Evidence map›Paper›PMID 26604664›Full record

ArticleEvolutionary bioinformatics online2015

Using Disease-Associated Coding Sequence Variation to Investigate Functional Compensation by Human Paralogous Proteins.

Sayaka Miura, Stephanie Tate, Sudhir Kumar

Open access · goldAbstract read
In one paragraph

Article in Evolutionary bioinformatics online, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 97% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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 2 institutions in 2 countries.

Sayaka MiuraInstitute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA.
Stephanie TateSchool of Life Sciences, Arizona State University, Tempe, AZ, USA.
Sudhir KumarInstitute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA. ; Department of Biology, Temple University, Philadelphia, PA, USA. ; Center for Excellence in Genome Medicine and Research, King Abdulaziz University, Jeddah, Saudi Arabia.
Temple University · USArizona State University · US

Funding

COMPARATIVE MOLECULAR SEQUENCE ANALYSISR01HG002096 · NHGRI · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI KUMAR, SUDHIR · 2000 to 2013
$3.0M
Graduate and Undergraduate Training in Biomedicine at ASUR25GM099650 · NIGMS · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI NEWFELD, STUART J · 2012 to 2015
$2.2M
Methods for Evolutionary Informed Network Analysis to Discover Disease VariationR01DK098242 · NIDDK · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI DUDLEY, JOEL THOMAS · 2013 to 2016
$1.7M
Computational diagnosis of non-synonymous variations using structural dynamicsR21LM011941 · NLM · TEMPLE UNIV OF THE COMMONWEALTH · PI GEREK INCE, ZEYNEP NEVIN · 2014 to 2015
$404k
NHGRI NIH HHS R01 HG002096NIDDK NIH HHS R01 DK098242NIGMS NIH HHS R25 GM099650NLM NIH HHS R21 LM011941
6 · The paper itself

Abstract

Gene duplication enables the functional diversification in species. It is thought that duplicated genes may be able to compensate if the function of one of the gene copies is disrupted. This possibility is extensively debated with some studies reporting proteome-wide compensation, whereas others suggest functional compensation among only recent gene duplicates or no compensation at all. We report results from a systematic molecular evolutionary analysis to test the predictions of the functional compensation hypothesis. We contrasted the density of Mendelian disease-associated single nucleotide variants (dSNVs) in proteins with no discernable paralogs (singletons) with the dSNV density in proteins found in multigene families. Under the functional compensation hypothesis, we expected to find greater numbers of dSNVs in singletons due to the lack of any compensating partners. Our analyses produced an opposite pattern; paralogs have over 35% higher dSNV density than singletons. We found that these patterns are concordant with similar differences in the rates of amino acid evolution (ie, functional constraints), as the proteins with paralogs have evolved 33% slower than singletons. Our evolutionary constraint explanation is robust to differences in family sizes, ages (young vs. old duplicates), and degrees of amino acid sequence similarities among paralogs. Therefore, disease-associated human variation does not exhibit significant signals of functional compensation among paralogous proteins, but rather an evolutionary constraint hypothesis provides a better explanation for the observed patterns of disease-associated and neutral polymorphisms in the human genome.

Indexed as

evolutionary ratefunctional compensationgene duplicationMendelian diseasesingle nucleotide variants

Identifiers

PMID26604664
PMCPMC4631161
OpenAlexW1905954292

What OpenQuestion holds

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Registered trials

None linked

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.