fe4c75c272ca27de55c0b42396c47f2b00637a4a jnavarr5 Mon Sep 28 16:36:20 2026 -0700 Linking the encode4ProCap trackDb.ra, saying why PRO-cap and contribution scores are hg38 only on the container page, and limiting the ProCapNet prediction claim to the primary chromosomes, refs #35528 diff --git src/hg/makeDb/trackDb/human/transcriptionStart.html src/hg/makeDb/trackDb/human/transcriptionStart.html index 88bf531564e..9287eae7c91 100644 --- src/hg/makeDb/trackDb/human/transcriptionStart.html +++ src/hg/makeDb/trackDb/human/transcriptionStart.html @@ -1,101 +1,103 @@ <h2>Description</h2> <p> Transcription begins when RNA polymerase II starts making an RNA at a transcription start site (TSS). A gene or a regulatory element does not use a single start site: polymerase initiates across a spread of nearby bases, on both strands, and which bases get used is set largely by the local DNA sequence and by the chromatin state around it. Knowing where transcription starts, and how sharply, matters for reading a promoter, for telling a promoter from an enhancer, and for deciding which of a gene's annotated transcripts is actually made in a given cell. </p> <p> Transcription start site is the common term and the one used here, but it names a position where transcription initiation is the event. Initiation is the more accurate word: polymerase does not start at one fixed point but initiates over a window of bases, at rates that differ base by base, so what these tracks report is the distribution of initiation across a region rather than a single site. </p> <p> No single assay settles where a TSS is. Run-on methods catch the nascent RNA at the moment it is made, cap-based methods read the protected 5' end of a finished transcript, long reads follow a transcript from one end to the other, and sequence models predict initiation without an experiment at all. Each sees a different slice of the same event, and they disagree in informative ways. This collection gathers those lines of evidence in one place so they can be compared at a locus. </p> <p> Tracks currently in the collection: </p> <ul> <li>PRO-cap: initiation events measured directly by PRO-cap in six cell lines by ENCODE 4. Available on GRCh38/hg38 only.</li> <li>ProCapNet: genome-wide, base-resolution predictions of initiation from DNA sequence alone, from six models each trained on one of those cell lines, together with per-base scores showing which bases each model used. The predictions are available on GRCh38/hg38 and T2T-CHM13/hs1; the per-base scores are available on GRCh38/hg38 only.</li> </ul> <p> Each track has its own description page covering what it measures or predicts, -how it was made, and how to download it. The PRO-cap experiments and the -contribution scores were produced against GRCh38, which is why neither is on -T2T-CHM13. More TSS evidence tracks will be added to this collection over time. +how it was made, and how to download it. The PRO-cap experiments were processed +by ENCODE against GRCh38 only, and the contribution scores are computed at MANE +Select transcription start sites, which are not defined for T2T-CHM13, so neither +is on T2T-CHM13. More TSS evidence tracks will be added to this collection over +time. </p> <h2>Display Conventions and Configuration</h2> <p> Tracks are grouped by the evidence they carry, with measurements before predictions. Signal tracks that distinguish the two strands draw the plus strand upward and the minus strand downward, so a divergent promoter reads as a pair of peaks straddling the element. </p> <h2>Data Access</h2> <p> Each track listed above has its own description page with details on methods, file locations and how to download and intersect the data. </p> <h2>Credits</h2> <p> PRO-cap data was generated as part of ENCODE by Sagar Shah and the Yu and Lis labs at Cornell University. ProCapNet was developed by Kelly Cochran in the Kundaje lab at Stanford University, and the genome-wide predictions and contribution scores were generated in collaboration with the GENCODE consortium. </p> <h2>References</h2> <p> Cochran K, Yin M, Mantripragada A, Schreiber J, Marinov GK, Shah SR, Yu H, Lis JT, Kundaje A. <a href="https://www.ncbi.nlm.nih.gov/pubmed/38853896" target="_blank"> Dissecting the cis-regulatory syntax of transcription initiation with deep learning</a>. <em>bioRxiv</em>. 2024 Nov 21;. PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/38853896" target="_blank">38853896</a>; PMC: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11160661/" target="_blank">PMC11160661</a> </p> <p> Kwak H, Fuda NJ, Core LJ, Lis JT. <a href="https://www.ncbi.nlm.nih.gov/pubmed/23430654" target="_blank"> Precise maps of RNA polymerase reveal how promoters direct initiation and pausing</a>. <em>Science</em>. 2013 Feb 22;339(6122):950-3. PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/23430654" target="_blank">23430654</a>; PMC: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3974810/" target="_blank">PMC3974810</a> </p>