--------------------------------------------------------------- rn7.trackDb.html : Differences exist between hgwbeta and hgw2 (RR fields taken from public MySql server, not individual machine) 1626,1839d1625 < crisprAllTargets | html < crisprAllTargets |

Description

< crisprAllTargets | < crisprAllTargets |

< crisprAllTargets | This track shows the DNA sequences targetable by CRISPR RNA guides using < crisprAllTargets | the Cas9 enzyme from S. pyogenes (PAM: NGG) over the entire < crisprAllTargets | rat (rn7) genome. CRISPR target sites were annotated with < crisprAllTargets | predicted specificity (off-target effects) and predicted efficiency < crisprAllTargets | (on-target cleavage) by various < crisprAllTargets | algorithms through the tool CRISPOR. Sp-Cas9 usually cuts double-stranded DNA three or < crisprAllTargets | four base pairs 5' of the PAM site. < crisprAllTargets |

< crisprAllTargets | < crisprAllTargets |

Display Conventions and Configuration

< crisprAllTargets | < crisprAllTargets |

< crisprAllTargets | The track "CRISPR Targets" shows all potential -NGG target sites across the genome. < crisprAllTargets | The target sequence of the guide is shown with a thick (exon) bar. The PAM < crisprAllTargets | motif match (NGG) is shown with a thinner bar. Guides < crisprAllTargets | are colored to reflect both predicted specificity and efficiency. Specificity < crisprAllTargets | reflects the "uniqueness" of a 20mer sequence in the genome; the less unique a < crisprAllTargets | sequence is, the more likely it is to cleave other locations of the genome < crisprAllTargets | (off-target effects). Efficiency is the frequency of cleavage at the target < crisprAllTargets | site (on-target efficiency).

< crisprAllTargets | < crisprAllTargets |

Shades of gray stand for sites that are hard to target specifically, as the < crisprAllTargets | 20mer is not very unique in the genome:

	impossible to target: target site has at least one identical copy in the genome and was not scored
	hard to target: many similar sequences in the genome that alignment stopped, repeat?
	hard to target: target site was aligned but results in a low specificity score <= 50 (see below)

< crisprAllTargets | < crisprAllTargets |

Colors highlight targets that are specific in the genome (MIT specificity > 50) but have different predicted efficiencies:

	unable to calculate Doench/Fusi 2016 efficiency score
	low predicted cleavage: Doench/Fusi 2016 Efficiency percentile <= 30
	medium predicted cleavage: Doench/Fusi 2016 Efficiency percentile > 30 and < 55
	high predicted cleavage: Doench/Fusi 2016 Efficiency > 55

< crisprAllTargets | < crisprAllTargets |

< crisprAllTargets | Mouse-over a target site to show predicted specificity and efficiency scores:
< crisprAllTargets |

The MIT Specificity score summarizes all off-targets into a single number from < crisprAllTargets | 0-100. The higher the number, the fewer off-target effects are expected. We < crisprAllTargets | recommend guides with an MIT specificity > 50.
The efficiency score tries to predict if a guide leads to rather strong or < crisprAllTargets | weak cleavage. According to (Haeussler et al. 2016), the < crisprAllTargets | Doench 2016 Efficiency score should be used to select the guide with the highest < crisprAllTargets | cleavage efficiency when expressing guides from RNA PolIII Promoters such as < crisprAllTargets | U6. Scores are given as percentiles, e.g. "70%" means that 70% of mammalian < crisprAllTargets | guides have a score equal or lower than this guide. The raw score number is < crisprAllTargets | also shown in parentheses after the percentile.
The Moreno-Mateos 2015 Efficiency < crisprAllTargets | score should be used instead of the Doench 2016 score when transcribing the < crisprAllTargets | guide in vitro with a T7 promoter, e.g. for injections in mouse, zebrafish or < crisprAllTargets | Xenopus embryos. The Moreno-Mateos score is given in percentiles and the raw value in parentheses, < crisprAllTargets | see the note above.

< crisprAllTargets |

< crisprAllTargets | < crisprAllTargets |

Click onto features to show all scores and predicted off-targets with up to < crisprAllTargets | four mismatches. The Out-of-Frame score by Bae et al. 2014 < crisprAllTargets | is correlated with < crisprAllTargets | the probability that mutations induced by the guide RNA will disrupt the open < crisprAllTargets | reading frame. The authors recommend out-of-frame scores > 66 to create < crisprAllTargets | knock-outs with a single guide efficiently.

< crisprAllTargets | < crisprAllTargets |

Off-target sites are sorted by the CFD (Cutting Frequency Determination) < crisprAllTargets | score (Doench et al. 2016). < crisprAllTargets | The higher the CFD score, the more likely there is off-target cleavage at that site. < crisprAllTargets | Off-targets with a CFD score < 0.023 are not shown on this page, but are available when < crisprAllTargets | following the link to the external CRISPOR tool. < crisprAllTargets | When compared against experimentally validated off-targets by < crisprAllTargets | Haeussler et al. 2016, the large majority of predicted < crisprAllTargets | off-targets with CFD scores < 0.023 were false-positives. For storage and performance < crisprAllTargets | reasons, on the level of individual off-targets, only CFD scores are available.

< crisprAllTargets | < crisprAllTargets |

Methods

< crisprAllTargets | < crisprAllTargets |

Relationship between predictions and experimental data

< crisprAllTargets | < crisprAllTargets |

< crisprAllTargets | Like most algorithms, the MIT specificity score is not always a perfect < crisprAllTargets | predictor of off-target effects. Despite low scores, many tested guides < crisprAllTargets | caused few and/or weak off-target cleavage when tested with whole-genome assays < crisprAllTargets | (Figure 2 from Haeussler < crisprAllTargets | et al. 2016), as shown below, and the published data contains few data points < crisprAllTargets | with high specificity scores. Overall though, the assays showed that the higher < crisprAllTargets | the specificity score, the lower the off-target effects.

< crisprAllTargets | < crisprAllTargets |

Similarly, efficiency scoring is not very accurate: guides with low < crisprAllTargets | scores can be efficient and vice versa. As a general rule, however, the higher < crisprAllTargets | the score, the less likely that a guide is very inefficient. The < crisprAllTargets | following histograms illustrate, for each type of score, how the share of < crisprAllTargets | inefficient guides drops with increasing efficiency scores: < crisprAllTargets |

< crisprAllTargets | < crisprAllTargets |

When reading this plot, keep in mind that both scores were evaluated on < crisprAllTargets | their own training data. Especially for the Moreno-Mateos score, the < crisprAllTargets | results are too optimistic, due to overfitting. When evaluated on independent < crisprAllTargets | datasets, the correlation of the prediction with other assays was around 25% < crisprAllTargets | lower, see Haeussler et al. 2016. At the time of < crisprAllTargets | writing, there is no independent dataset available yet to determine the < crisprAllTargets | Moreno-Mateos accuracy for each score percentile range.

< crisprAllTargets | < crisprAllTargets |

Track methods

< crisprAllTargets |

< crisprAllTargets | The entire rat (rn7) genome was scanned for the -NGG motif. Flanking 20mer < crisprAllTargets | guide sequences were < crisprAllTargets | aligned to the genome with BWA and scored with MIT Specificity scores using the < crisprAllTargets | command-line version of crispor.org. Non-unique guide sequences were skipped. < crisprAllTargets | Flanking sequences were extracted from the genome and input for Crispor < crisprAllTargets | efficiency scoring, available from the Crispor downloads page, which < crisprAllTargets | includes the Doench 2016, Moreno-Mateos 2015 and Bae < crisprAllTargets | 2014 algorithms, among others.

