Evidence map›Paper›PMID 25144359›Full record

ArticlePLoS computational biology2014

Tracing the evolution of lineage-specific transcription factor binding sites in a birth-death framework.

Ken Daigoro Yokoyama, Yang Zhang, Jian Ma

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.4field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
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  7. Predicting CTCF-mediated chromatin loops using CTCF-MP.Bioinformatics (Oxford, England) · 2018
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Ken Daigoro YokoyamaInstitute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.
Yang ZhangDepartment of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.
Jian MaInstitute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America; Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.
University of Illinois Urbana-Champaign · US

Funding

Computational Methods for Next-Generation Comparative GenomicsR01HG007352 · NHGRI · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI MA, JIAN · 2014 to 2023
$2.8M
IMPROVE GENOME ANNOTATION USING MULTIPLE SEQUENCE ALIGNMENT RELIABILITY SCORESR21HG006464 · NHGRI · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI MA, JIAN · 2012 to 2013
$383k
NHGRI NIH HHS HG006464NHGRI NIH HHS R21 HG006464
6 · The paper itself

Abstract

Changes in cis-regulatory element composition that result in novel patterns of gene expression are thought to be a major contributor to the evolution of lineage-specific traits. Although transcription factor binding events show substantial variation across species, most computational approaches to study regulatory elements focus primarily upon highly conserved sites, and rely heavily upon multiple sequence alignments. However, sequence conservation based approaches have limited ability to detect lineage-specific elements that could contribute to species-specific traits. In this paper, we describe a novel framework that utilizes a birth-death model to trace the evolution of lineage-specific binding sites without relying on detailed base-by-base cross-species alignments. Our model was applied to analyze the evolution of binding sites based on the ChIP-seq data for six transcription factors (GATA1, SOX2, CTCF, MYC, MAX, ETS1) along the lineage toward human after human-mouse common ancestor. We estimate that a substantial fraction of binding sites (∼58-79% for each factor) in humans have origins since the divergence with mouse. Over 15% of all binding sites are unique to hominids. Such elements are often enriched near genes associated with specific pathways, and harbor more common SNPs than older binding sites in the human genome. These results support the ability of our method to identify lineage-specific regulatory elements and help understand their roles in shaping variation in gene regulation across species.

Indexed as

Evolution, MolecularModels, GeneticAnimalsBase SequenceBinding SitesComputational BiologyHumansMiceMolecular Sequence DataPolymorphism, Single NucleotidePrimatesSequence AlignmentSpecies SpecificityTranscription FactorsTranscription Factors

Identifiers

PMID25144359
PMCPMC4140645
OpenAlexW2060652253

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.