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Rohilla M, Mazumder A, Chowdhury D, Bhardwaj R, Kumar Mondal T. Understanding natural genetic variation for nutritional quality in grain and identification of superior haplotypes in deepwater rice genotypes of Assam, India. Gene 2024; 928:148801. [PMID: 39068998 DOI: 10.1016/j.gene.2024.148801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 07/21/2024] [Accepted: 07/24/2024] [Indexed: 07/30/2024]
Abstract
Rice grown under deepwater ecosystem is considered to be natural farming and hence they are considered to be input efficient. Thus, to identify gene responsible for nutritional content under natural conditions, a genome-wide association study (GWAS)was performed. GWAS identified single nucleotide polymorphisms (SNPs) significantly associated with various nutritional quality traits such as Zn (mg/kg), Fe (mg/kg), Protein (%), Oil (%), Amylose (%), Starch (%), Phytic acid (%), Phenol (%) and TDF (%) in 184 deepwater rice accessions evaluated over 2 consecutive years. A total of 278 SNPs distributed across 12 chromosomes were found to be significantly associated with Zn, Oil and Phenol content. Among them, eight high confidence SNPs were significant and identified on chr1 (AX-95933712), chr7 (AX-95957036), and chr8 (AX-95965181) for Zn content. Similarly, on chr2 (AX-95945186), chr8 (AX-95964718), and chr11 (AX-95961099) have been found to be associated with Oil content and on chr3 (AX-95922121) and chr4 (AX-95963889) for Phenol content. Genomic regions of ± 220 kb flanking the three consistent lowest p value containing SNPs for each trait were considered for finding superior haplotypes. These SNPs showed significant phenotypic variations with different identified haplotype blocks. The allelic variations with phenotypes were considered to be superior haplotypes i.e., Block 1: Hap 1 (ACCC) for high Zn content, Block 2: Hap 1 (CT) for high Oil content, and Block 2: Hap 1(CGGG) for low Phenol content. The discovered superior haplotype with high nutritional content could be important for understanding the mechanisms involving nutrient use efficiency. Thus, the present study demonstrated that developing rice varieties with appropriate nutritional quality traits will be possible through the incorporation of such superior haplotypes in breeding programs.
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Affiliation(s)
- Megha Rohilla
- ICAR-National Institute for Plant Biotechnology, LBS Centre, Pusa, New Delhi 110012, India
| | - Abhishek Mazumder
- ICAR-National Institute for Plant Biotechnology, LBS Centre, Pusa, New Delhi 110012, India
| | - Dhiren Chowdhury
- Regional Agricultural Research Station, Assam Agricultural University, North Lakhimpur, Assam, India
| | - Rakesh Bhardwaj
- ICAR-National Bureau of Plant Genetic Resources, New Delhi 110012, India
| | - Tapan Kumar Mondal
- ICAR-National Institute for Plant Biotechnology, LBS Centre, Pusa, New Delhi 110012, India.
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Spoorthi V, Ramesh S, Sunitha NC, Vedashree, Vaijayanthi PV, Anilkumar C. Genetic dissection of green pod yield in dolichos bean, an orphan vegetable legume, using new molecular markers. J Appl Genet 2024; 65:429-438. [PMID: 38587611 DOI: 10.1007/s13353-024-00865-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 03/23/2024] [Accepted: 04/02/2024] [Indexed: 04/09/2024]
Abstract
In the era of genomic-assisted breeding for crop improvement, developing new molecular markers and validating them for use in breeding programs are the prelude. Dolichos bean is one of the most important vegetable legume crops owing to its nutrient-rich green pods used as vegetables. Limitations in genomic resources, including molecular markers, restrict the accelerated improvement of the crop. In the present investigation, a set of 430 new simple sequence repeat markers was developed from sequence information of a reference variety. These markers included di- and tri-nucleotide repeats. The markers were assayed on an association panel, which was evaluated for green pod yield over 5 years. A multi-locus model, FarmCPU, was used to assess the marker-trait association analysis. A total of 106 marker-trait associations were identified using an efficient mixed-model approach. Tri-nucleotide repeats were more informative and predominantly associated with trait. Among these markers, 17 were associated with a high level of significance. Markers LP-D-68 and LP-D-14 were identified with a high level of significance in 5-year pooled data and explained 12.70% and 12% of the phenotypic variance, respectively. These markers associated with a high level of confidence have significant scope for use in marker-assisted selection programmes. Other associated markers may be utilized for improving parents through marker-assisted recurrent selection or genomic selection programs.
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Affiliation(s)
- Vinayak Spoorthi
- University of Agricultural Sciences, Bangalore, Karnataka, India
| | - Sampangi Ramesh
- University of Agricultural Sciences, Bangalore, Karnataka, India.
| | | | - Vedashree
- University of Agricultural Sciences, Bangalore, Karnataka, India
| | | | - Chandrappa Anilkumar
- University of Agricultural Sciences, Bangalore, Karnataka, India.
- ICAR-National Rice Research Institute, Cuttack, Odisha, India.
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McNellie JP, May WE, Rieseberg LH, Hulke BS. Association studies of salinity tolerance in sunflower provide robust breeding and selection strategies under climate change. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:184. [PMID: 39008128 DOI: 10.1007/s00122-024-04672-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Accepted: 06/08/2024] [Indexed: 07/16/2024]
Abstract
Phytotoxic soil salinity is a global problem, and in the northern Great Plains and western Canada, salt accumulates on the surface of marine sediment soils with high water tables under annual crop cover, particularly near wetlands. Crop production can overcome saline-affected soils using crop species and cultivars with salinity tolerance along with changes in management practices. This research seeks to improve our understanding of sunflower (Helianthus annuus) genetic tolerance to high salinity soils. Genome-wide association was conducted using the Sunflower Association Mapping panel grown for two years in naturally occurring saline soils (2016 and 2017, near Indian Head, Saskatchewan, Canada), and six phenotypes were measured: days to bloom, height, leaf area, leaf mass, oil percentage, and yield. Plot level soil salinity was determined by grid sampling of soil followed by kriging. Three estimates of sunflower performance were calculated: (1) under low soil salinity (< 4 dS/m), (2) under high soil salinity (> 4 dS/m), and (3) plasticity (regression coefficient between phenotype and soil salinity). Fourteen loci were significant, with one instance of co-localization between a leaf area and a leaf mass locus. Some genomic regions identified as significant in this study were also significant in a recent greenhouse salinity experiment using the same panel. Also, some candidate genes underlying significant QTL have been identified in other plant species as having a role in salinity response. This research identifies alleles for cultivar improvement and for genetic studies to further elucidate salinity tolerance pathways.
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Affiliation(s)
- James P McNellie
- Sunflower and Plant Biology Research Unit, USDA-ARS Edward T Schafer Agricultural Research Center, 1616 Albrecht Blvd. N., Fargo, ND, 58102, USA
| | - William E May
- Indian Head Research Farm, Agriculture and Agri-Food Canada, 1 Government Rd., Indian Head, SK, S0G 2K0, Canada
| | - Loren H Rieseberg
- Department of Botany, University of British Columbia, 3156-6270 University Blvd., Vancouver, BC, V6T 1Z4, Canada
| | - Brent S Hulke
- Sunflower and Plant Biology Research Unit, USDA-ARS Edward T Schafer Agricultural Research Center, 1616 Albrecht Blvd. N., Fargo, ND, 58102, USA.
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Liu S, Chen X, Zhao T, Yu J, Chen P, Wang Y, Wang K, Zhao M, Jiang Y, Wang Y, Zhang M. Identification of PgRg1-3 Gene for Ginsenoside Rg1 Biosynthesis as Revealed by Combining Genome-Wide Association Study and Gene Co-Expression Network Analysis of Jilin Ginseng Core Collection. PLANTS (BASEL, SWITZERLAND) 2024; 13:1784. [PMID: 38999623 PMCID: PMC11244481 DOI: 10.3390/plants13131784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Revised: 06/21/2024] [Accepted: 06/22/2024] [Indexed: 07/14/2024]
Abstract
Ginseng, an important medicinal plant, is characterized by its main active component, ginsenosides. Among more than 40 ginsenosides, Rg1 is one of the ginsenosides used for measuring the quality of ginseng. Therefore, the identification and characterization of genes for Rg1 biosynthesis are important to elucidate the molecular basis of Rg1 biosynthesis. In this study, we utilized 39,327 SNPs and the corresponding Rg1 content from 344 core ginseng cultivars from Jilin Province. We conducted a genome-wide association study (GWAS) combining weighted gene co-expression network analysis (WGCNA), SNP-Rg1 content association analysis, and gene co-expression network analysis; three candidate Rg1 genes (PgRg1-1, PgRg1-2, and PgRg1-3) and one crucial candidate gene (PgRg1-3) were identified. Functional validation of PgRg1-3 was performed using methyl jasmonate (MeJA) regulation and RNAi, confirming that this gene regulates Rg1 biosynthesis. The spatial-temporal expression patterns of the PgRg1-3 gene and known key enzyme genes involved in ginsenoside biosynthesis differ. Furthermore, variations in their networks have a significant impact on Rg1 biosynthesis. This study established an accurate and efficient method for identifying candidate genes, cloned a novel gene controlling Rg1 biosynthesis, and identified 73 SNPs significantly associated with Rg1 content. This provides genetic resources and effective tools for further exploring the molecular mechanisms of Rg1 biosynthesis and molecular breeding.
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Affiliation(s)
- Sizhang Liu
- College of Life Science, Jilin Agricultural University, Changchun 130118, China
| | - Xiaxia Chen
- College of Life Science, Jilin Agricultural University, Changchun 130118, China
| | - Tianqi Zhao
- College of Life Science, Jilin Agricultural University, Changchun 130118, China
| | - Jinghui Yu
- College of Life Science, Jilin Agricultural University, Changchun 130118, China
| | - Ping Chen
- College of Life Science, Jilin Agricultural University, Changchun 130118, China
- Research Center for Ginseng Genetic Resources Development and Utilization, Jilin Province, Jilin Agricultural University, Changchun 130118, China
| | - Yanfang Wang
- College of Chinese Medicinal Materials, Jilin Agricultural University, Changchun 130118, China
| | - Kangyu Wang
- College of Life Science, Jilin Agricultural University, Changchun 130118, China
- Research Center for Ginseng Genetic Resources Development and Utilization, Jilin Province, Jilin Agricultural University, Changchun 130118, China
| | - Mingzhu Zhao
- College of Life Science, Jilin Agricultural University, Changchun 130118, China
- Research Center for Ginseng Genetic Resources Development and Utilization, Jilin Province, Jilin Agricultural University, Changchun 130118, China
| | - Yue Jiang
- College of Life Science, Jilin Agricultural University, Changchun 130118, China
| | - Yi Wang
- College of Life Science, Jilin Agricultural University, Changchun 130118, China
- Research Center for Ginseng Genetic Resources Development and Utilization, Jilin Province, Jilin Agricultural University, Changchun 130118, China
| | - Meiping Zhang
- College of Life Science, Jilin Agricultural University, Changchun 130118, China
- Research Center for Ginseng Genetic Resources Development and Utilization, Jilin Province, Jilin Agricultural University, Changchun 130118, China
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Yaman Y, Kişi YE, Şengül SS, Yıldırım Y, Bay V. Unveiling genetic signatures associated with resilience to neonatal diarrhea in lambs through two GWAS approaches. Sci Rep 2024; 14:13072. [PMID: 38844604 PMCID: PMC11156902 DOI: 10.1038/s41598-024-64093-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Accepted: 06/05/2024] [Indexed: 06/09/2024] Open
Abstract
Neonatal diarrhea presents a significant global challenge due to its multifactorial etiology, resulting in high morbidity and mortality rates, and substantial economic losses. While molecular-level studies on genetic resilience/susceptibility to neonatal diarrhea in farm animals are scarce, prior observations indicate promising research directions. Thus, the present study utilizes two genome-wide association approaches, pKWmEB and MLM, to explore potential links between genetic variations in innate immunity and neonatal diarrhea in Karacabey Merino lambs. Analyzing 707 lambs, including 180 cases and 527 controls, revealed an overall prevalence rate of 25.5%. The pKWmEB analysis identified 13 significant SNPs exceeding the threshold of ≥ LOD 3. Moreover, MLM detected one SNP (s61781.1) in the SLC22A8 gene (p-value, 1.85eE-7), which was co-detected by both methods. A McNemar's test was conducted as the final assessment to identify whether there are any major effective markers among the detected SNPs. Results indicate that four markers-oar3_OAR1_122352257, OAR17_77709936.1, oar3_OAR18_17278638, and s61781.1-have a substantial impact on neonatal diarrhea prevalence (odds ratio: 2.03 to 3.10; statistical power: 0.88 to 0.99). Therefore, we propose the annotated genes harboring three of the associated markers, TIAM1, YDJC, and SLC22A8, as candidate major genes for selective breeding against neonatal diarrhea.
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Affiliation(s)
- Yalçın Yaman
- Department of Genetics, Faculty of Veterinary Medicine, Siirt University, Siirt, 56000, Türkiye.
| | - Yiğit Emir Kişi
- Sheep Research and Breeding Institute, Bandırma Balikesir, Türkiye
| | - Serkan S Şengül
- Sheep Research and Breeding Institute, Bandırma Balikesir, Türkiye
| | - Yasin Yıldırım
- Sheep Research and Breeding Institute, Bandırma Balikesir, Türkiye
| | - Veysel Bay
- Department of Animal Science, Faculty of Agriculture, Ege University, İzmir, 35100, Türkiye
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Elias M, Chere D, Lule D, Serba D, Tirfessa A, Gelmesa D, Tesso T, Bantte K, Menamo TM. Multi-locus genome-wide association study reveal genomic regions underlying root system architecture traits in Ethiopian sorghum germplasm. THE PLANT GENOME 2024; 17:e20436. [PMID: 38361379 DOI: 10.1002/tpg2.20436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 01/19/2024] [Accepted: 01/24/2024] [Indexed: 02/17/2024]
Abstract
The identification of genomic regions underlying the root system architecture (RSA) is vital for improving crop abiotic stress tolerance. To improve sorghum (Sorghum bicolor L. Moench) for environmental stress tolerance, information on genetic variability and genomic regions linked to RSA traits is paramount. The aim of this study was, therefore, to investigate common quantitative trait nucleotides (QTNs) via multiple methodologies and identify genomic regions linked to RSA traits in a panel of 274 Ethiopian sorghum accessions. Multi-locus genome-wide association study was conducted using 265,944 high-quality single nucleotide polymorphism markers. Considering the QTN detected by at least three different methods, a total of 17 reliable QTNs were found to be significantly associated with root angle, number, length, and dry weight. Four QTNs were detected on chromosome SBI-05, followed by SBI-01 and SBI-02 with three QTNs each. Among the 17 QTNs, 11 are colocated with previously identified root traits quantitative trait loci and the remaining six are genome regions with novel genes. A total of 118 genes are colocated with these up- and down-streams of the QTNs. Moreover, five QTNs were found intragenic. These QTNs are S5_8994835 (number of nodal roots), S10_55702393 (number of nodal roots), S1_56872999 (nodal root angle), S9_1212069 (nodal root angle), and S5_5667192 (root dry weight) intragenic regions of Sobic.005G073101, Sobic.010G198000, Sobic.001G273000, Sobic.009G013600, and Sobic.005G054700, respectively. Particularly, Sobic.005G073101, Sobic.010G198000, and Sobic.009G013600 were found responsible for the plant growth hormone-induced RSA. These genes may regulate root development in the seedling stage. Further analysis on these genes might be important to explore the genetic structure of RSA of sorghum.
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Affiliation(s)
- Masarat Elias
- School of Plant Science, Haramaya University, Dire Dawa, Ethiopia
| | - Diriba Chere
- Department of Agronomy, Kansas State University, Manhattan, Kansas, USA
| | - Dagnachew Lule
- Ethiopia Agricultural Transformation Institute, Addis Ababa, Ethiopia
| | - Desalegn Serba
- United States Department of Agriculture, Agricultural Research Service, U.S. Arid Land Agricultural Research Center, Maricopa, Arizona, USA
| | - Alemu Tirfessa
- Ethiopian Institute of Agricultural Research (EIAR), Melkassa Agricultural Research Center, Adama, Ethiopia
| | - Dandena Gelmesa
- School of Plant Science, Haramaya University, Dire Dawa, Ethiopia
| | - Tesfaye Tesso
- Department of Agronomy, Kansas State University, Manhattan, Kansas, USA
| | - Kassahun Bantte
- Department of Plant Science and Horticulture, Jimma University, Jimma, Ethiopia
| | - Temesgen M Menamo
- Department of Plant Science and Horticulture, Jimma University, Jimma, Ethiopia
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Asfaw A, Agre P, Matsumoto R, Olatunji AA, Edemodu A, Olusola T, Odom-Kolombia OL, Adesokan M, Alamu OE, Adebola P, Asiedu R, Maziya-Dixon B. Genome-wide dissection of the genetic factors underlying food quality in boiled and pounded white Guinea yam. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2024; 104:4880-4894. [PMID: 37386916 DOI: 10.1002/jsfa.12816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 05/30/2023] [Accepted: 06/30/2023] [Indexed: 07/01/2023]
Abstract
BACKGROUND Food quality traits related to the genetics of yam influence the acceptability for its consumption. This study aimed at identifying genetic factors underlying sensory and textural quality attributes of boiled and pounded yam, the two dominant food products from white Guinea yam. RESULTS A genome-wide association study (GWAS) of a panel of 184 genotypes derived from five multi-parent crosses population was conducted. The panel was phenotyped for the qualities of boiled and pounded yam using sensory quality and instrument-based textural profile assays. The genotypes displayed significant variation for most of the attributes. Population differentiation and structure analysis using principal component analysis (PCA) and population structure-based Bayesian information criteria revealed the presence of four well-defined clusters. The GWAS results from a multi-random mixed linear model with kinship and PCA used as covariate identified 13 single-nucleotide polymorphic (SNP) markers significantly associated with the boiled and pounded yam food qualities. The associated SNP markers explained 7.51-13.04% of the total phenotypic variance with a limit of detection exceeding 4. CONCLUSION Regions on chromosomes 7 and 15 were found to be associated with boiled and pounded yam quality attributes from sensory and instrument-based assays. Gene annotation analysis for the regions of associated SNPs revealed co-localization of several known putative genes involved in glucose export, hydrolysis and glycerol metabolism. Our study is one of the first reports of genetic factors underlying the boiled and pounded yam food quality to pave the way for marker-assisted selection in white Guinea yam. © 2023 Society of Chemical Industry.