< crisprAllTargets |

< crisprAllTargets | Note that the Doench 2016 scores were updated by < crisprAllTargets | the Broad institute in 2017 ("Azimuth" update). As a result, earlier versions of < crisprAllTargets | the track show the old Doench 2016 scores and this version of the track shows new < crisprAllTargets | Doench 2016 scores. Old and new scores are almost identical, they are < crisprAllTargets | correlated to 0.99 and for more than 80% of the guides the difference is below 0.02. < crisprAllTargets | However, for very few guides, the difference can be bigger. In case of doubt, we recommend < crisprAllTargets | the new scores. Crispor.org can display both < crisprAllTargets | scores and many more with the "Show all scores" link.

< crisprAllTargets | < crisprAllTargets |

Data Access

< crisprAllTargets |

< crisprAllTargets | Positional data can be explored interactively with the < crisprAllTargets | Table < crisprAllTargets | Browser or the Data Integrator. < crisprAllTargets | For small programmatic positional queries, the track can be accessed using our < crisprAllTargets | REST API. For genome-wide data or < crisprAllTargets | automated analysis, CRISPR genome annotations can be downloaded from < crisprAllTargets | our download server < crisprAllTargets | as a bigBedFile.

< crisprAllTargets |

< crisprAllTargets | The files for this track are called crispr.bb, which lists positions and < crisprAllTargets | scores, and crisprDetails.tab, which has information about off-target matches. Individual < crisprAllTargets | regions or whole genome annotations can be obtained using our tool bigBedToBed, < crisprAllTargets | which can be compiled from the source code or downloaded as a pre-compiled < crisprAllTargets | binary for your system. Instructions for downloading source code and binaries can be found < crisprAllTargets | here. The tool < crisprAllTargets | can also be used to obtain only features within a given range, e.g.

< crisprAllTargets |

< crisprAllTargets | bigBedToBed < crisprAllTargets | http://hgdownload.soe.ucsc.edu/gbdb/rn7/crisprAllTargets/crispr.bb -chrom=chr21 < crisprAllTargets | -start=0 -end=1000000 stdout

< crisprAllTargets | < crisprAllTargets |

Credits

< crisprAllTargets | < crisprAllTargets |

< crisprAllTargets | Track created by Maximilian Haeussler, with helpful input < crisprAllTargets | from Jean-Paul Concordet (MNHN Paris) and Alberto Stolfi (NYU). < crisprAllTargets |

< crisprAllTargets | < crisprAllTargets |

References

< crisprAllTargets | < crisprAllTargets |

< crisprAllTargets | Haeussler M, Schönig K, Eckert H, Eschstruth A, Mianné J, Renaud JB, Schneider-Maunoury S, < crisprAllTargets | Shkumatava A, Teboul L, Kent J et al. < crisprAllTargets | Evaluation of off-target and on-target scoring algorithms and integration into the < crisprAllTargets | guide RNA selection tool CRISPOR. < crisprAllTargets | Genome Biol. 2016 Jul 5;17(1):148. < crisprAllTargets | PMID: 27380939; PMC: PMC4934014 < crisprAllTargets |

< crisprAllTargets | < crisprAllTargets |

< crisprAllTargets | Bae S, Kweon J, Kim HS, Kim JS. < crisprAllTargets | < crisprAllTargets | Microhomology-based choice of Cas9 nuclease target sites. < crisprAllTargets | Nat Methods. 2014 Jul;11(7):705-6. < crisprAllTargets | PMID: 24972169 < crisprAllTargets |

< crisprAllTargets | < crisprAllTargets |

< crisprAllTargets | Doench JG, Fusi N, Sullender M, Hegde M, Vaimberg EW, Donovan KF, Smith I, Tothova Z, Wilen C, < crisprAllTargets | Orchard R et al. < crisprAllTargets | < crisprAllTargets | Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9. < crisprAllTargets | Nat Biotechnol. 2016 Feb;34(2):184-91. < crisprAllTargets | PMID: 26780180; PMC: PMC4744125 < crisprAllTargets |

< crisprAllTargets | < crisprAllTargets |

< crisprAllTargets | Hsu PD, Scott DA, Weinstein JA, Ran FA, Konermann S, Agarwala V, Li Y, Fine EJ, Wu X, Shalem O < crisprAllTargets | et al. < crisprAllTargets | < crisprAllTargets | DNA targeting specificity of RNA-guided Cas9 nucleases. < crisprAllTargets | Nat Biotechnol. 2013 Sep;31(9):827-32. < crisprAllTargets | PMID: 23873081; PMC: PMC3969858 < crisprAllTargets |

< crisprAllTargets | < crisprAllTargets |

< crisprAllTargets | Moreno-Mateos MA, Vejnar CE, Beaudoin JD, Fernandez JP, Mis EK, Khokha MK, Giraldez AJ. < crisprAllTargets | < crisprAllTargets | CRISPRscan: designing highly efficient sgRNAs for CRISPR-Cas9 targeting in vivo. < crisprAllTargets | Nat Methods. 2015 Oct;12(10):982-8. < crisprAllTargets | PMID: 26322839; PMC: PMC4589495 < crisprAllTargets |

< crisprAllTargets | 1989,2631d1774 < evaSnp | html < evaSnp |

Description

< evaSnp |

< evaSnp | This track contains mappings of single nucleotide variants < evaSnp | and small insertions and deletions (indels) < evaSnp | from the European Variation Archive < evaSnp | (EVA) < evaSnp | Release 3 for the rat rn7 genome. The dbSNP database at NCBI no longer < evaSnp | hosts non-human variants. < evaSnp |

< evaSnp | < evaSnp |

Interpreting and Configuring the Graphical Display

< evaSnp |

< evaSnp | Variants are shown as single tick marks at most zoom levels. < evaSnp | When viewing the track at or near base-level resolution, the displayed < evaSnp | width of the SNP variant corresponds to the width of the variant in the < evaSnp | reference sequence. Insertions are indicated by a single tick mark displayed < evaSnp | between two nucleotides, single nucleotide polymorphisms are displayed as the < evaSnp | width of a single base, and multiple nucleotide variants are represented by a < evaSnp | block that spans two or more bases. The display is set to automatically collapse to < evaSnp | dense visibility when there are more than 100k variants in the window. < evaSnp | When the window size is more than 250k bp, the display is switched to density graph mode. < evaSnp |

< evaSnp | < evaSnp |

Searching, details, and filtering

< evaSnp |

< evaSnp | Navigation to an individual variant can be accomplished by typing or copying < evaSnp | the variant identifier (rsID) or the genomic coordinates into the Position/Search box on the < evaSnp | Browser.

< evaSnp | < evaSnp |

< evaSnp | A click on an item in the graphical display displays a page with data about < evaSnp | that variant. Data fields include the Reference and Alternate Alleles, the < evaSnp | class of the variant as reported by EVA, the source of the data, the amino acid < evaSnp | change, if any, and the functional class as determined by UCSC's Variant Annotation < evaSnp | Integrator. < evaSnp |

< evaSnp | < evaSnp |

Variants can be filtered using the track controls to show subsets of the < evaSnp | data by either EVA Sequence Ontology (SO) term, UCSC-generated functional effect, or < evaSnp | by color, which bins the UCSC functional effects into general classes.

