Identification of major QTLs for soybean seed size and seed weight traits using a RIL population in different environments
IntroductionThe seed weight of soybean [Glycine max (L.) Merr.] is one of the major traits that determine soybean yield and is closely related to seed size. However, the genetic basis of the synergistic regulation of traits related to soybean yield is unclear.MethodsTo understand the molecular genet...
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| Language: | English |
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Frontiers Media S.A.
2023-01-01
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| Series: | Frontiers in Plant Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpls.2022.1094112/full |
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| author | Shilin Luo Shilin Luo Shilin Luo Jia Jia Jia Jia Jia Jia Riqian Liu Riqian Liu Riqian Liu Ruqian Wei Ruqian Wei Ruqian Wei Zhibin Guo Zhibin Guo Zhibin Guo Zhandong Cai Zhandong Cai Zhandong Cai Bo Chen Bo Chen Bo Chen Fuwei Liang Fuwei Liang Fuwei Liang Qiuju Xia Hai Nian Hai Nian Hai Nian Yanbo Cheng Yanbo Cheng Yanbo Cheng |
| author_facet | Shilin Luo Shilin Luo Shilin Luo Jia Jia Jia Jia Jia Jia Riqian Liu Riqian Liu Riqian Liu Ruqian Wei Ruqian Wei Ruqian Wei Zhibin Guo Zhibin Guo Zhibin Guo Zhandong Cai Zhandong Cai Zhandong Cai Bo Chen Bo Chen Bo Chen Fuwei Liang Fuwei Liang Fuwei Liang Qiuju Xia Hai Nian Hai Nian Hai Nian Yanbo Cheng Yanbo Cheng Yanbo Cheng |
| author_sort | Shilin Luo |
| collection | DOAJ |
| description | IntroductionThe seed weight of soybean [Glycine max (L.) Merr.] is one of the major traits that determine soybean yield and is closely related to seed size. However, the genetic basis of the synergistic regulation of traits related to soybean yield is unclear.MethodsTo understand the molecular genetic basis for the formation of soybean yield traits, the present study focused on QTLs mapping for seed size and weight traits in different environments and target genes mining.ResultsA total of 85 QTLs associated with seed size and weight traits were identified using a recombinant inbred line (RIL) population developed from Guizao1×B13 (GB13). We also detected 18 environmentally stable QTLs. Of these, qSL-3-1 was a novel QTL with a stable main effect associated with seed length. It was detected in all environments, three of which explained more than 10% of phenotypic variance (PV), with a maximum of 15.91%. In addition, qSW-20-3 was a novel QTL with a stable main effect associated with seed width, which was identified in four environments. And the amount of phenotypic variance explained (PVE) varied from 9.22 to 21.93%. Five QTL clusters associated with both seed size and seed weight were summarized by QTL cluster identification. Fifteen candidate genes that may be involved in regulating soybean seed size and weight were also screened based on gene function annotation and GO enrichment analysis.DiscussionThe results provide a biologically basic reference for understanding the formation of soybean seed size and weight traits. |
| first_indexed | 2024-04-10T23:44:39Z |
| format | Article |
| id | doaj.art-5a34c5f1ff4047e0b3d83cfa8e8e0ba6 |
| institution | Directory Open Access Journal |
| issn | 1664-462X |
| language | English |
| last_indexed | 2024-04-10T23:44:39Z |
| publishDate | 2023-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Plant Science |
| spelling | doaj.art-5a34c5f1ff4047e0b3d83cfa8e8e0ba62023-01-11T05:24:11ZengFrontiers Media S.A.Frontiers in Plant Science1664-462X2023-01-011310.3389/fpls.2022.10941121094112Identification of major QTLs for soybean seed size and seed weight traits using a RIL population in different environmentsShilin Luo0Shilin Luo1Shilin Luo2Jia Jia3Jia Jia4Jia Jia5Riqian Liu6Riqian Liu7Riqian Liu8Ruqian Wei9Ruqian Wei10Ruqian Wei11Zhibin Guo12Zhibin Guo13Zhibin Guo14Zhandong Cai15Zhandong Cai16Zhandong Cai17Bo Chen18Bo Chen19Bo Chen20Fuwei Liang21Fuwei Liang22Fuwei Liang23Qiuju Xia24Hai Nian25Hai Nian26Hai Nian27Yanbo Cheng28Yanbo Cheng29Yanbo Cheng30The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, Guangdong, ChinaThe Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, Guangdong, ChinaGuangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, Guangdong, ChinaThe State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, Guangdong, ChinaThe Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, Guangdong, ChinaGuangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, Guangdong, ChinaThe State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, Guangdong, ChinaThe Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, Guangdong, ChinaGuangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, Guangdong, ChinaThe