Evidence map›Paper›PMID 38589730›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2024

Genetic dissection of ten photosynthesis-related traits based on InDel- and SNP-GWAS in soybean.

Dezhou Hu, Yajun Zhao, Lixun Zhu, Xiao Li, Jinyu Zhang, Xuan Cui, Wenlong Li, Derong Hao, Zhongyi Yang, Fei Wu and 4 more

Abstract read
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In one paragraph

Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
7.2field-weighted citation impact, top 3% 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

9 citing papers in PubMed, 12 citations in OpenAlex.

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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 2 institutions in 1 country.

Dezhou HuNational Center for Soybean Improvement, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China.
Yajun ZhaoNational Center for Soybean Improvement, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China.
Lixun ZhuNational Center for Soybean Improvement, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China.
Xiao LiNational Center for Soybean Improvement, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China.
Jinyu ZhangHenan Collaborative Innovation Center of Modern Biological Breeding, School of Agriculture, Henan Institute of Science and Technology, Xinxiang, 453003, China.
Xuan CuiNational Center for Soybean Improvement, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China.
Wenlong LiNational Center for Soybean Improvement, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China.
Derong HaoJiangsu Yanjiang Institute of Agricultural Sciences, Nantong, 226012, China.
Zhongyi YangNational Center for Soybean Improvement, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China.
Fei WuNational Center for Soybean Improvement, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China.
Shupeng DongNational Center for Soybean Improvement, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China.
Xiaoyue SuNational Center for Soybean Improvement, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China.
Fang HuangNational Center for Soybean Improvement, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China. fhuang@njau.edu.cn.
Deyue YuNational Center for Soybean Improvement, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China. dyyu@njau.edu.cn.ORCID http://orcid.org/0000-0001-7263-2750
Nanjing Agricultural University · CNHenan Institute of Science and Technology · CN

Funding

China Postdoctoral Science Foundation 2022M721656Hainan Yazhou Bay Seed Lab B23CQ153PHainan Yazhou Bay Seed Lab B23YQ1503Jiangsu Agriculture Science and Technology Innovation Fund [CX(22)2003]Major Project in Agricultural Biological Breeding 2022ZD0400701National Key Research and Development Program of China 2021YFF1001204National Natural Science Foundation of China 31871649National Natural Science Foundation of China 32072080National Natural Science Foundation of China 32090065National Natural Science Foundation of China 32101742National Natural Science Foundation of China 32301831
6 · The paper itself

Abstract

key messageA total of 416 InDels and 112 SNPs were significantly associated with soybean photosynthesis-related traits. GmIWS1 and GmCDC48 might be related to chlorophyll fluorescence and gas-exchange parameters, respectively. Photosynthesis is one of the main factors determining crop yield. A better understanding of the genetic architecture for photosynthesis is of great significance for soybean yield improvement. Our previous studies identified 5,410,112 single nucleotide polymorphisms (SNPs) from the resequencing data of 219 natural soybean accessions. Here, we identified 634,106 insertions and deletions (InDels) from these 219 accessions and used these InDel variations to perform principal component and linkage disequilibrium analysis of this population. The genome-wide association study (GWAS) were conducted on six chlorophyll fluorescence parameters (chlorophyll content, light energy absorbed per reaction center, quantum yield for electron transport, probability that a trapped exciton moves an electron into the electron transport chain beyond primary quinone acceptor, maximum quantum yield of photosystem II primary photochemistry in the dark-adapted state, performance index on absorption basis) and four gas-exchange parameters (intercellular carbon dioxide concentration, stomatal conductance, net photosynthesis rate, transpiration rate) and revealed 416 significant InDels and 112 significant SNPs. Based on GWAS results, GmIWS1 (encoding a transcription elongation factor) and GmCDC48 (encoding a cell division cycle protein) with the highest expression in the mapping region were determined as the candidate genes responsible for chlorophyll fluorescence and gas-exchange parameters, respectively. Further identification of favorable haplotypes with higher photosynthesis, seed weight and seed yield were carried out for GmIWS1 and GmCDC48. Overall, this study revealed the natural variations and candidate genes underlying the photosynthesis-related traits based on abundant phenotypic and genetic data, providing valuable insights into the genetic mechanisms controlling photosynthesis and yield in soybean.

Indexed as

Genome-Wide Association StudyGlycine maxChlorophyllPhotosynthesisPolymorphism, Single NucleotideQuantitative Trait LociChlorophyll

Identifiers

PMID38589730
OpenAlexW4394581189

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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.