< evaSnp | < evaSnp |

Mouse-over

< evaSnp |

< evaSnp | Mousing over an item shows the ucscClass, which is the consequence according to the < evaSnp | Variant Annotation Integrator, and < evaSnp | the aaChange when one is available, which is the change in amino acid in HGVS.p < evaSnp | terms. Items may have multiple ucscClasses, which will all be shown in the mouse-over < evaSnp | in a comma-separated list. Likewise, multiple HGVS.p terms may be shown for each rsID < evaSnp | separated by spaces describing all possible AA changes.

< evaSnp |

< evaSnp | Multiple items may appear due to different variant predictions on multiple gene transcripts. < evaSnp | For all organisms the gene models used were ncbiRefSeqCurated, except for mm39 which < evaSnp | used ncbiRefSeqSelect.

< evaSnp |

< evaSnp | < evaSnp |

Track colors

< evaSnp | < evaSnp |

< evaSnp | Variants are colored according to the most potentially deleterious functional effect prediction < evaSnp | according to the Variant Annotation Integrator. Specific bins can be seen in the Methods section < evaSnp | below. < evaSnp |

< evaSnp | < evaSnp |

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

< evaSnp | < evaSnp |

Sequence ontology (SO)

< evaSnp | < evaSnp |

< evaSnp | Variants are classified by EVA into one of the following sequence ontology terms: < evaSnp |

< evaSnp | < evaSnp |

substitution — < evaSnp | A single nucleotide in the reference is replaced by another, alternate allele < evaSnp |
deletion — < evaSnp | One or more nucleotides is deleted. The representation in the database is to < evaSnp | display one additional nucleotide in both the Reference field (Ref) and the < evaSnp | Alternate Allele field (Alt). E.g. a variant that is a deletion of an A < evaSnp | maybe be represented as Ref = GA and Alt = G. < evaSnp |
insertion — < evaSnp | One or more nucleotides is inserted. The representation in the database is to < evaSnp | display one additional nucleotide in both the Reference field (Ref) and the < evaSnp | Alternate Allele field (Alt). E.g. a variant that is an insertion of a T maybe < evaSnp | be represented as Ref = G and Alt = GT < evaSnp |
delins — < evaSnp | Similar to tandemRepeat, in that the runs of Ref and Alt Alleles are of < evaSnp | different length, except that there is more than one type of nucleotide, < evaSnp | e.g., Ref = CCAAAAACAAAAACA, Alt = ACAAAAAC. < evaSnp |
multipleNucleotideVariant — < evaSnp | More than one nucleotide is substituted by an equal number of different < evaSnp | nucleotides, e.g., Ref = AA, Alt = GC. < evaSnp |
sequence alteration — < evaSnp | A parent term meant to signify a deviation from another sequence. Can be < evaSnp | assigned to variants that have not been characterized yet. < evaSnp |

< evaSnp |

< evaSnp | < evaSnp |

Methods

< evaSnp |

< evaSnp | Data were downloaded from the European Variation Archive EVA release 3 (2022-02-24) < evaSnp | current_ids.vcf.gz files corresponding to the proper assembly.

< evaSnp |

< evaSnp | Chromosome names were converted to UCSC-style, a few problematic variants were removed, < evaSnp | and the variants passed through the < evaSnp | Variant Annotation Integrator to < evaSnp | predict consequence. For every organism the ncbiRefSeqCurated gene models were used to < evaSnp | predict the consequences, except for mm39 which used the ncbiRefSeqSelect models.

< evaSnp |

< evaSnp | Variants were then colored according to their predicted consequence in the following fashion: < evaSnp |

Protein-altering variants and < evaSnp | splice site variants < evaSnp | - exon_loss_variant, frameshift_variant, < evaSnp | inframe_deletion, inframe_insertion, initiator_codon_variant, missense_variant, < evaSnp | splice_acceptor_variant, splice_donor_variant, splice_region_variant, stop_gained, < evaSnp | stop_lost, coding_sequence_variant, transcript_ablation
Synonymous codon variants < evaSnp | - synonymous_variant, stop_retained_variant
Non-coding transcript or < evaSnp | Untranslated Region (UTR) variants < evaSnp | - 5_prime_UTR_variant, < evaSnp | 3_prime_UTR_variant, complex_transcript_variant, non_coding_transcript_exon_variant
Intergenic and intronic variants - upstream_gene_variant, downstream_gene_variant, < evaSnp | intron_variant, intergenic_variant, NMD_transcript_variant, no_sequence_alteration

< evaSnp |

< evaSnp | < evaSnp |

< evaSnp | Sequence Ontology ("SO:") < evaSnp | terms were converted to the variant classes, then the files were converted to BED, < evaSnp | and then bigBed format. < evaSnp |

< evaSnp |

< evaSnp | No functional annotations were provided by the EVA (e.g., missense, nonsense, etc). < evaSnp | These were computed using UCSC's Variant Annotation Integrator (Hinrichs, et al., 2016). < evaSnp | Amino-acid substitutions for missense variants are based < evaSnp | on RefSeq alignments of mRNA transcripts, which do not always match the amino acids < evaSnp | predicted from translating the genomic sequence. Therefore, in some instances, the < evaSnp | variant and the genomic nucleotide and associated amino acid may be reversed. < evaSnp | E.g., a Pro > Arg change from the perspective of the mRNA would be Arg > Pro from < evaSnp | the persepective the genomic sequence. < evaSnp | For complete documentation of the processing of these tracks, read the < evaSnp | < evaSnp | EVA Release 3 MakeDoc.

< evaSnp | < evaSnp |

Data Access

< evaSnp |

< evaSnp | Note: It is not recommeneded to use LiftOver to convert SNPs between assemblies, < evaSnp | and more information about how to convert SNPs between assemblies can be found on the following < evaSnp | FAQ entry.

< evaSnp |

< evaSnp | The data can be explored interactively with the Table Browser, < evaSnp | or the Data Integrator. For automated analysis, the data may be < evaSnp | queried from our REST API. Please refer to our < evaSnp | mailing list archives < evaSnp | for questions, or our Data Access FAQ for more < evaSnp | information.

< evaSnp | < evaSnp |

< evaSnp | For automated download and analysis, this annotation is stored in a bigBed file that < evaSnp | can be downloaded from our download server. The file for this track is called evaSnp.bb. < evaSnp | Individual regions or the whole genome annotation can be obtained using our tool < evaSnp | bigBedToBed which can be compiled from the source code or downloaded as a precompiled < evaSnp | binary for your system. Instructions for downloading source code and binaries can be found < evaSnp | here. < evaSnp | The tool can also be used to obtain only features within a given range, e.g. < evaSnp |

< evaSnp | bigBedToBed https://hgdownload.soe.ucsc.edu/gbdb/rn7/bbi/evaSnp.bb -chrom=chr21 -start=0 -end=100000000 stdout < evaSnp |

< evaSnp | < evaSnp |

Credits

< evaSnp |

< evaSnp | This track was produced from the European < evaSnp | Variation Archive release 3 data. Consequences were predicted using UCSC's Variant Annotation < evaSnp | Integrator and NCBI's RefSeq gene models. < evaSnp |