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Affiliation(s)
- Asrat Asfaw
- Yam Breeding, International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria
- Yam Breeding, International Institute of Tropical Agriculture (IITA), Abuja, Nigeria
| | - Paterne Agre
- Yam Breeding, International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria
| | - Ryo Matsumoto
- Yam Breeding, International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria
| | | | - Alex Edemodu
- Yam Breeding, International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria
| | - Theresa Olusola
- Yam Breeding, International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria
| | | | - Michael Adesokan
- Food and Nutrition Sciences Laboratory, International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria
| | - Oladeji Emmanuel Alamu
- International Institute of Tropical Agriculture, Southern Africa Research and Administration Hub (SARAH) Campus, Lusaka, Zambia
| | - Patrick Adebola
- Yam Breeding, International Institute of Tropical Agriculture (IITA), Abuja, Nigeria
| | - Robert Asiedu
- Yam Breeding, International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria
| | - Busie Maziya-Dixon
- Food and Nutrition Sciences Laboratory, International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria
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Wang JT, Chang XY, Zhao Q, Zhang YM. FastBiCmrMLM: a fast and powerful compressed variance component mixed logistic model for big genomic case-control genome-wide association study. Brief Bioinform 2024; 25:bbae290. [PMID: 38888457 PMCID: PMC11184901 DOI: 10.1093/bib/bbae290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 05/19/2024] [Accepted: 06/09/2024] [Indexed: 06/20/2024] Open
Abstract
Large sample datasets have been regarded as the primary basis for innovative discoveries and the solution to missing heritability in genome-wide association studies. However, their computational complexity cannot consider all comprehensive effects and all polygenic backgrounds, which reduces the effectiveness of large datasets. To address these challenges, we included all effects and polygenic backgrounds in a mixed logistic model for binary traits and compressed four variance components into two. The compressed model combined three computational algorithms to develop an innovative method, called FastBiCmrMLM, for large data analysis. These algorithms were tailored to sample size, computational speed, and reduced memory requirements. To mine additional genes, linkage disequilibrium markers were replaced by bin-based haplotypes, which are analyzed by FastBiCmrMLM, named FastBiCmrMLM-Hap. Simulation studies highlighted the superiority of FastBiCmrMLM over GMMAT, SAIGE and fastGWA-GLMM in identifying dominant, small α (allele substitution effect), and rare variants. In the UK Biobank-scale dataset, we demonstrated that FastBiCmrMLM could detect variants as small as 0.03% and with α ≈ 0. In re-analyses of seven diseases in the WTCCC datasets, 29 candidate genes, with both functional and TWAS evidence, around 36 variants identified only by the new methods, strongly validated the new methods. These methods offer a new way to decipher the genetic architecture of binary traits and address the challenges outlined above.
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Affiliation(s)
| | | | | | - Yuan-Ming Zhang
- Corresponding author. College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China. Tel.: +086-13505161564; E-mail:
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Kaur N, Lozada DN, Bhatta M, Barchenger DW, Khokhar ES, Nourbakhsh SS, Sanogo S. Insights into the genetic architecture of Phytophthora capsici root rot resistance in chile pepper (Capsicum spp.) from multi-locus genome-wide association study. BMC PLANT BIOLOGY 2024; 24:416. [PMID: 38760676 PMCID: PMC11100198 DOI: 10.1186/s12870-024-05097-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 05/02/2024] [Indexed: 05/19/2024]
Abstract
BACKGROUND Phytophthora root rot, a major constraint in chile pepper production worldwide, is caused by the soil-borne oomycete, Phytophthora capsici. This study aimed to detect significant regions in the Capsicum genome linked to Phytophthora root rot resistance using a panel consisting of 157 Capsicum spp. genotypes. Multi-locus genome wide association study (GWAS) was conducted using single nucleotide polymorphism (SNP) markers derived from genotyping-by-sequencing (GBS). Individual plants were separately inoculated with P. capsici isolates, 'PWB-185', 'PWB-186', and '6347', at the 4-8 leaf stage and were scored for disease symptoms up to 14-days post-inoculation. Disease scores were used to calculate disease parameters including disease severity index percentage, percent of resistant plants, area under disease progress curve, and estimated marginal means for each genotype. RESULTS Most of the genotypes displayed root rot symptoms, whereas five accessions were completely resistant to all the isolates and displayed no symptoms of infection. A total of 55,117 SNP markers derived from GBS were used to perform multi-locus GWAS which identified 330 significant SNP markers associated with disease resistance. Of these, 56 SNP markers distributed across all the 12 chromosomes were common across the isolates, indicating association with more durable resistance. Candidate genes including nucleotide-binding site leucine-rich repeat (NBS-LRR), systemic acquired resistance (SAR8.2), and receptor-like kinase (RLKs), were identified within 0.5 Mb of the associated markers. CONCLUSIONS Results will be used to improve resistance to Phytophthora root rot in chile pepper by the development of Kompetitive allele-specific markers (KASP®) for marker validation, genomewide selection, and marker-assisted breeding.
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Affiliation(s)
- Navdeep Kaur
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA
- Current address: Department of Horticultural Sciences, Texas A&M University, College Station, TX, 77843, USA
| | - Dennis N Lozada
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA.
- Chile Pepper Institute, New Mexico State University, Las Cruces, NM, 88003, USA.
| | | | | | - Ehtisham S Khokhar
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA
| | - Seyed Shahabeddin Nourbakhsh
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA
- Department of Extension Plant Sciences, New Mexico State University, Las Cruces, NM, 88003, USA
| | - Soum Sanogo
- Department of Entomology, Plant Pathology and Weed Science, New Mexico State University, Las Cruces, NM, 88003, USA
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Sahu TK, Verma SK, Gayacharan, Singh NP, Joshi DC, Wankhede DP, Singh M, Bhardwaj R, Singh B, Parida SK, Chattopadhyay D, Singh GP, Singh AK. Transcriptome-wide association mapping provides insights into the genetic basis and candidate genes governing flowering, maturity and seed weight in rice bean (Vigna umbellata). BMC PLANT BIOLOGY 2024; 24:379. [PMID: 38720284 PMCID: PMC11077894 DOI: 10.1186/s12870-024-04976-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 04/02/2024] [Indexed: 05/12/2024]
Abstract
BACKGROUND Rice bean (Vigna umbellata), an underrated legume, adapts to diverse climatic conditions with the potential to support food and nutritional security worldwide. It is used as a vegetable, minor food crop and a fodder crop, being a rich source of proteins, minerals, and essential fatty acids. However, little effort has been made to decipher the genetic and molecular basis of various useful traits in this crop. Therefore, we considered three economically important traits i.e., flowering, maturity and seed weight of rice bean and identified the associated candidate genes employing an associative transcriptomics approach on 100 diverse genotypes out of 1800 evaluated rice bean accessions from the Indian National Genebank. RESULTS The transcriptomics-based genotyping of one-hundred diverse rice bean cultivars followed by pre-processing of genotypic data resulted in 49,271 filtered markers. The STRUCTURE, PCA and Neighbor-Joining clustering of 100 genotypes revealed three putative sub-populations. The marker-trait association analysis involving various genome-wide association study (GWAS) models revealed significant association of 82 markers on 48 transcripts for flowering, 26 markers on 22 transcripts for maturity and 22 markers on 21 transcripts for seed weight. The transcript annotation provided information on the putative candidate genes for the considered traits. The candidate genes identified for flowering include HSC80, P-II PsbX, phospholipid-transporting-ATPase-9, pectin-acetylesterase-8 and E3-ubiquitin-protein-ligase-RHG1A. Further, the WRKY1 and DEAD-box-RH27 were found to be associated with seed weight. Furthermore, the associations of PIF3 and pentatricopeptide-repeat-containing-gene with maturity and seed weight, and aldo-keto-reductase with flowering and maturity were revealed. CONCLUSION This study offers insights into the genetic basis of key agronomic traits in rice bean, including flowering, maturity, and seed weight. The identified markers and associated candidate genes provide valuable resources for future exploration and targeted breeding, aiming to enhance the agronomic performance of rice bean cultivars. Notably, this research represents the first transcriptome-wide association study in pulse crop, uncovering the candidate genes for agronomically useful traits.
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Affiliation(s)
- Tanmaya Kumar Sahu
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, 110012, India
- ICAR-Indian Grassland and Fodder Research Institute, Jhansi, Uttar Pradesh, India
| | - Sachin Kumar Verma
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, 110012, India
| | - Gayacharan
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, 110012, India
| | | | - Dinesh Chandra Joshi
- ICAR-Vivekananda Parvatiya Krishi Anusandhan Sansthan, Almora, Uttarakhand, India
| | - D P Wankhede
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, 110012, India
| | - Mohar Singh
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, 110012, India
| | - Rakesh Bhardwaj
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, 110012, India
| | - Badal Singh
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, 110012, India
| | - Swarup Kumar Parida
- National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi, India
| | | | | | - Amit Kumar Singh
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, 110012, India.
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11
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He L, Sui Y, Che Y, Liu L, Liu S, Wang X, Cao G. New Insights into the Genetic Basis of Lysine Accumulation in Rice Revealed by Multi-Model GWAS. Int J Mol Sci 2024; 25:4667. [PMID: 38731885 PMCID: PMC11083390 DOI: 10.3390/ijms25094667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2024] [Revised: 04/21/2024] [Accepted: 04/22/2024] [Indexed: 05/13/2024] Open
Abstract
Lysine is an essential amino acid that cannot be synthesized in humans. Rice is a global staple food for humans but has a rather low lysine content. Identification of the quantitative trait nucleotides (QTNs) and genes underlying lysine content is crucial to increase lysine accumulation. In this study, five grain and three leaf lysine content datasets and 4,630,367 single nucleotide polymorphisms (SNPs) of 387 rice accessions were used to perform a genome-wide association study (GWAS) by ten statistical models. A total of 248 and 71 common QTNs associated with grain/leaf lysine content were identified. The accuracy of genomic selection/prediction RR-BLUP models was up to 0.85, and the significant correlation between the number of favorable alleles per accession and lysine content was up to 0.71, which validated the reliability and additive effects of these QTNs. Several key genes were uncovered for fine-tuning lysine accumulation. Additionally, 20 and 30 QTN-by-environment interactions (QEIs) were detected in grains/leaves. The QEI-sf0111954416 candidate gene LOC_Os01g21380 putatively accounted for gene-by-environment interaction was identified in grains. These findings suggested the application of multi-model GWAS facilitates a better understanding of lysine accumulation in rice. The identified QTNs and genes hold the potential for lysine-rich rice with a normal phenotype.
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Affiliation(s)
- Liqiang He
- School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China
| | - Yao Sui
- School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China
| | - Yanru Che
- School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China
| | - Lihua Liu
- School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China
| | - Shuo Liu
- School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China
| | - Xiaobing Wang
- Institute of Tropical Crop Genetic Resources, Chinese Academy of Tropical Agricultural Sciences, Danzhou 571737, China
| | - Guangping Cao
- Hainan Key Laboratory of Crop Genetics and Breeding, Institute of Food Crops, Hainan Academy of Agricultural Sciences, Haikou 571100, China
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12
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Zhao X, Zhan Y, Li K, Zhang Y, Zhou C, Yuan M, Liu M, Li Y, Zuo P, Han Y, Zhao X. Multi-omics analysis reveals novel loci and a candidate regulatory gene of unsaturated fatty acids in soybean (Glycine max (L.) Merr). BIOTECHNOLOGY FOR BIOFUELS AND BIOPRODUCTS 2024; 17:43. [PMID: 38493136 PMCID: PMC10944593 DOI: 10.1186/s13068-024-02489-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Accepted: 03/07/2024] [Indexed: 03/18/2024]
Abstract
BACKGROUND Soybean is a major oil crop; the nutritional components of soybean oil are mainly controlled by unsaturated fatty acids (FA). Unsaturated FAs mainly include oleic acid (OA, 18:1), linoleic acid (LLA, 18:2), and linolenic acid (LNA, 18:3). The genetic architecture of unsaturated FAs in soybean seeds has not been fully elucidated, although many independent studies have been conducted. A 3 V multi-locus random single nucleotide polymorphism (SNP)-effect mixed linear model (3VmrMLM) was established to identify quantitative trait loci (QTLs) and QTL-by-environment interactions (QEIs) for complex traits. RESULTS In this study, 194 soybean accessions with 36,981 SNPs were calculated using the 3VmrMLM model. As a result, 94 quantitative trait nucleotides (QTNs) and 19 QEIs were detected using single-environment (QTN) and multi-environment (QEI) methods. Three significant QEIs, namely rs4633292, rs39216169, and rs14264702, overlapped with a significant single-environment QTN. CONCLUSIONS For QTNs and QEIs, further haplotype analysis of candidate genes revealed that the Glyma.03G040400 and Glyma.17G236700 genes were beneficial haplotypes that may be associated with unsaturated FAs. This result provides ideas for the identification of soybean lipid-related genes and provides insights for breeding high oil soybean varieties in the future.
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Affiliation(s)
- Xunchao Zhao
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (Key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, 150030, China
| | - Yuhang Zhan
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (Key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, 150030, China
| | - Kaiming Li
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (Key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, 150030, China
| | - Yan Zhang
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (Key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, 150030, China
| | - Changjun Zhou
- Daqing Branch, Heilongjiang Academy of Agricultural Science, Daqing, China
| | - Ming Yuan
- Qiqihar Branch, Heilongjiang Academy of Agricultural Science, Qiqihar, China
| | - Miao Liu
- Crop Tillage and Cultivation Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Yongguang Li
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (Key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, 150030, China
| | - Peng Zuo
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (Key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, 150030, China.
| | - Yingpeng Han
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (Key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, 150030, China.
| | - Xue Zhao
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (Key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, 150030, China.
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13
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Dijoux J, Rio S, Hervouet C, Garsmeur O, Barau L, Dumont T, Rott P, D'Hont A, Hoarau JY. Unveiling the predominance of Saccharum spontaneum alleles for resistance to orange rust in sugarcane using genome-wide association. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:81. [PMID: 38478168 DOI: 10.1007/s00122-024-04583-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 02/14/2024] [Indexed: 04/16/2024]
Abstract
KEY MESSAGE Six QTLs of resistance to sugarcane orange rust were identified in modern interspecific hybrids by GWAS. For five of them, the resistance alleles originated from S. spontaneum. Altogether, they efficiently predict disease resistance. Sugarcane orange rust (SOR) is a threatening emerging disease in many sugarcane industries worldwide. Improving the genetic resistance of commercial cultivars remains the most promising solution to control this disease. In this study, an association panel of 568 modern interspecific sugarcane hybrids (Saccharum officinarum x S. spontaneum) from Réunion's breeding program was evaluated for its resistance to SOR under natural conditions of infection. Two genome-wide association studies (GWAS) were conducted between disease reactions and 183,842 single nucleotide polymorphism (SNP) markers obtained by targeted genotyping-by-sequencing. Five resistance quantitative trait loci (QTLs), named Oru1, Oru2, Oru3, Oru4 and Oru5, were identified using a single-locus GWAS (SL-GWAS). These five QTLs all originated from the species S. spontaneum. A multi-locus GWAS (ML-GWAS) uncovered an additional but less significant resistance QTL named Oru6, which originated from S. officinarum. All six QTLs had a moderate to major phenotypic effect on disease resistance. Prediction accuracy estimated with linear regression models based on each of the five QTLs identified by SL-GWAS was between 0.16-0.41. Altogether, these five QTLs provided a relatively high prediction accuracy of 0.60. In comparison, accuracies obtained with six genome-wide prediction models (i.e., GBLUP, Bayes-A, Bayes-B, Bayes-C, Bayesian Lasso and RKHS) reached only 0.65. The good prediction accuracy of disease resistance provided by the QTLs and the predominant S. spontaneum origin of their resistance alleles pave the way for effective marker-assisted breeding strategies.
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Affiliation(s)
- Jordan Dijoux
- eRcane, 29 rue d'Emmerez de Charmoy, 97490, Sainte-Clotilde, La Réunion, France
- CIRAD, UMR PHIM, F-34398, Montpellier, France
- PHIM, Univ Montpellier, CIRAD, INRAE, Institut Agro, IRD, Montpellier, France
- CIRAD, UMR AGAP Institut, F-34398, Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France
| | - Simon Rio
- CIRAD, UMR AGAP Institut, F-34398, Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France
| | - Catherine Hervouet
- CIRAD, UMR AGAP Institut, F-34398, Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France
| | - Olivier Garsmeur
- CIRAD, UMR AGAP Institut, F-34398, Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France
| | - Laurent Barau
- eRcane, 29 rue d'Emmerez de Charmoy, 97490, Sainte-Clotilde, La Réunion, France
| | - Thomas Dumont
- eRcane, 29 rue d'Emmerez de Charmoy, 97490, Sainte-Clotilde, La Réunion, France
| | - Philippe Rott
- CIRAD, UMR PHIM, F-34398, Montpellier, France
- PHIM, Univ Montpellier, CIRAD, INRAE, Institut Agro, IRD, Montpellier, France
| | - Angélique D'Hont
- CIRAD, UMR AGAP Institut, F-34398, Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France
| | - Jean-Yves Hoarau
- eRcane, 29 rue d'Emmerez de Charmoy, 97490, Sainte-Clotilde, La Réunion, France.
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France.
- CIRAD, UMR AGAP Institut, F-97494, Sainte-Clotilde, La Réunion, France.
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14
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Koo HJ, Pan W. Are trait-associated genes clustered together in a gene network? Genet Epidemiol 2024. [PMID: 38472164 DOI: 10.1002/gepi.22557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 01/25/2024] [Accepted: 02/23/2024] [Indexed: 03/14/2024]
Abstract
Genome-wide association studies (GWAS) have provided an abundance of information about the genetic variants and their loci that are associated to complex traits and diseases. However, due to linkage disequilibrium (LD) and noncoding regions of loci, it remains a challenge to pinpoint the causal genes. Gene network-based approaches, paired with network diffusion methods, have been proposed to prioritize causal genes and to boost statistical power in GWAS based on the assumption that trait-associated genes are clustered in a gene network. Due to the difficulty in mapping trait-associated variants to genes in GWAS, this assumption has never been directly or rigorously tested empirically. On the other hand, whole exome sequencing (WES) data focuses on the protein-coding regions, directly identifying trait-associated genes. In this study, we tested the assumption by leveraging the recently available exome-based association statistics from the UK Biobank WES data along with two types of networks. We found that almost all trait-associated genes were significantly more proximal to each other than randomly selected genes within both networks. These results support the assumption that trait-associated genes are clustered in gene networks, which can be further leveraged to boost the power of GWAS such as by introducing less stringent p value thresholds.