State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, Guangdong, ChinaThe Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, Guangdong, ChinaGuangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, Guangdong, ChinaThe State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, Guangdong, ChinaThe Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, Guangdong, ChinaGuangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, Guangdong, ChinaThe State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, Guangdong, ChinaThe Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, Guangdong, ChinaGuangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, Guangdong, ChinaThe State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, Guangdong, ChinaThe Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, Guangdong, ChinaGuangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, Guangdong, ChinaThe State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, Guangdong, ChinaThe Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, Guangdong, ChinaGuangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, Guangdong, ChinaRice Molecular Breeding Institute, Granlux Associated Grains, Shenzhen, Guangdong, ChinaThe State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, Guangdong, ChinaThe Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, Guangdong, ChinaGuangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, Guangdong, ChinaThe State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, Guangdong, ChinaThe Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, Guangdong, ChinaGuangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, Guangdong, ChinaIntroductionThe seed weight of soybean [Glycine max (L.) Merr.] is one of the major traits that determine soybean yield and is closely related to seed size. However, the genetic basis of the synergistic regulation of traits related to soybean yield is unclear.MethodsTo understand the molecular genetic basis for the formation of soybean yield traits, the present study focused on QTLs mapping for seed size and weight traits in different environments and target genes mining.ResultsA total of 85 QTLs associated with seed size and weight traits were identified using a recombinant inbred line (RIL) population developed from Guizao1×B13 (GB13). We also detected 18 environmentally stable QTLs. Of these, qSL-3-1 was a novel QTL with a stable main effect associated with seed length. It was detected in all environments, three of which explained more than 10% of phenotypic variance (PV), with a maximum of 15.91%. In addition, qSW-20-3 was a novel QTL with a stable main effect associated with seed width, which was identified in four environments. And the amount of phenotypic variance explained (PVE) varied from 9.22 to 21.93%. Five QTL clusters associated with both seed size and seed weight were summarized by QTL cluster identification. Fifteen candidate genes that may be involved in regulating soybean seed size and weight were also screened based on gene function annotation and GO enrichment analysis.DiscussionThe results provide a biologically basic reference for understanding the formation of soybean seed size and weight traits.https://www.frontiersin.org/articles/10.3389/fpls.2022.1094112/fullsoybeanseed sizeseed weightstable QTLsQTL clusters |
| spellingShingle | Shilin Luo Shilin Luo Shilin Luo Jia Jia Jia Jia Jia Jia Riqian Liu Riqian Liu Riqian Liu Ruqian Wei Ruqian Wei Ruqian Wei Zhibin Guo Zhibin Guo Zhibin Guo Zhandong Cai Zhandong Cai Zhandong Cai Bo Chen Bo Chen Bo Chen Fuwei Liang Fuwei Liang Fuwei Liang Qiuju Xia Hai Nian Hai Nian Hai Nian Yanbo Cheng Yanbo Cheng Yanbo Cheng Identification of major QTLs for soybean seed size and seed weight traits using a RIL population in different environments Frontiers in Plant Science soybean seed size seed weight stable QTLs QTL clusters |
| title | Identification of major QTLs for soybean seed size and seed weight traits using a RIL population in different environments |
| title_full | Identification of major QTLs for soybean seed size and seed weight traits using a RIL population in different environments |
| title_fullStr | Identification of major QTLs for soybean seed size and seed weight traits using a RIL population in different environments |
| title_full_unstemmed | Identification of major QTLs for soybean seed size and seed weight traits using a RIL population in different environments |
| title_short | Identification of major QTLs for soybean seed size and seed weight traits using a RIL population in different environments |
| title_sort | identification of major qtls for soybean seed size and seed weight traits using a ril population in different environments |
| topic | soybean seed size seed weight stable QTLs QTL clusters |
| url | https://www.frontiersin.org/articles/10.3389/fpls.2022.1094112/full |
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