< evaSnp | < evaSnp |

References

< evaSnp |

< evaSnp | Cezard T, Cunningham F, Hunt SE, Koylass B, Kumar N, Saunders G, Shen A, Silva AF, < evaSnp | Tsukanov K, Venkataraman S et al. The European Variation Archive: a FAIR resource of genomic variation for all < evaSnp | species. Nucleic Acids Res. 2021 Oct 28:gkab960. < evaSnp | doi:10.1093/nar/gkab960. < evaSnp | Epub ahead of print. PMID: 34718739. PMID: PMC8728205. < evaSnp |

< evaSnp |

< evaSnp | Hinrichs AS, Raney BJ, Speir ML, Rhead B, Casper J, Karolchik D, Kuhn RM, Rosenbloom KR, Zweig AS, < evaSnp | Haussler D, Kent WJ. < evaSnp | UCSC Data Integrator and Variant Annotation Integrator. < evaSnp | Bioinformatics. 2016 May 1;32(9):1430-2. < evaSnp | PMID: 26740527; PMC: < evaSnp | PMC4848401 < evaSnp |

< evaSnp | < evaSnp4 | html < evaSnp4 |

Description

< evaSnp4 |

< evaSnp4 | This track contains mappings of single nucleotide variants < evaSnp4 | and small insertions and deletions (indels) < evaSnp4 | from the European Variation Archive < evaSnp4 | (EVA) < evaSnp4 | Release 4 for the rat rn7 genome. The dbSNP database at NCBI no longer < evaSnp4 | hosts non-human variants. < evaSnp4 |

< evaSnp4 | < evaSnp4 |

Interpreting and Configuring the Graphical Display

< evaSnp4 |

< evaSnp4 | Variants are shown as single tick marks at most zoom levels. < evaSnp4 | When viewing the track at or near base-level resolution, the displayed < evaSnp4 | width of the SNP variant corresponds to the width of the variant in the < evaSnp4 | reference sequence. Insertions are indicated by a single tick mark displayed < evaSnp4 | between two nucleotides, single nucleotide polymorphisms are displayed as the < evaSnp4 | width of a single base, and multiple nucleotide variants are represented by a < evaSnp4 | block that spans two or more bases. The display is set to automatically collapse to < evaSnp4 | dense visibility when there are more than 100k variants in the window. < evaSnp4 | When the window size is more than 250k bp, the display is switched to density graph mode. < evaSnp4 |

< evaSnp4 | < evaSnp4 |

Searching, details, and filtering

< evaSnp4 |

< evaSnp4 | Navigation to an individual variant can be accomplished by typing or copying < evaSnp4 | the variant identifier (rsID) or the genomic coordinates into the Position/Search box on the < evaSnp4 | Browser.

< evaSnp4 | < evaSnp4 |

< evaSnp4 | A click on an item in the graphical display displays a page with data about < evaSnp4 | that variant. Data fields include the Reference and Alternate Alleles, the < evaSnp4 | class of the variant as reported by EVA, the source of the data, the amino acid < evaSnp4 | change, if any, and the functional class as determined by UCSC's Variant Annotation < evaSnp4 | Integrator. < evaSnp4 |

< evaSnp4 | < evaSnp4 |

Variants can be filtered using the track controls to show subsets of the < evaSnp4 | data by either EVA Sequence Ontology (SO) term, UCSC-generated functional effect, or < evaSnp4 | by color, which bins the UCSC functional effects into general classes.

< evaSnp4 | < evaSnp4 |

Mouse-over

< evaSnp4 |

< evaSnp4 | Mousing over an item shows the ucscClass, which is the consequence according to the < evaSnp4 | Variant Annotation Integrator, and < evaSnp4 | the aaChange when one is available, which is the change in amino acid in HGVS.p < evaSnp4 | terms. Items may have multiple ucscClasses, which will all be shown in the mouse-over < evaSnp4 | in a comma-separated list. Likewise, multiple HGVS.p terms may be shown for each rsID < evaSnp4 | separated by spaces describing all possible AA changes.

< evaSnp4 |

< evaSnp4 | Multiple items may appear due to different variant predictions on multiple gene transcripts. < evaSnp4 | For all organisms the gene models used were the NCBI RefSeq curated when available, if not then < evaSnp4 | ensembl genes, or finally UCSC mappings of RefSeq if neither of the previous models was possible. < evaSnp4 |

< evaSnp4 | < evaSnp4 |

Track colors

< evaSnp4 | < evaSnp4 |

< evaSnp4 | Variants are colored according to the most potentially deleterious functional effect prediction < evaSnp4 | according to the Variant Annotation Integrator. Specific bins can be seen in the Methods section < evaSnp4 | below. < evaSnp4 |

< evaSnp4 | < evaSnp4 |

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

< evaSnp4 | < evaSnp4 |

Sequence ontology (SO)

< evaSnp4 | < evaSnp4 |

< evaSnp4 | Variants are classified by EVA into one of the following sequence ontology terms: < evaSnp4 |

< evaSnp4 | < evaSnp4 |

substitution — < evaSnp4 | A single nucleotide in the reference is replaced by another, alternate allele < evaSnp4 |
deletion — < evaSnp4 | One or more nucleotides is deleted. The representation in the database is to < evaSnp4 | display one additional nucleotide in both the Reference field (Ref) and the < evaSnp4 | Alternate Allele field (Alt). E.g. a variant that is a deletion of an A < evaSnp4 | maybe be represented as Ref = GA and Alt = G. < evaSnp4 |
insertion — < evaSnp4 | One or more nucleotides is inserted. The representation in the database is to < evaSnp4 | display one additional nucleotide in both the Reference field (Ref) and the < evaSnp4 | Alternate Allele field (Alt). E.g. a variant that is an insertion of a T maybe < evaSnp4 | be represented as Ref = G and Alt = GT < evaSnp4 |
delins — < evaSnp4 | Similar to tandemRepeat, in that the runs of Ref and Alt Alleles are of < evaSnp4 | different length, except that there is more than one type of nucleotide, < evaSnp4 | e.g., Ref = CCAAAAACAAAAACA, Alt = ACAAAAAC. < evaSnp4 |
multipleNucleotideVariant — < evaSnp4 | More than one nucleotide is substituted by an equal number of different < evaSnp4 | nucleotides, e.g., Ref = AA, Alt = GC. < evaSnp4 |
sequence alteration — < evaSnp4 | A parent term meant to signify a deviation from another sequence. Can be < evaSnp4 | assigned to variants that have not been characterized yet. < evaSnp4 |

< evaSnp4 |

< evaSnp4 | < evaSnp4 |

Methods

< evaSnp4 |

< evaSnp4 | Data were downloaded from the European Variation Archive EVA release 4 (2022-11-21) < evaSnp4 | current_ids.vcf.gz files corresponding to the proper assembly.

< evaSnp4 |

< evaSnp4 | Chromosome names were converted to UCSC-style < evaSnp4 | and the variants passed through the < evaSnp4 | Variant Annotation Integrator to < evaSnp4 | predict consequence. For every organism the NCBI RefSeq curated models were used when available, < evaSnp4 | followed by ensembl genes, and finally UCSC mapping of RefSeq when neither of the previous models < evaSnp4 | were possible.

