt Sequence Conflicts Differences between Genbank sequences and the UniProt sequence. UniProt Repeats Regions of repeated sequence motifs or repeated domains. UniProt Other Annotations All other annotations, e.g. compositional bias For consistency and convenience for users of mutation-related tracks, the subtrack "UniProt/SwissProt Variants" is a copy of the track "UniProt Variants" in the track group "Phenotype and Literature", or "Variation and Repeats", depending on the assembly. Display Conventions and Configuration Genomic locations of UniProt/SwissProt annotations are labeled with a short name for the type of annotation (e.g. "glyco", "disulf bond", "Signal peptide" etc.). A click on them shows the full annotation and provides a link to the UniProt/SwissProt record for more details. TrEMBL annotations are always shown in light blue, except in the Signal Peptides, Extracellular Domains, Transmembrane Domains, and Cytoplamsic domains subtracks. Mouse over a feature to see the full UniProt annotation comment. For variants, the mouse over will show the full name of the UniProt disease acronym. The subtracks for domains related to subcellular location are sorted from outside to inside of the cell: Signal peptide, extracellular, transmembrane, and cytoplasmic. In the "UniProt Modifications" track, lipoification sites are highlighted in dark blue, glycosylation sites in dark green, and phosphorylation in light green. Duplicate annotations are removed as far as possible: if a TrEMBL annotation has the same genome position and same feature type, comment, disease and mutated amino acids as a SwissProt annotation, it is not shown again. Two annotations mapped through different protein sequence alignments but with the same genome coordinates are only shown once. On the configuration page of this track, you can choose to hide any TrEMBL annotations. This filter will also hide the UniProt alternative isoform protein sequences because both types of information are less relevant to most users. Please contact us if you want more detailed filtering features. Note that for the human hg38 assembly and SwissProt annotations, there also is a public track hub prepared by UniProt itself, with genome annotations maintained by UniProt using their own mapping method based on those Gencode/Ensembl gene models that are annotated in UniProt for a given protein. For proteins that differ from the genome, UniProt's mapping method will, in most cases, map a protein and its annotations to an unexpected location (see below for details on UCSC's mapping method). Methods Briefly, UniProt protein sequences were aligned to the transcripts associated with the protein, the top-scoring alignments were retained, and the result was projected to the genome through a transcript-to-genome alignment. Depending on the genome, the transcript-genome alignments was either provided by the source database (NBCI RefSeq), created at UCSC (UCSC RefSeq) or derived from the transcripts (Ensembl/Augustus). The transcript set is NCBI RefSeq for hg38, UCSC RefSeq for hg19 (due to alt/fix haplotype misplacements in the NCBI RefSeq set on hg19). For other genomes, RefSeq, Ensembl and Augustus are tried, in this order. The resulting protein-genome alignments of this process are available in the file formats for liftOver or pslMap from our data archive (see "Data Access" section below). An important step of the mapping process protein -> transcript -> genome is filtering the alignment from protein to transcript. Due to differences between the UniProt proteins and the transcripts (proteins were made many years before the transcripts were made, and human genomes have variants), the transcript with the highest BLAST score when aligning the protein to all transcripts is not always the correct transcript for a protein sequence. Therefore, the protein sequence is aligned to only a very short list of one or sometimes more transcripts, selected by a three-step procedure: Use transcripts directly annotated by UniProt: for organisms that have a RefSeq transcript track, proteins are aligned to the RefSeq transcripts that are annotated by UniProt for this particular protein. Use transcripts for NCBI Gene ID annotated by UniProt: If no transcripts are annotated on the protein, or the annotated ones have been deprecated by NCBI, but a NCBI Gene ID is annotated, the RefSeq transcripts for this Gene ID are used. This can result in multiple matching transcripts