Evidence map›Paper›PMID 36142739›Full record

ArticleInternational journal of molecular sciences2022

Identification of Quantitative Trait Locus and Candidate Genes for Drought Tolerance in a Soybean Recombinant Inbred Line Population.

Wenqi Ouyang, Limiao Chen, Junkui Ma, Xiaorong Liu, Haifeng Chen, Hongli Yang, Wei Guo, Zhihui Shan, Zhonglu Yang, Shuilian Chen and 4 more

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2022. 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
2.7field-weighted citation impact, top 10% 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

7 citing papers in PubMed, 14 citations in OpenAlex.

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  5. Molecular Genetics Enhances Plant Breeding.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 at 3 institutions in 1 country.

Wenqi OuyangKey Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China.
Limiao ChenKey Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China.
Junkui MaThe Industrial Crop Institute, Shanxi Academy of Agricultural Sciences, Taiyuan 030006, China.
Xiaorong LiuThe Industrial Crop Institute, Shanxi Academy of Agricultural Sciences, Taiyuan 030006, China.
Haifeng ChenKey Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China.
Hongli YangKey Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China.
Wei GuoKey Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China.ORCID 0000-0003-0245-3508
Zhihui ShanKey Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China.
Zhonglu YangKey Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China.
Shuilian ChenKey Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China.
Yong ZhanCrop Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Key Laboratory of Cereal Quality Research and Genetic Improvement, Xinjiang Production and Construction Crops, Shihezi 832000, China.
Hengbin ZhangCrop Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Key Laboratory of Cereal Quality Research and Genetic Improvement, Xinjiang Production and Construction Crops, Shihezi 832000, China.
Dong CaoKey Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China.ORCID 0000-0003-3446-5669
Xinan ZhouKey Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China.
Chinese Academy of Agricultural Sciences · CNShanxi Academy of Agricultural Sciences · CNXinjiang Academy of Agricultural and Reclamation Science · CN

Funding

The work was funded by The National Natural Science Foundation of China; The Agricultural Science and Technology Innovation Program; The Opening Project of the Key Laboratory of Oil Crop Biology and Genetics Breeding, Ministry of Agriculture, National Gen 32171957;ASTIP No. CAAS-ZDRW202201;KF2018007;2016ZX08004-002;2016ZX08004-005
6 · The paper itself

Abstract

With global warming and regional decreases in precipitation, drought has become a problem worldwide. As the number of arid regions in the world is increasing, drought has become a major factor leading to significant crop yield reductions and food crises. Soybean is a crop that is relatively sensitive to drought. It is also a crop that requires more water during growth and development. The aim of this study was to identify the quantitative trait locus (QTL) that affects drought tolerance in soybean by using a recombinant inbred line (RIL) population from a cross between the drought-tolerant cultivar 'Jindou21' and the drought-sensitive cultivar 'Zhongdou33'. Nine agronomic and physiological traits were identified under drought and well-watered conditions. Genetic maps were constructed with 923,420 polymorphic single nucleotide polymorphism (SNP) markers distributed on 20 chromosomes at an average genetic distance of 0.57 centimorgan (cM) between markers. A total of five QTLs with a logarithm of odds (LOD) value of 4.035-8.681 were identified on five chromosomes. Under well-watered conditions and drought-stress conditions, one QTL related to the main stem node number was located on chromosome 16, accounting for 17.177% of the phenotypic variation. Nine candidate genes for drought resistance were screened from this QTL, namely

Indexed as

Glycine maxQuantitative Trait LociChromosome MappingDroughtsGATA Transcription FactorsPhenotypePlant BreedingWaterGATA Transcription FactorsWaterdroughtQTLsresequencingRILsoybean

Identifiers

PMID36142739
PMCPMC9504156
OpenAlexW4296353871

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.