Evidence map›Paper›PMID 34800993›Full record

ArticleBMC plant biology2021

Identification of cold tolerance QTLs at the bud burst stage in 211 rice landraces by GWAS.

Caijing Li, Jindong Liu, Jianxin Bian, Tao Jin, Baoli Zou, Shilei Liu, Xiangyu Zhang, Peng Wang, Jingai Tan, Guangliang Wu and 8 more

Open access · goldAbstract readComparative Study
In one paragraph

Article in BMC plant biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
5.0field-weighted citation impact, top 4% of its field
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

17 citing papers in PubMed, 35 citations in OpenAlex.

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  16. The grain yield regulatorFrontiers in genetics · 2022
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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

18 authors at 3 institutions in 1 country.

Caijing LiKey Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045, Jiangxi Province, China.
Jindong LiuAgricultural Genomics Institute in Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518000, Guangdong Province, China.
Jianxin BianPeking University Institute of Advanced Agricultural Sciences, Weifang, 261325, Shandong Province, China.
Tao JinKey Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045, Jiangxi Province, China.
Baoli ZouKey Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045, Jiangxi Province, China.
Shilei LiuKey Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045, Jiangxi Province, China.
Xiangyu ZhangKey Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045, Jiangxi Province, China.
Peng WangKey Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045, Jiangxi Province, China.
Jingai TanKey Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045, Jiangxi Province, China.
Guangliang WuKey Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045, Jiangxi Province, China.
Qin ChenKey Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045, Jiangxi Province, China.
Yanning WangKey Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045, Jiangxi Province, China.
Qi ZhongKey Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045, Jiangxi Province, China.
Shiying HuangKey Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045, Jiangxi Province, China.
Mengmeng YangKey Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045, Jiangxi Province, China.
Tao HuangKey Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045, Jiangxi Province, China.
Haohua HeKey Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045, Jiangxi Province, China. hhhua64@163.com.
Jianmin BianKey Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045, Jiangxi Province, China. jmbian81@126.com.
Jiangxi Agricultural University · CNPeking University · CNAgricultural Genomics Institute at Shenzhen · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRice is a crop that is very sensitive to low temperature, and its morphological development and production are greatly affected by low temperature. Therefore, understanding the genetic basis of cold tolerance in rice is of great significance for mining favorable genes and cultivating excellent rice varieties. However, there have been limited studies focusing on cold tolerance at the bud burst stage; therefore, considerable attention should be given to the genetic basis of cold tolerance at this stage.

resultsIn this study, a natural population consisting of 211 rice landraces collected from 15 provinces in China and other countries was used for the first time to evaluate cold tolerance at the bud burst stage. Population structure analysis showed that this population was divided into two groups and was rich in genetic diversity. Our evaluation results confirmed that japonica rice was more tolerant to cold at the bud burst stage than indica rice. A genome-wide association study (GWAS) was performed with the phenotypic data of 211 rice landraces and a 36,727 SNP dataset under a mixed linear model. Twelve QTLs (P < 0.0001) were identified for the seedling survival rate (SR) after treatment at 4 °C, in which there were five QTLs (qSR2-2, qSR3-1, qSR3-2, qSR3-3 and qSR9) that were colocalized with those from previous studies and seven QTLs (qSR2-1, qSR3-4, qSR3-5, qSR3-6, qSR3-7, qSR4 and qSR7) that were reported for the first time. Among these QTLs, qSR9, harboring the most significant SNP, explained the most phenotypic variation. Through bioinformatics analysis, five genes (LOC_Os09g12440, LOC_Os09g12470, LOC_Os09g12520, LOC_Os09g12580 and LOC_Os09g12720) were identified as candidates for qSR9.

conclusionThis natural population consisting of 211 rice landraces combined with high-density SNPs will serve as a better choice for identifying rice QTLs/genes in the future, and the detected QTLs associated with cold tolerance at the bud burst stage in rice will be conducive to further mining favorable genes and breeding rice varieties under cold stress.

Indexed as

Cold TemperatureCold-Shock ResponseCrops, AgriculturalFlowersGene Expression Regulation, PlantGenes, PlantGenetic VariationGenome-Wide Association StudyGenotypeOryzaQuantitative Trait LociCold toleranceGWASQTLRice landracesSeedling survival rate (SR)

Identifiers

PMID34800993
PMCPMC8605578
OpenAlexW3217432117

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Registered trials

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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.