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Dilla-Ermita CJ, Goldman P, Anchieta A, Feldmann MJ, Pincot DDA, Famula RA, Vachev M, Cole GS, Knapp SJ, Klosterman SJ, Henry PM. Secreted in Xylem 6 ( SIX6) Mediates Fusarium oxysporum f. sp. fragariae Race 1 Avirulence on FW1-Resistant Strawberry Cultivars. MOLECULAR PLANT-MICROBE INTERACTIONS : MPMI 2024; 37:530-541. [PMID: 38552146 DOI: 10.1094/mpmi-02-24-0012-r] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/25/2024]
Abstract
Fusarium oxysporum f. sp. fragariae (Fof) race 1 is avirulent on cultivars with the dominant resistance gene FW1, while Fof race 2 is virulent on FW1-resistant cultivars. We hypothesized there was a gene-for-gene interaction between a gene at the FW1 locus and an avirulence gene (AvrFW1) in Fof race 1. To identify a candidate AvrFW1, we compared genomes of 24 Fof race 1 and three Fof race 2 isolates. We found one candidate gene that was present in race 1, was absent in race 2, was highly expressed in planta, and was homologous to a known effector, secreted in xylem 6 (SIX6). We knocked out SIX6 in two Fof race 1 isolates by homologous recombination. All SIX6 knockout transformants (ΔSIX6) gained virulence on FW1/fw1 cultivars, whereas ectopic transformants and the wildtype isolates remained avirulent. ΔSIX6 isolates were quantitatively less virulent on FW1/fw1 cultivars Fronteras and San Andreas than fw1/fw1 cultivars. Seedlings from an FW1/fw1 × fw1/fw1 population were genotyped for FW1 and tested for susceptibility to a SIX6 knockout isolate. Results suggested that additional minor-effect quantitative resistance genes could be present at the FW1 locus. This work demonstrates that SIX6 acts as an avirulence factor interacting with a resistance gene at the FW1 locus. The identification of AvrFW1 enables surveillance for Fof race 2 and provides insight into the mechanisms of FW1-mediated resistance. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.
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Affiliation(s)
- Christine Jade Dilla-Ermita
- Crop Improvement and Protection Research, USDA-ARS, 1636 E. Alisal St., Salinas, CA 93905
- Department of Plant Sciences, University of California Davis, One Shields Ave., Davis, CA 95616
| | - Polly Goldman
- Crop Improvement and Protection Research, USDA-ARS, 1636 E. Alisal St., Salinas, CA 93905
| | - Amy Anchieta
- Crop Improvement and Protection Research, USDA-ARS, 1636 E. Alisal St., Salinas, CA 93905
| | - Mitchell J Feldmann
- Department of Plant Sciences, University of California Davis, One Shields Ave., Davis, CA 95616
| | - Dominique D A Pincot
- Department of Plant Sciences, University of California Davis, One Shields Ave., Davis, CA 95616
| | - Randi A Famula
- Department of Plant Sciences, University of California Davis, One Shields Ave., Davis, CA 95616
| | - Mishi Vachev
- Department of Plant Sciences, University of California Davis, One Shields Ave., Davis, CA 95616
| | - Glenn S Cole
- Department of Plant Sciences, University of California Davis, One Shields Ave., Davis, CA 95616
| | - Steven J Knapp
- Department of Plant Sciences, University of California Davis, One Shields Ave., Davis, CA 95616
| | - Steven J Klosterman
- Crop Improvement and Protection Research, USDA-ARS, 1636 E. Alisal St., Salinas, CA 93905
| | - Peter M Henry
- Crop Improvement and Protection Research, USDA-ARS, 1636 E. Alisal St., Salinas, CA 93905
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Knapp SJ, Cole GS, Pincot DDA, Dilla-Ermita CJ, Bjornson M, Famula RA, Gordon TR, Harshman JM, Henry PM, Feldmann MJ. Transgressive segregation, hopeful monsters, and phenotypic selection drove rapid genetic gains and breakthroughs in predictive breeding for quantitative resistance to Macrophomina in strawberry. HORTICULTURE RESEARCH 2024; 11:uhad289. [PMID: 38487295 PMCID: PMC10939388 DOI: 10.1093/hr/uhad289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 12/17/2023] [Indexed: 03/17/2024]
Abstract