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Affiliation(s)
- Hyun Jung Koo
- School of Statistics, University of Minnesota, Minneapolis, Minnesota, USA
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
| | - Wei Pan
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
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15
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Su J, Zeng J, Wang S, Zhang X, Zhao L, Wen S, Zhang F, Jiang J, Chen F. Multi-locus genome-wide association studies reveal the dynamic genetic architecture of flowering time in chrysanthemum. PLANT CELL REPORTS 2024; 43:84. [PMID: 38448703 DOI: 10.1007/s00299-024-03172-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 02/07/2024] [Indexed: 03/08/2024]
Abstract
KEY MESSAGE The dynamic genetic architecture of flowering time in chrysanthemum was elucidated by GWAS. Thirty-six known genes and 14 candidate genes were identified around the stable QTNs and QEIs, among which ERF-1 was highlighted. Flowering time (FT) adaptation is one of the major breeding goals in chrysanthemum, a multipurpose ornamental plant. In order to reveal the dynamic genetic architecture of FT in chrysanthemum, phenotype investigation of ten FT-related traits was conducted on 169 entries in 2 environments. The broad-sense heritability of five non-conditional FT traits, i.e., budding (FBD), visible coloring (VC), early opening (EO), full-bloom (OF) and decay period (DP), ranged from 56.93 to 84.26%, which were higher than that of the five derived conditional FT traits (38.51-75.13%). The phenotypic variation coefficients of OF_EO and DP_OF were relatively large ranging from 30.59 to 36.17%. Based on 375,865 SNPs, the compressed variance component mixed linear model 3VmrMLM was applied for a multi-locus genome-wide association study (GWAS). As a result, 313 quantitative trait nucleotides (QTNs) were identified for the non-conditional FT traits in single-environment analysis, while 119 QTNs and 67 QTN-by-environment interactions (QEIs) were identified in multi-environment analysis. As for the conditional traits, 343 QTNs were detected in single-environment analysis, and 119 QTNs and 83 QEIs were identified in multi- environment analysis. Among the genes around stable QTNs and QEIs, 36 were orthologs of known FT genes in Arabidopsis and other plants; 14 candidates were mined by combining the transcriptomics data and functional annotation, including ERF-1, ACA10, and FOP1. Furthermore, the haplotype analysis of ERF-1 revealed six elite accessions with extreme FBD. Our findings contribute to the understanding of dynamic genetic architecture of FT and provide valuable resources for future chrysanthemum molecular breeding programs.
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Affiliation(s)
- Jiangshuo Su
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Weigang No.1, Nanjing, 210095, Jiangsu Province, China
| | - Junwei Zeng
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Weigang No.1, Nanjing, 210095, Jiangsu Province, China
| | - Siyue Wang
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Weigang No.1, Nanjing, 210095, Jiangsu Province, China
| | - Xuefeng Zhang
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Weigang No.1, Nanjing, 210095, Jiangsu Province, China
| | - Limin Zhao
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Weigang No.1, Nanjing, 210095, Jiangsu Province, China
| | - Shiyun Wen
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Weigang No.1, Nanjing, 210095, Jiangsu Province, China
| | - Fei Zhang
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Weigang No.1, Nanjing, 210095, Jiangsu Province, China
- Zhongshan Biological Breeding Laboratory, No.50 Zhongling Street, Nanjing, 210014, China
| | - Jiafu Jiang
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Weigang No.1, Nanjing, 210095, Jiangsu Province, China
- Zhongshan Biological Breeding Laboratory, No.50 Zhongling Street, Nanjing, 210014, China
| | - Fadi Chen
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Weigang No.1, Nanjing, 210095, Jiangsu Province, China.
- Zhongshan Biological Breeding Laboratory, No.50 Zhongling Street, Nanjing, 210014, China.
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16
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Gnanapragasam N, Prasanth VV, Sundaram KT, Kumar A, Pahi B, Gurjar A, Venkateshwarlu C, Kalia S, Kumar A, Dixit S, Kohli A, Singh UM, Singh VK, Sinha P. Extreme trait GWAS (Et-GWAS): Unraveling rare variants in the 3,000 rice genome. Life Sci Alliance 2024; 7:e202302352. [PMID: 38148113 PMCID: PMC10751245 DOI: 10.26508/lsa.202302352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 12/12/2023] [Accepted: 12/13/2023] [Indexed: 12/28/2023] Open
Abstract
Identifying high-impact, rare genetic variants associated with specific traits is crucial for crop improvement. The 3,010 rice genome (3K RG) dataset offers a valuable resource for discovering genomic regions with potential applications in crop breeding. We used Extreme Trait GWAS (Et-GWAS), employing bulk pooling and allele frequency measurement to efficiently extract rare variants from the 3K RG. This innovative approach facilitates the detection of associations between genetic variants and target traits, concentrating and quantifying rare alleles. In our study, on grain yield under drought stress, Et-GWAS successfully identified five key genes (OsPP2C11, OsK5.2, OsIRO2, OsPEX1, and OsPWA1) known for enhancing yield under drought. In addition, we examined the overlap of our results with previously reported qDTY-QTLs and observed that OsUCH1 and OsUCH2 genes were located within qDTY2.2 We compared Et-GWAS with conventional GWAS, finding it effectively capturing most candidate genes associated with the target trait. Validation with resistant starch showed similar results. To enhance user-friendliness, we developed a GUI for Et-GWAS; https://et-gwas.shinyapps.io/Et-GWAS/.
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Affiliation(s)
| | | | | | - Ajay Kumar
- International Rice Research Institute, South Asia Hub, Patancheru, India
| | - Bandana Pahi
- International Rice Research Institute, South Asia Hub, Patancheru, India
| | - Anoop Gurjar
- International Rice Research Institute, South-Asia Regional Centre, Varanasi, India
| | | | - Sanjay Kalia
- Department of Biotechnology, CGO Complex, New Delhi, India
| | - Arvind Kumar
- International Rice Research Institute, South-Asia Regional Centre, Varanasi, India
| | - Shalabh Dixit
- International Rice Research Institute, Los Banos, Philippines
| | - Ajay Kohli
- International Rice Research Institute, Los Banos, Philippines
| | - Uma Maheshwer Singh
- International Rice Research Institute, South-Asia Regional Centre, Varanasi, India
| | - Vikas Kumar Singh
- International Rice Research Institute, South Asia Hub, Patancheru, India
| | - Pallavi Sinha
- International Rice Research Institute, South Asia Hub, Patancheru, India
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17
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Lu X, Liu P, Tu L, Guo X, Wang A, Zhu Y, Jiang Y, Zhang C, Xu Y, Chen Z, Wu X. Joint-GWAS, Linkage Mapping, and Transcriptome Analysis to Reveal the Genetic Basis of Plant Architecture-Related Traits in Maize. Int J Mol Sci 2024; 25:2694. [PMID: 38473942 DOI: 10.3390/ijms25052694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 02/04/2024] [Accepted: 02/22/2024] [Indexed: 03/14/2024] Open
Abstract
Plant architecture is one of the key factors affecting maize yield formation and can be divided into secondary traits, such as plant height (PH), ear height (EH), and leaf number (LN). It is a viable approach for exploiting genetic resources to improve plant density. In this study, one natural panel of 226 inbred lines and 150 family lines derived from the offspring of T32 crossed with Qi319 were genotyped by using the MaizeSNP50 chip and the genotyping by sequence (GBS) method and phenotyped under three different environments. Based on the results, a genome-wide association study (GWAS) and linkage mapping were analyzed by using the MLM and ICIM models, respectively. The results showed that 120 QTNs (quantitative trait nucleotides) and 32 QTL (quantitative trait loci) related to plant architecture were identified, including four QTL and 40 QTNs of PH, eight QTL and 41 QTNs of EH, and 20 QTL and 39 QTNs of LN. One dominant QTL, qLN7-2, was identified in the Zhangye environment. Six QTNs were commonly identified to be related to PH, EH, and LN in different environments. The candidate gene analysis revealed that Zm00001d021574 was involved in regulating plant architecture traits through the autophagy pathway, and Zm00001d044730 was predicted to interact with the male sterility-related gene ms26. These results provide abundant genetic resources for improving maize plant architecture traits by using approaches to biological breeding.
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Affiliation(s)
- Xuefeng Lu
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
- Ministry of Agriculture and Rural Affairs Key Laboratory of Crop Genetic Resources and Germplasm Innovation in Karst Region, Guiyang 550006, China
| | - Pengfei Liu
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
| | - Liang Tu
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
| | - Xiangyang Guo
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
| | - Angui Wang
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
| | - Yunfang Zhu
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
| | - Yulin Jiang
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
- Ministry of Agriculture and Rural Affairs Key Laboratory of Crop Genetic Resources and Germplasm Innovation in Karst Region, Guiyang 550006, China
| | - Chunlan Zhang
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
| | - Yan Xu
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
| | - Zehui Chen
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
| | - Xun Wu
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
- Ministry of Agriculture and Rural Affairs Key Laboratory of Crop Genetic Resources and Germplasm Innovation in Karst Region, Guiyang 550006, China
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18
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Sachdeva S, Singh R, Maurya A, Singh VK, Singh UM, Kumar A, Singh GP. New insights into QTNs and potential candidate genes governing rice yield via a multi-model genome-wide association study. BMC PLANT BIOLOGY 2024; 24:124. [PMID: 38373874 PMCID: PMC10877931 DOI: 10.1186/s12870-024-04810-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 02/08/2024] [Indexed: 02/21/2024]
Abstract
BACKGROUND Rice (Oryza sativa L.) is one of the globally important staple food crops, and yield-related traits are prerequisites for improved breeding efficiency in rice. Here, we used six different genome-wide association study (GWAS) models for 198 accessions, with 553,229 single nucleotide markers (SNPs) to identify the quantitative trait nucleotides (QTNs) and candidate genes (CGs) governing rice yield. RESULTS Amongst the 73 different QTNs in total, 24 were co-localized with already reported QTLs or loci in previous mapping studies. We obtained fifteen significant QTNs, pathway analysis revealed 10 potential candidates within 100kb of these QTNs that are predicted to govern plant height, days to flowering, and plot yield in rice. Based on their superior allelic information in 20 elite and 6 inferior genotypes, we found a higher percentage of superior alleles in the elite genotypes in comparison to inferior genotypes. Further, we implemented expression analysis and enrichment analysis enabling the identification of 73 candidate genes and 25 homologues of Arabidopsis, 19 of which might regulate rice yield traits. Of these candidate genes, 40 CGs were found to be enriched in 60 GO terms of the studied traits for instance, positive regulator metabolic process (GO:0010929), intracellular part (GO:0031090), and nucleic acid binding (GO:0090079). Haplotype and phenotypic variation analysis confirmed that LOC_OS09G15770, LOC_OS02G36710 and LOC_OS02G17520 are key candidates associated with rice yield. CONCLUSIONS Overall, we foresee that the QTNs, putative candidates elucidated in the study could summarize the polygenic regulatory networks controlling rice yield and be useful for breeding high-yielding varieties.
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Grants
- BT/PR32853/AGIII/103/1159/2019 Department of Biotechnology, Ministry of Science and Technology, India
- BT/PR32853/AGIII/103/1159/2019 Department of Biotechnology, Ministry of Science and Technology, India
- BT/PR32853/AGIII/103/1159/2019 Department of Biotechnology, Ministry of Science and Technology, India
- BT/PR32853/AGIII/103/1159/2019 Department of Biotechnology, Ministry of Science and Technology, India
- BT/PR32853/AGIII/103/1159/2019 Department of Biotechnology, Ministry of Science and Technology, India
- BT/PR32853/AGIII/103/1159/2019 Department of Biotechnology, Ministry of Science and Technology, India
- BT/PR32853/AGIII/103/1159/2019 Department of Biotechnology, Ministry of Science and Technology, India
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Affiliation(s)
- Supriya Sachdeva
- Division of Genomic Resources, ICAR-NBPGR, Pusa, New Delhi, India
| | - Rakesh Singh
- Division of Genomic Resources, ICAR-NBPGR, Pusa, New Delhi, India.
| | - Avantika Maurya
- Division of Genomic Resources, ICAR-NBPGR, Pusa, New Delhi, India
| | - Vikas K Singh
- International Rice Research Institute (IRRI), South Asia Hub, ICRISAT, Hyderabad, India
| | - Uma Maheshwar Singh
- International Rice Research Institute (IRRI), South Asia Regional Centre (ISARC), Varanasi, India
| | - Arvind Kumar
- International Crops Research Institute for the Semi-Arid Tropics, Patancheru, Telangana, India
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Gao J, Li J, Zhang J, Sun Y, Ju X, Li W, Duan H, Xue Z, Sun L, Hussain Sahito J, Fu Z, Zhang X, Tang J. Identification of Novel QTL for Mercury Accumulation in Maize Using an Enlarged SNP Panel. Genes (Basel) 2024; 15:257. [PMID: 38397246 PMCID: PMC10888321 DOI: 10.3390/genes15020257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 02/14/2024] [Accepted: 02/17/2024] [Indexed: 02/25/2024] Open
Abstract
Mercury (Hg) pollution not only poses a threat to the environment but also adversely affects the growth and development of plants, with potential repercussions for animals and humans through bioaccumulation in the food chain. Maize, a crucial source of food, industrial materials, and livestock feed, requires special attention in understanding the genetic factors influencing mercury accumulation. Developing maize varieties with low mercury accumulation is vital for both maize production and human health. In this study, a comprehensive genome-wide association study (GWAS) was conducted using an enlarged SNP panel comprising 1.25 million single nucleotide polymorphisms (SNPs) in 230 maize inbred lines across three environments. The analysis identified 111 significant SNPs within 78 quantitative trait loci (QTL), involving 169 candidate genes under the Q model. Compared to the previous study, the increased marker density and optimized statistical model led to the discovery of 74 additional QTL, demonstrating improved statistical power. Gene ontology (GO) enrichment analysis revealed that most genes participate in arsenate reduction and stress responses. Notably, GRMZM2G440968, which has been reported in previous studies, is associated with the significant SNP chr6.S_155668107 in axis tissue. It encodes a cysteine proteinase inhibitor, implying its potential role in mitigating mercury toxicity by inhibiting cysteine. Haplotype analyses provided further insights, indicating that lines carrying hap3 exhibited the lowest mercury content compared to other haplotypes. In summary, our study significantly enhances the statistical power of GWAS, identifying additional genes related to mercury accumulation and metabolism. These findings offer valuable insights into unraveling the genetic basis of mercury content in maize and contribute to the development of maize varieties with low mercury accumulation.
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Affiliation(s)
- Jionghao Gao
- Key Laboratory of Wheat and Maize Crops Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China; (J.G.); (J.L.); (J.Z.); (Y.S.); (X.J.); (W.L.); (H.D.); (Z.X.); (L.S.); (J.H.S.); (Z.F.)
| | - Jianxin Li
- Key Laboratory of Wheat and Maize Crops Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China; (J.G.); (J.L.); (J.Z.); (Y.S.); (X.J.); (W.L.); (H.D.); (Z.X.); (L.S.); (J.H.S.); (Z.F.)
| | - Jihong Zhang
- Key Laboratory of Wheat and Maize Crops Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China; (J.G.); (J.L.); (J.Z.); (Y.S.); (X.J.); (W.L.); (H.D.); (Z.X.); (L.S.); (J.H.S.); (Z.F.)
| | - Yan Sun
- Key Laboratory of Wheat and Maize Crops Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China; (J.G.); (J.L.); (J.Z.); (Y.S.); (X.J.); (W.L.); (H.D.); (Z.X.); (L.S.); (J.H.S.); (Z.F.)
| | - Xiaolong Ju
- Key Laboratory of Wheat and Maize Crops Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China; (J.G.); (J.L.); (J.Z.); (Y.S.); (X.J.); (W.L.); (H.D.); (Z.X.); (L.S.); (J.H.S.); (Z.F.)
| | - Wenlong Li
- Key Laboratory of Wheat and Maize Crops Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China; (J.G.); (J.L.); (J.Z.); (Y.S.); (X.J.); (W.L.); (H.D.); (Z.X.); (L.S.); (J.H.S.); (Z.F.)
| | - Haiyang Duan
- Key Laboratory of Wheat and Maize Crops Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China; (J.G.); (J.L.); (J.Z.); (Y.S.); (X.J.); (W.L.); (H.D.); (Z.X.); (L.S.); (J.H.S.); (Z.F.)
| | - Zhengjie Xue
- Key Laboratory of Wheat and Maize Crops Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China; (J.G.); (J.L.); (J.Z.); (Y.S.); (X.J.); (W.L.); (H.D.); (Z.X.); (L.S.); (J.H.S.); (Z.F.)
| | - Li Sun
- Key Laboratory of Wheat and Maize Crops Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China; (J.G.); (J.L.); (J.Z.); (Y.S.); (X.J.); (W.L.); (H.D.); (Z.X.); (L.S.); (J.H.S.); (Z.F.)
| | - Javed Hussain Sahito
- Key Laboratory of Wheat and Maize Crops Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China; (J.G.); (J.L.); (J.Z.); (Y.S.); (X.J.); (W.L.); (H.D.); (Z.X.); (L.S.); (J.H.S.); (Z.F.)
| | - Zhiyuan Fu
- Key Laboratory of Wheat and Maize Crops Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China; (J.G.); (J.L.); (J.Z.); (Y.S.); (X.J.); (W.L.); (H.D.); (Z.X.); (L.S.); (J.H.S.); (Z.F.)
| | - Xuehai Zhang
- Key Laboratory of Wheat and Maize Crops Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China; (J.G.); (J.L.); (J.Z.); (Y.S.); (X.J.); (W.L.); (H.D.); (Z.X.); (L.S.); (J.H.S.); (Z.F.)
| | - Jihua Tang
- Key Laboratory of Wheat and Maize Crops Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China; (J.G.); (J.L.); (J.Z.); (Y.S.); (X.J.); (W.L.); (H.D.); (Z.X.); (L.S.); (J.H.S.); (Z.F.)
- The Shennong Laboratory, Zhengzhou 450002, China
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20
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Fofana B, Soto-Cerda B, Zaidi M, Main D, Fillmore S. Genome-wide genetic architecture for plant maturity and drought tolerance in diploid potatoes. Front Genet 2024; 14:1306519. [PMID: 38357658 PMCID: PMC10864671 DOI: 10.3389/fgene.2023.1306519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 12/18/2023] [Indexed: 02/16/2024] Open
Abstract
Cultivated potato (Solanum tuberosum) is known to be highly susceptible to drought. With climate change and its frequent episodes of drought, potato growers will face increased challenges to achieving their yield goals. Currently, a high proportion of untapped potato germplasm remains within the diploid potato relatives, and the genetic architecture of the drought tolerance and maturity traits of diploid potatoes is still unknown. As such, a panel of 384 ethyl methanesulfonate-mutagenized diploid potato clones were evaluated for drought tolerance and plant maturity under field conditions. Genome-wide association studies (GWAS) were conducted to dissect the genetic architecture of the traits. The results obtained from the genetic structure analysis of the panel showed five main groups and seven subgroups. Using the Genome Association and Prediction Integrated Tool-mixed linear model GWAS statistical model, 34 and 17 significant quantitative trait nucleotides (QTNs) were found associated with maturity and drought traits, respectively. Chromosome 5 carried most of the QTNs, some of which were also detected by using the restricted two-stage multi-locus multi-allele-GWAS haploblock-based model, and two QTNs were found to be pleiotropic for both maturity and drought traits. Using the non-parametric U-test, one and three QTNs, with 5.13%-7.4% phenotypic variations explained, showed favorable allelic effects that increase the maturity and drought trait values. The quantitaive trait loci (QTLs)/QTNs associated with maturity and drought trait were found co-located in narrow (0.5-1 kb) genomic regions with 56 candidate genes playing roles in plant development and senescence and in abiotic stress responses. A total of 127 potato clones were found to be late maturing and tolerant to drought, while nine were early to moderate-late maturing and tolerant to drought. Taken together, the data show that the studied germplasm panel and the identified candidate genes are prime genetic resources for breeders and biologists in conventional breeding and targeted gene editing as climate adaptation tools.
