1
|
Angira B, Cerioli T, Famoso AN. Discovery and Validation of Grain Shape Loci in U.S. Rice Germplasm Through Haplotype Characterization. Front Genet 2022; 13:923078. [PMID: 36171886 PMCID: PMC9511171 DOI: 10.3389/fgene.2022.923078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 06/10/2022] [Indexed: 11/21/2022] Open
Abstract
Rice grain shape is a major determinant of rice market value and the end-use. We mapped quantitative trait loci (QTL) for grain shape traits in a bi-parental recombinant inbred line population (Trenasse/Jupiter) and discovered two major grain length QTLs—qGL3.1 and qGL7.1. Previously, a major grain shape gene GS3 was reported in the qGL3.1 region and grain length gene GL7 was reported to be encompassing qGL7.1 locus. The re-sequencing SNP data on the International Rice Research Institute (IRRI) 3K Rice Genome Project (RGP) panel were obtained from the IRRI SNP-Seek database for both genes and haplotype diversity was characterized for each gene in this diverse panel. United States rice germplasm was not well represented in the IRRI 3K RGP database. Therefore, a minimum SNP set was identified for each gene that could differentiate all the characterized haplotypes. These haplotypes in the 3K RGP panel were screened across 323 elite U.S. genotypes using the minimum SNP set. The screening of haplotypes and phenotype association confirmed the role of GS3 under qGL3.1. However, screening of the GL7 haplotypes in the U.S. germplasm panel showed that GL7 did not play a role in qGL7.1, and in addition, GL7.1 did not segregate in the Trenasse/Jupiter RIL population. This concluded that qGL7.1 is a novel QTL discovered on chr7 for grain shape in the Trenasse/Jupiter RIL population. A high-throughput KASP-based SNP marker for each locus (GS3 and qGL7.1) was identified and validated in elite U.S. rice germplasm to be used in an applied rice breeding program.
Collapse
Affiliation(s)
- Brijesh Angira
- H. Rouse Caffey Rice Research Station, Louisiana State University Agricultural Center, Baton Rouge, LA, United States
- *Correspondence: Brijesh Angira, ; Adam N. Famoso,
| | - Tommaso Cerioli
- School of Plant, Environmental and Soil Science, Louisiana State University, Baton Rouge, LA, United States
| | - Adam N. Famoso
- H. Rouse Caffey Rice Research Station, Louisiana State University Agricultural Center, Baton Rouge, LA, United States
- *Correspondence: Brijesh Angira, ; Adam N. Famoso,
| |
Collapse
|
2
|
Belzile F, Jean M, Torkamaneh D, Tardivel A, Lemay MA, Boudhrioua C, Arsenault-Labrecque G, Dussault-Benoit C, Lebreton A, de Ronne M, Tremblay V, Labbé C, O’Donoughue L, St-Amour VTB, Copley T, Fortier E, Ste-Croix DT, Mimee B, Cober E, Rajcan I, Warkentin T, Gagnon É, Legay S, Auclair J, Bélanger R. The SoyaGen Project: Putting Genomics to Work for Soybean Breeders. FRONTIERS IN PLANT SCIENCE 2022; 13:887553. [PMID: 35557742 PMCID: PMC9087807 DOI: 10.3389/fpls.2022.887553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 03/24/2022] [Indexed: 06/15/2023]
Abstract
The SoyaGen project was a collaborative endeavor involving Canadian soybean researchers and breeders from academia and the private sector as well as international collaborators. Its aims were to develop genomics-derived solutions to real-world challenges faced by breeders. Based on the needs expressed by the stakeholders, the research efforts were focused on maximizing realized yield through optimization of maturity and improved disease resistance. The main deliverables related to molecular breeding in soybean will be reviewed here. These include: (1) SNP datasets capturing the genetic diversity within cultivated soybean (both within a worldwide collection of > 1,000 soybean accessions and a subset of 102 short-season accessions (MG0 and earlier) directly relevant to this group); (2) SNP markers for selecting favorable alleles at key maturity genes as well as loci associated with increased resistance to key pathogens and pests (Phytophthora sojae, Heterodera glycines, Sclerotinia sclerotiorum); (3) diagnostic tools to facilitate the identification and mapping of specific pathotypes of P. sojae; and (4) a genomic prediction approach to identify the most promising combinations of parents. As a result of this fruitful collaboration, breeders have gained new tools and approaches to implement molecular, genomics-informed breeding strategies. We believe these tools and approaches are broadly applicable to soybean breeding efforts around the world.
