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Record W2951648000 · doi:10.1093/molbev/msz098

Transposable Elements Are Important Contributors to Standing Variation in Gene Expression in Capsella Grandiflora

2019· article· en· W2951648000 on OpenAlexafffund
Jasmina Uzunović, Emily B. Josephs, John R. Stinchcombe, Stephen Wright

Bibliographic record

VenueMolecular Biology and Evolution · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicChromosomal and Genetic Variations
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsBiologyGeneticsExpression quantitative trait lociSingle-nucleotide polymorphismGeneGenomePopulationTransposable elementQuantitative trait locusEnhancerGene expressionRegulation of gene expressionGenotype

Abstract

fetched live from OpenAlex

Transposable elements (TEs) make up a significant portion of eukaryotic genomes and are important drivers of genome evolution. However, the extent to which TEs affect gene expression variation on a genome-wide scale in comparison with other types of variants is still unclear. We characterized TE insertion polymorphisms and their association with gene expression in 124 whole-genome sequences from a single population of Capsella grandiflora, and contrasted this with the effects of single nucleotide polymorphisms (SNPs). Population frequency of insertions was negatively correlated with distance to genes, as well as density of conserved noncoding elements, suggesting that the negative effects of TEs on gene regulation are important in limiting their abundance. Rare TE variants strongly influence gene expression variation, predominantly through downregulation. In contrast, rare SNPs contribute equally to up- and down-regulation, but have a weaker individual effect than TEs. An expression quantitative trait loci (eQTL) analysis shows that a greater proportion of common TEs are eQTLs as opposed to common SNPs, and a third of the genes with TE eQTLs do not have SNP eQTLs. In contrast with rare TE insertions, common insertions are more likely to increase expression, consistent with recent models of cis-regulatory evolution favoring enhancer alleles. Taken together, these results imply that TEs are a significant contributor to gene expression variation and are individually more likely than rare SNPs to cause extreme changes in gene expression.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.555
Threshold uncertainty score0.168

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.216
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations57
Published2019
Admission routes2
Has abstractyes

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