Evidence map›Paper›PMID 32439738›Full record

ArticleG3 (Bethesda, Md.)2020

Low Additive Genetic Variation in a Trait Under Selection in Domesticated Rice.

Nicholas G Karavolias, Anthony J Greenberg, Luz S Barrero, Lyza G Maron, Yuxin Shi, Eliana Monteverde, Miguel A Piñeros, Susan R McCouch

Abstract read
In one paragraph

Article in G3 (Bethesda, Md.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Multiple Small-Effect Alleles ofFrontiers in plant science · 2020
    Article
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

8 authors.

Nicholas G KaravoliasSection of Plant Breeding and Genetics, Cornell University, Ithaca, NY.ORCID 0000-0003-1213-771X
Anthony J GreenbergBayesic Research, Ithaca, NY.ORCID 0000-0003-3296-5811
Luz S BarreroSection of Plant Breeding and Genetics, Cornell University, Ithaca, NY.ORCID 0000-0001-6475-2357
Lyza G MaronSection of Plant Breeding and Genetics, Cornell University, Ithaca, NY.
Yuxin ShiSection of Plant Breeding and Genetics, Cornell University, Ithaca, NY.
Eliana MonteverdeSection of Plant Breeding and Genetics, Cornell University, Ithaca, NY.ORCID 0000-0003-1136-198X
Miguel A PiñerosRobert W. Holey Center for Agriculture and Health, USDA-ARS, Ithaca, NY.
Susan R McCouchSection of Plant Breeding and Genetics, Cornell University, Ithaca, NY, srm4@cornell.edu.ORCID 0000-0001-9246-3106

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative traits are important targets of both natural and artificial selection. The genetic architecture of these traits and its change during the adaptive process is thus of fundamental interest. The fate of the additive effects of variants underlying a trait receives particular attention because they constitute the genetic variation component that is transferred from parents to offspring and thus governs the response to selection. While estimation of this component of phenotypic variation is challenging, the increasing availability of dense molecular markers puts it within reach. Inbred plant species offer an additional advantage because phenotypes of genetically identical individuals can be measured in replicate. This makes it possible to estimate marker effects separately from the contribution of the genetic background not captured by genotyped loci. We focused on root growth in domesticated rice,

Indexed as

OryzaBayes TheoremGenetic VariationHumansPhenotypePolymorphism, Single NucleotideQuantitative Trait Lociheritability GWAS abiotic stress stress tolerance

Identifiers

PMID32439738
PMCPMC7341149

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.