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Affiliation(s)
- Bourlaye Fofana
- Charlottetown Research and Development Centre, Agriculture and Agri-Food Canada, Charlottetown, PE, Canada
| | - Braulio Soto-Cerda
- Departamento de Ciencias Agropecuarias y Acuícolas, Universidad Católica de Temuco, Temuco, Chile
- Núcleo de Investigación en Producción Alimentaria, Facultad de Recursos Naturales, Universidad Católica de Temuco, Temuco, Chile
| | - Moshin Zaidi
- Charlottetown Research and Development Centre, Agriculture and Agri-Food Canada, Charlottetown, PE, Canada
| | - David Main
- Charlottetown Research and Development Centre, Agriculture and Agri-Food Canada, Charlottetown, PE, Canada
| | - Sherry Fillmore
- Kentville Research and Development Centre, Agriculture and Agri-Food Canada, Kentville, NS, Canada
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21
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Alsamman AM, H. Mousa K, Istanbuli T, Abd El-Maksoud MM, Tawkaz S, Hamwieh A. Unveiling the genetic basis of Fusarium wilt resistance in chickpea using GWAS analysis and characterization of candidate genes. Front Genet 2024; 14:1292009. [PMID: 38327700 PMCID: PMC10849131 DOI: 10.3389/fgene.2023.1292009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Accepted: 12/26/2023] [Indexed: 02/09/2024] Open
Abstract
Introduction: Chickpea is a legume crop that thrives in regions with semi-arid or temperate climates. Its seeds are an excellent source of proteins, carbohydrates, and minerals, especially high-quality proteins. Chickpea cultivation faces several challenges including Fusarium wilt (FW), a major fungal disease that significantly reduces productivity. Methods: In this study, a Genome-wide Association Analysis (GWAS) was conducted to identify multiple genomic loci associated with FW resistance in chickpea. We conducted a comprehensive evaluation of 180 chickpea genotypes for FW resistance across three distinct locations (Ethiopia, Tunisia, and Lebanon) during the 2-year span from 2015 to 2016. Disease infection measurements were recorded, and the wilt incidence of each genotype was calculated. We employed a set of 11,979 single nucleotide polymorphisms (SNPs) markers distributed across the entire chickpea genome for SNP genotyping. Population structure analysis was conducted to determine the genetic structure of the genotypes. Results and Discussion: The population structure unveiled that the analyzed chickpea germplasm could be categorized into four sub-populations. Notably, these sub-populations displayed diverse geographic origins. The GWAS identified 11 SNPs associated with FW resistance, dispersed across the genome. Certain SNPs were consistent across trials, while others were specific to particular environments. Chromosome CA2 harbored five SNP markers, CA5 featured two, and CA4, CA6, CA7, and CA8 each had one representative marker. Four SNPs demonstrated an association with FW resistance, consistently observed across a minimum of three distinct environments. These SNPs included SNP5826041, SNP5825086, SNP11063413, SNP5825195, which located in CaFeSOD, CaS13like, CaNTAQ1, and CaAARS genes, respectively. Further investigations were conducted to gain insights into the functions of these genes and their role in FW resistance. This progress holds promise for reducing the negative impact of the disease on chickpea production.
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Affiliation(s)
- Alsamman M. Alsamman
- International Center for Agricultural Research in the Dry Areas (ICARDA), Giza, Egypt
- Agricultural Research Center (ARC), Agricultural Genetic Engineering Research Institute (AGERI), Giza, Egypt
| | - Khaled H. Mousa
- International Center for Agricultural Research in the Dry Areas (ICARDA), Giza, Egypt
| | - Tawffiq Istanbuli
- International Center for Agricultural Research in the Dry Areas (ICARDA), Terbol, Lebanon
| | | | - Sawsan Tawkaz
- International Center for Agricultural Research in the Dry Areas (ICARDA), Giza, Egypt
| | - Aladdin Hamwieh
- International Center for Agricultural Research in the Dry Areas (ICARDA), Giza, Egypt
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22
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Sachdeva S, Singh R, Maurya A, Singh VK, Singh UM, Kumar A, Singh GP. Multi-model genome-wide association studies for appearance quality in rice. FRONTIERS IN PLANT SCIENCE 2024; 14:1304388. [PMID: 38273959 PMCID: PMC10808671 DOI: 10.3389/fpls.2023.1304388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 12/22/2023] [Indexed: 01/27/2024]
Abstract
Improving the quality of the appearance of rice is critical to meet market acceptance. Mining putative quality-related genes has been geared towards the development of effective breeding approaches for rice. In the present study, two SL-GWAS (CMLM and MLM) and three ML-GWAS (FASTmrEMMA, mrMLM, and FASTmrMLM) genome-wide association studies were conducted in a subset of 3K-RGP consisting of 198 rice accessions with 553,831 SNP markers. A total of 594 SNP markers were identified using the mixed linear model method for grain quality traits. Additionally, 70 quantitative trait nucleotides (QTNs) detected by the ML-GWAS models were strongly associated with grain aroma (AR), head rice recovery (HRR, %), and percentage of grains with chalkiness (PGC, %). Finally, 39 QTNs were identified using single- and multi-locus GWAS methods. Among the 39 reliable QTNs, 20 novel QTNs were identified for the above-mentioned three quality-related traits. Based on annotation and previous studies, four functional candidate genes (LOC_Os01g66110, LOC_Os01g66140, LOC_Os07g44910, and LOC_Os02g14120) were found to influence AR, HRR (%), and PGC (%), which could be utilized in rice breeding to improve grain quality traits.
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Affiliation(s)
- Supriya Sachdeva
- Division of Genomic Resources, ICAR-National Bureau of Plant Genetic Resources (NBPGR), New Delhi, India
| | - Rakesh Singh
- Division of Genomic Resources, ICAR-National Bureau of Plant Genetic Resources (NBPGR), New Delhi, India
| | - Avantika Maurya
- Division of Genomic Resources, ICAR-National Bureau of Plant Genetic Resources (NBPGR), New Delhi, India
| | - Vikas Kumar Singh
- International Rice Research Institute, South Asia Hub, International Crop Reseach Institute for Semi Arid Tropics (ICRISAT), Hyderabad, India
| | - Uma Maheshwar Singh
- International Rice Research Institute, South Asia Regional Centre (ISARC), Varanasi, India
| | - Arvind Kumar
- International Crops Research Institute for the Semi-Arid Tropics, Patancheru, Telangana, India
| | - Gyanendra Pratap Singh
- Indian Council of Agricultural Research (ICAR)-National Bureau of Plant Genetic Resources, New Delhi, India
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23
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Liu Z, Li H, Wang X, Zhang Y, Gou Z, Zhao X, Ren H, Wen Z, Li Y, Yu L, Gao H, Wang D, Qi X, Qiu L. QTL for yield per plant under water deficit and well-watered conditions and drought susceptibility index in soybean ( Glycine max (L.) Merr.). BIOTECHNOL BIOTEC EQ 2023. [DOI: 10.1080/13102818.2022.2155569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Affiliation(s)
- Zhangxiong Liu
- National Key Facility for Gene Resources and Genetic Improvement/Key Laboratory of Crop Germplasm Utilization, Ministry of Agriculture/Center of Crop Germplasm Resource, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, PR China
| | - Huihui Li
- National Key Facility for Gene Resources and Genetic Improvement/Key Laboratory of Crop Germplasm Utilization, Ministry of Agriculture/Center of Crop Germplasm Resource, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, PR China
| | - Xingrong Wang
- Laboratory of Crop Germplasm Resource, Institute of Crop Sciences, Gansu Academy of Agricultural Sciences, Lanzhou, Gansu, PR China
| | - Yanjun Zhang
- Laboratory of Crop Germplasm Resource, Institute of Crop Sciences, Gansu Academy of Agricultural Sciences, Lanzhou, Gansu, PR China
| | - Zuowang Gou
- Laboratory of Crop Germplasm Resource, Institute of Crop Sciences, Gansu Academy of Agricultural Sciences, Lanzhou, Gansu, PR China
| | - Xingzhen Zhao
- National Key Facility for Gene Resources and Genetic Improvement/Key Laboratory of Crop Germplasm Utilization, Ministry of Agriculture/Center of Crop Germplasm Resource, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, PR China
| | - Honglei Ren
- Laboratory of Disease Resistance Breeding, Maize Research Institute, Heilongjiang Academy of Agricultural Sciences, Haerbin, Heilongjiang, PR China
| | - Zixiang Wen
- Department of Plant, Soil and Microbial Sciences, College of Agriculture & Natural Resources, Michigan State University, East Lansing, MI, USA
| | - Yinghui Li
- National Key Facility for Gene Resources and Genetic Improvement/Key Laboratory of Crop Germplasm Utilization, Ministry of Agriculture/Center of Crop Germplasm Resource, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, PR China
| | - Lili Yu
- National Key Facility for Gene Resources and Genetic Improvement/Key Laboratory of Crop Germplasm Utilization, Ministry of Agriculture/Center of Crop Germplasm Resource, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, PR China
| | - Huawei Gao
- National Key Facility for Gene Resources and Genetic Improvement/Key Laboratory of Crop Germplasm Utilization, Ministry of Agriculture/Center of Crop Germplasm Resource, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, PR China
| | - Dechun Wang
- Department of Plant, Soil and Microbial Sciences, College of Agriculture & Natural Resources, Michigan State University, East Lansing, MI, USA
| | - Xusheng Qi
- Laboratory of Crop Germplasm Resource, Institute of Crop Sciences, Gansu Academy of Agricultural Sciences, Lanzhou, Gansu, PR China
| | - Lijuan Qiu
- National Key Facility for Gene Resources and Genetic Improvement/Key Laboratory of Crop Germplasm Utilization, Ministry of Agriculture/Center of Crop Germplasm Resource, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, PR China
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24
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Soto-Cerda BJ, Larama G, Cloutier S, Fofana B, Inostroza-Blancheteau C, Aravena G. The Genetic Dissection of Nitrogen Use-Related Traits in Flax ( Linum usitatissimum L.) at the Seedling Stage through the Integration of Multi-Locus GWAS, RNA-seq and Genomic Selection. Int J Mol Sci 2023; 24:17624. [PMID: 38139451 PMCID: PMC10743809 DOI: 10.3390/ijms242417624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 12/10/2023] [Accepted: 12/12/2023] [Indexed: 12/24/2023] Open
Abstract
Nitrogen (N), the most important macro-nutrient for plant growth and development, is a key factor that determines crop yield. Yet its excessive applications pollute the environment and are expensive. Hence, studying nitrogen use efficiency (NUE) in crops is fundamental for sustainable agriculture. Here, an association panel consisting of 123 flax accessions was evaluated for 21 NUE-related traits at the seedling stage under optimum N (N+) and N deficiency (N-) treatments to dissect the genetic architecture of NUE-related traits using a multi-omics approach integrating genome-wide association studies (GWAS), transcriptome analysis and genomic selection (GS). Root traits exhibited significant and positive correlations with NUE under N- conditions (r = 0.33 to 0.43, p < 0.05). A total of 359 QTLs were identified, accounting for 0.11% to 23.1% of the phenotypic variation in NUE-related traits. Transcriptomic analysis identified 1034 differentially expressed genes (DEGs) under contrasting N conditions. DEGs involved in N metabolism, root development, amino acid transport and catabolism and others, were found near the QTLs. GS models to predict NUE stress tolerance index (NUE_STI) trait were tested using a random genome-wide SNP dataset and a GWAS-derived QTLs dataset. The latter produced superior prediction accuracy (r = 0.62 to 0.79) compared to the genome-wide SNP marker dataset (r = 0.11) for NUE_STI. Our results provide insights into the QTL architecture of NUE-related traits, identify candidate genes for further studies, and propose genomic breeding tools to achieve superior NUE in flax under low N input.
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Affiliation(s)
- Braulio J. Soto-Cerda
- Departamento de Ciencias Agropecuarias y Acuícolas, Universidad Católica de Temuco, Rudecindo Ortega 02950, Temuco 4781312, Chile; (C.I.-B.); (G.A.)
- Núcleo de Investigación en Producción Alimentaria, Facultad de Recursos Naturales, Universidad Católica de Temuco, Rudecindo Ortega 02950, Temuco 4781312, Chile
| | - Giovanni Larama
- Center of Plant, Soil Interaction and Natural Resources Biotechnology, Scientific and Technological Bioresource Nucleus, Universidad de La Frontera, Temuco 4811230, Chile;
- Biocontrol Research Laboratory, Universidad de La Frontera, Temuco 4811230, Chile
| | - Sylvie Cloutier
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, 960 Carling Avenue, Ottawa, ON K1A 0C6, Canada;
| | - Bourlaye Fofana
- Charlottetown Research and Development Centre, Agriculture and Agri-Food Canada, 440 University Avenue, Charlottetown, PE C1A 4N6, Canada
| | - Claudio Inostroza-Blancheteau
- Departamento de Ciencias Agropecuarias y Acuícolas, Universidad Católica de Temuco, Rudecindo Ortega 02950, Temuco 4781312, Chile; (C.I.-B.); (G.A.)
- Núcleo de Investigación en Producción Alimentaria, Facultad de Recursos Naturales, Universidad Católica de Temuco, Rudecindo Ortega 02950, Temuco 4781312, Chile
| | - Gabriela Aravena
- Departamento de Ciencias Agropecuarias y Acuícolas, Universidad Católica de Temuco, Rudecindo Ortega 02950, Temuco 4781312, Chile; (C.I.-B.); (G.A.)
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25
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Su J, Lu Z, Zeng J, Zhang X, Yang X, Wang S, Zhang F, Jiang J, Chen F. Multi-locus genome-wide association study and genomic prediction for flowering time in chrysanthemum. PLANTA 2023; 259:13. [PMID: 38063918 DOI: 10.1007/s00425-023-04297-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 11/15/2023] [Indexed: 12/18/2023]
Abstract
MAIN CONCLUSION Multi-locus GWAS detected several known and candidate genes responsible for flowering time in chrysanthemum. The associations could greatly increase the predictive ability of genome selection that accelerates the possible application of GS in chrysanthemum breeding. Timely flowering is critical for successful reproduction and determines the economic value for ornamental plants. To investigate the genetic architecture of flowering time in chrysanthemum, a multi-locus genome-wide association study (GWAS) was performed using a collection of 200 accessions and 330,710 single-nucleotide polymorphisms (SNPs) via 3VmrMLM method. Five flowering time traits including budding (FBD), visible colouring (VC), early opening (EO), full-bloom (OF) and senescing (SF) stages, plus five derived conditional traits were recorded in two environments. Extensive phenotypic variations were observed for these flowering time traits with coefficients of variation ranging from 6.42 to 38.27%, and their broad-sense heritability ranged from 71.47 to 96.78%. GWAS revealed 88 stable quantitative trait nucleotides (QTNs) and 93 QTN-by-environment interactions (QEIs) associated with flowering time traits, accounting for 0.50-8.01% and 0.30-10.42% of the phenotypic variation, respectively. Amongst the genes around these stable QTNs and QEIs, 21 and 10 were homologous to known flowering genes in Arabidopsis; 20 and 11 candidate genes were mined by combining the functional annotation and transcriptomics data, respectively, such as MYB55, FRIGIDA-like, WRKY75 and ANT. Furthermore, genomic selection (GS) was assessed using three models and seven unique marker datasets. We found the prediction accuracy (PA) using significant SNPs identified by GWAS under SVM model exhibited the best performance with PA ranging from 0.90 to 0.95. Our findings provide new insights into the dynamic genetic architecture of flowering time and the identified significant SNPs and candidate genes will accelerate the future molecular improvement of chrysanthemum.
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Affiliation(s)
- Jiangshuo Su
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Weigang No. 1, Nanjing, 210095, Jiangsu, People's Republic of China
| | - Zhaowen Lu
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Weigang No. 1, Nanjing, 210095, Jiangsu, People's Republic of China
| | - Junwei Zeng
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Weigang No. 1, Nanjing, 210095, Jiangsu, People's Republic of China
| | - Xuefeng Zhang
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Weigang No. 1, Nanjing, 210095, Jiangsu, People's Republic of China
| | - Xiuwei Yang
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Weigang No. 1, Nanjing, 210095, Jiangsu, People's Republic of China
| | - Siyue Wang
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Weigang No. 1, Nanjing, 210095, Jiangsu, People's Republic of China
| | - Fei Zhang
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Weigang No. 1, Nanjing, 210095, Jiangsu, People's Republic of China
- Zhongshan Biological Breeding Laboratory, No. 50 Zhongling Street, Nanjing, 210014, China
| | - Jiafu Jiang
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Weigang No. 1, Nanjing, 210095, Jiangsu, People's Republic of China
- Zhongshan Biological Breeding Laboratory, No. 50 Zhongling Street, Nanjing, 210014, China
| | - Fadi Chen
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Weigang No. 1, Nanjing, 210095, Jiangsu, People's Republic of China.
- Zhongshan Biological Breeding Laboratory, No. 50 Zhongling Street, Nanjing, 210014, China.
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Zhang YM, Jia Z, Dunwell JM. Editorial: The applications of new multi-locus GWAS methodologies in the genetic dissection of complex traits, volume II. FRONTIERS IN PLANT SCIENCE 2023; 14:1340767. [PMID: 38146269 PMCID: PMC10749431 DOI: 10.3389/fpls.2023.1340767] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Accepted: 11/27/2023] [Indexed: 12/27/2023]
Affiliation(s)
- Yuan-Ming Zhang
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Zhenyu Jia
- Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA, United States
| | - Jim M. Dunwell
- School of Agriculture, Policy and Development, University of Reading, Reading, United Kingdom
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Esders SL, Hülskötter K, Schreiner T, Wohlsein P, Schmitz J, Bräsen JH, Distl O. Single Nucleotide Polymorphisms Associated with AA-Amyloidosis in Siamese and Oriental Shorthair Cats. Genes (Basel) 2023; 14:2126. [PMID: 38136948 PMCID: PMC10742459 DOI: 10.3390/genes14122126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 11/21/2023] [Accepted: 11/23/2023] [Indexed: 12/24/2023] Open
Abstract
AA-amyloidosis in Siamese and Oriental shorthair cats is a lethal condition in which amyloid deposits accumulate systemically, especially in the liver and the thyroid gland. The age at death of affected cats varies between one and seven years. A previous study indicated a complex mode of inheritance involving a major locus. In the present study, we performed a multi-locus genome-wide association study (GWAS) using five methods (mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB and ISIS EM-BLASSO) to identify variants associated with AA-amyloidosis in Siamese/Oriental cats. We genotyped 20 affected mixed Siamese/Oriental cats from a cattery and 48 healthy controls from the same breeds using the Illumina Infinium Feline 63 K iSelect DNA array. The multi-locus GWAS revealed eight significantly associated single nucleotide polymorphisms (SNPs) on FCA A1, D1, D2 and D3. The genomic regions harboring these SNPs contain 55 genes, of which 3 are associated with amyloidosis in humans or mice. One of these genes is SAA1, which encodes for a member of the Serum Amyloid A family, the precursor protein of Amyloid A, and a mutation in the promotor of this gene causes hereditary AA-amyloidosis in humans. These results provide novel knowledge regarding the complex genetic background of hereditary AA-amyloidosis in Siamese/Oriental cats and, therefore, contribute to future genomic studies of this disease in cats.
