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Record W2982109274 · doi:10.1101/819615

Common homozygosity for predicted loss-of-function variants reveals both redundant and advantageous effects of dispensable human genes

2019· preprint· en· W2982109274 on OpenAlexaff
Antonio Rausell, Ya-Dan Luo, Marie Lopez, Yoann Seeleuthner, Franck Rapaport, Antoine Favier, Stenson Pd, D.N. Cooper, Étienne Patin, Jean‐Laurent Casanova, Lluís Quintana‐Murci, Laurent Abel

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsSickKids FoundationHospital for Sick Children
FundersNational Center for Advancing Translational SciencesFondation pour la Recherche MédicaleNational Institutes of HealthAgence Nationale de la RechercheSt. Giles Foundation
KeywordsBiologyPseudogeneGeneticsGeneLoss functionPhenotypeAllelePopulationHuman genomeFunction (biology)Genome

Abstract

fetched live from OpenAlex

Abstract Humans homozygous or hemizygous for variants predicted to cause a loss of function of the corresponding protein do not necessarily present with overt clinical phenotypes. However, the set of effectively dispensable genes in the human genome has not yet been fully characterized. We report here 190 autosomal genes with 207 predicted loss-of-function variants, for which the frequency of homozygous individuals exceeds 1% in at least one human population from five major ancestry groups. No such genes were identified on the X and Y chromosomes. Manual curation revealed that 28 variants (15%) had been misannotated as loss-of-function, mainly due to linkage disequilibrium with different compensatory variants. Of the 179 remaining variants in 166 genes (0.82% of 20,232 genes), only 11 alleles in 11 genes had previously been confirmed experimentally to be loss-of-function. The set of 166 dispensable genes was enriched in olfactory receptor genes (41 genes), but depleted of genes expressed in a wide range of organs and in leukocytes. The 125 dispensable non-olfactory receptor genes displayed a relaxation of selective constraints both between species and within humans, consistent with greater redundancy. In total, 62 of these 125 genes were found to be dispensable in at least three human populations, suggesting possible evolution toward pseudogenes. Out of the 179 common loss-of-function variants, 72 could be tested for two neutrality selection statistics, and eight displayed robust signals of positive selection. These variants included the known FUT2 mutant allele conferring resistance to intestinal viruses and an APOL3 variant involved in resistance to parasitic infections. Finally, the 41 dispensable olfactory receptor genes also displayed a strong relaxation of selective constraints similar to that observed for the 341 non-dispensable olfactory receptor genes. Overall, the identification of 166 genes for which a sizeable proportion of humans are homozygous for predicted loss-of-function alleles reveals both redundancies and advantages of such deficiencies for human survival. Significance statement Human genes homozygous for seemingly loss of function (LoF) variants are increasingly reported in a sizeable proportion of individuals without overt clinical phenotypes. Here, we found 166 genes with 179 predicted LoF variants for which the frequency of homozygous individuals exceeds 1% in at least one of the populations present in databases ExAC and gnomAD. This set of putatively dispensable genes showed relaxation of selective constraints suggesting that a large number of these genes are undergoing pseudogenization. Eight of the common LoF variants displayed robust signals of positive selection including two variants located in genes involved in resistance to infectious diseases. The identification of dispensable genes will allow identifying functions that are, at least nowadays, redundant, or possibly advantageous, for human survival.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.007
GPT teacher head0.224
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), 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".

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Citations3
Published2019
Admission routes1
Has abstractyes

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