Evidence map›Paper›PMID 26714258›Full record

ArticlePloS one2015

Genome-Wide Association Study of Grain Appearance and Milling Quality in a Worldwide Collection of Indica Rice Germplasm.

Xianjin Qiu, Yunlong Pang, Zhihua Yuan, Danying Xing, Jianlong Xu, Michael Dingkuhn, Zhikang Li, Guoyou Ye

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing 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

42 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Meta-analysis of QTLs and candidate genes associated with seed germination in rice (Physiology and molecular biology of plants : an international journal of functional plant biology · 2022
    Article
  18. Article
  19. Article
  20. RiceFrontiers in plant science · 2022
    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.

Xianjin QiuEngineering Research Center of Ecology and Agricultural Use of Wetland, Ministry of Education/College of Agriculture, Yangtze University, Jingzhou 434025, China.
Yunlong PangInstitute of Crop Science/National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
Zhihua YuanEngineering Research Center of Ecology and Agricultural Use of Wetland, Ministry of Education/College of Agriculture, Yangtze University, Jingzhou 434025, China.
Danying XingEngineering Research Center of Ecology and Agricultural Use of Wetland, Ministry of Education/College of Agriculture, Yangtze University, Jingzhou 434025, China.
Jianlong XuInstitute of Crop Science/National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
Michael DingkuhnInternational Rice Research Institute, DAPO Box 7777, Metro Manila, Philippines.
Zhikang LiInstitute of Crop Science/National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
Guoyou YeInternational Rice Research Institute, DAPO Box 7777, Metro Manila, Philippines.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Grain appearance quality and milling quality are the main determinants of market value of rice. Breeding for improved grain quality is a major objective of rice breeding worldwide. Identification of genes/QTL controlling quality traits is the prerequisite for increasing breeding efficiency through marker-assisted selection. Here, we reported a genome-wide association study in indica rice to identify QTL associated with 10 appearance and milling quality related traits, including grain length, grain width, grain length to width ratio, grain thickness, thousand grain weight, degree of endosperm chalkiness, percentage of grains with chalkiness, brown rice rate, milled rice rate and head milled rice rate. A diversity panel consisting of 272 indica accessions collected worldwide was evaluated in four locations including Hangzhou, Jingzhou, Sanya and Shenzhen representing indica rice production environments in China and genotyped using genotyping-by-sequencing and Diversity Arrays Technology based on next-generation sequencing technique called DArTseq™. A wide range of variation was observed for all traits in all environments. A total of 16 different association analysis models were compared to determine the best model for each trait-environment combination. Association mapping based on 18,824 high quality markers yielded 38 QTL for the 10 traits. Five of the detected QTL corresponded to known genes or fine mapped QTL. Among the 33 novel QTL identified, qDEC1.1 (qGLWR1.1), qBRR2.2 (qGL2.1), qTGW2.1 (qGL2.2), qGW11.1 (qMRR11.1) and qGL7.1 affected multiple traits with relatively large effects and/or were detected in multiple environments. The research provided an insight of the genetic architecture of rice grain quality and important information for mining genes/QTL with large effects within indica accessions for rice breeding.

Indexed as

Food QualityGenome-Wide Association StudyEdible GrainEnvironmentGenetic MarkersLinkage DisequilibriumOryzaPhenotypeQuantitative Trait LociGenetic Markers

Identifiers

PMID26714258
PMCPMC4694703

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.