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Affiliation(s)
- Stella L. Esders
- Institute for Animal Breeding and Genetics, University of Veterinary Medicine Hannover (Foundation), 30559 Hannover, Germany;
| | - Kirsten Hülskötter
- Department of Pathology, University of Veterinary Medicine Hannover (Foundation), 30559 Hannover, Germany; (K.H.); (T.S.); (P.W.)
| | - Tom Schreiner
- Department of Pathology, University of Veterinary Medicine Hannover (Foundation), 30559 Hannover, Germany; (K.H.); (T.S.); (P.W.)
| | - Peter Wohlsein
- Department of Pathology, University of Veterinary Medicine Hannover (Foundation), 30559 Hannover, Germany; (K.H.); (T.S.); (P.W.)
| | - Jessica Schmitz
- Nephropathology Unit, Institute of Pathology, Hannover Medical School, 30625 Hannover, Germany; (J.S.); (J.H.B.)
| | - Jan H. Bräsen
- Nephropathology Unit, Institute of Pathology, Hannover Medical School, 30625 Hannover, Germany; (J.S.); (J.H.B.)
| | - Ottmar Distl
- Institute for Animal Breeding and Genetics, University of Veterinary Medicine Hannover (Foundation), 30559 Hannover, Germany;
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Yang M, Wen Y, Zheng J, Zhang J, Zhao T, Feng J. Improving power of genome-wide association studies via transforming ordinal phenotypes into continuous phenotypes. FRONTIERS IN PLANT SCIENCE 2023; 14:1247181. [PMID: 38023883 PMCID: PMC10652869 DOI: 10.3389/fpls.2023.1247181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Accepted: 10/18/2023] [Indexed: 12/01/2023]
Abstract
Introduction Ordinal traits are important complex traits in crops, while genome-wide association study (GWAS) is a widely-used method in their gene mining. Presently, GWAS of continuous quantitative traits (C-GWAS) and single-locus association analysis method of ordinal traits are the main methods used for ordinal traits. However, the detection power of these two methods is low. Methods To address this issue, we proposed a new method, named MTOTC, in which hierarchical data of ordinal traits are transformed into continuous phenotypic data (CPData). Results Then, FASTmrMLM, one C-GWAS method, was used to conduct GWAS for CPData. The results from the simulation studies showed that, MTOTC+FASTmrMLM for ordinal traits was better than the classical methods when there were four and fewer hierarchical levels. In addition, when MTOTC was combined with FASTmrEMMA, mrMLM, ISIS EM-BLASSO, pLARmEB, and pKWmEB, relatively high power and low false positive rate in QTN detection were observed as well. Subsequently, MTOTC was applied to analyze the hierarchical data of soybean salt-alkali tolerance. It was revealed that more significant QTNs were detected when MTOTC was combined with any of the above six C-GWAs. Discussion Accordingly, the new method increases the choices of the GWAS methods for ordinal traits and helps to mine the genes for ordinal traits in resource populations.
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Affiliation(s)
- Ming Yang
- Key Laboratory of Biology and Genetics Improvement of Soybean, Ministry of Agriculture/Zhongshan Biological Breeding Laboratory (ZSBBL)/National Innovation Platform for Soybean Breeding and Industry-Education Integration/State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization/College of Agriculture, Nanjing Agricultural University, Nanjing, China
| | - Yangjun Wen
- College of Science, Nanjing Agricultural University, Nanjing, China
| | - Jinchang Zheng
- Key Laboratory of Biology and Genetics Improvement of Soybean, Ministry of Agriculture/Zhongshan Biological Breeding Laboratory (ZSBBL)/National Innovation Platform for Soybean Breeding and Industry-Education Integration/State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization/College of Agriculture, Nanjing Agricultural University, Nanjing, China
| | - Jin Zhang
- College of Science, Nanjing Agricultural University, Nanjing, China
| | - Tuanjie Zhao
- Key Laboratory of Biology and Genetics Improvement of Soybean, Ministry of Agriculture/Zhongshan Biological Breeding Laboratory (ZSBBL)/National Innovation Platform for Soybean Breeding and Industry-Education Integration/State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization/College of Agriculture, Nanjing Agricultural University, Nanjing, China
| | - Jianying Feng
- Key Laboratory of Biology and Genetics Improvement of Soybean, Ministry of Agriculture/Zhongshan Biological Breeding Laboratory (ZSBBL)/National Innovation Platform for Soybean Breeding and Industry-Education Integration/State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization/College of Agriculture, Nanjing Agricultural University, Nanjing, China
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Xiao L, Fang Y, Zhang H, Quan M, Zhou J, Li P, Wang D, Ji L, Ingvarsson PK, Wu HX, El-Kassaby YA, Du Q, Zhang D. Natural variation in the prolyl 4-hydroxylase gene PtoP4H9 contributes to perennial stem growth in Populus. THE PLANT CELL 2023; 35:4046-4065. [PMID: 37522322 PMCID: PMC10615208 DOI: 10.1093/plcell/koad212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 07/07/2023] [Indexed: 08/01/2023]
Abstract
Perennial trees must maintain stem growth throughout their entire lifespan to progressively increase in size as they age. The overarching question of the molecular mechanisms that govern stem perennial growth in trees remains largely unanswered. Here we deciphered the genetic architecture that underlies perennial growth trajectories using genome-wide association studies (GWAS) for measures of growth traits across years in a natural population of Populus tomentosa. By analyzing the stem growth trajectory, we identified PtoP4H9, encoding prolyl 4-hydroxylase 9, which is responsible for the natural variation in the growth rate of diameter at breast height (DBH) across years. Quantifying the dynamic genetic contribution of PtoP4H9 loci to stem growth showed that PtoP4H9 played a pivotal role in stem growth regulation. Spatiotemporal expression analysis showed that PtoP4H9 was highly expressed in cambium tissues of poplars of various ages. Overexpression and knockdown of PtoP4H9 revealed that it altered cell expansion to regulate cell wall modification and mechanical characteristics, thereby promoting stem growth in Populus. We showed that natural variation in PtoP4H9 occurred in a BASIC PENTACYSTEINE transcription factor PtoBPC1-binding promoter element controlling PtoP4H9 expression. The geographic distribution of PtoP4H9 allelic variation was consistent with the modes of selection among populations. Altogether, our study provides important genetic insights into dynamic stem growth in Populus, and we confirmed PtoP4H9 as a potential useful marker for breeding or genetic engineering of poplars.
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Affiliation(s)
- Liang Xiao
- School of Landscape Architecture, Beijing University of Agriculture, Beijing 102206,China
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083,China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083,China
| | - Yuanyuan Fang
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083,China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083,China
| | - He Zhang
- State Key Laboratory of Protein and Plant Gene Research, School of Advanced Agricultural Sciences, Peking University, Beijing 100871,China
| | - Mingyang Quan
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083,China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083,China
| | - Jiaxuan Zhou
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083,China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083,China
| | - Peng Li
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083,China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083,China
| | - Dan Wang
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083,China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083,China
| | - Li Ji
- MOE Engineering Research Center of Forestry Biomass Materials and Bioenergy, Beijing Forestry University, Beijing 100083,China
| | - Pär K Ingvarsson
- Linnean Center for Plant Biology, Department of Plant Biology, Swedish University of Agricultural Sciences, Box 7080, SE-750 07 Uppsala,Sweden
| | - Harry X Wu
- Umeå Plant Science Centre, Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Science, 90183 Umeå,Sweden
| | - Yousry A El-Kassaby
- Department of Forest and Conservation Sciences, Faculty of Forestry, The University of British Columbia, Vancouver, British Columbia V6T 1Z4,Canada
| | - Qingzhang Du
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083,China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083,China
- State Key Laboratory of Tree Genetics and Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, 100083,China
| | - Deqiang Zhang
- School of Landscape Architecture, Beijing University of Agriculture, Beijing 102206,China
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083,China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083,China
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He L, Sui Y, Che Y, Wang H, Rashid KY, Cloutier S, You FM. Genome-wide association studies using multi-models and multi-SNP datasets provide new insights into pasmo resistance in flax. FRONTIERS IN PLANT SCIENCE 2023; 14:1229457. [PMID: 37954993 PMCID: PMC10634603 DOI: 10.3389/fpls.2023.1229457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 07/24/2023] [Indexed: 11/14/2023]
Abstract
Introduction Flax (Linum usitatissimum L.) is an economically important crop due to its oil and fiber. However, it is prone to various diseases, including pasmo caused by the fungus Septoria linicola. Methods In this study, we conducted field evaluations of 445 flax accessions over a five-year period (2012-2016) to assess their resistance to pasmo A total of 246,035 single nucleotide polymorphisms (SNPs) were used for genetic analysis. Four statistical models, including the single-locus model GEMMA and the multi-locus models FarmCPU, mrMLM, and 3VmrMLM, were assessed to identify quantitative trait nucleotides (QTNs) associated with pasmo resistance. Results We identified 372 significant QTNs or 132 tag QTNs associated with pasmo resistance from five pasmo resistance datasets (PAS2012-PAS2016 and the 5-year average, namely PASmean) and three genotypic datasets (the all SNPs/ALL, the gene-based SNPs/GB and the RGA-based SNPs/RGAB). The tag QTNs had R2 values of 0.66-16.98% from the ALL SNP dataset, 0.68-20.54%from the GB SNP dataset, and 0.52-22.42% from the RGAB SNP dataset. Of these tag QTNs, 93 were novel. Additionally, 37 resistance gene analogs (RGAs)co-localizing with 39 tag QTNs were considered as potential candidates for controlling pasmo resistance in flax and 50 QTN-by-environment interactions(QEIs) were identified to account for genes by environmental interactions. Nine RGAs were predicted as candidate genes for ten QEIs. Discussion Our results suggest that pasmo resistance in flax is polygenic and potentially influenced by environmental factors. The identified QTNs provide potential targets for improving pasmo resistance in flax breeding programs. This study sheds light on the genetic basis of pasmo resistance and highlights the importance of considering both genetic and environmental factors in breeding programs for flax.
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Affiliation(s)
- Liqiang He
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON, Canada
- School of Tropical Agriculture and Forestry, School of Tropical Crops, Hainan University, Haikou, China
| | - Yao Sui
- School of Tropical Agriculture and Forestry, School of Tropical Crops, Hainan University, Haikou, China
| | - Yanru Che
- School of Tropical Agriculture and Forestry, School of Tropical Crops, Hainan University, Haikou, China
| | - Huixian Wang
- School of Tropical Agriculture and Forestry, School of Tropical Crops, Hainan University, Haikou, China
| | - Khalid Y. Rashid
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON, Canada
| | - Sylvie Cloutier
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON, Canada
| | - Frank M. You
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON, Canada
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Martínez-García PJ, Mas-Gómez J, Prudencio ÁS, Barriuso JJ, Cantín CM. Genome-wide association analysis of Monilinia fructicola lesion in a collection of Spanish peach landraces. FRONTIERS IN PLANT SCIENCE 2023; 14:1165847. [PMID: 37936940 PMCID: PMC10626550 DOI: 10.3389/fpls.2023.1165847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 09/25/2023] [Indexed: 11/09/2023]
Abstract
Brown rot, caused by the Monilinia spp., is the disease that causes the greatest losses in stone fruit worldwide. Currently, M. fructicola has become the dominant species in the main peach production area in Spain. The fruit cuticle is the first barrier of protection against external aggressions and may have a key role in the susceptibility to brown rot. However, information on the role of skin fruit on the resistance to brown rot in peach is scarce. Previous genetic analyses in peach have demonstrated that brown rot resistance is a complex and quantitative trait in which different fruit parts and resistance mechanisms are involved. To search for genomic areas involved in the control of the cultivar susceptibility to brown rot and to elucidate the role of fruit skin against this infection, we have studied, for two consecutive seasons (2019 and 2020), the fruit susceptibility to M. fructicola, together with fruit cuticle thickness (CT) and density (CD), in a collection of 80 Spanish and 5 foreign peach cultivars from the National Peach Collection at CITA (Zaragoza, Spain). Brown rot incidence, lesion diameter, and severity index were calculated after 5 days of inoculation on non-wounded fruit. The peach collection has also been genotyped using the new peach SNP chip (9 + 9K). Genotypic and phenotypic data have been used to perform a genome-wide association analysis (GWAS). Phenotyping has shown a wide variability on the brown rot susceptibility within the Spanish germplasm as well as on CD and CT. The GWAS results have identified several significant SNPs associated with disease severity index (DSI), CD, and CT, five of which were considered as reliable SNP-trait associations. A wide protein network analysis, using 127 genes within the regions of the reliable SNPs and previously identified candidate genes (169) associated with Monilinia spp. resistance, highlighted several genes involved in classical hypersensitive response (HR), genes related to wax layers as ceramidases and lignin precursors catalyzers, and a possible role of autophagy during brown rot infection. This work adds relevant information on the complexity resistance mechanisms to brown rot infection in peach fruits and the genetics behind them.
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Affiliation(s)
- Pedro J. Martínez-García
- Department of Plant Breeding, Centre of Edaphology and Applied Biology of Segura, Spanish National Research Council (CEBAS-CSIC), Murcia, Spain
| | - Jorge Mas-Gómez
- Department of Plant Breeding, Centre of Edaphology and Applied Biology of Segura, Spanish National Research Council (CEBAS-CSIC), Murcia, Spain
| | - Ángela S. Prudencio
- Department of Plant Breeding, Centre of Edaphology and Applied Biology of Segura, Spanish National Research Council (CEBAS-CSIC), Murcia, Spain
| | - Juan José Barriuso
- AgriFood Institute of Aragon (IA2), CITA-Universidad de Zaragoza, Zaragoza, Spain
| | - Celia M. Cantín
- Department of Pomology, Experimental Station of Aula Dei-CSIC, Spanish National Research Council, Zaragoza, Spain
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Haile JK, Sertse D, N’Diaye A, Klymiuk V, Wiebe K, Ruan Y, Chawla HS, Henriquez MA, Wang L, Kutcher HR, Steiner B, Buerstmayr H, Pozniak CJ. Multi-locus genome-wide association studies reveal the genetic architecture of Fusarium head blight resistance in durum wheat. FRONTIERS IN PLANT SCIENCE 2023; 14:1182548. [PMID: 37900749 PMCID: PMC10601657 DOI: 10.3389/fpls.2023.1182548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 09/18/2023] [Indexed: 10/31/2023]
Abstract
Durum wheat is more susceptible to Fusarium head blight (FHB) than other types or classes of wheat. The disease is one of the most devastating in wheat; it reduces yield and end-use quality and contaminates the grain with fungal mycotoxins such as deoxynivalenol (DON). A panel of 265 Canadian and European durum wheat cultivars, as well as breeding and experimental lines, were tested in artificially inoculated field environments (2019-2022, inclusive) and two greenhouse trials (2019 and 2020). The trials were assessed for FHB severity and incidence, visual rating index, Fusarium-damaged kernels, DON accumulation, anthesis or heading date, maturity date, and plant height. In addition, yellow pigment and protein content were analyzed for the 2020 field season. To capture loci underlying FHB resistance and related traits, GWAS was performed using single-locus and several multi-locus models, employing 13,504 SNPs. Thirty-one QTL significantly associated with one or more FHB-related traits were identified, of which nine were consistent across environments and associated with multiple FHB-related traits. Although many of the QTL were identified in regions previously reported to affect FHB, the QTL QFhb-3B.2, associated with FHB severity, incidence, and DON accumulation, appears to be novel. We developed KASP markers for six FHB-associated QTL that were consistently detected across multiple environments and validated them on the Global Durum Panel (GDP). Analysis of allelic diversity and the frequencies of these revealed that the lines in the GDP harbor between zero and six resistance alleles. This study provides a comprehensive assessment of the genetic basis of FHB resistance and DON accumulation in durum wheat. Accessions with multiple favorable alleles were identified and will be useful genetic resources to improve FHB resistance in durum breeding programs through marker-assisted recurrent selection and gene stacking.
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Affiliation(s)
- Jemanesh K. Haile
- Department of Plant Sciences, Crop Development Centre, University of Saskatchewan, Saskatoon, SK, Canada
| | - Demissew Sertse
- Aquatic and Crop Resource Development, National Research Council Canada, Saskatoon, SK, Canada
| | - Amidou N’Diaye
- Department of Plant Sciences, Crop Development Centre, University of Saskatchewan, Saskatoon, SK, Canada
| | - Valentyna Klymiuk
- Department of Plant Sciences, Crop Development Centre, University of Saskatchewan, Saskatoon, SK, Canada
| | - Krystalee Wiebe
- Department of Plant Sciences, Crop Development Centre, University of Saskatchewan, Saskatoon, SK, Canada
| | - Yuefeng Ruan
- Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada
| | - Harmeet S. Chawla
- Department of Plant Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Maria-Antonia Henriquez
- Morden Research and Development Centre, Agriculture and Agri-Food Canada, Morden, MB, Canada
| | - Lipu Wang
- Department of Plant Sciences, Crop Development Centre, University of Saskatchewan, Saskatoon, SK, Canada
| | - Hadley R. Kutcher
- Department of Plant Sciences, Crop Development Centre, University of Saskatchewan, Saskatoon, SK, Canada
| | - Barbara Steiner
- Department of Agrobiotechnology, Institute of Biotechnology in Plant Production, University of Natural Resources and Life Sciences Vienna, Tulln, Austria
| | - Hermann Buerstmayr
- Department of Agrobiotechnology, Institute of Biotechnology in Plant Production, University of Natural Resources and Life Sciences Vienna, Tulln, Austria
| | - Curtis J. Pozniak
- Department of Plant Sciences, Crop Development Centre, University of Saskatchewan, Saskatoon, SK, Canada
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Shu G, Wang A, Wang X, Ding J, Chen R, Gao F, Wang A, Li T, Wang Y. Identification of southern corn rust resistance QTNs in Chinese summer maize germplasm via multi-locus GWAS and post-GWAS analysis. FRONTIERS IN PLANT SCIENCE 2023; 14:1221395. [PMID: 37810381 PMCID: PMC10552154 DOI: 10.3389/fpls.2023.1221395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 08/15/2023] [Indexed: 10/10/2023]
Abstract
Southern corn rust (SCR) caused by Puccinia polysora Underw is a major disease leading to severe yield losses in China Summer Corn Belt. Using six multi-locus GWAS methods, we identified a set of SCR resistance QTNs from a diversity panel of 140 inbred lines collected from China Summer Corn Belt. Thirteen QTNs on chromosomes 1, 2, 4, 5, 6, and 8 were grouped into three types of allele effects and their associations with SCR phenotypes were verified by post-GWAS case-control sampling, allele/haplotype effect analysis. Relative resistance (RRR) and relative susceptibility (RRs) catering to its inbred carrier were estimated from single QTN and QTN-QTN combos and epistatitic effects were estimated for QTN-QTN combos. By transcriptomic annotation, a set of candidate genes were predicted to be involved in transcriptional regulation (S5_145, Zm00001d01613, transcription factor GTE4), phosphorylation (S8_123, Zm00001d010672, Pgk2- phosphoglycerate kinase 2), and temperature stress response (S6_164a/S6_164b, Zm00001d038806, hsp101, and S5_211, Zm00001d017978, cellulase25). The breeding implications of the above findings were discussed.
