Evidence map›Paper›PMID 31253955›Full record

ArticleHeredity2020

Analysis of trait heritability in functionally partitioned rice genomes.

Julong Wei, Weibo Xie, Ruidong Li, Shibo Wang, Han Qu, Renyuan Ma, Xiang Zhou, Zhenyu Jia

Abstract read
In one paragraph

Article in Heredity, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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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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

7 citing papers in PubMed.

  1. Article
  2. Genomic selection for genotype performance and stability using information on multiple traits and multiple environments.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023
    Article
  3. Article
  4. Article
  5. Review
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  7. Review
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.

Julong WeiCollege of Animal Science and Technology, Nanjing Agricultural University, Nanjing, Jiangsu, China.
Weibo XieNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, Hubei, China.ORCID http://orcid.org/0000-0002-2768-3572
Ruidong LiDepartment of Botany & Plant Sciences, University of California (Riverside), Riverside, CA, USA.
Shibo WangDepartment of Botany & Plant Sciences, University of California (Riverside), Riverside, CA, USA.ORCID http://orcid.org/0000-0001-5937-4718
Han QuDepartment of Botany & Plant Sciences, University of California (Riverside), Riverside, CA, USA.
Renyuan MaDepartment of Botany & Plant Sciences, University of California (Riverside), Riverside, CA, USA.
Xiang ZhouDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
Zhenyu JiaDepartment of Botany & Plant Sciences, University of California (Riverside), Riverside, CA, USA. zhenyuj@ucr.edu.ORCID http://orcid.org/0000-0002-1428-904X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Knowledge of the genetic architecture of importantly agronomical traits can speed up genetic improvement in cultivated rice (Oryza sativa L.). Many recent investigations have leveraged genome-wide association studies (GWAS) to identify single nucleotide polymorphisms (SNPs), associated with agronomic traits in various rice populations. The reported trait-relevant SNPs appear to be arbitrarily distributed along the genome, including genic and nongenic regions. Whether the SNPs in different genomic regions play different roles in trait heritability and which region is more responsible for phenotypic variation remains opaque. We analyzed a natural rice population of 524 accessions with 3,616,597 SNPs to compare the genetic contributions of functionally distinct genomic regions for five agronomic traits, i.e., yield, heading date, plant height, grain length, and grain width. An analysis of heritability in the functionally partitioned rice genome showed that regulatory or intergenic regions account for the most trait heritability. A close look at the trait-associated SNPs (TASs) indicated that the majority of the TASs are located in nongenic regions, and the genetic effects of the TASs in nongenic regions are generally greater than those in genic regions. We further compared the predictabilities using the genetic variants from genic regions with those using nongenic regions. The results revealed that nongenic regions play a more important role than genic regions in trait heritability in rice, which is consistent with findings in humans and maize. This conclusion not only offers clues for basic research to disclose genetics behind these agronomic traits, but also provides a new perspective to facilitate genomic selection in rice.

Indexed as

Genome, PlantOryzaPolymorphism, Single NucleotideCrops, AgriculturalGenetic Association StudiesPhenotypeQuantitative Trait Loci

Identifiers

PMID31253955
PMCPMC7029009

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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.