Collapse
Affiliation(s)
- François Belzile
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
| | - Martine Jean
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
| | - Davoud Torkamaneh
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
| | - Aurélie Tardivel
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
- Centre de Recherche sur les Grains (CEROM), Saint-Mathieu-de-Beloeil, QC, Canada
| | - Marc-André Lemay
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
| | - Chiheb Boudhrioua
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
| | | | | | - Amandine Lebreton
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
| | - Maxime de Ronne
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
| | - Vanessa Tremblay
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
| | - Caroline Labbé
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
| | - Louise O’Donoughue
- Centre de Recherche sur les Grains (CEROM), Saint-Mathieu-de-Beloeil, QC, Canada
| | - Vincent-Thomas Boucher St-Amour
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
- Centre de Recherche sur les Grains (CEROM), Saint-Mathieu-de-Beloeil, QC, Canada
| | - Tanya Copley
- Centre de Recherche sur les Grains (CEROM), Saint-Mathieu-de-Beloeil, QC, Canada
| | - Eric Fortier
- Centre de Recherche sur les Grains (CEROM), Saint-Mathieu-de-Beloeil, QC, Canada
| | | | - Benjamin Mimee
- Agriculture and Agri-Food Canada, St-Jean-sur-Richelieu, QC, Canada
| | - Elroy Cober
- Agriculture and Agri-Food Canada, Ottawa, ON, Canada
| | - Istvan Rajcan
- Department of Plant Agriculture, University of Guelph, Guelph, ON, Canada
| | - Tom Warkentin
- Department of Plant Sciences, University of Saskatchewan, Saskatoon, SK, Canada
| | - Éric Gagnon
- Semences Prograin Inc., Saint-Césaire, QC, Canada
- Sevita Genetics, Inkerman, ON, Canada
| | | | | | - Richard Bélanger
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
| |
Collapse
|
3
|
Ficht A, Bruce R, Torkamaneh D, Grainger CM, Eskandari M, Rajcan I. Genetic analysis of sucrose concentration in soybean seeds using a historical soybean genomic panel. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:1375-1383. [PMID: 35112143 DOI: 10.1007/s00122-022-04040-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 01/12/2022] [Indexed: 06/14/2023]
Abstract
KEY MESSAGE Significant QTL for sucrose concentration have been identified using a historical soybean genomic panel, which could aid in the development of food-grade soybean cultivars. Soybean (Glycine max (L.) Merr) is a crop of global importance for both human and animal consumption, which was domesticated in China more than 6000 years ago. A concern about losing genetic diversity as a result of decades of breeding has been expressed by soybean researchers. In order to develop new cultivars, it is critical for breeders to understand the genetic variability present for traits of interest in their program germplasm. Sucrose concentration is becoming an increasingly important trait for the production of soy-food products. The objective of this study was to use a genome-wide association study (GWAS) to identify putative QTL for sucrose concentration in soybean seed. A GWAS panel consisting of 266 historic and current soybean accessions was genotyped with 76 k genotype-by-sequencing (GBS) SNP data and phenotyped in four field locations in Ontario (Canada) from 2015 to 2017. Seven putative QTL were identified on chromosomes 1, 6, 8, 9, 10, 13 and 14. A key gene related to sucrose synthase (Glyma.06g182700) was found to be associated with the QTL located on chromosome 6. This information will facilitate efforts to increase the available genetic variability for sucrose concentration in soybean breeding programs and develop new and improved high-sucrose soybean cultivars suitable for the soy-food industry.
Collapse
Affiliation(s)
- Alexandra Ficht
- Department of Plant Agriculture, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
| | - Robert Bruce
- Department of Plant Agriculture, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
| | - Davoud Torkamaneh
- Department of Plant Agriculture, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
| | - Christopher M Grainger
- Department of Plant Agriculture, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
| | - Milad Eskandari
- Department of Plant Agriculture, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
| | - Istvan Rajcan
- Department of Plant Agriculture, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada.
| |
Collapse
|
4
|
Yoosefzadeh-Najafabadi M, Eskandari M, Belzile F, Torkamaneh D. Genome-Wide Association Study Statistical Models: A Review. Methods Mol Biol 2022; 2481:43-62. [PMID: 35641758 DOI: 10.1007/978-1-0716-2237-7_4] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Statistical models are at the core of the genome-wide association study (GWAS). In this chapter, we provide an overview of single- and multilocus statistical models, Bayesian, and machine learning approaches for association studies in plants. These models are discussed based on their basic methodology, cofactors adjustment accounted for, statistical power and computational efficiency. New statistical models and machine learning algorithms are both showing improved performance in detecting missed signals, rare mutations and prioritizing causal genetic variants; nevertheless, further optimization and validation studies are required to maximize the power of GWAS.
Collapse
Affiliation(s)
| | - Milad Eskandari
- Department of Plant Agriculture, University of Guelph, Guelph, ON, Canada
| | - François Belzile
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, QC, Canada
| | - Davoud Torkamaneh
- Département de Phytologie, Université Laval, Quebec City, QC, Canada.