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Affiliation(s)
- Guoping Shu
- Center of Biotechnology, Beijing Lantron Seed, LongPing High-tech Corp., Zhengzhou, Henan, China
| | - Aifang Wang
- Center of Biotechnology, Beijing Lantron Seed, LongPing High-tech Corp., Zhengzhou, Henan, China
| | - Xingchuan Wang
- Henan LongPing-Lantron AgriScience & Technology Co., LTD, Zhengzhou, LongPing High-tech Corp., Zhengzhou, Henan, China
| | - Junqiang Ding
- College of Agronomy, Henan Agricultural University, Zhengzhou, Henan, China
| | - Ruijie Chen
- Henan LongPing-Lantron AgriScience & Technology Co., LTD, Zhengzhou, LongPing High-tech Corp., Zhengzhou, Henan, China
| | - Fei Gao
- Henan LongPing-Lantron AgriScience & Technology Co., LTD, Zhengzhou, LongPing High-tech Corp., Zhengzhou, Henan, China
| | - Aifen Wang
- Henan LongPing-Lantron AgriScience & Technology Co., LTD, Zhengzhou, LongPing High-tech Corp., Zhengzhou, Henan, China
| | - Ting Li
- Center of Biotechnology, Beijing Lantron Seed, LongPing High-tech Corp., Zhengzhou, Henan, China
| | - Yibo Wang
- Henan LongPing-Lantron AgriScience & Technology Co., LTD, Zhengzhou, LongPing High-tech Corp., Zhengzhou, Henan, China
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Zakieh M, Alemu A, Henriksson T, Pareek N, Singh PK, Chawade A. Exploring GWAS and genomic prediction to improve Septoria tritici blotch resistance in wheat. Sci Rep 2023; 13:15651. [PMID: 37730954 PMCID: PMC10511425 DOI: 10.1038/s41598-023-42856-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 09/15/2023] [Indexed: 09/22/2023] Open
Abstract
Septoria tritici blotch (STB) is a destructive foliar diseases threatening wheat grain yield. Wheat breeding for STB disease resistance has been identified as the most sustainable and environment-friendly approach. In this work, a panel of 316 winter wheat breeding lines from a commercial breeding program were evaluated for STB resistance at the seedling stage under controlled conditions followed by genome-wide association study (GWAS) and genomic prediction (GP). The study revealed a significant genotypic variation for STB seedling resistance, while disease severity scores exhibited a normal frequency distribution. Moreover, we calculated a broad-sense heritability of 0.62 for the trait. Nine single- and multi-locus GWAS models identified 24 marker-trait associations grouped into 20 quantitative trait loci (QTLs) for STB seedling-stage resistance. The seven QTLs located on chromosomes 1B, 2A, 2B, 5B (two), 7A, and 7D are reported for the first time and could potentially be novel. The GP cross-validation analysis in the RR-BLUP model estimated the genomic-estimated breeding values (GEBVs) of STB resistance with a prediction accuracy of 0.49. Meanwhile, the GWAS assisted wRR-BLUP model improved the accuracy to 0.58. The identified QTLs can be used for marker-assisted backcrossing against STB in winter wheat. Moreover, the higher prediction accuracy recorded from the GWAS-assisted GP analysis implies its power to successfully select superior candidate lines based on their GEBVs for STB resistance.
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Affiliation(s)
- Mustafa Zakieh
- Department of Plant Breeding, Swedish University of Agricultural Sciences, 23422, Lomma, Sweden
| | - Admas Alemu
- Department of Plant Breeding, Swedish University of Agricultural Sciences, 23422, Lomma, Sweden
| | | | - Nidhi Pareek
- Department of Microbiology, School of Life Sciences, Central University of Rajasthan, Bandarsindri, Kishangarh, Ajmer, Rajasthan, 305801, India
| | - Pawan K Singh
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Aakash Chawade
- Department of Plant Breeding, Swedish University of Agricultural Sciences, 23422, Lomma, Sweden.
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Sadeqi MB, Ballvora A, Léon J. Local and Bayesian Survival FDR Estimations to Identify Reliable Associations in Whole Genome of Bread Wheat. Int J Mol Sci 2023; 24:14011. [PMID: 37762314 PMCID: PMC10531084 DOI: 10.3390/ijms241814011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 09/02/2023] [Accepted: 09/07/2023] [Indexed: 09/29/2023] Open
Abstract
Estimating the FDR significance threshold in genome-wide association studies remains a major challenge in distinguishing true positive hypotheses from false positive and negative errors. Several comparative methods for multiple testing comparison have been developed to determine the significance threshold; however, these methods may be overly conservative and lead to an increase in false negative results. The local FDR approach is suitable for testing many associations simultaneously based on the empirical Bayes perspective. In the local FDR, the maximum likelihood estimator is sensitive to bias when the GWAS model contains two or more explanatory variables as genetic parameters simultaneously. The main criticism of local FDR is that it focuses only locally on the effects of single nucleotide polymorphism (SNP) in tails of distribution, whereas the signal associations are distributed across the whole genome. The advantage of the Bayesian perspective is that knowledge of prior distribution comes from other genetic parameters included in the GWAS model, such as linkage disequilibrium (LD) analysis, minor allele frequency (MAF) and call rate of significant associations. We also proposed Bayesian survival FDR to solve the multi-collinearity and large-scale problems, respectively, in grain yield (GY) vector in bread wheat with large-scale SNP information. The objective of this study was to obtain a short list of SNPs that are reliably associated with GY under low and high levels of nitrogen (N) in the population. The five top significant SNPs were compared with different Bayesian models. Based on the time to events in the Bayesian survival analysis, the differentiation between minor and major alleles within the association panel can be identified.
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Affiliation(s)
| | - Agim Ballvora
- INRES-Plant Breeding, Rheinische Friedrich-Wilhelms-Universität Bonn, 53113 Bonn, Germany; (M.B.S.); (J.L.)
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Sun F, Yang Y, Wang P, Ma J, Du X. Quantitative trait loci and candidate genes for yield-related traits of upland cotton revealed by genome-wide association analysis under drought conditions. BMC Genomics 2023; 24:531. [PMID: 37679709 PMCID: PMC10485960 DOI: 10.1186/s12864-023-09640-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 08/30/2023] [Indexed: 09/09/2023] Open
Abstract
BACKGROUND Due to the influence of extreme weather, the environment in China's main cotton-producing areas is prone to drought stress conditions, which affect the growth and development of cotton and lead to a decrease in cotton yield. RESULTS In this study, 188 upland cotton germplasm resources were phenotyped for data of 8 traits (including 3 major yield traits) under drought conditions in three environments for two consecutive years. Correlation analysis revealed significant positive correlations between the three yield traits. Genetic analysis showed that the estimated heritability of the seed cotton index (SC) under drought conditions was the highest (80.81%), followed by that of boll weight (BW) (80.64%) and the lint cotton index (LC) (70.49%) With genome-wide association study (GWAS) analysis, a total of 75 quantitative trait loci (QTLs) were identified, including two highly credible new QTL hotspots. Three candidate genes (Gh_D09G064400, Gh_D10G261000 and Gh_D10G254000) located in the two new QTL hotspots, QTL51 and QTL55, were highly expressed in the early stage of fiber development and showed significant correlations with SC, LC and BW. The expression of three candidate genes in two extreme materials after drought stress was analyzed by qRT-PCR, and the expression of these two materials in fibers at 15, 20 and 25 DPA. The expression of these three candidate genes was significantly upregulated after drought stress and was significantly higher in drought-tolerant materials than in drought-sensitive materials. In addition, the expression levels of the three candidate genes were higher in the early stage of fiber development (15 DPA), and the expression levels in drought-tolerant germplasm were higher than those in drought-sensitive germplasm. These three candidate genes may play an important role in determining cotton yield under drought conditions. CONCLUSIONS This study is helpful for understanding the regulatory genes affecting cotton yield under drought conditions and provides germplasm and candidate gene resources for breeding high-yield cotton varieties under these conditions.
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Affiliation(s)
- Fenglei Sun
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, 455000, China
- Hainan Yazhou Bay Seed Laboratory, Sanya, Hainan, 572000, China
| | - Yanlong Yang
- Research Institute of Economic Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China.
| | - Penglong Wang
- Research Institute of Economic Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China
| | - Jun Ma
- Research Institute of Economic Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China
| | - Xiongming Du
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
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Zheng Y, Thi KM, Lin L, Xie X, Khine EE, Nyein EE, Lin MHW, New WW, Aye SS, Wu W. Genome-wide association study of cooking-caused grain expansion in rice ( Oryza sativa L.). FRONTIERS IN PLANT SCIENCE 2023; 14:1250854. [PMID: 37711286 PMCID: PMC10498926 DOI: 10.3389/fpls.2023.1250854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 08/14/2023] [Indexed: 09/16/2023]
Abstract
Cooking-caused rice grain expansion (CCRGE) is a critical trait for evaluating the cooking quality of rice. Previous quantitative trait locus (QTL) mapping studies on CCRGE have been limited to bi-parental populations, which restrict the exploration of natural variation and mapping resolution. To comprehensively and precisely dissect the genetic basis of CCRGE, we performed a genome-wide association study (GWAS) on three related indices: grain breadth expansion index (GBEI), grain length expansion index (GLEI), and grain length-breadth ratio expansion index (GREI), using 345 rice accessions grown in two years (environments) and 193,582 SNP markers. By analyzing each environment separately using seven different methods (3VmrMLM, mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, pKWmEB, ISIS EM-BLASSO), we identified a total of 32, 19 and 27 reliable quantitative trait nucleotides (QTNs) associated with GBEI, GLEI and GREI, respectively. Furthermore, by jointly analyzing the two environments using 3VmrMLM, we discovered 19, 22 and 25 QTNs, as well as 9, 5 and 7 QTN-by-environment interaction (QEIs) associated with GBEI, GLEI and GREI, respectively. Notably, 12, 9 and 15 QTNs for GBEI, GLEI and GREI were found within the intervals of previously reported QTLs. In the vicinity of these QTNs or QEIs, based on analyses of mutation type, gene ontology classification, haplotype, and expression pattern, we identified five candidate genes that are related to starch synthesis and endosperm development. The five candidate genes, namely, LOC_Os04g53310 (OsSSIIIb, near QTN qGREI-4.5s), LOC_Os05g02070 (OsMT2b, near QTN qGLEI-5.1s), LOC_Os06g04200 (wx, near QEI qGBEI-6.1i and QTNs qGREI-6.1s and qGLEI-6.1t), LOC_Os06g12450 (OsSSIIa, near QTN qGLEI-6.2t), and LOC_Os08g09230 (OsSSIIIa, near QTN qGBEI-8.1t), are predicted to be involved in the process of rice grain starch synthesis and to influence grain expansion after cooking. Our findings provide valuable insights and will facilitate genetic research and improvement of CCRGE.
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Affiliation(s)
- Yan Zheng
- College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
- Fujian Provincial Key Laboratory of Crop Breeding by Design, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
- Key Laboratory of Genetics, Breeding and Multiple Utilization of Crops, Ministry of Education, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
| | - Khin Mar Thi
- Fujian Provincial Key Laboratory of Crop Breeding by Design, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
- Key Laboratory of Genetics, Breeding and Multiple Utilization of Crops, Ministry of Education, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
| | - Lihui Lin
- Fujian Provincial Key Laboratory of Crop Breeding by Design, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
- Key Laboratory of Genetics, Breeding and Multiple Utilization of Crops, Ministry of Education, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
| | - Xiaofang Xie
- College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
- Fujian Provincial Key Laboratory of Crop Breeding by Design, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
- Key Laboratory of Genetics, Breeding and Multiple Utilization of Crops, Ministry of Education, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
| | - Ei Ei Khine
- Fujian Provincial Key Laboratory of Crop Breeding by Design, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
- Key Laboratory of Genetics, Breeding and Multiple Utilization of Crops, Ministry of Education, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
| | - Ei Ei Nyein
- Fujian Provincial Key Laboratory of Crop Breeding by Design, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
- Key Laboratory of Genetics, Breeding and Multiple Utilization of Crops, Ministry of Education, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
| | - Min Htay Wai Lin
- Department of Botany, Mawlamyine University, Mawlamyine, Myanmar
| | - Win Win New
- Department of Botany, Mawlamyine University, Mawlamyine, Myanmar
| | - San San Aye
- Department of Botany, Mawlamyine University, Mawlamyine, Myanmar
| | - Weiren Wu
- Fujian Provincial Key Laboratory of Crop Breeding by Design, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
- Key Laboratory of Genetics, Breeding and Multiple Utilization of Crops, Ministry of Education, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
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Zhang D, Gao B, Feng Q, Manichaikul A, Peloso GM, Tracy RP, Durda P, Taylor KD, Liu Y, Johnson WC, Gabriel S, Gupta N, Smith JD, Aguet F, Ardlie KG, Blackwell TW, Gerszten RE, Rich SS, Rotter JI, Scott LJ, Zhou X, Lee S. Proteome-Wide Association Studies for Blood Lipids and Comparison with Transcriptome-Wide Association Studies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.17.553749. [PMID: 37662416 PMCID: PMC10473643 DOI: 10.1101/2023.08.17.553749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Blood lipid traits are treatable and heritable risk factors for heart disease, a leading cause of mortality worldwide. Although genome-wide association studies (GWAS) have discovered hundreds of variants associated with lipids in humans, most of the causal mechanisms of lipids remain unknown. To better understand the biological processes underlying lipid metabolism, we investigated the associations of plasma protein levels with total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL), and low-density lipoprotein cholesterol (LDL) in blood. We trained protein prediction models based on samples in the Multi-Ethnic Study of Atherosclerosis (MESA) and applied them to conduct proteome-wide association studies (PWAS) for lipids using the Global Lipids Genetics Consortium (GLGC) data. Of the 749 proteins tested, 42 were significantly associated with at least one lipid trait. Furthermore, we performed transcriptome-wide association studies (TWAS) for lipids using 9,714 gene expression prediction models trained on samples from peripheral blood mononuclear cells (PBMCs) in MESA and 49 tissues in the Genotype-Tissue Expression (GTEx) project. We found that although PWAS and TWAS can show different directions of associations in an individual gene, 40 out of 49 tissues showed a positive correlation between PWAS and TWAS signed p-values across all the genes, which suggests a high-level consistency between proteome-lipid associations and transcriptome-lipid associations.
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Affiliation(s)
- Daiwei Zhang
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI USA
| | - Boran Gao
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI USA
| | - Qidi Feng
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA USA
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI USA
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA USA
| | - Gina M Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA USA
| | - Russell P Tracy
- Departments of Pathology & Laboratory Medicine, and Biochemistry, Larner College of Medicine, University of Vermont, Burlington, VT USA
| | - Peter Durda
- Departments of Pathology & Laboratory Medicine, Larner College of Medicine, The University of Vermont, Burlington, VT USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA USA
| | - Yongmei Liu
- Department of Medicine, Divisions of Cardiology and Neurology, Duke University Medical Center, Durham, NC USA
| | - W Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, WA USA
| | - Stacey Gabriel
- Genomics Platform, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA USA
| | - Namrata Gupta
- Genomics Platform, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA USA
| | - Joshua D Smith
- Department of Genome Sciences, Human Genetics and Translational Genomics, The University of Washington, Seattle, WA, USA
| | - Francois Aguet
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA USA
| | - Kristin G Ardlie
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA USA
| | - Thomas W Blackwell
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO USA
| | - Robert E Gerszten
- Genomics Platform, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA USA
| | - Laura J Scott
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI USA
| | - Xiang Zhou
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI USA
| | - Seunggeun Lee
- Graduate School of Data Science, Seoul National University, Seoul, Republic of Korea
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI USA
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39
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Sui Y, Che Y, Zhong Y, He L. Genome-Wide Association Studies Using 3VmrMLM Model Provide New Insights into Branched-Chain Amino Acid Contents in Rice Grains. PLANTS (BASEL, SWITZERLAND) 2023; 12:2970. [PMID: 37631180 PMCID: PMC10459631 DOI: 10.3390/plants12162970] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 08/07/2023] [Accepted: 08/09/2023] [Indexed: 08/27/2023]
Abstract
Rice (Oryza sativa L.) is a globally important food source providing carbohydrates, amino acids, and dietary fiber for humans and livestock. The branched-chain amino acid (BCAA) level is a complex trait related to the nutrient quality of rice. However, the genetic mechanism underlying the BCAA (valine, leucine, and isoleucine) accumulation in rice grains remains largely unclear. In this study, the grain BCAA contents and 239,055 SNPs of a diverse panel containing 422 rice accessions were adopted to perform a genome-wide association study (GWAS) using a recently proposed 3VmrMLM model. A total of 357 BCAA-content-associated main-effect quantitative trait nucleotides (QTNs) were identified from 15 datasets (12 BCAA content datasets and 3 BLUP datasets of BCAA). Furthermore, the allelic variation of two novel candidate genes, LOC_Os01g52530 and LOC_Os06g15420, responsible for the isoleucine (Ile) content alteration were identified. To reveal the genetic basis of the potential interactions between the gene and environmental factor, 53 QTN-by-environment interactions (QEIs) were detected using the 3VmrMLM model. The LOC_Os03g24460, LOC_Os01g55590, and LOC_Os12g31820 were considered as the candidate genes potentially contributing to the valine (Val), leucine (Leu), and isoleucine (Ile) accumulations, respectively. Additionally, 10 QTN-by-QTN interactions (QQIs) were detected using the 3VmrMLM model, which were putative gene-by-gene interactions related to the Leu and Ile contents. Taken together, these findings suggest that the implementation of the 3VmrMLM model in a GWAS may provide new insights into the deeper understanding of BCAA accumulation in rice grains. The identified QTNs/QEIs/QQIs serve as potential targets for the genetic improvement of rice with high BCAA levels.
