Evidence map›Paper›PMID 24911413›Full record

ArticlePloS one2014

Human genome variation and the concept of genotype networks.

Giovanni Marco Dall'Olio, Jaume Bertranpetit, Andreas Wagner, Hafid Laayouni

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

9 citing papers in PubMed, 21 citations in OpenAlex.

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  9. Impacts of a biobank: Bridging the gap in translational cancer medicine.Indian journal of medical and paediatric oncology : official journal of Indian Society of Medical & Paediatric Oncology
    Review
4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

4 authors at 3 institutions in 3 countries.

Giovanni Marco Dall'OlioInstitut de Biologia Evolutiva, CSIC-Universitat Pompeu Fabra, Barcelona, Catalonia, Spain.
Jaume BertranpetitInstitut de Biologia Evolutiva, CSIC-Universitat Pompeu Fabra, Barcelona, Catalonia, Spain.
Andreas WagnerInstitute of Evolutionary Biology and Environmental Studies, University of Zurich, Zürich, Switzerland; The Swiss Institute of Bioinformatics, Lausanne, Switzerland; The Santa Fe Institute, Santa Fe, New Mexico, United States of America.
Hafid LaayouniInstitut de Biologia Evolutiva, CSIC-Universitat Pompeu Fabra, Barcelona, Catalonia, Spain; Universitat Autonòma de Barcelona, Barcelona, Spain.
Universitat Pompeu Fabra · ESSIB Swiss Institute of Bioinformatics · CHUniversitat Autònoma de Barcelona · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genotype networks are a concept used in systems biology to study sets of genotypes having the same phenotype, and the ability of these to bring forth novel phenotypes. In the past they have been applied to determine the genetic heterogeneity, and stability to mutations, of systems such as metabolic networks and RNA folds. Recently, they have been the base for reconciling the neutralist and selectionist views on evolution. Here, we adapted this concept to the study of population genetics data. Specifically, we applied genotype networks to the human 1000 genomes dataset, and analyzed networks composed of short haplotypes of Single Nucleotide Variants (SNV). The result is a scan of how properties related to genetic heterogeneity and stability to mutations are distributed along the human genome. We found that genes involved in acquired immunity, such as some HLA and MHC genes, tend to have the most heterogeneous and connected networks, and that coding regions tend to be more heterogeneous and stable to mutations than non-coding regions. We also found, using coalescent simulations, that regions under selection have more extended and connected networks. The application of the concept of genotype networks can provide a new opportunity to understand the evolutionary processes that shaped our genome. Learning how the genotype space of each region of our genome has been explored during the evolutionary history of the human species can lead to a better understanding on how selective pressures and neutral factors have shaped genetic diversity within populations and among individuals. Combined with the availability of larger datasets of sequencing data, genotype networks represent a new approach to the study of human genetic diversity that looks to the whole genome, and goes beyond the classical division between selection and neutrality methods.

Indexed as

Genetic Association StudiesGenetic VariationGenome, HumanGenotypeBiological EvolutionComputer SimulationGenetic HeterogeneityGenetic LociGenetics, PopulationGenome-Wide Association StudyHaplotypesHumansModels, GeneticOpen Reading FramesSystems Biology

Identifiers

PMID24911413
PMCPMC4049842
OpenAlexW2061504218

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.