for a protein. Use best matching transcript: If no NCBI Gene is annotated, then BLAST scores are used to pick the transcripts. There can be multiple transcripts for one protein, as their coding sequences can be identical. All transcripts within 1% of the highest observed BLAST score are used. For strategy 2 and 3, many of the transcripts found do not differ in coding sequence, so the resulting alignments on the genome will be identical. Therefore, any identical alignments are removed in a final filtering step. The details page of these alignments will contain a list of all transcripts that result in the same protein-genome alignment. On hg38, only a handful of edge cases (pseudogenes, very recently added proteins) remain in 2023 where strategy 3 has to be used. In other words, when an NCBI or UCSC RefSeq track is used for the mapping and to align a protein sequence to the correct transcript, we use a three stage process: If UniProt has annotated a given RefSeq transcript for a given protein sequence, the protein is aligned to this transcript. Any difference in the version suffix is tolerated in this comparison. If no transcript is annotated or the transcript cannot be found in the NCBI/UCSC RefSeq track, the UniProt-annotated NCBI Gene ID is resolved to a set of NCBI RefSeq transcript IDs via the most current version of NCBI genes tables. Only the top match of the resulting alignments and all others within 1% of its score are used for the mapping. If no transcript can be found after step (2), the protein is aligned to all transcripts, the top match, and all others within 1% of its score are used. This system was designed to resolve the problem of incorrect mappings of proteins, mostly on hg38, due to differences between the SwissProt sequences and the genome reference sequence, which has changed since the proteins were defined. The problem is most pronounced for gene families composed of either very repetitive or very similar proteins. To make sure that the alignments always go to the best chromosome location, all _alt and _fix reference patch sequences are ignored for the alignment, so the patches are entirely free of UniProt annotations. Please contact us if you have feedback on this process or example edge cases. We are not aware of a way to evaluate the results completely and in an automated manner. Proteins were aligned to transcripts with TBLASTN, converted to PSL, filtered with pslReps (93% query coverage, keep alignments within top 1% score), lifted to genome positions with pslMap and filtered again with pslReps. UniProt annotations were obtained from the UniProt XML file. The UniProt annotations were then mapped to the genome through the alignment described above using the pslMap program. This approach draws heavily on the LS-SNP pipeline by Mark Diekhans. Like all Genome Browser source code, the main script used to build this track can be found on Github. Older releases This track is automatically updated on an ongoing basis, every 2-3 months. The current version name is always shown on the track details page, it includes the release of UniProt, the version of the transcript set and a unique MD5 that is based on the protein sequences, the transcript sequences, the mapping file between both and the transcript-genome alignment. The exact transcript that was used for the alignment is shown when clicking a protein alignment in one of the two alignment tracks. For reproducibility of older analysis results and for manual inspection, previous versions of this track are available for browsing in the form of the UCSC UniProt Archive Track Hub (click this link to connect the hub now). The underlying data of all releases of this track (past and current) can be obtained from our downloads server, including the UniProt protein-to-genome alignment. Data Access The raw data of the current track can be explored interactively with the Table Browser, or the Data Integrator. For automated analysis, the genome annotation is stored in a bigBed file that can be downloaded from the download server. The exact filenames can be found in the track configuration file. Annotations can be converted to ASCII text by 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, for example: bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/cb3/uniprot/unipStruct.bb -chrom=chr6 -start=0 -end=1000000 stdout Please refer to our mailing list archives for questions, or our Data Access FAQ for more