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Affiliation(s)
| | | | | | - Liqiang He
- School of Tropical Agriculture and Forestry, School of Tropical Crops, Hainan University, Haikou 570228, China
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40
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Adejumobi II, Agre PA, Adewumi AS, Shonde TE, Cipriano IM, Komoy JL, Adheka JG, Onautshu DO. Association mapping in multiple yam species (Dioscorea spp.) of quantitative trait loci for yield-related traits. BMC PLANT BIOLOGY 2023; 23:357. [PMID: 37434107 DOI: 10.1186/s12870-023-04350-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 06/16/2023] [Indexed: 07/13/2023]
Abstract
BACKGROUND Yam (Dioscorea spp.) is multiple species with various ploidy level and considered as cash crop in many producing areas. Selection based phenotyping for yield and its related traits such as mosaic virus and anthracnose diseases resistance and plant vigor in multiple species of yam is lengthy however, marker information has proven to enhance selection efficiency. METHODOLOGY In this study, a panel of 182 yam accessions distributed across six yam species were assessed for diversity and marker-traits association study using SNP markers generated from Diversity Array Technology platform. For the traits association analysis, the relation matrix alongside the population structure were used as co-factor to avoid false discovery using Multiple random Mixed Linear Model (MrMLM) followed by gene annotation. RESULTS Accessions performance were significantly different (p < 0.001) across all the traits with high broad-sense heritability (H2). Phenotypic and genotypic correlations showed positive relationships between yield and vigor but negative for yield and yam mosaic disease severity. Population structure revealed k = 6 as optimal clusters-based species. A total of 22 SNP markers were identified to be associated with yield, vigor, mosaic and anthracnose diseases resistance. Gene annotation for the significant SNP loci identified some putative genes associated with primary metabolism, pest and resistance to anthracnose disease, maintenance of NADPH in biosynthetic reaction especially those involving nitro-oxidative stress for resistance to mosaic virus, and seed development, photosynthesis, nutrition use efficiency, stress tolerance, vegetative and reproductive development for tuber yield. CONCLUSION This study provides valuable insights into the genetic control of plant vigor, anthracnose, mosaic virus resistance, and tuber yield in yam and thus, opens an avenue for developing additional genomic resources for markers-assisted selection focusing on multiple yam species.
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Affiliation(s)
- I I Adejumobi
- Department of Biotechnology, Faculty of Science, University of Kisangani, Kisangani, DR, Congo
- International Institute of Tropical Agriculture, Lagos, Nigeria
| | - Paterne A Agre
- International Institute of Tropical Agriculture, Lagos, Nigeria.
| | - A S Adewumi
- International Institute of Tropical Agriculture, Lagos, Nigeria
| | - T E Shonde
- International Institute of Tropical Agriculture, Lagos, Nigeria
| | - I M Cipriano
- Department of Biotechnology, Faculty of Science, University of Kisangani, Kisangani, DR, Congo
| | - J L Komoy
- Department of Biotechnology, Faculty of Science, University of Kisangani, Kisangani, DR, Congo
| | - J G Adheka
- Department of Biotechnology, Faculty of Science, University of Kisangani, Kisangani, DR, Congo
| | - D O Onautshu
- Department of Biotechnology, Faculty of Science, University of Kisangani, Kisangani, DR, Congo
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Zhou GL, Xu FJ, Qiao JK, Che ZX, Xiang T, Liu XL, Li XY, Zhao SH, Zhu MJ. E-GWAS: an ensemble-like GWAS strategy that provides effective control over false positive rates without decreasing true positives. Genet Sel Evol 2023; 55:46. [PMID: 37407918 DOI: 10.1186/s12711-023-00820-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 06/23/2023] [Indexed: 07/07/2023] Open
Abstract
BACKGROUND Genome-wide association studies (GWAS) are an effective way to explore genotype-phenotype associations in humans, animals, and plants. Various GWAS methods have been developed based on different genetic or statistical assumptions. However, no single method is optimal for all traits and, for many traits, the putative single nucleotide polymorphisms (SNPs) that are detected by the different methods do not entirely overlap due to the diversity of the genetic architecture of complex traits. Therefore, multi-tool-based GWAS strategies that combine different methods have been increasingly employed. To take this one step further, we propose an ensemble-like GWAS strategy (E-GWAS) that statistically integrates GWAS results from different single GWAS methods. RESULTS E-GWAS was compared with various single GWAS methods using simulated phenotype traits with different genetic architectures. E-GWAS performed stably across traits with different genetic architectures and effectively controlled the number of false positive genetic variants detected without decreasing the number of true positive variants. In addition, its performance could be further improved by using a bin-merged strategy and the addition of more distinct single GWAS methods. Our results show that the numbers of true and false positive SNPs detected by the E-GWAS strategy slightly increased and decreased, respectively, with increasing bin size and when the number and the diversity of individual GWAS methods that were integrated in E-GWAS increased, the latter being more effective than the bin-merged strategy. The E-GWAS strategy was also applied to a real dataset to study backfat thickness in a pig population, and 10 candidate genes related to this trait and expressed in adipose-associated tissues were identified. CONCLUSIONS Using both simulated and real datasets, we show that E-GWAS is a reliable and robust strategy that effectively integrates the GWAS results of different methods and reduces the number of false positive SNPs without decreasing that of true positive SNPs.
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Affiliation(s)
- Guang-Liang Zhou
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China
| | - Fang-Jun Xu
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China
| | - Jia-Kun Qiao
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China
| | - Zhao-Xuan Che
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China
| | - Tao Xiang
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China
- The Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan, 430070, China
| | - Xiao-Lei Liu
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China
- The Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan, 430070, China
| | - Xin-Yun Li
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China
- The Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan, 430070, China
| | - Shu-Hong Zhao
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China
- The Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan, 430070, China
| | - Meng-Jin Zhu
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China.
- The Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan, 430070, China.
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Cabral AL, Ruan Y, Cuthbert RD, Li L, Zhang W, Boyle K, Berraies S, Henriquez MA, Burt A, Kumar S, Fobert P, Piche I, Bokore FE, Meyer B, Sangha J, Knox RE. Multi-locus genome-wide association study of fusarium head blight in relation to days to anthesis and plant height in a spring wheat association panel. FRONTIERS IN PLANT SCIENCE 2023; 14:1166282. [PMID: 37457352 PMCID: PMC10346453 DOI: 10.3389/fpls.2023.1166282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 05/03/2023] [Indexed: 07/18/2023]
Abstract
Fusarium head blight (FHB) is a highly destructive fungal disease of wheat to which host resistance is quantitatively inherited and largely influenced by the environment. Resistance to FHB has been associated with taller height and later maturity; however, a further understanding of these relationships is needed. An association mapping panel (AMP) of 192 predominantly Canadian spring wheat was genotyped with the wheat 90K single-nucleotide polymorphism (SNP) array. The AMP was assessed for FHB incidence (INC), severity (SEV) and index (IND), days to anthesis (DTA), and plant height (PLHT) between 2015 and 2017 at three Canadian FHB-inoculated nurseries. Seven multi-environment trial (MET) datasets were deployed in a genome-wide association study (GWAS) using a single-locus mixed linear model (MLM) and a multi-locus random SNP-effect mixed linear model (mrMLM). MLM detected four quantitative trait nucleotides (QTNs) for INC on chromosomes 2D and 3D and for SEV and IND on chromosome 3B. Further, mrMLM identified 291 QTNs: 50 (INC), 72 (SEV), 90 (IND), 41 (DTA), and 38 (PLHT). At two or more environments, 17 QTNs for FHB, DTA, and PLHT were detected. Of these 17, 12 QTNs were pleiotropic for FHB traits, DTA, and PLHT on chromosomes 1A, 1D, 2D, 3B, 5A, 6B, 7A, and 7B; two QTNs for DTA were detected on chromosomes 1B and 7A; and three PLHT QTNs were located on chromosomes 4B and 6B. The 1B DTA QTN and the three pleiotropic QTNs on chromosomes 1A, 3B, and 6B are potentially identical to corresponding quantitative trait loci (QTLs) in durum wheat. Further, the 3B pleiotropic QTN for FHB INC, SEV, and IND co-locates with TraesCS3B02G024900 within the Fhb1 region on chromosome 3B and is ~3 Mb from a cloned Fhb1 candidate gene TaHRC. While the PLHT QTN on chromosome 6B is putatively novel, the 1B DTA QTN co-locates with a disease resistance protein located ~10 Mb from a Flowering Locus T1-like gene TaFT3-B1, and the 7A DTA QTN is ~5 Mb away from a maturity QTL QMat.dms-7A.3 of another study. GWAS and QTN candidate genes enabled the characterization of FHB resistance in relation to DTA and PLHT. This approach should eventually generate additional and reliable trait-specific markers for breeding selection, in addition to providing useful information for FHB trait discovery.
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Affiliation(s)
- Adrian L. Cabral
- Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada
| | - Yuefeng Ruan
- Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada
| | - Richard D. Cuthbert
- Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada
| | - Lin Li
- Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada
| | - Wentao Zhang
- Aquatic and Crop Resource Development Research Centre, National Research Council of Canada, Saskatoon, SK, Canada
| | - Kerry Boyle
- Aquatic and Crop Resource Development Research Centre, National Research Council of Canada, Saskatoon, SK, Canada
| | - Samia Berraies
- Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada
| | - Maria Antonia Henriquez
- Morden Research and Development Centre, Agriculture and Agri-Food Canada, Morden, MB, Canada
| | - Andrew Burt
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON, Canada
| | - Santosh Kumar
- Brandon Research and Development Centre, Agriculture and Agri-Food Canada, Brandon, MB, Canada
| | - Pierre Fobert
- Aquatic and Crop Resource Development Research Centre, National Research Council of Canada, Ottawa, ON, Canada
| | - Isabelle Piche
- Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada
| | - Firdissa E. Bokore
- Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada
| | - Brad Meyer
- Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada
| | - Jatinder Sangha
- Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada
| | - Ron E. Knox
- Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada
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Kumari J, Lakhwani D, Jakhar P, Sharma S, Tiwari S, Mittal S, Avashthi H, Shekhawat N, Singh K, Mishra KK, Singh R, Yadav MC, Singh GP, Singh AK. Association mapping reveals novel genes and genomic regions controlling grain size architecture in mini core accessions of Indian National Genebank wheat germplasm collection. FRONTIERS IN PLANT SCIENCE 2023; 14:1148658. [PMID: 37457353 PMCID: PMC10345843 DOI: 10.3389/fpls.2023.1148658] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 04/11/2023] [Indexed: 07/18/2023]
Abstract
Wheat (Triticum aestivum L.) is a staple food crop for the global human population, and thus wheat breeders are consistently working to enhance its yield worldwide. In this study, we utilized a sub-set of Indian wheat mini core germplasm to underpin the genetic architecture for seed shape-associated traits. The wheat mini core subset (125 accessions) was genotyped using 35K SNP array and evaluated for grain shape traits such as grain length (GL), grain width (GW), grain length, width ratio (GLWR), and thousand grain weight (TGW) across the seven different environments (E1, E2, E3, E4, E5, E5, E6, and E7). Marker-trait associations were determined using a multi-locus random-SNP-effect Mixed Linear Model (mrMLM) program. A total of 160 non-redundant quantitative trait nucleotides (QTNs) were identified for four grain shape traits using two or more GWAS models. Among these 160 QTNs, 27, 36, 38, and 35 QTNs were associated for GL, GW, GLWR, and TGW respectively while 24 QTNs were associated with more than one trait. Of these 160 QTNs, 73 were detected in two or more environments and were considered reliable QTLs for the respective traits. A total of 135 associated QTNs were annotated and located within the genes, including ABC transporter, Cytochrome450, Thioredoxin_M-type, and hypothetical proteins. Furthermore, the expression pattern of annotated QTNs demonstrated that only 122 were differentially expressed, suggesting these could potentially be related to seed development. The genomic regions/candidate genes for grain size traits identified in the present study represent valuable genomic resources that can potentially be utilized in the markers-assisted breeding programs to develop high-yielding varieties.
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Affiliation(s)
- Jyoti Kumari
- ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | - Deepika Lakhwani
- ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | - Preeti Jakhar
- ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | - Shivani Sharma
- ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | - Shailesh Tiwari
- ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | - Shikha Mittal
- ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
- Jaypee University of Information Technology, Solan, India
| | | | - Neelam Shekhawat
- ICAR-National Bureau of Plant Genetic Resources, Regional Station, Jodhpur, Jodhpur, India
| | - Kartar Singh
- ICAR-National Bureau of Plant Genetic Resources, Regional Station, Jodhpur, Jodhpur, India
| | | | - Rakesh Singh
- ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | - Mahesh C. Yadav
- ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | | | - Amit Kumar Singh
- ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
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Pasam RK, Kant S, Thoday-Kennedy E, Dimech A, Joshi S, Keeble-Gagnere G, Forrest K, Tibbits J, Hayden M. Haplotype-Based Genome-Wide Association Analysis Using Exome Capture Assay and Digital Phenotyping Identifies Genetic Loci Underlying Salt Tolerance Mechanisms in Wheat. PLANTS (BASEL, SWITZERLAND) 2023; 12:2367. [PMID: 37375992 DOI: 10.3390/plants12122367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 06/14/2023] [Accepted: 06/16/2023] [Indexed: 06/29/2023]
Abstract
Soil salinity can impose substantial stress on plant growth and cause significant yield losses. Crop varieties tolerant to salinity stress are needed to sustain yields in saline soils. This requires effective genotyping and phenotyping of germplasm pools to identify novel genes and QTL conferring salt tolerance that can be utilised in crop breeding schemes. We investigated a globally diverse collection of 580 wheat accessions for their growth response to salinity using automated digital phenotyping performed under controlled environmental conditions. The results show that digitally collected plant traits, including digital shoot growth rate and digital senescence rate, can be used as proxy traits for selecting salinity-tolerant accessions. A haplotype-based genome-wide association study was conducted using 58,502 linkage disequilibrium-based haplotype blocks derived from 883,300 genome-wide SNPs and identified 95 QTL for salinity tolerance component traits, of which 54 were novel and 41 overlapped with previously reported QTL. Gene ontology analysis identified a suite of candidate genes for salinity tolerance, some of which are already known to play a role in stress tolerance in other plant species. This study identified wheat accessions that utilise different tolerance mechanisms and which can be used in future studies to investigate the genetic and genic basis of salinity tolerance. Our results suggest salinity tolerance has not arisen from or been bred into accessions from specific regions or groups. Rather, they suggest salinity tolerance is widespread, with small-effect genetic variants contributing to different levels of tolerance in diverse, locally adapted germplasm.
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Affiliation(s)
- Raj K Pasam
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083, Australia
| | - Surya Kant
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083, Australia
- Agriculture Victoria, Grains Innovation Park, Horsham, VIC 3400, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083, Australia
| | | | - Adam Dimech
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083, Australia
| | - Sameer Joshi
- Agriculture Victoria, Grains Innovation Park, Horsham, VIC 3400, Australia
| | | | - Kerrie Forrest
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083, Australia
| | - Josquin Tibbits
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083, Australia
| | - Matthew Hayden
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083, Australia
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Su Y, Zhang Z, He J, Zeng W, Cai Z, Lai Z, Pan Y, Hao X, Xing G, Wang W, Zhang J, Li Y, Sun Z, Gai J. Gene-allele system of shade tolerance in southern China soybean germplasm revealed by genome-wide association study using gene-allele sequence as markers. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:152. [PMID: 37310498 DOI: 10.1007/s00122-023-04390-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Accepted: 05/16/2023] [Indexed: 06/14/2023]
Abstract
KEY MESSAGE Fifty-three shade tolerance genes with 281 alleles in the SCSGP were identified directly using gene-allele sequence as markers in RTM GWAS, from which optimized crosses, evolutionary motivators, and gene-allele networks were explored. Shade tolerance is a key for optimal cultivation of soybean inter/relay-cropped with corn. To explore the shade tolerance gene-allele system in the southern China soybean germplasm, we proposed using gene-allele sequence markers (GASMs) in a restricted two-stage multi-locus model genome-wide association study (GASM-RTM-GWAS). A representative sample with 394 accessions was tested for their shade tolerance index (STI), in Nanning, China. Through whole-genome re-sequencing, 47,586 GASMs were assembled. From GASM-RTM-GWAS, 53 main-effect STI genes with 281 alleles (2-13 alleles/gene) (totally 63 genes with 308 alleles, including 38 G × E genes with 191 alleles) were identified and then organized into a gene-allele matrix composed of eight submatrices corresponding to geo-seasonal subpopulations. The population featured mild STI changes (1.69 → 1.56-1.82) and mild gene-allele changes (92.5% alleles inherited, 0% alleles excluded, 7.5% alleles emerged) from the primitive (SAIII) to the derived seven subpopulations, but large transgressive recombination potentials and optimal crosses were predicted. The 63 STI genes were annotated into six biological categories (metabolic process, catalytic activity, response to stresses, transcription and translation, signal transduction and transport and unknown functions), interacted as gene networks. From the STI gene-allele system, 38 important alleles of 22 genes were nominated for further in-depth study. GASM-RTM-GWAS performed powerful and efficient in germplasm population genetic study comparing to other procedures through facilitating direct and thorough identification of its gene-allele system, from which genome-wide breeding by design could be achieved, and evolutionary motivators and gene-allele networks could be explored.
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Affiliation(s)
- Yanzhu Su
- Soybean Research Institute and MARA National Center for Soybean Improvement and MARA Key Laboratory of Biology and Genetic Improvement of Soybean and State Key Laboratory for Crop Genetics and Germplasm Enhancement and State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding and Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Zhipeng Zhang
- Soybean Research Institute and MARA National Center for Soybean Improvement and MARA Key Laboratory of Biology and Genetic Improvement of Soybean and State Key Laboratory for Crop Genetics and Germplasm Enhancement and State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding and Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Jianbo He
- Soybean Research Institute and MARA National Center for Soybean Improvement and MARA Key Laboratory of Biology and Genetic Improvement of Soybean and State Key Laboratory for Crop Genetics and Germplasm Enhancement and State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding and Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Weiying Zeng
- Institute of Economic Crops, Guangxi Academy of Agricultural Sciences, Nanning, 5300007, Guangxi, China
| | - Zhaoyan Cai
- Institute of Economic Crops, Guangxi Academy of Agricultural Sciences, Nanning, 5300007, Guangxi, China
| | - Zhenguang Lai
- Institute of Economic Crops, Guangxi Academy of Agricultural Sciences, Nanning, 5300007, Guangxi, China
| | - Yongpeng Pan
- Soybean Research Institute and MARA National Center for Soybean Improvement and MARA Key Laboratory of Biology and Genetic Improvement of Soybean and State Key Laboratory for Crop Genetics and Germplasm Enhancement and State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding and Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Xiaoshuai Hao
- Soybean Research Institute and MARA National Center for Soybean Improvement and MARA Key Laboratory of Biology and Genetic Improvement of Soybean and State Key Laboratory for Crop Genetics and Germplasm Enhancement and State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding and Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Guangnan Xing
- Soybean Research Institute and MARA National Center for Soybean Improvement and MARA Key Laboratory of Biology and Genetic Improvement of Soybean and State Key Laboratory for Crop Genetics and Germplasm Enhancement and State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding and Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Wubin Wang
- Soybean Research Institute and MARA National Center for Soybean Improvement and MARA Key Laboratory of Biology and Genetic Improvement of Soybean and State Key Laboratory for Crop Genetics and Germplasm Enhancement and State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding and Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Jiaoping Zhang
- Soybean Research Institute and MARA National Center for Soybean Improvement and MARA Key Laboratory of Biology and Genetic Improvement of Soybean and State Key Laboratory for Crop Genetics and Germplasm Enhancement and State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding and Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Yan Li
- Soybean Research Institute and MARA National Center for Soybean Improvement and MARA Key Laboratory of Biology and Genetic Improvement of Soybean and State Key Laboratory for Crop Genetics and Germplasm Enhancement and State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding and Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Zudong Sun
- Institute of Economic Crops, Guangxi Academy of Agricultural Sciences, Nanning, 5300007, Guangxi, China.
| | - Junyi Gai
- Soybean Research Institute and MARA National Center for Soybean Improvement and MARA Key Laboratory of Biology and Genetic Improvement of Soybean and State Key Laboratory for Crop Genetics and Germplasm Enhancement and State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding and Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China.
