A genome-wide association study and genomic prediction for Phakopsora pachyrhizi resistance in soybean
Soybean brown rust (SBR), caused by Phakopsora pachyrhizi, is a devastating fungal disease that threatens global soybean production. This study conducted a genome-wide association study (GWAS) with seven models on a panel of 3,082 soybean accessions to identify the markers associated with SBR resist...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2023-05-01
|
| Series: | Frontiers in Plant Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fpls.2023.1179357/full |
| _version_ | 1797817473864564736 |
|---|---|
| author | Haizheng Xiong Yilin Chen Yong-Bao Pan Jinshe Wang Weiguo Lu Ainong Shi |
| author_facet | Haizheng Xiong Yilin Chen Yong-Bao Pan Jinshe Wang Weiguo Lu Ainong Shi |
| author_sort | Haizheng Xiong |
| collection | DOAJ |
| description | Soybean brown rust (SBR), caused by Phakopsora pachyrhizi, is a devastating fungal disease that threatens global soybean production. This study conducted a genome-wide association study (GWAS) with seven models on a panel of 3,082 soybean accessions to identify the markers associated with SBR resistance by 30,314 high quality single nucleotide polymorphism (SNPs). Then five genomic selection (GS) models, including Ridge regression best linear unbiased predictor (rrBLUP), Genomic best linear unbiased predictor (gBLUP), Bayesian least absolute shrinkage and selection operator (Bayesian LASSO), Random Forest (RF), and Support vector machines (SVM), were used to predict breeding values of SBR resistance using whole genome SNP sets and GWAS-based marker sets. Four SNPs, namely Gm18_57,223,391 (LOD = 2.69), Gm16_29,491,946 (LOD = 3.86), Gm06_45,035,185 (LOD = 4.74), and Gm18_51,994,200 (LOD = 3.60), were located near the reported P. pachyrhizi R genes, Rpp1, Rpp2, Rpp3, and Rpp4, respectively. Other significant SNPs, including Gm02_7,235,181 (LOD = 7.91), Gm02_7234594 (LOD = 7.61), Gm03_38,913,029 (LOD = 6.85), Gm04_46,003,059 (LOD = 6.03), Gm09_1,951,644 (LOD = 10.07), Gm10_39,142,024 (LOD = 7.12), Gm12_28,136,735 (LOD = 7.03), Gm13_16,350,701(LOD = 5.63), Gm14_6,185,611 (LOD = 5.51), and Gm19_44,734,953 (LOD = 6.02), were associated with abundant disease resistance genes, such as Glyma.02G084100, Glyma.03G175300, Glyma.04g189500, Glyma.09G023800, Glyma.12G160400, Glyma.13G064500, Glyma.14g073300, and Glyma.19G190200. The annotations of these genes included but not limited to: LRR class gene, cytochrome 450, cell wall structure, RCC1, NAC, ABC transporter, F-box domain, etc. The GWAS based markers showed more accuracies in genomic prediction than the whole genome SNPs, and Bayesian LASSO model was the ideal model in SBR resistance prediction with 44.5% ~ 60.4% accuracies. This study aids breeders in predicting selection accuracy of complex traits such as disease resistance and can shorten the soybean breeding cycle by the identified markers |
| first_indexed | 2024-03-13T08:53:58Z |
| format | Article |
| id | doaj.art-16889bab8f7c470b919e6c53ceeeb5da |
| institution | Directory Open Access Journal |
| issn | 1664-462X |
| language | English |
| last_indexed | 2024-03-13T08:53:58Z |
| publishDate | 2023-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Plant Science |
| spelling | doaj.art-16889bab8f7c470b919e6c53ceeeb5da2023-05-29T04:23:23ZengFrontiers Media S.A.Frontiers in Plant Science1664-462X2023-05-011410.3389/fpls.2023.11793571179357A genome-wide association study and genomic prediction for Phakopsora pachyrhizi resistance in soybeanHaizheng Xiong0Yilin Chen1Yong-Bao Pan2Jinshe Wang3Weiguo Lu4Ainong Shi5Department of Horticulture, University of Arkansas, Fayetteville, AR, United StatesDepartment of Horticulture, University of Arkansas, Fayetteville, AR, United StatesSugarcane Research Unit, Untied State Department of Agriculture – Agriculture Research Service (USDA-ARS), Houma, LA, United StatesHenan Academy of Crops Molecular Breeding, National Centre for Plant Breeding, Zhengzhou, ChinaHenan Academy of Crops Molecular Breeding, National Centre for Plant Breeding, Zhengzhou, ChinaDepartment of Horticulture, University of Arkansas, Fayetteville, AR, United StatesSoybean brown rust (SBR), caused by Phakopsora pachyrhizi, is a devastating fungal disease that threatens global soybean production. This study conducted a genome-wide association study (GWAS) with seven models on a panel of 