information. Lifting from UniProt to genome coordinates in pipelines To facilitate mapping protein coordinates to the genome, we provide the alignment files in formats that are suitable for our command line tools. Our command line programs liftOver or pslMap can be used to map coordinates on protein sequences to genome coordinates. The filenames are unipToGenome.over.chain.gz (liftOver) and unipToGenomeLift.psl.gz (pslMap). Example commands: wget -q https://hgdownload.soe.ucsc.edu/goldenPath/archive/hg38/uniprot/2022_03/unipToGenome.over.chain.gz wget -q https://hgdownload.soe.ucsc.edu/admin/exe/linux.x86_64/liftOver chmod a+x liftOver echo 'Q99697 1 10 annotationOnProtein' > prot.bed liftOver prot.bed unipToGenome.over.chain.gz genome.bed cat genome.bed Credits This track was created by Maximilian Haeussler at UCSC, with a lot of input from Chris Lee, Mark Diekhans and Brian Raney, feedback from the UniProt staff, Alejo Mujica, Regeneron Pharmaceuticals and Pia Riestra, GeneDx. Thanks to UniProt for making all data available for download. References UniProt Consortium. Reorganizing the protein space at the Universal Protein Resource (UniProt). Nucleic Acids Res. 2012 Jan;40(Database issue):D71-5. PMID: 22102590; PMC: PMC3245120 Yip YL, Scheib H, Diemand AV, Gattiker A, Famiglietti LM, Gasteiger E, Bairoch A. The Swiss-Prot variant page and the ModSNP database: a resource for sequence and structure information on human protein variants. Hum Mutat. 2004 May;23(5):464-70. PMID: 15108278 
unipConflict Seq. Conflicts UniProt Sequence Conflicts Genes and Gene Predictions 
unipRepeat Repeats UniProt Repeats Genes and Gene Predictions 
unipStruct Structure UniProt Protein Primary/Secondary Structure Annotations Genes and Gene Predictions 
unipOther Other Annot. UniProt Other Annotations Genes and Gene Predictions 
unipMut Mutations UniProt Amino Acid Mutations Genes and Gene Predictions 
unipModif AA Modifications UniProt Amino Acid Modifications Genes and Gene Predictions 
unipDomain Domains UniProt Domains Genes and Gene Predictions 
unipDisulfBond Disulf. Bonds UniProt Disulfide Bonds Genes and Gene Predictions 
unipChain Chains UniProt Mature Protein Products (Polypeptide Chains) Genes and Gene Predictions 
unipLocCytopl Cytoplasmic UniProt Cytoplasmic Domains Genes and Gene Predictions 
unipLocTransMemb Transmembrane UniProt Transmembrane Domains Genes and Gene Predictions 
unipInterest Interest UniProt Regions of Interest Genes and Gene Predictions 
unipLocExtra Extracellular UniProt Extracellular Domain Genes and Gene Predictions 
unipLocSignal Signal Peptide UniProt Signal Peptides Genes and Gene Predictions 
unipAliTrembl TrEMBL Aln. UCSC alignment of TrEMBL proteins to genome Genes and Gene Predictions 
unipAliSwissprot SwissProt Aln. UCSC alignment of SwissProt proteins to genome (dark blue: main isoform, light blue: alternative isoforms) Genes and Gene Predictions 
spMut UniProt Variants UniProt/SwissProt Amino Acid Substitutions Variation and Repeats Description NOTE: This track is intended for use primarily by physicians and other professionals concerned with genetic disorders, by genetics researchers, and by advanced students in science and medicine. While the genome browser database is open to the public, users seeking information about a personal medical or genetic condition are urged to consult with a qualified physician for diagnosis and for answers to personal questions. This track shows the genomic positions of natural and artifical amino acid variants in the UniProt/SwissProt database. The data has been curated from scientific publications by the UniProt staff. Display Conventions and Configuration Genomic locations of UniProt/SwissProt variants are labeled with the amino acid change at a given position and, if known, the abbreviated disease name. A "?" is used if there is no disease annotated at this location, but the protein is described as being linked to only a single disease in UniProt. Mouse over a mutation to see the UniProt comments. Artificially-introduced mutations are colored green and naturally-occurring variants are colored red. For full information about a particular variant, click the "UniProt variant" linkout. The "UniProt record" linkout lists all variants of a particular protein sequence. The "Source articles" linkout lists the articles in PubMed that originally described the variant(s) and were used as evidence by the UniProt curators. Methods UniProt