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Saroha A, Gomashe SS, Kaur V, Pal D, Ujjainwal S, Aravind J, Singh M, Rajkumar S, Singh K, Kumar A, Wankhede DP. Genetic dissection of thousand-seed weight in linseed ( Linum usitatissimum L.) using multi-locus genome-wide association study. FRONTIERS IN PLANT SCIENCE 2023; 14:1166728. [PMID: 37332700 PMCID: PMC10272591 DOI: 10.3389/fpls.2023.1166728] [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: 02/15/2023] [Accepted: 05/08/2023] [Indexed: 06/20/2023]
Abstract
Flaxseed/linseed is an important oilseed crop having applications in the food, nutraceutical, and paint industry. Seed weight is one of the most crucial determinants of seed yield in linseed. Here, quantitative trait nucleotides (QTNs) associated with thousand-seed weight (TSW) have been identified using multi-locus genome-wide association study (ML-GWAS). Field evaluation was carried out in five environments in multi-year-location trials. SNP genotyping information of the AM panel of 131 accessions comprising 68,925 SNPs was employed for ML-GWAS. From the six ML-GWAS methods employed, five methods helped identify a total of 84 unique significant QTNs for TSW. QTNs identified in ≥ 2 methods/environments were designated as stable QTNs. Accordingly, 30 stable QTNs have been identified for TSW accounting up to 38.65% trait variation. Alleles with positive effect on trait were analyzed for 12 strong QTNs with r 2 ≥ 10.00%, which showed significant association of specific alleles with higher trait value in three or more environments. A total of 23 candidate genes have been identified for TSW, which included B3 domain-containing transcription factor, SUMO-activating enzyme, protein SCARECROW, shaggy-related protein kinase/BIN2, ANTIAUXIN-RESISTANT 3, RING-type E3 ubiquitin transferase E4, auxin response factors, WRKY transcription factor, and CBS domain-containing protein. In silico expression analysis of candidate genes was performed to validate their possible role in different stages of seed development process. The results from this study provide significant insight and elevate our understanding on genetic architecture of TSW trait in linseed.
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Affiliation(s)
- Ankit Saroha
- Division of Genomic Resources, Indian Council of Agricultural Research (ICAR)-National Bureau of Plant Genetic Resources, New Delhi, India
| | - Sunil S. Gomashe
- ICAR-National Bureau of Plant Genetic Resources, Regional Station Akola, Maharashtra, India
| | - Vikender Kaur
- Division of Germplasm Evaluation, ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | - Deepa Pal
- Division of Genomic Resources, Indian Council of Agricultural Research (ICAR)-National Bureau of Plant Genetic Resources, New Delhi, India
| | - Shraddha Ujjainwal
- Division of Genomic Resources, Indian Council of Agricultural Research (ICAR)-National Bureau of Plant Genetic Resources, New Delhi, India
| | - J. Aravind
- Division of Germplasm Conservation, ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | - Mamta Singh
- Division of Germplasm Evaluation, ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | - S. Rajkumar
- Division of Genomic Resources, Indian Council of Agricultural Research (ICAR)-National Bureau of Plant Genetic Resources, New Delhi, India
| | - Kuldeep Singh
- ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | - Ashok Kumar
- Division of Germplasm Evaluation, ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | - Dhammaprakash Pandhari Wankhede
- Division of Genomic Resources, Indian Council of Agricultural Research (ICAR)-National Bureau of Plant Genetic Resources, New Delhi, India
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Wang C, Hao X, Liu X, Su Y, Pan Y, Zong C, Wang W, Xing G, He J, Gai J. An Improved Genome-Wide Association Procedure Explores Gene-Allele Constitutions and Evolutionary Drives of Growth Period Traits in the Global Soybean Germplasm Population. Int J Mol Sci 2023; 24:ijms24119570. [PMID: 37298521 DOI: 10.3390/ijms24119570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Revised: 05/26/2023] [Accepted: 05/29/2023] [Indexed: 06/12/2023] Open
Abstract
In soybeans (Glycine max (L.) Merr.), their growth periods, DSF (days of sowing-to-flowering), and DFM (days of flowering-to-maturity) are determined by their required accumulative day-length (ADL) and active temperature (AAT). A sample of 354 soybean varieties from five world eco-regions was tested in four seasons in Nanjing, China. The ADL and AAT of DSF and DFM were calculated from daily day-lengths and temperatures provided by the Nanjing Meteorological Bureau. The improved restricted two-stage multi-locus genome-wide association study using gene-allele sequences as markers (coded GASM-RTM-GWAS) was performed. (i) For DSF and its related ADLDSF and AATDSF, 130-141 genes with 384-406 alleles were explored, and for DFM and its related ADLDFM and AATDFM, 124-135 genes with 362-384 alleles were explored, in a total of six gene-allele systems. DSF shared more ADL and AAT contributions than DFM. (ii) Comparisons between the eco-region gene-allele submatrices indicated that the genetic adaptation from the origin to the geographic sub-regions was characterized by allele emergence (mutation), while genetic expansion from primary maturity group (MG)-sets to early/late MG-sets featured allele exclusion (selection) without allele emergence in addition to inheritance (migration). (iii) Optimal crosses with transgressive segregations in both directions were predicted and recommended for breeding purposes, indicating that allele recombination in soybean is an important evolutionary drive. (iv) Genes of the six traits were mostly trait-specific involved in four categories of 10 groups of biological functions. GASM-RTM-GWAS showed potential in detecting directly causal genes with their alleles, identifying differential trait evolutionary drives, predicting recombination breeding potentials, and revealing population gene networks.
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Affiliation(s)
- Can Wang
- Soybean Research Institute, MARA National Center for Soybean Improvement, MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), State Key Laboratory for Crop Genetics and Germplasm Enhancement, State Innovation Platform for Integrated Production and Education in Soybean Bio-breeding, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Xiaoshuai Hao
- Soybean Research Institute, MARA National Center for Soybean Improvement, MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), State Key Laboratory for Crop Genetics and Germplasm Enhancement, State Innovation Platform for Integrated Production and Education in Soybean Bio-breeding, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Xueqin Liu
- Soybean Research Institute, MARA National Center for Soybean Improvement, MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), State Key Laboratory for Crop Genetics and Germplasm Enhancement, State Innovation Platform for Integrated Production and Education in Soybean Bio-breeding, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Yanzhu Su
- Soybean Research Institute, MARA National Center for Soybean Improvement, MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), State Key Laboratory for Crop Genetics and Germplasm Enhancement, State Innovation Platform for Integrated Production and Education in Soybean Bio-breeding, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Yongpeng Pan
- Soybean Research Institute, MARA National Center for Soybean Improvement, MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), State Key Laboratory for Crop Genetics and Germplasm Enhancement, State Innovation Platform for Integrated Production and Education in Soybean Bio-breeding, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Chunmei Zong
- Soybean Research Institute, MARA National Center for Soybean Improvement, MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), State Key Laboratory for Crop Genetics and Germplasm Enhancement, State Innovation Platform for Integrated Production and Education in Soybean Bio-breeding, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Wubin Wang
- Soybean Research Institute, MARA National Center for Soybean Improvement, MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), State Key Laboratory for Crop Genetics and Germplasm Enhancement, State Innovation Platform for Integrated Production and Education in Soybean Bio-breeding, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Guangnan Xing
- Soybean Research Institute, MARA National Center for Soybean Improvement, MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), State Key Laboratory for Crop Genetics and Germplasm Enhancement, State Innovation Platform for Integrated Production and Education in Soybean Bio-breeding, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Jianbo He
- Soybean Research Institute, MARA National Center for Soybean Improvement, MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), State Key Laboratory for Crop Genetics and Germplasm Enhancement, State Innovation Platform for Integrated Production and Education in Soybean Bio-breeding, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Junyi Gai
- Soybean Research Institute, MARA National Center for Soybean Improvement, MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), State Key Laboratory for Crop Genetics and Germplasm Enhancement, State Innovation Platform for Integrated Production and Education in Soybean Bio-breeding, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
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Wang Y, Liu H, Meng Y, Liu J, Ye G. Validation of genes affecting rice mesocotyl length through candidate association analysis and identification of the superior haplotypes. FRONTIERS IN PLANT SCIENCE 2023; 14:1194119. [PMID: 37324692 PMCID: PMC10267709 DOI: 10.3389/fpls.2023.1194119] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Accepted: 05/02/2023] [Indexed: 06/17/2023]
Abstract
Mesocotyl is an essential organ of rice for pushing buds out of soil and plays a crucial role in seeding emergence and development in direct-seeding. Thus, identify the loci associated with mesocotyl length (ML) could accelerate breeding progresses for direct-seeding cultivation. Mesocotyl elongation was mainly regulated by plant hormones. Although several regions and candidate genes governing ML have been reported, the effects of them in diverse breeding populations were still indistinct. In this study, 281 genes related to plant hormones at the genomic regions associated with ML were selected and evaluated by single-locus mixed linear model (SL-MLM) and multi-locus random-SNP-effect mixed linear model (mr-MLM) in two breeding panels (Trop and Indx) originated from the 3K re-sequence project. Furthermore, superior haplotypes with longer mesocotyl were also identified for marker assisted selection (MAS) breeding. Totally, LOC_Os02g17680 (explained 7.1-8.9% phenotypic variations), LOC_Os04g56950 (8.0%), LOC_Os07g24190 (9.3%) and LOC_Os12g12720 (5.6-8.0%) were identified significantly associated with ML in Trop panel, whereas LOC_Os02g17680 (6.5-7.4%), LOC_Os04g56950 (5.5%), LOC_Os06g24850 (4.8%) and LOC_Os07g40240 (4.8-7.1%) were detected in Indx panel. Among these, LOC_Os02g17680 and LOC_Os04g56950 were identified in both panels. Haplotype analysis for the six significant genes indicated that haplotype distribution of the same gene varies at Trop and Indx panels. Totally, 8 (LOC_Os02g17680-Hap1 and Hap2, LOC_Os04g56950-Hap1, Hap2 and Hap8, LOC_Os07g24190-Hap3, LOC_Os12g12720-Hap3 and Hap6) and six superior haplotypes (LOC_Os02g17680-Hap2, Hap5 and Hap7, LOC_Os04g56950-Hap4, LOC_Os06g24850-Hap2 and LOC_Os07g40240-Hap3) with higher ML were identified in Trop and Indx panels, respectively. In addition, significant additive effects for ML with more superior haplotypes were identified in both panels. Overall, the 6 significantly associated genes and their superior haplotypes could be used to enhancing ML through MAS breeding and further promote direct-seedling cultivation.
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Affiliation(s)
- Yamei Wang
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
- CAAS-IRRI Joint Laboratory for Genomics-Assisted Germplasm Enhancement, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- School of Agriculture, Sun Yat-sen University, Shenzhen, China
| | - Hongyan Liu
- Sanya Nanfan Research Institute of Hainan University, Hainan University, Sanya, China
| | - Yun Meng
- CAAS-IRRI Joint Laboratory for Genomics-Assisted Germplasm Enhancement, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Sanya Nanfan Research Institute of Hainan University, Hainan University, Sanya, China
| | - Jindong Liu
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
- CAAS-IRRI Joint Laboratory for Genomics-Assisted Germplasm Enhancement, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Guoyou Ye
- CAAS-IRRI Joint Laboratory for Genomics-Assisted Germplasm Enhancement, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Strategic Innovation Platform, International Rice Research Institute, Manila, Philippines
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Vallarino JG, Jun H, Wang S, Wang X, Sade N, Orf I, Zhang D, Shi J, Shen S, Cuadros-Inostroza Á, Xu Q, Luo J, Fernie AR, Brotman Y. Limitations and advantages of using metabolite-based genome-wide association studies: focus on fruit quality traits. PLANT SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 2023; 333:111748. [PMID: 37230189 DOI: 10.1016/j.plantsci.2023.111748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Revised: 05/19/2023] [Accepted: 05/21/2023] [Indexed: 05/27/2023]
Abstract
In the last decades, linkage mapping has help in the location of metabolite quantitative trait loci (QTL) in many species; however, this approach shows some limitations. Recently, thanks to the most recent advanced in high-throughput genotyping technologies like next-generation sequencing, metabolite genome-wide association study (mGWAS) has been proposed a powerful tool to identify the genetic variants in polygenic agrinomic traits. Fruit flavor is a complex interaction of aroma volatiles and taste being sugar and acid ratio key parameter for flavor acceptance. Here, we review recent progress of mGWAS in pinpoint gene polymorphisms related to flavor-related metabolites in fruits. Despite clear successes in discovering novel genes or regions associated with metabolite accumulation affecting sensory attributes in fruits, GWAS incurs in several limitations summarized in this review. In addition, in our own work, we performed mGWAS on 194 Citrus grandis accessions to investigate the genetic control of individual primary and lipid metabolites in ripe fruit. We have identified a total of 667 associations for 14 primary metabolites including amino acids, sugars, and organic acids, and 768 associations corresponding to 47 lipids. Furthermore, candidate genes related to important metabolites related to fruit quality such as sugars, organic acids and lipids were discovered.
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Affiliation(s)
- José G Vallarino
- Instituto de Hortofruticultura Subtropical y Mediterránea "La Mayora", Universidad de Málaga-Consejo Superior de Investigaciones Científicas, Departamento de Biología Molecular y Bioquímica, Campus de Teatinos, 29071 Málaga, Spain
| | - Hong Jun
- Department of Genetics and Developmental Science, Joint International Research Laboratory of Metabolic and Developmental Sciences, State Key Laboratory of Hybrid Rice, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China; Waite Research Institute, School of Agriculture, Food and Wine, University of Adelaide, Urrbrae, SA, Australia
| | | | - Xia Wang
- Key Laboratory of Horticultural Plant Biology (Ministry of Education), Huazhong Agricultural University, Wuhan, China
| | - Nir Sade
- School of Plant Sciences and Food Security, Tel Aviv University, P.O.B. 39040, 55 Haim Levanon St., Tel Aviv 6139001, Israel
| | - Isabel Orf
- Department of Life Sciences, Ben Gurion University of the Negev, Beersheva, Israel
| | - Dabing Zhang
- Department of Genetics and Developmental Science, Joint International Research Laboratory of Metabolic and Developmental Sciences, State Key Laboratory of Hybrid Rice, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China; Waite Research Institute, School of Agriculture, Food and Wine, University of Adelaide, Urrbrae, SA, Australia
| | - Jianxin Shi
- Department of Genetics and Developmental Science, Joint International Research Laboratory of Metabolic and Developmental Sciences, State Key Laboratory of Hybrid Rice, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
| | - Shuangqian Shen
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
| | | | - Qiang Xu
- Key Laboratory of Horticultural Plant Biology (Ministry of Education), Huazhong Agricultural University, Wuhan, China
| | - Jie Luo
- College of Tropical Crops, Hainan University, Haikou, China; National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
| | - Alisdair R Fernie
- Department of Root Biology and Symbiosis, Max Planck Institute of Molecular Plant Physiology, 1 Am Mühlenberg, Golm, Potsdam 14476, Germany; Department of Plant Metabolomics, Center for Plant Systems Biology and Biotechnology, 139 Ruski Blvd., Plovdiv 4000, Bulgaria.
| | - Yariv Brotman
- Department of Life Sciences, Ben Gurion University of the Negev, Beersheva, Israel.
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Adeniyi OO, Medugorac I, Grochowska E, Düring RA, Lühken G. Single-Locus and Multi-Locus Genome-Wide Association Studies Identify Genes Associated with Liver Cu Concentration in Merinoland Sheep. Genes (Basel) 2023; 14:genes14051053. [PMID: 37239413 DOI: 10.3390/genes14051053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 05/02/2023] [Accepted: 05/04/2023] [Indexed: 05/28/2023] Open
Abstract
Economic losses due to copper intoxication or deficiency is a problem encountered by sheep farmers. The aim of this study was to investigate the ovine genome for genomic regions and candidate genes responsible for variability in liver copper concentration. Liver samples were collected from slaughtered lambs of the Merinoland breed from two farms, and used for measurement of copper concentration and genome-wide association study (GWAS). A total of 45,511 SNPs and 130 samples were finally used for analysis, in which single-locus and several multi-locus GWAS (SL-GWAS; ML-GWAS) methods were employed. Gene enrichment analysis was performed for identified candidate genes to detect gene ontology (GO) terms significantly associated with hepatic copper levels. The SL-GWAS and a minimum of two ML-GWAS identified two and thirteen significant SNPs, respectively. Within genomic regions surrounding identified SNPs, we observed nine promising candidate genes such as DYNC1I2, VPS35, SLC38A9 and CHMP1A. GO terms such as lysosomal membrane, mitochondrial inner membrane and sodium:proton antiporter activity were significantly enriched. Genes involved in these identified GO terms mediate multivesicular body (MVB) fusion with lysosome for degradation and control mitochondrial membrane permeability. This reveals the polygenic status of this trait and candidate genes for further studies on breeding for copper tolerance in sheep.
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Affiliation(s)
- Olusegun O Adeniyi
- Institute of Animal Breeding and Genetics, Justus Liebig University Giessen, Ludwigstrasse 21, 35390 Giessen, Germany
| | - Ivica Medugorac
- Population Genomics Group, Department of Veterinary Sciences, Ludwig Maximilian University Munich, Lena-Christ-Str. 48, 82152 Martinsried, Germany
| | - Ewa Grochowska
- Department of Animal Biotechnology and Genetics, Bydgoszcz University of Science and Technology, Mazowiecka 28 St., 85-084 Bydgoszcz, Poland
| | - Rolf-Alexander Düring
- Institute of Soil Science and Soil Conservation, Interdisciplinary Research Center for Biosystems, Land Use and Nutrition (IFZ), Justus Liebig University Giessen, Heinrich-Buff-Ring 26-32, 35392 Giessen, Germany
| | - Gesine Lühken
- Institute of Animal Breeding and Genetics, Justus Liebig University Giessen, Ludwigstrasse 21, 35390 Giessen, Germany
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