Evidence map›Paper›PMID 36968399›Full record

ArticleFrontiers in plant science2023

Meta-QTL and haplo-pheno analysis reveal superior haplotype combinations associated with low grain chalkiness under high temperature in rice.

Anita Kumari, Divya Sharma, Priya Sharma, Sahil, Chaoxin Wang, Vibha Verma, Arun Patil, Md Imran, Madan Pal Singh, Kuldeep Kumar and 8 more

Erratum issuedOpen access · goldFull text read
In one paragraph

Article in Frontiers in plant science, 2023. 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 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
5.0field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

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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

10 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Meta-QTL and ortho analysis unravels the genetic architecture and key candidate genes for cold tolerance at seedling stage in rice.Physiology and molecular biology of plants : an international journal of functional plant biology · 2024
    Article
  9. Article
  10. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors at 3 institutions in 2 countries.

Anita KumariDepartment of Botany, University of Delhi, Delhi, India.
Divya SharmaDepartment of Botany, University of Delhi, Delhi, India.
Priya SharmaDepartment of Botany, University of Delhi, Delhi, India.
Sahil
Chaoxin WangDepartment of Computer Science, Kansas State University, Manhattan, KS, United States.
Vibha VermaDepartment of Plant Molecular Biology, University of Delhi, New Delhi, India.
Arun PatilDepartment of Plant Molecular Biology and Biotechnology, Indira Gandhi Krishi Vishwavidyalaya, Chattisgarh, India.
Md ImranDepartment of Botany, University of Delhi, Delhi, India.
Madan Pal SinghDivision of Plant Physiology, Indian Council of Agricultural Research (ICAR), New Delhi, India.
Kuldeep KumarNational Institute for Plant Biotechnology, Indian Council of Agricultural Research (ICAR), New Delhi, India.
Kumar ParitoshCentre for Genetic Manipulation of Crop Plants, New Delhi, India.
Doina CarageaDepartment of Computer Science, Kansas State University, Manhattan, KS, United States.
Sanjay KapoorDepartment of Plant Molecular Biology, University of Delhi, New Delhi, India.
Girish ChandelDepartment of Plant Molecular Biology and Biotechnology, Indira Gandhi Krishi Vishwavidyalaya, Chattisgarh, India.
Anil GroverDepartment of Plant Molecular Biology, University of Delhi, New Delhi, India.
S V Krishna JagadishDepartment of Plant and Soil Science, Texas Tech University, Lubbock, TX, United States.
Surekha Katiyar-AgarwalDepartment of Plant Molecular Biology, University of Delhi, New Delhi, India.
Manu AgarwalDepartment of Botany, University of Delhi, Delhi, India.
University of Delhi · INIndian Council of Agricultural Research · INKansas State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chalk, an undesirable grain quality trait in rice, is primarily formed due to high temperatures during the grain-filling process. Owing to the disordered starch granule structure, air spaces and low amylose content, chalky grains are easily breakable during milling thereby lowering head rice recovery and its market price. Availability of multiple QTLs associated with grain chalkiness and associated attributes, provided us an opportunity to perform a meta-analysis and identify candidate genes and their alleles contributing to enhanced grain quality. From the 403 previously reported QTLs, 64 Meta-QTLs encompassing 5262 non-redundant genes were identified. MQTL analysis reduced the genetic and physical intervals and nearly 73% meta-QTLs were narrower than 5cM and 2Mb, revealing the hotspot genomic regions. By investigating expression profiles of 5262 genes in previously published datasets, 49 candidate genes were shortlisted on the basis of their differential regulation in at least two of the datasets. We identified non-synonymous allelic variations and haplotypes in 39 candidate genes across the 3K rice genome panel. Further, we phenotyped a subset panel of 60 rice accessions by exposing them to high temperature stress under natural field conditions over two Rabi cropping seasons. Haplo-pheno analysis uncovered haplotype combinations of two starch synthesis genes,

Indexed as

grain chalkinessgranule bound starch synthase Ihaplo-pheno analysishaplotypemeta-QTL analysisstarch metabolismstarch synthase IIa

Identifiers

PMID36968399
PMCPMC10031497
OpenAlexW4323569436

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LicenceCC BY
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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.