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, QC, Canada.
| |
Collapse
|
5
|
Identification of yield-related genes through genome-wide association: case study of weeping forsythia, an emerging medicinal crop. Genes Genomics 2022; 44:145-154. [PMID: 34767154 PMCID: PMC8586636 DOI: 10.1007/s13258-021-01186-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 11/02/2021] [Indexed: 11/12/2022]
Abstract
KEY MESSAGE This study identified candidate genes related to fruit yield for an emerging medicinal crop, weeping forsythia. BACKGROUND The genetic basis of crop yield is an agricultural research hotspot. Identifying the genes related to yield traits is the key to increase the yield. Weeping forsythia is an emerging medicinal crop that currently lacks excellent varieties. The genes related to fruit yield in weeping forsythia have not been identified. OBJECTIVE Thus, we aimed to screen the candidate genes related to fruit yield of weeping forsythia by using genome-wide association analysis. METHODS Here, 60 samples from the same field and source of weeping forsythia were collected to identify its yield-related candidate genes. Association analysis was performed on the variant loci and the traits related to yield, i.e., fruit length, width, thickness, and weight. RESULTS Results from admixture, neighbor-joining, and kinship matrix analyses supported the non-significant genetic differentiation of these samples. Significant association was found between 2 variant loci and fruit length, 8 loci and fruit width, 24 loci and fruit thickness, and 13 loci and fruit weight. Further search on the 20 kb up/downstream of these variant loci revealed 1 gene related to fruit length, 16 genes related to fruit width, 12 genes related to fruit thickness, and 13 genes related to fruit weight. Among which, 4 genes, namely, WRKY transcription factor 35, salicylic acid-binding protein, auxin response factor 6, and alpha-mannosidase were highly related to the fruit development of weeping forsythia. CONCLUSION This study identify four candidate genes related to fruit development, which will provide useful information for the subsequent molecular-assisted and genetic breeding of weeping forsythia.
Collapse
|
6
|
Bhat JA, Yu D, Bohra A, Ganie SA, Varshney RK. Features and applications of haplotypes in crop breeding. Commun Biol 2021; 4:1266. [PMID: 34737387 PMCID: PMC8568931 DOI: 10.1038/s42003-021-02782-y] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 10/09/2021] [Indexed: 12/17/2022] Open
Abstract
Climate change with altered pest-disease dynamics and rising abiotic stresses threatens resource-constrained agricultural production systems worldwide. Genomics-assisted breeding (GAB) approaches have greatly contributed to enhancing crop breeding efficiency and delivering better varieties. Fast-growing capacity and affordability of DNA sequencing has motivated large-scale germplasm sequencing projects, thus opening exciting avenues for mining haplotypes for breeding applications. This review article highlights ways to mine haplotypes and apply them for complex trait dissection and in GAB approaches including haplotype-GWAS, haplotype-based breeding, haplotype-assisted genomic selection. Improvement strategies that efficiently deploy superior haplotypes to hasten breeding progress will be key to safeguarding global food security.
Collapse
Affiliation(s)
- Javaid Akhter Bhat
- National Center for Soybean Improvement, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Deyue Yu
- National Center for Soybean Improvement, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Abhishek Bohra
- Crop Improvement Division, ICAR- Indian Institute of Pulses Research (ICAR- IIPR), Kanpur, India
| | - Showkat Ahmad Ganie
- Department of Biotechnology, Visva-Bharati, Santiniketan, 731235, WB, India.
| | - Rajeev K Varshney
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India.
- State Agricultural Biotechnology Centre, Centre for Crop & Food Research Innovation, Food Futures Institute, Murdoch University, Murdoch, WA, Australia.
| |
Collapse
|
7
|
Shook JM, Lourenco D, Singh AK. PATRIOT: A Pipeline for Tracing Identity-by-Descent for Chromosome Segments to Improve Genomic Prediction in Self-Pollinating Crop Species. FRONTIERS IN PLANT SCIENCE 2021; 12:676269. [PMID: 34737757 PMCID: PMC8562157 DOI: 10.3389/fpls.2021.676269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 09/01/2021] [Indexed: 06/13/2023]
Abstract
The lowering genotyping cost is ushering in a wider interest and adoption of genomic prediction and selection in plant breeding programs worldwide. However, improper conflation of historical and recent linkage disequilibrium between markers and genes restricts high accuracy of genomic prediction (GP). Multiple ancestors may share a common haplotype surrounding a gene, without sharing the same allele of that gene. This prevents parsing out genetic effects associated with the underlying allele of that gene among the set of ancestral haplotypes. We present "Parental Allele Tracing, Recombination Identification, and Optimal predicTion" (i.e., PATRIOT) approach that utilizes marker data to allow for a rapid identification of lines carrying specific alleles, increases the accuracy of genomic relatedness and diversity estimates, and improves genomic prediction. Leveraging identity-by-descent relationships, PATRIOT showed an improvement in GP accuracy by 16.6% relative to the traditional rrBLUP method. This approach will help to increase the rate of genetic gain and allow available information to be more effectively utilized within breeding programs.
Collapse
Affiliation(s)
| | - Daniela Lourenco
- Department of Animal and Dairy Science, University of Georgia, Athens, GA, United States
| | - Asheesh K. Singh
- Department of Agronomy, Iowa State University, Ames, IA, United States
| |
Collapse
|