Evidence map›Paper›PMID 26172569›Full record

ArticlePLoS genetics2015

A Genome Scan for Genes Underlying Microgeographic-Scale Local Adaptation in a Wild Arabidopsis Species.

Shosei Kubota, Takaya Iwasaki, Kousuke Hanada, Atsushi J Nagano, Asao Fujiyama, Atsushi Toyoda, Sumio Sugano, Yutaka Suzuki, Kouki Hikosaka, Motomi Ito and 1 more

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in PLoS genetics, 2015. 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 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
8.2field-weighted citation impact, top 2% 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

34 citing papers in PubMed, 79 citations in OpenAlex.

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  14. Genomic basis of parallel adaptation varies with divergence inProceedings of the National Academy of Sciences of the United States of America · 2021
    Article
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  19. Parallel Alpine Differentiation inFrontiers in plant science · 2020
    Article
  20. AoB PLANTS · 2019
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 8 institutions in 1 country.

Shosei KubotaGraduate School of Arts and Sciences, The University of Tokyo, Meguro, Tokyo, Japan; College of Bioresource Sciences, Nihon University, Fujisawa, Kanagawa, Japan. skubota44@gmail.com.
Takaya IwasakiGraduate School of Arts and Sciences, The University of Tokyo, Meguro, Tokyo, Japan.
Kousuke HanadaCenter for Sustainable Resource Science, RIKEN, Yokohama, Kanagawa, Japan; Frontier Research Academy for Young Researchers, Kyushu Institute of Technology, Iizuka, Fukuoka, Japan; CREST, Japan Science and Technology Agency, Kawaguchi, Saitama, Japan.
Atsushi J NaganoCenter for Ecological Research, Kyoto University, Otsu, Shiga, Japan; PRESTO, Japan Science and Technology Agency, Kawaguchi, Saitama, Japan.
Asao FujiyamaCenter for Information Biology, National Institute of Genetics, Mishima, Shizuoka, Japan.
Atsushi ToyodaCenter for Information Biology, National Institute of Genetics, Mishima, Shizuoka, Japan.
Sumio SuganoGraduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Chiba, Japan.
Yutaka SuzukiGraduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Chiba, Japan.
Kouki HikosakaCREST, Japan Science and Technology Agency, Kawaguchi, Saitama, Japan; Graduate School of Life Sciences, Tohoku University, Sendai, Miyagai, Japan.
Motomi ItoGraduate School of Arts and Sciences, The University of Tokyo, Meguro, Tokyo, Japan.
Shin-Ichi MorinagaCollege of Bioresource Sciences, Nihon University, Fujisawa, Kanagawa, Japan; CREST, Japan Science and Technology Agency, Kawaguchi, Saitama, Japan.
National Institute of Genetics · JPThe University of Tokyo · JPTokyo University of the Arts · JPJapan Science and Technology Agency · JPKyoto University · JPKyushu Institute of Technology · JPNihon University · JPTohoku University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adaptive divergence at the microgeographic scale has been generally disregarded because high gene flow is expected to disrupt local adaptation. Yet, growing number of studies reporting adaptive divergence at a small spatial scale highlight the importance of this process in evolutionary biology. To investigate the genetic basis of microgeographic local adaptation, we conducted a genome-wide scan among sets of continuously distributed populations of Arabidopsis halleri subsp. gemmifera that show altitudinal phenotypic divergence despite gene flow. Genomic comparisons were independently conducted in two distinct mountains where similar highland ecotypes are observed, presumably as a result of convergent evolution. Here, we established a de novo reference genome and employed an individual-based resequencing for a total of 56 individuals. Among 527,225 reliable SNP loci, we focused on those showing a unidirectional allele frequency shift across altitudes. Statistical tests on the screened genes showed that our microgeographic population genomic approach successfully retrieve genes with functional annotations that are in line with the known phenotypic and environmental differences between altitudes. Furthermore, comparison between the two distinct mountains enabled us to screen out those genes that are neutral or adaptive only in either mountain, and identify the genes involved in the convergent evolution. Our study demonstrates that the genomic comparison among a set of genetically connected populations, instead of the commonly-performed comparison between two isolated populations, can also offer an effective screening for the genetic basis of local adaptation.

Indexed as

Genetics, PopulationAcclimatizationArabidopsisBiological EvolutionGene FlowGene FrequencyGenome, PlantGeographyPhenotypePolymorphism, Single NucleotideReference ValuesSelection, Genetic

Identifiers

PMID26172569
PMCPMC4501782
OpenAlexW1956414220

What OpenQuestion holds

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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.