< evaSnp4 |

< evaSnp4 | Variants were then colored according to their predicted consequence in the following fashion: < evaSnp4 |

Protein-altering variants and < evaSnp4 | splice site variants < evaSnp4 | - exon_loss_variant, frameshift_variant, < evaSnp4 | inframe_deletion, inframe_insertion, initiator_codon_variant, missense_variant, < evaSnp4 | splice_acceptor_variant, splice_donor_variant, splice_region_variant, stop_gained, < evaSnp4 | stop_lost, coding_sequence_variant, transcript_ablation
Synonymous codon variants < evaSnp4 | - synonymous_variant, stop_retained_variant
Non-coding transcript or < evaSnp4 | Untranslated Region (UTR) variants < evaSnp4 | - 5_prime_UTR_variant, < evaSnp4 | 3_prime_UTR_variant, complex_transcript_variant, non_coding_transcript_exon_variant
Intergenic and intronic variants - upstream_gene_variant, downstream_gene_variant, < evaSnp4 | intron_variant, intergenic_variant, NMD_transcript_variant, no_sequence_alteration

< evaSnp4 |

< evaSnp4 | < evaSnp4 |

< evaSnp4 | Sequence Ontology ("SO:") < evaSnp4 | terms were converted to the variant classes, then the files were converted to BED, < evaSnp4 | and then bigBed format. < evaSnp4 |

< evaSnp4 |

< evaSnp4 | No functional annotations were provided by the EVA (e.g., missense, nonsense, etc). < evaSnp4 | These were computed using UCSC's Variant Annotation Integrator (Hinrichs, et al., 2016). < evaSnp4 | Amino-acid substitutions for missense variants are based < evaSnp4 | on RefSeq alignments of mRNA transcripts, which do not always match the amino acids < evaSnp4 | predicted from translating the genomic sequence. Therefore, in some instances, the < evaSnp4 | variant and the genomic nucleotide and associated amino acid may be reversed. < evaSnp4 | E.g., a Pro > Arg change from the perspective of the mRNA would be Arg > Pro from < evaSnp4 | the persepective the genomic sequence. Also, in bosTau9, galGal5, rheMac8, < evaSnp4 | danRer10 and danRer11 the mitochondrial sequence was removed or renamed to match UCSC. < evaSnp4 | For complete documentation of the processing of these tracks, read the < evaSnp4 | < evaSnp4 | EVA Release 4 MakeDoc.

< evaSnp4 | < evaSnp4 |

Data Access

< evaSnp4 |

< evaSnp4 | Note: It is not recommeneded to use LiftOver to convert SNPs between assemblies, < evaSnp4 | and more information about how to convert SNPs between assemblies can be found on the following < evaSnp4 | FAQ entry.

< evaSnp4 |

< evaSnp4 | The data can be explored interactively with the Table Browser, < evaSnp4 | or the Data Integrator. For automated analysis, the data may be < evaSnp4 | queried from our REST API. Please refer to our < evaSnp4 | mailing list archives < evaSnp4 | for questions, or our Data Access FAQ for more < evaSnp4 | information.

< evaSnp4 | < evaSnp4 |

< evaSnp4 | For automated download and analysis, this annotation is stored in a bigBed file that < evaSnp4 | can be downloaded from our download server. The file for this track is called evaSnp4.bb. < evaSnp4 | Individual regions or the whole genome annotation can be obtained using our tool < evaSnp4 | bigBedToBed which can be compiled from the source code or downloaded as a precompiled < evaSnp4 | binary for your system. Instructions for downloading source code and binaries can be found < evaSnp4 | here. < evaSnp4 | The tool can also be used to obtain only features within a given range, e.g. < evaSnp4 |

< evaSnp4 | bigBedToBed https://hgdownload.soe.ucsc.edu/gbdb/rn7/bbi/evaSnp4.bb -chrom=chr21 -start=0 -end=100000000 stdout < evaSnp4 |

< evaSnp4 | < evaSnp4 |

Credits

< evaSnp4 |

< evaSnp4 | This track was produced from the European < evaSnp4 | Variation Archive release 4 data. Consequences were predicted using UCSC's Variant Annotation < evaSnp4 | Integrator and NCBI's RefSeq as well as ensembl gene models. < evaSnp4 |

< evaSnp4 | < evaSnp4 |

References

< evaSnp4 |

< evaSnp4 | Cezard T, Cunningham F, Hunt SE, Koylass B, Kumar N, Saunders G, Shen A, Silva AF, < evaSnp4 | Tsukanov K, Venkataraman S et al. The European Variation Archive: a FAIR resource of genomic variation for all < evaSnp4 | species. Nucleic Acids Res. 2021 Oct 28:gkab960. < evaSnp4 | doi:10.1093/nar/gkab960. < evaSnp4 | Epub ahead of print. PMID: 34718739. PMID: PMC8728205. < evaSnp4 |

< evaSnp4 |

< evaSnp4 | Hinrichs AS, Raney BJ, Speir ML, Rhead B, Casper J, Karolchik D, Kuhn RM, Rosenbloom KR, Zweig AS, < evaSnp4 | Haussler D, Kent WJ. < evaSnp4 | UCSC Data Integrator and Variant Annotation Integrator. < evaSnp4 | Bioinformatics. 2016 May 1;32(9):1430-2. < evaSnp4 | PMID: 26740527; PMC: < evaSnp4 | PMC4848401 < evaSnp4 |

< evaSnp4 | < evaSnp5 | html < evaSnp5 |

Description

< evaSnp5 |

< evaSnp5 | This track contains mappings of single nucleotide variants < evaSnp5 | and small insertions and deletions (indels) < evaSnp5 | from the European Variation Archive < evaSnp5 | (EVA) < evaSnp5 | Release 5 for the rat rn7 genome. The dbSNP database at NCBI no longer < evaSnp5 | hosts non-human variants. < evaSnp5 |

< evaSnp5 | < evaSnp5 |

Interpreting and Configuring the Graphical Display

< evaSnp5 |

< evaSnp5 | Variants are shown as single tick marks at most zoom levels. < evaSnp5 | When viewing the track at or near base-level resolution, the displayed < evaSnp5 | width of the SNP variant corresponds to the width of the variant in the < evaSnp5 | reference sequence. Insertions are indicated by a single tick mark displayed < evaSnp5 | between two nucleotides, single nucleotide polymorphisms are displayed as the < evaSnp5 | width of a single base, and multiple nucleotide variants are represented by a < evaSnp5 | block that spans two or more bases. The display is set to automatically collapse to < evaSnp5 | dense visibility when there are more than 100k variants in the window. < evaSnp5 | When the window size is more than 250k bp, the display is switched to density graph mode. < evaSnp5 |

< evaSnp5 | < evaSnp5 |

Searching, details, and filtering

< evaSnp5 |

< evaSnp5 | Navigation to an individual variant can be accomplished by typing or copying < evaSnp5 | the variant identifier (rsID) or the genomic coordinates into the Position/Search box on the < evaSnp5 | Browser.

< evaSnp5 | < evaSnp5 |

< evaSnp5 | A click on an item in the graphical display displays a page with data about < evaSnp5 | that variant. Data fields include the Reference and Alternate Alleles, the < evaSnp5 | class of the variant as reported by EVA, the source of the data, the amino acid < evaSnp5 | change, if any, and the functional class as determined by UCSC's Variant Annotation < evaSnp5 | Integrator. < evaSnp5 |

< evaSnp5 | < evaSnp5 |

Variants can be filtered using the track controls to show subsets of the < evaSnp5 | data by either EVA Sequence Ontology (SO) term, UCSC-generated functional effect, or < evaSnp5 | by color, which bins the UCSC functional effects into general classes.

