Evidence map›Paper›PMID 31076960›Full record

ArticleRice (New York, N.Y.)2019

Development of Three Sets of High-Throughput Genotyped Rice Chromosome Segment Substitution Lines and QTL Mapping for Eleven Traits.

Bin Zhang, Lianguang Shang, Banpu Ruan, Anpeng Zhang, Shenglong Yang, Hongzhen Jiang, Chaolei Liu, Kai Hong, Hai Lin, Zhenyu Gao and 4 more

Abstract read
In one paragraph

Article in Rice (New York, N.Y.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

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

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Natural variation in WRKY53 confers cold tolerance at the booting stage between japonica and indica rice.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
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  8. BSA-Seq for the Identification of Major Genes for EPN in Rice.International journal of molecular sciences · 2023
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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

14 authors.

Bin ZhangState Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China.
Lianguang ShangAgricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, China.
Banpu RuanState Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China.
Anpeng ZhangState Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China.
Shenglong YangState Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China.
Hongzhen JiangState Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China.
Chaolei LiuState Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China.
Kai HongAgricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, China.
Hai LinAgricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, China.
Zhenyu GaoState Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China.
Jiang HuState Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China.
Dali ZengState Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China.
Longbiao GuoState Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China.
Qian QianState Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China. qianqian188@hotmail.com.ORCID http://orcid.org/0000-0002-5847-9750

Funding

Major Research Plan 91735304National Natural Science Foundation of China 31521064National Postdoctoral Program for Innovative Talents BX201600151Shenzhen Science and Technology Program JSGG20160608160725473Shenzhen Science and Technology Program KQTD2016113010482651
6 · The paper itself

Abstract

backgroundDetecting and mapping chromosomal regions that are related to quantitative phenotypic variation in chromosome segment substitution lines (CSSLs) provides an effective means to characterize the genetic basis of complex agronomic trait. CSSLs are also powerful tools for studying the effects of quantitative trait loci (QTLs) pyramiding and interaction on phenotypic variation.

resultsHere, we developed three sets of CSSLs consisting of 81, 55, and 61 lines, which were derived from PA64s × 9311, Nipponbare × 9311 and PA64s × Nipponbare crosses, respectively. All of the 197 CSSLs were subjected to high-throughput genotyping by whole-genome resequencing to obtain accurate physical maps for the 3 sets of CSSLs. The 3 sets of CSSLs were used to analyze variation for 11 major agronomic traits in Hangzhou and Shenzhen and led to the detection of 71 QTLs with phenotypic effect that ranged from 7.6% to 44.8%. Eight QTLs were commonly detected under two environments for the same phenotype, and there were also 8 QTL clusters that were found. Combined with GWAS on grain length and expression profiles on young panicle tissues, qGL1 detected in CSSLs was fine mapped within a 119 kb region on chromosome 1 and LOC_Os01g53140 and LOC_Os01g53250 were the two most likely candidate genes.

conclusionsOur results indicate that developing CSSLs genotyped by whole-genome resequencing are powerful tools for basic genetic research and provide a platform for the rational design of rice breeding. Meanwhile, the conjoint analysis of different CSSLs, natural population and expression profiles can facilitate QTL fine mapping.

Indexed as

Chromosome segment substitution lines (CSSLs)Grain lengthGWASHigh-throughput resequencingQTL mapping

Identifiers

PMID31076960
PMCPMC6510774

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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.