Two decades have passed since the strawberry (Fragaria x ananassa) disease caused by Macrophomina phaseolina, a necrotrophic soilborne fungal pathogen, began surfacing in California, Florida, and elsewhere. This disease has since become one of the most common causes of plant death and yield losses in strawberry. The Macrophomina problem emerged and expanded in the wake of the global phase-out of soil fumigation with methyl bromide and appears to have been aggravated by an increase in climate change-associated abiotic stresses. Here we show that sources of resistance to this pathogen are rare in gene banks and that the favorable alleles they carry are phenotypically unobvious. The latter were exposed by transgressive segregation and selection in populations phenotyped for resistance to Macrophomina under heat and drought stress. The genetic gains were immediate and dramatic. The frequency of highly resistant individuals increased from 1% in selection cycle 0 to 74% in selection cycle 2. Using GWAS and survival analysis, we found that phenotypic selection had increased the frequencies of favorable alleles among 10 loci associated with resistance and that favorable alleles had to be accumulated among four or more of these loci for an individual to acquire resistance. An unexpectedly straightforward solution to the Macrophomina disease resistance breeding problem emerged from our studies, which showed that highly resistant cultivars can be developed by genomic selection per se or marker-assisted stacking of favorable alleles among a comparatively small number of large-effect loci.
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Affiliation(s)
- Steven J Knapp
- Department of Plant Sciences, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA
| | - Glenn S Cole
- Department of Plant Sciences, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA
| | - Dominique D A Pincot
- Department of Plant Sciences, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA
| | - Christine Jade Dilla-Ermita
- Department of Plant Sciences, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA
- Crop Improvement and Protection Research, USDA-ARS, 1636 E. Alisal Street, CA 93905, USA
| | - Marta Bjornson
- Department of Plant Sciences, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA
| | - Randi A Famula
- Department of Plant Sciences, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA
| | - Thomas R Gordon
- Department of Plant Pathology, University of California, One Shields Avenue, Davis, CA 95616, USA
| | - Julia M Harshman
- Department of Plant Sciences, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA
| | - Peter M Henry
- Crop Improvement and Protection Research, USDA-ARS, 1636 E. Alisal Street, CA 93905, USA
| | - Mitchell J Feldmann
- Department of Plant Sciences, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA
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Feldmann MJ, Covarrubias-Pazaran G, Piepho HP. Complex traits and candidate genes: estimation of genetic variance components across multiple genetic architectures. G3 (BETHESDA, MD.) 2023; 13:jkad148. [PMID: 37405459 PMCID: PMC10468314 DOI: 10.1093/g3journal/jkad148] [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: 04/27/2023] [Revised: 06/09/2023] [Accepted: 06/12/2023] [Indexed: 07/06/2023]
Abstract
Large-effect loci-those statistically significant loci discovered by genome-wide association studies or linkage mapping-associated with key traits segregate amidst a background of minor, often undetectable, genetic effects in wild and domesticated plants and animals. Accurately attributing mean differences and variance explained to the correct components in the linear mixed model analysis is vital for selecting superior progeny and parents in plant and animal breeding, gene therapy, and medical genetics in humans. Marker-assisted prediction and its successor, genomic prediction, have many advantages for selecting superior individuals and understanding disease risk. However, these two approaches are less often integrated to study complex traits with different genetic architectures. This simulation study demonstrates that the average semivariance can be applied to models incorporating Mendelian, oligogenic, and polygenic terms simultaneously and yields accurate estimates of the variance explained for all relevant variables. Our previous research focused on large-effect loci and polygenic variance separately. This work aims to synthesize and expand the average semivariance framework to various genetic architectures and the corresponding mixed models. This framework independently accounts for the effects of large-effect loci and the polygenic genetic background and is universally applicable to genetics studies in humans, plants, animals, and microbes.