3,082 soybean accessions to identify the markers associated with SBR resistance by 30,314 high quality single nucleotide polymorphism (SNPs). Then five genomic selection (GS) models, including Ridge regression best linear unbiased predictor (rrBLUP), Genomic best linear unbiased predictor (gBLUP), Bayesian least absolute shrinkage and selection operator (Bayesian LASSO), Random Forest (RF), and Support vector machines (SVM), were used to predict breeding values of SBR resistance using whole genome SNP sets and GWAS-based marker sets. Four SNPs, namely Gm18_57,223,391 (LOD = 2.69), Gm16_29,491,946 (LOD = 3.86), Gm06_45,035,185 (LOD = 4.74), and Gm18_51,994,200 (LOD = 3.60), were located near the reported P. pachyrhizi R genes, Rpp1, Rpp2, Rpp3, and Rpp4, respectively. Other significant SNPs, including Gm02_7,235,181 (LOD = 7.91), Gm02_7234594 (LOD = 7.61), Gm03_38,913,029 (LOD = 6.85), Gm04_46,003,059 (LOD = 6.03), Gm09_1,951,644 (LOD = 10.07), Gm10_39,142,024 (LOD = 7.12), Gm12_28,136,735 (LOD = 7.03), Gm13_16,350,701(LOD = 5.63), Gm14_6,185,611 (LOD = 5.51), and Gm19_44,734,953 (LOD = 6.02), were associated with abundant disease resistance genes, such as Glyma.02G084100, Glyma.03G175300, Glyma.04g189500, Glyma.09G023800, Glyma.12G160400, Glyma.13G064500, Glyma.14g073300, and Glyma.19G190200. The annotations of these genes included but not limited to: LRR class gene, cytochrome 450, cell wall structure, RCC1, NAC, ABC transporter, F-box domain, etc. The GWAS based markers showed more accuracies in genomic prediction than the whole genome SNPs, and Bayesian LASSO model was the ideal model in SBR resistance prediction with 44.5% ~ 60.4% accuracies. This study aids breeders in predicting selection accuracy of complex traits such as disease resistance and can shorten the soybean breeding cycle by the identified markershttps://www.frontiersin.org/articles/10.3389/fpls.2023.1179357/fullGWASsoybeandisease resistancegenomic predictionPhakopsora pachyrhizi |
| spellingShingle | Haizheng Xiong Yilin Chen Yong-Bao Pan Jinshe Wang Weiguo Lu Ainong Shi A genome-wide association study and genomic prediction for Phakopsora pachyrhizi resistance in soybean Frontiers in Plant Science GWAS soybean disease resistance genomic prediction Phakopsora pachyrhizi |
| title | A genome-wide association study and genomic prediction for Phakopsora pachyrhizi resistance in soybean |
| title_full | A genome-wide association study and genomic prediction for Phakopsora pachyrhizi resistance in soybean |
| title_fullStr | A genome-wide association study and genomic prediction for Phakopsora pachyrhizi resistance in soybean |
| title_full_unstemmed | A genome-wide association study and genomic prediction for Phakopsora pachyrhizi resistance in soybean |
| title_short | A genome-wide association study and genomic prediction for Phakopsora pachyrhizi resistance in soybean |
| title_sort | genome wide association study and genomic prediction for phakopsora pachyrhizi resistance in soybean |
| topic | GWAS soybean disease resistance genomic prediction Phakopsora pachyrhizi |
| url | https://www.frontiersin.org/articles/10.3389/fpls.2023.1179357/full |
| work_keys_str_mv | AT haizhengxiong agenomewideassociationstudyandgenomicpredictionforphakopsorapachyrhiziresistanceinsoybean AT yilinchen agenomewideassociationstudyandgenomicpredictionforphakopsorapachyrhiziresistanceinsoybean AT yongbaopan agenomewideassociationstudyandgenomicpredictionforphakopsorapachyrhiziresistanceinsoybean AT jinshewang agenomewideassociationstudyandgenomicpredictionforphakopsorapachyrhiziresistanceinsoybean AT weiguolu agenomewideassociationstudyandgenomicpredictionforphakopsorapachyrhiziresistanceinsoybean AT ainongshi agenomewideassociationstudyandgenomicpredictionforphakopsorapachyrhiziresistanceinsoybean AT haizhengxiong genomewideassociationstudyandgenomicpredictionforphakopsorapachyrhiziresistanceinsoybean AT yilinchen genomewideassociationstudyandgenomicpredictionforphakopsorapachyrhiziresistanceinsoybean AT yongbaopan genomewideassociationstudyandgenomicpredictionforphakopsorapachyrhiziresistanceinsoybean AT jinshewang genomewideassociationstudyandgenomicpredictionforphakopsorapachyrhiziresistanceinsoybean AT weiguolu genomewideassociationstudyandgenomicpredictionforphakopsorapachyrhiziresistanceinsoybean AT ainongshi genomewideassociationstudyandgenomicpredictionforphakopsorapachyrhiziresistanceinsoybean |