< evaSnp5 | < evaSnp5 |

Mouse-over

< evaSnp5 |

< evaSnp5 | Mousing over an item shows the ucscClass, which is the consequence according to the < evaSnp5 | Variant Annotation Integrator, and < evaSnp5 | the aaChange when one is available, which is the change in amino acid in HGVS.p < evaSnp5 | terms. Items may have multiple ucscClasses, which will all be shown in the mouse-over < evaSnp5 | in a comma-separated list. Likewise, multiple HGVS.p terms may be shown for each rsID < evaSnp5 | separated by spaces describing all possible AA changes.

< evaSnp5 |

< evaSnp5 | Multiple items may appear due to different variant predictions on multiple gene transcripts. < evaSnp5 | For all organisms the gene models used were the NCBI RefSeq curated when available, if not then < evaSnp5 | ensembl genes, or finally UCSC mappings of RefSeq if neither of the previous models was possible. < evaSnp5 |

< evaSnp5 | < evaSnp5 |

Track colors

< evaSnp5 | < evaSnp5 |

< evaSnp5 | Variants are colored according to the most potentially deleterious functional effect prediction < evaSnp5 | according to the Variant Annotation Integrator. Specific bins can be seen in the Methods section < evaSnp5 | below. < evaSnp5 |

< evaSnp5 | < evaSnp5 |

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

< evaSnp5 | < evaSnp5 |

Sequence ontology (SO)

< evaSnp5 | < evaSnp5 |

< evaSnp5 | Variants are classified by EVA into one of the following sequence ontology terms: < evaSnp5 |

< evaSnp5 | < evaSnp5 |

substitution — < evaSnp5 | A single nucleotide in the reference is replaced by another, alternate allele < evaSnp5 |
deletion — < evaSnp5 | One or more nucleotides is deleted. The representation in the database is to < evaSnp5 | display one additional nucleotide in both the Reference field (Ref) and the < evaSnp5 | Alternate Allele field (Alt). E.g. a variant that is a deletion of an A < evaSnp5 | maybe be represented as Ref = GA and Alt = G. < evaSnp5 |
insertion — < evaSnp5 | One or more nucleotides is inserted. The representation in the database is to < evaSnp5 | display one additional nucleotide in both the Reference field (Ref) and the < evaSnp5 | Alternate Allele field (Alt). E.g. a variant that is an insertion of a T maybe < evaSnp5 | be represented as Ref = G and Alt = GT < evaSnp5 |
delins — < evaSnp5 | Similar to tandemRepeat, in that the runs of Ref and Alt Alleles are of < evaSnp5 | different length, except that there is more than one type of nucleotide, < evaSnp5 | e.g., Ref = CCAAAAACAAAAACA, Alt = ACAAAAAC. < evaSnp5 |
multipleNucleotideVariant — < evaSnp5 | More than one nucleotide is substituted by an equal number of different < evaSnp5 | nucleotides, e.g., Ref = AA, Alt = GC. < evaSnp5 |
sequence alteration — < evaSnp5 | A parent term meant to signify a deviation from another sequence. Can be < evaSnp5 | assigned to variants that have not been characterized yet. < evaSnp5 |

< evaSnp5 |

< evaSnp5 | < evaSnp5 |

Methods

< evaSnp5 |

< evaSnp5 | Data were downloaded from the European Variation Archive EVA release 5 (2023-9-7) < evaSnp5 | current_ids.vcf.gz files corresponding to the proper assembly.

< evaSnp5 |

< evaSnp5 | Chromosome names were converted to UCSC-style < evaSnp5 | and the variants passed through the < evaSnp5 | Variant Annotation Integrator to < evaSnp5 | predict consequence. For every organism the NCBI RefSeq curated models were used when available, < evaSnp5 | followed by ensembl genes, and finally UCSC mapping of RefSeq when neither of the previous models < evaSnp5 | were possible.

< evaSnp5 |

< evaSnp5 | Variants were then colored according to their predicted consequence in the following fashion: < evaSnp5 |

Protein-altering variants and < evaSnp5 | splice site variants < evaSnp5 | - exon_loss_variant, frameshift_variant, < evaSnp5 | inframe_deletion, inframe_insertion, initiator_codon_variant, missense_variant, < evaSnp5 | splice_acceptor_variant, splice_donor_variant, splice_region_variant, stop_gained, < evaSnp5 | stop_lost, coding_sequence_variant, transcript_ablation
Synonymous codon variants < evaSnp5 | - synonymous_variant, stop_retained_variant
Non-coding transcript or < evaSnp5 | Untranslated Region (UTR) variants < evaSnp5 | - 5_prime_UTR_variant, < evaSnp5 | 3_prime_UTR_variant, complex_transcript_variant, non_coding_transcript_exon_variant
Intergenic and intronic variants - upstream_gene_variant, downstream_gene_variant, < evaSnp5 | intron_variant, intergenic_variant, NMD_transcript_variant, no_sequence_alteration

< evaSnp5 |

< evaSnp5 | < evaSnp5 |

< evaSnp5 | Sequence Ontology ("SO:") < evaSnp5 | terms were converted to the variant classes, then the files were converted to BED, < evaSnp5 | and then bigBed format. < evaSnp5 |

< evaSnp5 |

< evaSnp5 | No functional annotations were provided by the EVA (e.g., missense, nonsense, etc). < evaSnp5 | These were computed using UCSC's Variant Annotation Integrator (Hinrichs, et al., 2016). < evaSnp5 | Amino-acid substitutions for missense variants are based < evaSnp5 | on RefSeq alignments of mRNA transcripts, which do not always match the amino acids < evaSnp5 | predicted from translating the genomic sequence. Therefore, in some instances, the < evaSnp5 | variant and the genomic nucleotide and associated amino acid may be reversed. < evaSnp5 | E.g., a Pro > Arg change from the perspective of the mRNA would be Arg > Pro from < evaSnp5 | the persepective the genomic sequence. Also, in bosTau9, galGal5, rheMac8, < evaSnp5 | danRer10 and danRer11 the mitochondrial sequence was removed or renamed to match UCSC. < evaSnp5 | For complete documentation of the processing of these tracks, read the < evaSnp5 | < evaSnp5 | EVA Release 5 MakeDoc.

< evaSnp5 | < evaSnp5 |

Data Access

< evaSnp5 |

< evaSnp5 | Note: It is not recommeneded to use LiftOver to convert SNPs between assemblies, < evaSnp5 | and more information about how to convert SNPs between assemblies can be found on the following < evaSnp5 | FAQ entry.

< evaSnp5 |

< evaSnp5 | The data can be explored interactively with the Table Browser, < evaSnp5 | or the Data Integrator. For automated analysis, the data may be < evaSnp5 | queried from our REST API. Please refer to our < evaSnp5 | mailing list archives < evaSnp5 | for questions, or our Data Access FAQ for more < evaSnp5 | information.