sequences were aligned to RefSeq sequences first with BLAT, then lifted to genome positions with pslMap. UniProt variants were parsed from the UniProt XML file. The variants were then mapped to the genome through the alignment using the pslMap program. This mapping approach draws heavily on the LS-SNP pipeline by Mark Diekhans. The complete script is part of the kent source tree and is located in src/hg/utils/uniprotMutations. Data Access The raw data can be explored interactively with the Table Browser, or the Data Integrator. For automated analysis, the genome annotation is stored in a bigBed file that can be downloaded from the download server. The underlying data file for this track is called spMut.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, for example: bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/cb3/bbi/uniprot/spMut.bb -chrom=chr6 -start=0 -end=1000000 stdout Please refer to our mailing list archives for questions, or our Data Access FAQ for more information. Credits This track was created by Maximilian Haeussler, with advice from Mark Diekhans and Brian Raney. References UniProt Consortium. Reorganizing the protein space at the Universal Protein Resource (UniProt). Nucleic Acids Res. 2012 Jan;40(Database issue):D71-5. PMID: 22102590; PMC: PMC3245120 Yip YL, Scheib H, Diemand AV, Gattiker A, Famiglietti LM, Gasteiger E, Bairoch A. The Swiss-Prot variant page and the ModSNP database: a resource for sequence and structure information on human protein variants. Hum Mutat. 2004 May;23(5):464-70. PMID: 15108278 
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 cb3.fa -output wm_counts windowmasker -ustat wm_counts -sdust true -input cb3.fa -output repeats.bed The repeats.bed (BED3) file was loaded into the "windowmaskerSdust" table for this track. References Morgulis A, Gertz EM, Schäffer AA, Agarwala R. WindowMasker: window-based masker for sequenced genomes. Bioinformatics. 2006 Jan 15;22(2):134-41. PMID: 16287941 
chainPriPac1 P. pacificus Chain P. pacificus (Feb. 2007 (WUGSC 5.0/priPac1)) Chained Alignments Comparative Genomics Description This track shows alignments of P. pacificus (priPac1, Feb. 2007 (WUGSC 5.0/priPac1)) to the C. briggsae genome using a gap scoring system that allows longer gaps than traditional affine gap scoring systems. It can also tolerate gaps in both P. pacificus and C. briggsae simultaneously. These "double-sided" 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 P. pacificus assembly or an insertion in the C. briggsae 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 C. briggsae 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 "pack" and "full" display modes, the individual feature names indicate the chromosome, strand, and location (in thousands) of the match for each matching alignment. Display Conventions and Configuration 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 "off" 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. Methods Transposons that have been inserted since the P. pacificus/C. briggsae split were removed from the assemblies. The abbreviated genomes were aligned with blastz using dynamic masking, and the transposons were then added back in. The resulting alignments were converted into psl format using the lavToPsl program. The axt alignments were fed into axtChain, which organizes all alignments between a single P. pacificus chromosome and a single C. briggsae 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:  ACGT A91-114-31-123 C-114100-125-31 G-31-125100-114 T-123-31-11491 Chains scoring below a threshold of 2000 were discarded; the remaining chains are displayed in this track. Credits Blastz was developed at Pennsylvania State University by Minmei Hou, Scott Schwartz, Zheng Zhang, and Webb Miller with advice from Ross Hardison. Repeat areas we marked in the genome with WindowMasker as developed by: Morgulis A, Gertz EM, Schäffer AA, Agarwala R. 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 were generated by Robert Baertsch and Jim Kent. References 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 Morgulis A, Gertz EM, Schäffer AA, Agarwala R. WindowMasker: window-based masker for sequenced genomes. Bioinformatics. 2006 Jan 15;22(2):134-41. PMID: 16287941 Schwartz S, Kent WJ, Smit A, Zhang Z, Baertsch R, Hardison R, Haussler D, Miller W. Human-Mouse Alignments with BLASTZ. Genome Res. 2003 Jan;13(1):103-7. PMID: 12529312; PMC: PMC430961 
