Evidence map›Paper›PMID 26424194›Full record

ArticleGenome biology2015

New genes drive the evolution of gene interaction networks in the human and mouse genomes.

Wenyu Zhang, Patrick Landback, Andrea R Gschwend, Bairong Shen, Manyuan Long

Abstract read
In one paragraph

Article in Genome biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.

0numbers the graph read from it
0cells of the map it votes in
66citing papers in PubMed
–field-weighted citation impact
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

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3 · Its place in the literature

Who cites it

66 citing papers in PubMed.

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  14. Horticulture research · 2024
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6 more citing papers are in PubMed but not listed here.

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

5 authors.

Wenyu ZhangCenter for Systems Biology, Soochow University, Suzhou, Jiangsu, 215006, China. wyzhang@uchicago.edu.
Patrick LandbackCommittee on Genetics, The University of Chicago, Chicago, IL, 60637, USA. landback@uchicago.edu.
Andrea R GschwendDepartment of Ecology and Evolution, The University of Chicago, Chicago, IL, 60637, USA. agschwend@uchicago.edu.
Bairong ShenCenter for Systems Biology, Soochow University, Suzhou, Jiangsu, 215006, China. bairong.shen@suda.edu.cn.
Manyuan LongDepartment of Ecology and Evolution, The University of Chicago, Chicago, IL, 60637, USA. mlong@uchicago.edu.

Funding

Genomic analysis of feeding behavior and fitness in DrosophilaR01GM100768 · NIGMS · UNIVERSITY OF CHICAGO · PI LONG, MANYUAN, ZHUANG, XIAOXI · 2012 to 2015
$1.6M
NIGMS NIH HHS R01 GM100768NIGMS NIH HHS R01GM100768-01A1
6 · The paper itself

Abstract

backgroundThe origin of new genes with novel functions creates genetic and phenotypic diversity in organisms. To acquire functional roles, new genes must integrate into ancestral gene-gene interaction (GGI) networks. The mechanisms by which new genes are integrated into ancestral networks, and their evolutionary significance, are yet to be characterized. Herein, we present a study investigating the rates and patterns of new gene-driven evolution of GGI networks in the human and mouse genomes.

resultsWe examine the network topological and functional evolution of new genes that originated at various stages in the human and mouse lineages by constructing and analyzing three different GGI datasets. We find a large number of new genes integrated into GGI networks throughout vertebrate evolution. These genes experienced a gradual integration process into GGI networks, starting on the network periphery and gradually becoming highly connected hubs, and acquiring pleiotropic and essential functions. We identify a few human lineage-specific hub genes that have evolved brain development-related functions. Finally, we explore the possible underlying mechanisms driving the GGI network evolution and the observed patterns of new gene integration process.

conclusionsOur results unveil a remarkable network topological integration process of new genes: over 5000 new genes were integrated into the ancestral GGI networks of human and mouse; new genes gradually acquire increasing number of gene partners; some human-specific genes evolved into hub structure with critical phenotypic effects. Our data cast new conceptual insights into the evolution of genetic networks.

Indexed as

Evolution, MolecularGene Regulatory NetworksGenome, HumanAnimalsBrainGenomeHumansMice

Identifiers

PMID26424194
PMCPMC4590697

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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.