< evaSnp5 | < evaSnp5 |

< evaSnp5 | For automated download and analysis, this annotation is stored in a bigBed file that < evaSnp5 | can be downloaded from our download server. The file for this track is called evaSnp5.bb. < evaSnp5 | Individual regions or the whole genome annotation can be obtained using our tool < evaSnp5 | bigBedToBed which can be compiled from the source code or downloaded as a precompiled < evaSnp5 | binary for your system. Instructions for downloading source code and binaries can be found < evaSnp5 | here. < evaSnp5 | The tool can also be used to obtain only features within a given range, e.g. < evaSnp5 |

< evaSnp5 | bigBedToBed https://hgdownload.soe.ucsc.edu/gbdb/rn7/bbi/evaSnp5.bb -chrom=chr21 -start=0 -end=100000000 stdout < evaSnp5 |

< evaSnp5 | < evaSnp5 |

Credits

< evaSnp5 |

< evaSnp5 | This track was produced from the European < evaSnp5 | Variation Archive release 5 data. Consequences were predicted using UCSC's Variant Annotation < evaSnp5 | Integrator and NCBI's RefSeq as well as ensembl gene models. < evaSnp5 |

< evaSnp5 | < evaSnp5 |

References

< evaSnp5 |

< evaSnp5 | Cezard T, Cunningham F, Hunt SE, Koylass B, Kumar N, Saunders G, Shen A, Silva AF, < evaSnp5 | Tsukanov K, Venkataraman S et al. The European Variation Archive: a FAIR resource of genomic variation for all < evaSnp5 | species. Nucleic Acids Res. 2021 Oct 28:gkab960. < evaSnp5 | doi:10.1093/nar/gkab960. < evaSnp5 | Epub ahead of print. PMID: 34718739. PMID: PMC8728205. < evaSnp5 |

< evaSnp5 |

< evaSnp5 | Hinrichs AS, Raney BJ, Speir ML, Rhead B, Casper J, Karolchik D, Kuhn RM, Rosenbloom KR, Zweig AS, < evaSnp5 | Haussler D, Kent WJ. < evaSnp5 | UCSC Data Integrator and Variant Annotation Integrator. < evaSnp5 | Bioinformatics. 2016 May 1;32(9):1430-2. < evaSnp5 | PMID: 26740527; PMC: < evaSnp5 | PMC4848401 < evaSnp5 |

Description

< uniprot | < uniprot |

< uniprot | This track shows protein sequences and annotations on them from the UniProt/SwissProt database, < uniprot | mapped to genomic coordinates. < uniprot |

< uniprot |

< uniprot | UniProt/SwissProt data has been curated from scientific publications by the UniProt staff, < uniprot | UniProt/TrEMBL data has been predicted by various computational algorithms. < uniprot | The annotations are divided into multiple subtracks, based on their "feature type" in UniProt. < uniprot | The first two subtracks below - one for SwissProt, one for TrEMBL - show the < uniprot | alignments of protein sequences to the genome, all other tracks below are the protein annotations < uniprot | mapped through these alignments to the genome. < uniprot |

Track Name	Description
UCSC Alignment, SwissProt = curated protein sequences	Protein sequences from SwissProt mapped to the genome. All other < uniprot \| tracks are (start,end) SwissProt annotations on these sequences mapped < uniprot \| through this alignment. Even protein sequences without a single curated < uniprot \| annotation (splice isoforms) are visible in this track. Each UniProt protein < uniprot \| has one main isoform, which is colored in dark. Alternative isoforms are < uniprot \| sequences that do not have annotations on them and are colored in light-blue. < uniprot \| 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 < uniprot \| below are (start,end) TrEMBL annotations mapped to the genome using < uniprot \| this track. This track is hidden by default. To show it, click its < uniprot \| 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

< uniprot |

< uniprot | For consistency and convenience for users of mutation-related tracks, < uniprot | the subtrack "UniProt/SwissProt Variants" is a copy of the track < uniprot | "UniProt Variants" in the track group "Phenotype and Literature", or < uniprot | "Variation and Repeats", depending on the assembly. < uniprot |

< uniprot | < uniprot |

Display Conventions and Configuration

< uniprot | < uniprot |

< uniprot | Genomic locations of UniProt/SwissProt annotations are labeled with a short name for < uniprot | the type of annotation (e.g. "glyco", "disulf bond", "Signal peptide" < uniprot | etc.). A click on them shows the full annotation and provides a link to the UniProt/SwissProt < uniprot | record for more details. TrEMBL annotations are always shown in < uniprot | light blue, except in the Signal Peptides, < uniprot | Extracellular Domains, Transmembrane Domains, and Cytoplamsic domains subtracks.

< uniprot | < uniprot |

< uniprot | Mouse over a feature to see the full UniProt annotation comment. For variants, the mouse over will < uniprot | show the full name of the UniProt disease acronym. < uniprot |

< uniprot | < uniprot |

< uniprot | The subtracks for domains related to subcellular location are sorted from outside to inside of < uniprot | the cell: Signal peptide, < uniprot | extracellular, < uniprot | transmembrane, and cytoplasmic. < uniprot |

< uniprot | < uniprot |

< uniprot | Features in the "UniProt Modifications" (modified residues) track are drawn in < uniprot | light green. Disulfide bonds are shown in < uniprot | dark grey. Topological domains < uniprot | in maroon and zinc finger regions in < uniprot | olive green. < uniprot |

< uniprot | < uniprot |

< uniprot | Duplicate annotations are removed as far as possible: if a TrEMBL annotation < uniprot | has the same genome position and same feature type, comment, disease and < uniprot | mutated amino acids as a SwissProt annotation, it is not shown again. Two < uniprot | annotations mapped through different protein sequence alignments but with the same genome < uniprot | coordinates are only shown once.

< uniprot | < uniprot |

On the configuration page of this track, you can choose to hide any TrEMBL annotations. < uniprot | This filter will also hide the UniProt alternative isoform protein sequences because < uniprot | both types of information are less relevant to most users. Please contact us if you < uniprot | want more detailed filtering features.

< uniprot | < uniprot |

Note that for the human hg38 assembly and SwissProt annotations, there < uniprot | also is a public < uniprot | track hub prepared by UniProt itself, with < uniprot | genome annotations maintained by UniProt using their own mapping < uniprot | method based on those Gencode/Ensembl gene models that are annotated in UniProt < uniprot | for a given protein. For proteins that differ from the genome, UniProt's mapping method < uniprot | will, in most cases, map a protein and its annotations to an unexpected location < uniprot | (see below for details on UCSC's mapping method).

< uniprot | < uniprot |

Methods

< uniprot | < uniprot |

< uniprot | Briefly, UniProt protein sequences were aligned to the transcripts associated < uniprot | with the protein, the top-scoring alignments were retained, and the result was < uniprot | projected to the genome through a transcript-to-genome alignment. < uniprot | Depending on the genome, the transcript-genome alignments was either < uniprot | provided by the source database (NBCI RefSeq), created at UCSC (UCSC RefSeq) or < uniprot | derived from the transcripts (Ensembl/Augustus). The transcript set is NCBI < uniprot | RefSeq for hg38, UCSC RefSeq for hg19 (due to alt/fix haplotype misplacements < uniprot | in the NCBI RefSeq set on hg19). For other genomes, RefSeq, Ensembl and Augustus < uniprot | are tried, in this order. The resulting protein-genome alignments of this process < uniprot | are available in the file formats for liftOver or pslMap from our data archive < uniprot | (see "Data Access" section below). < uniprot |

< uniprot | < uniprot |

An important step of the mapping process protein -> transcript -> < uniprot | genome is filtering the alignment from protein to transcript. Due to < uniprot | differences between the UniProt proteins and the transcripts (proteins were < uniprot | made many years before the transcripts were made, and human genomes have < uniprot | variants), the transcript with the highest BLAST score when aligning the < uniprot | protein to all transcripts is not always the correct transcript for a protein < uniprot | sequence. Therefore, the protein sequence is aligned to only a very short list < uniprot | of one or sometimes more transcripts, selected by a three-step procedure: < uniprot |