netPriPac1 P. pacificus Net P. pacificus (Feb. 2007 (WUGSC 5.0/priPac1)) Alignment Net Comparative Genomics Description This track shows the best P. pacificus/C. briggsae chain for every part of the C. briggsae genome. It is useful for finding orthologous regions and for studying genome rearrangement. The P. pacificus sequence used in this annotation is from the Feb. 2007 (WUGSC 5.0/priPac1) (priPac1) assembly. Display Conventions and Configuration 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 Chains were derived from blastz 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 The chainNet, netSyntenic, and netClass programs were developed at the University of California Santa Cruz by Jim Kent. Blastz was developed at Pennsylvania State University by Minmei Hou, Scott Schwartz, Zheng Zhang, and Webb Miller with advice from Ross Hardison. The browser display and database storage of the nets were made by Robert Baertsch and Jim Kent. References 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 R, Haussler D, Miller W. Human-Mouse Alignments with BLASTZ. Genome Res. 2003 Jan;13(1):103-7. PMID: 12529312; PMC: PMC430961 
chainCaeRem2 C. remanei Chain C. remanei (Mar. 2006 (WUGSC 1.0/caeRem2)) Chained Alignments Comparative Genomics Description This track shows alignments of C. remanei (caeRem2, Mar. 2006 (WUGSC 1.0/caeRem2)) to the C. briggsae genome using a gap scoring system that allows longer gaps than traditional affine gap scoring systems. It can also tolerate gaps in both C. remanei and C. briggsae simultaneously. These "double-sided" 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 C. remanei assembly or an insertion in the C. briggsae 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 C. briggsae 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 "pack" and "full" display modes, the individual feature names indicate the chromosome, strand, and location (in thousands) of the match for each matching alignment. Display Conventions and Configuration 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 "off" 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. Methods Transposons that have been inserted since the C. remanei/C. briggsae split were removed from the assemblies. The abbreviated genomes were aligned with blastz using dynamic masking, and the transposons were then added back in. The resulting alignments were converted into psl format using the lavToPsl program. The axt alignments were fed into axtChain, which organizes all alignments between a single C. remanei chromosome and a single C. briggsae 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:  ACGT A91-114-31-123 C-114100-125-31 G-31-125100-114 T-123-31-11491 Chains scoring below a threshold of 2000 were discarded; the remaining chains are displayed in this track. Credits Blastz was developed at Pennsylvania State University by Minmei Hou, Scott Schwartz, Zheng Zhang, and Webb Miller with advice from Ross Hardison. Repeat areas we marked in the genome with WindowMasker as developed by: Morgulis A, Gertz EM, Schäffer AA, Agarwala R. 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 were generated by Robert Baertsch and Jim Kent. References 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 Morgulis A, Gertz EM, Schäffer AA, Agarwala R. WindowMasker: window-based masker for sequenced genomes. Bioinformatics. 2006 Jan 15;22(2):134-41. PMID: 16287941 Schwartz S, Kent WJ, Smit A, Zhang Z, Baertsch R, Hardison R, Haussler D, Miller W. Human-Mouse Alignments with BLASTZ. Genome Res. 2003 Jan;13(1):103-7. PMID: 12529312; PMC: PMC430961 
chainCe6 C. elegans Chain C. elegans (May 2008 (WS190/ce6)) Chained Alignments Comparative Genomics Description This track shows alignments of C. elegans (ce6, May 2008 (WS190/ce6)) to the C. briggsae genome using a gap scoring system that allows longer gaps than traditional affine gap scoring systems. It can also tolerate gaps in both C. elegans and C. briggsae simultaneously. These "double-sided" 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 C. elegans assembly or an insertion in the C. briggsae 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 C. briggsae 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 "pack" and "full" display modes, the individual feature names indicate the chromosome, strand, and location (in thousands) of the match for each matching alignment. Display Conventions and Configuration 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 "off" 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. Methods Transposons that have been inserted since the C. elegans/C. briggsae split were removed from the assemblies. The abbreviated genomes were aligned with blastz using dynamic masking, and the transposons were then added back in. The resulting alignments were converted into psl format using the lavToPsl program. The axt alignments were fed into axtChain, which organizes all alignments between a single C. elegans chromosome and a single C. briggsae 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:  ACGT A91-114-31-123 C-114100-125-31 G-31-125100-114 T-123-31-11491 Chains scoring below a threshold of 2000 were discarded; the remaining chains are displayed in this track. Credits Blastz was developed at Pennsylvania State University by Minmei Hou, Scott Schwartz, Zheng Zhang, and Webb Miller with advice from Ross Hardison. Repeat areas we marked in the genome with WindowMasker as developed by: Morgulis A, Gertz EM, Schäffer AA, Agarwala R. 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 were generated by Robert Baertsch and Jim Kent. References 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 Morgulis A, Gertz EM, Schäffer AA, Agarwala R. WindowMasker: window-based masker for sequenced genomes. Bioinformatics. 2006 Jan 15;22(2):134-41. PMID: 16287941 Schwartz S, Kent WJ, Smit A, Zhang Z, Baertsch R, Hardison R, Haussler D, Miller W. Human-Mouse Alignments with BLASTZ. Genome Res. 2003 Jan;13(1):103-7. PMID: 12529312; PMC: PMC430961 
netCe6 C. elegans Net C. elegans (May 2008 (WS190/ce6)) Alignment Net Comparative Genomics Description This track shows the best C. elegans/C. briggsae chain for every part of the C. briggsae genome. It is useful for finding orthologous regions and for studying genome rearrangement. The C. elegans sequence used in this annotation is from the May 2008 (WS190/ce6) (ce6) assembly. Display Conventions and Configuration 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 Chains were derived from blastz 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 The chainNet, netSyntenic, and netClass programs were developed at the University of California Santa Cruz by Jim Kent. Blastz was developed at Pennsylvania State University by Minmei Hou, Scott Schwartz, Zheng Zhang, and Webb Miller with advice from Ross Hardison. The browser display and database storage of the nets were made by Robert Baertsch and Jim Kent. References 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 R, Haussler D, Miller W. Human-Mouse Alignments with BLASTZ. Genome Res. 2003 Jan;13(1):103-7. PMID: 12529312; PMC: PMC430961 
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, J. (2000) in the References section below. 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) 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. 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. 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 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. 
netCaeRem2 C. remanei Net C. remanei (Mar. 2006 (WUGSC 1.0/caeRem2)) Alignment Net Comparative Genomics Description This track shows the best C. remanei/C. briggsae chain for every part of the C. briggsae genome. It is useful for finding orthologous regions and for studying genome rearrangement. The C. remanei sequence used in this annotation is from the Mar. 2006 (WUGSC 1.0/caeRem2) (caeRem2) assembly. Display Conventions and Configuration 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 Chains were derived from blastz 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 The chainNet, netSyntenic, and netClass programs were developed at the University of California Santa Cruz by Jim Kent. Blastz was developed at Pennsylvania State University by Minmei Hou, Scott Schwartz, Zheng Zhang, and Webb Miller with advice from Ross Hardison. The browser display and database storage of the nets were made by Robert Baertsch and Jim Kent. References 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 R, Haussler D, Miller W. Human-Mouse Alignments with BLASTZ. Genome Res. 2003 Jan;13(1):103-7. PMID: 12529312; PMC: PMC430961 