Use transcripts directly annotated by UniProt: for organisms that have a RefSeq transcript track, < uniprot | proteins are aligned to the RefSeq transcripts that are annotated < uniprot | by UniProt for this particular protein. < uniprot |
Use transcripts for NCBI Gene ID annotated by UniProt: If no transcripts are annotated on the < uniprot | protein, or the annotated ones have been deprecated by NCBI, but a NCBI Gene ID is < uniprot | annotated, the RefSeq transcripts for this Gene ID are used. This can result in multiple matching transcripts for a protein. < uniprot |
Use best matching transcript: If no NCBI Gene is < uniprot | annotated, then BLAST scores are used to pick the transcripts. There can be multiple transcripts for one < uniprot | protein, as their coding sequences can be identical. All transcripts within 1% of the highest observed BLAST score are used. < uniprot |

< uniprot |

< uniprot | < uniprot |

< uniprot | For strategy 2 and 3, many of the transcripts found do not differ in coding < uniprot | sequence, so the resulting alignments on the genome will be identical. < uniprot | Therefore, any identical alignments are removed in a final filtering step. The < uniprot | details page of these alignments will contain a list of all transcripts that < uniprot | result in the same protein-genome alignment. On hg38, only a handful of edge < uniprot | cases (pseudogenes, very recently added proteins) remain in 2023 where strategy < uniprot | 3 has to be used.

< uniprot | < uniprot |

In other words, when an NCBI or UCSC RefSeq track is used for the mapping and to align a < uniprot | protein sequence to the correct transcript, we use a three stage process: < uniprot |

If UniProt has annotated a given RefSeq transcript for a given protein < uniprot | sequence, the protein is aligned to this transcript. Any difference in the < uniprot | version suffix is tolerated in this comparison. < uniprot |
If no transcript is annotated or the transcript cannot be found in the < uniprot | NCBI/UCSC RefSeq track, the UniProt-annotated NCBI Gene ID is resolved to a < uniprot | set of NCBI RefSeq transcript IDs via the most current version of NCBI < uniprot | genes tables. Only the top match of the resulting alignments and all < uniprot | others within 1% of its score are used for the mapping. < uniprot |
If no transcript can be found after step (2), the protein is aligned to all transcripts, < uniprot | the top match, and all others within 1% of its score are used. < uniprot |

< uniprot | < uniprot |

This system was designed to resolve the problem of incorrect mappings of < uniprot | proteins, mostly on hg38, due to differences between the SwissProt < uniprot | sequences and the genome reference sequence, which has changed since the < uniprot | proteins were defined. The problem is most pronounced for gene families < uniprot | composed of either very repetitive or very similar proteins. To make sure that < uniprot | the alignments always go to the best chromosome location, all _alt and _fix < uniprot | reference patch sequences are ignored for the alignment, so the patches are < uniprot | entirely free of UniProt annotations. Please contact us if you have feedback on < uniprot | this process or example edge cases. We are not aware of a way to evaluate the < uniprot | results completely and in an automated manner.

< uniprot |

< uniprot | Proteins were aligned to transcripts with TBLASTN, converted to PSL, filtered < uniprot | with pslReps (93% query coverage, keep alignments within top 1% score), lifted to genome < uniprot | positions with pslMap and filtered again with pslReps. UniProt annotations were < uniprot | obtained from the UniProt XML file. The UniProt annotations were then mapped to the < uniprot | genome through the alignment described above using the pslMap program. This approach < uniprot | draws heavily on the LS-SNP pipeline by Mark Diekhans. < uniprot | Like all Genome Browser source code, the main script used to build this track < uniprot | can be found on Github. < uniprot |

< uniprot | < uniprot |

Older releases

< uniprot |

< uniprot | This track is automatically updated on an ongoing basis, every 2-3 months. < uniprot | The current version name is always shown on the track details page, it includes the < uniprot | release of UniProt, the version of the transcript set and a unique MD5 that is < uniprot | based on the protein sequences, the transcript sequences, the mapping file < uniprot | between both and the transcript-genome alignment. The exact transcript < uniprot | that was used for the alignment is shown when clicking a protein alignment < uniprot | in one of the two alignment tracks. < uniprot |

< uniprot | < uniprot |

< uniprot | For reproducibility of older analysis results and for manual inspection, previous versions of this track < uniprot | 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 < uniprot | all releases of this track (past and current) can be obtained from our downloads server, including the UniProt < uniprot | protein-to-genome alignment.

< uniprot | < uniprot |

Data Access

< uniprot | < uniprot |

< uniprot | The raw data of the current track can be explored interactively with the < uniprot | Table Browser, or the < uniprot | Data Integrator. < uniprot | For automated analysis, the genome annotation is stored in a bigBed file that < uniprot | can be downloaded from the < uniprot | download server. < uniprot | The exact filenames can be found in the < uniprot | track configuration file. < uniprot | Annotations can be converted to ASCII text by our tool bigBedToBed < uniprot | which can be compiled from the source code or downloaded as a precompiled < uniprot | binary for your system. Instructions for downloading source code and binaries can be found < uniprot | here. < uniprot | The tool can also be used to obtain only features within a given range, for example: < uniprot |

< uniprot | bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/rn7/uniprot/unipStruct.bb -chrom=chr6 -start=0 -end=1000000 stdout < uniprot |

< uniprot | < uniprot |

Lifting from UniProt to genome coordinates in pipelines

< uniprot |

To facilitate mapping protein coordinates to the genome, we provide the < uniprot | alignment files in formats that are suitable for our command line tools. Our < uniprot | command line programs liftOver or pslMap can be used to map < uniprot | coordinates on protein sequences to genome coordinates. The filenames are < uniprot | unipToGenome.over.chain.gz (liftOver) and unipToGenomeLift.psl.gz (pslMap).

< uniprot | < uniprot |

Example commands: < uniprot |

< uniprot | wget -q https://hgdownload.soe.ucsc.edu/goldenPath/archive/hg38/uniprot/2022_03/unipToGenome.over.chain.gz
< uniprot | wget -q https://hgdownload.soe.ucsc.edu/admin/exe/linux.x86_64/liftOver
< uniprot | chmod a+x liftOver
< uniprot | echo 'Q99697 1 10 annotationOnProtein' > prot.bed
< uniprot | liftOver prot.bed unipToGenome.over.chain.gz genome.bed
< uniprot | cat genome.bed
< uniprot |

< uniprot |

< uniprot | < uniprot |

Credits

< uniprot | < uniprot |

< uniprot | This track was created by Maximilian Haeussler at UCSC, with a lot of input from Chris < uniprot | Lee, Mark Diekhans and Brian Raney, feedback from the UniProt staff, Alejo < uniprot | Mujica, Regeneron Pharmaceuticals and Pia Riestra, GeneDx. Thanks to UniProt for making all data < uniprot | available for download. < uniprot |

< uniprot | < uniprot |

References

< uniprot | < uniprot |

< uniprot | < uniprot |

< uniprot | Yip YL, Scheib H, Diemand AV, Gattiker A, Famiglietti LM, Gasteiger E, Bairoch A. < uniprot | < uniprot | The Swiss-Prot variant page and the ModSNP database: a resource for sequence and structure < uniprot | information on human protein variants. < uniprot | Hum Mutat. 2004 May;23(5):464-70. < uniprot | PMID: 15108278 < uniprot |

< uniprot | < unipStruct | html < unipStruct |