chainCaePb1 C. brenneri Chain C. brenneri (Jan. 2007 (WUGSC 4.0/caePb1)) Chained Alignments Comparative Genomics Description This track shows alignments of C. brenneri (caePb1, Jan. 2007 (WUGSC 4.0/caePb1)) to the C. briggsae genome using a gap scoring system that allows longer gaps than traditional affine gap scoring systems. It can also tolerate gaps in both C. brenneri and C. briggsae simultaneously. These "double-sided" 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 C. brenneri assembly or an insertion in the C. briggsae 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 C. briggsae 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 "pack" and "full" display modes, the individual feature names indicate the chromosome, strand, and location (in thousands) of the match for each matching alignment. Display Conventions and Configuration 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 "off" 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. Methods Transposons that have been inserted since the C. brenneri/C. briggsae split were removed from the assemblies. The abbreviated genomes were aligned with blastz using dynamic masking, and the transposons were then added back in. The resulting alignments were converted into psl format using the lavToPsl program. The axt alignments were fed into axtChain, which organizes all alignments between a single C. brenneri chromosome and a single C. briggsae 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:  ACGT A91-114-31-123 C-114100-125-31 G-31-125100-114 T-123-31-11491 Chains scoring below a threshold of 2000 were discarded; the remaining chains are displayed in this track. Credits Blastz was developed at Pennsylvania State University by Minmei Hou, Scott Schwartz, Zheng Zhang, and Webb Miller with advice from Ross Hardison. Repeat areas we marked in the genome with WindowMasker as developed by: Morgulis A, Gertz EM, Schäffer AA, Agarwala R. 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 were generated by Robert Baertsch and Jim Kent. References 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 Morgulis A, Gertz EM, Schäffer AA, Agarwala R. WindowMasker: window-based masker for sequenced genomes. Bioinformatics. 2006 Jan 15;22(2):134-41. PMID: 16287941 Schwartz S, Kent WJ, Smit A, Zhang Z, Baertsch R, Hardison R, Haussler D, Miller W. Human-Mouse Alignments with BLASTZ. Genome Res. 2003 Jan;13(1):103-7. PMID: 12529312; PMC: PMC430961 
netCaePb1 C. brenneri Net C. brenneri (Jan. 2007 (WUGSC 4.0/caePb1)) Alignment Net Comparative Genomics Description This track shows the best C. brenneri/C. briggsae chain for every part of the C. briggsae genome. It is useful for finding orthologous regions and for studying genome rearrangement. The C. brenneri sequence used in this annotation is from the Jan. 2007 (WUGSC 4.0/caePb1) (caePb1) assembly. Display Conventions and Configuration 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 Chains were derived from blastz 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 The chainNet, netSyntenic, and netClass programs were developed at the University of California Santa Cruz by Jim Kent. Blastz was developed at Pennsylvania State University by Minmei Hou, Scott Schwartz, Zheng Zhang, and Webb Miller with advice from Ross Hardison. The browser display and database storage of the nets were made by Robert Baertsch and Jim Kent. References 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 R, Haussler D, Miller W. Human-Mouse Alignments with BLASTZ. Genome Res. 2003 Jan;13(1):103-7. PMID: 12529312; PMC: PMC430961 
blastCe6SG C.elegans Prot. C. elegans Proteins WS190 Mapped by Chained tBLASTn Genes and Gene Predictions Description This track contains tBLASTn alignments of the peptides from the WormBase gene annotations on C. elegans version WS190 (UCSC ce6). Methods First, the predicted proteins from the C. elegans WormBase Genes track were aligned to the C. elegans genome using the blat program to discover exon boundaries. Next, the amino acid sequences that make up each exon were aligned with the C. briggsae sequence using the tBLASTn program. Finally, the putative C. briggsae exons were chained together using a maximum gap size of 50,000 but no gap penalty. The single best exon chains extending over more than 60% of the query protein were included. Exon chains that extended over 60% of the query and matched at least 60% of the protein's amino acids were also included. Credits tBLASTn is part of the NCBI Blast tool set. For more information on Blast, see Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990 Oct 5;215(3):403-410. Blat was written by Jim Kent. The remaining utilities used to produce this track were written by Jim Kent, Brian Raney and Hiram Clawson.