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Affiliation(s)
- Mitchell J Feldmann
- Department of Plant Sciences, University of California Davis, One Shields Ave, Davis, CA 95616, USA
| | - Giovanny Covarrubias-Pazaran
- International Maize and Wheat Improvement Center (CIMMYT), Carretera México-Veracruz, El Batán, 56130 Texcoco, Edo. de México, México
| | - Hans-Peter Piepho
- Biostatistics Unit, Institute of Crop Science, University of Hohenheim, Stuttgart 70599, Germany
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Jiménez NP, Feldmann MJ, Famula RA, Pincot DDA, Bjornson M, Cole GS, Knapp SJ. Harnessing underutilized gene bank diversity and genomic prediction of cross usefulness to enhance resistance to Phytophthora cactorum in strawberry. THE PLANT GENOME 2023; 16:e20275. [PMID: 36480594 DOI: 10.1002/tpg2.20275] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 09/19/2022] [Indexed: 05/10/2023]
Abstract
The development of strawberry (Fragaria × ananassa Duchesne ex Rozier) cultivars resistant to Phytophthora crown rot (PhCR), a devastating disease caused by the soil-borne pathogen Phytophthora cactorum (Lebert & Cohn) J. Schröt., has been challenging partly because the resistance phenotypes are quantitative and only moderately heritable. To develop deeper insights into the genetics of resistance and build the foundation for applying genomic selection, a genetically diverse training population was screened for resistance to California isolates of the pathogen. Here we show that genetic gains in breeding for resistance to PhCR have been negligible (3% of the cultivars tested were highly resistant and none surpassed early 20th century cultivars). Narrow-sense genomic heritability for PhCR resistance ranged from 0.41 to 0.75 among training population individuals. Using multivariate genome-wide association studies (GWAS), we identified a large-effect locus (predicted to be RPc2) that explained 43.6-51.6% of the genetic variance, was necessary but not sufficient for resistance, and was associated with calcium channel and other candidate genes with known plant defense functions. The addition of underutilized gene bank resources to our training population doubled additive genetic variance, increased the accuracy of genomic selection, and enabled the discovery of individuals carrying favorable alleles that are either rare or not present in modern cultivars. The incorporation of an RPc2-associated single-nucleotide polymorphism (SNP) as a fixed effect increased genomic prediction accuracy from 0.40 to 0.55. Finally, we show that parent selection using genomic-estimated breeding values, genetic variances, and cross usefulness holds promise for enhancing resistance to PhCR in strawberry.
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Affiliation(s)
- Nicolás P Jiménez
- Dep. of Plant Sciences, Univ. of California, One Shields Ave, Davis, CA, 95616, USA
| | - Mitchell J Feldmann
- Dep. of Plant Sciences, Univ. of California, One Shields Ave, Davis, CA, 95616, USA
| | - Randi A Famula
- Dep. of Plant Sciences, Univ. of California, One Shields Ave, Davis, CA, 95616, USA
| | - Dominique D A Pincot
- Dep. of Plant Sciences, Univ. of California, One Shields Ave, Davis, CA, 95616, USA
| | - Marta Bjornson
- Dep. of Plant Sciences, Univ. of California, One Shields Ave, Davis, CA, 95616, USA
| | - Glenn S Cole
- Dep. of Plant Sciences, Univ. of California, One Shields Ave, Davis, CA, 95616, USA
| | - Steven J Knapp
- Dep. of Plant Sciences, Univ. of California, One Shields Ave, Davis, CA, 95616, USA
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Zhang J, Wang S, Wu X, Han L, Wang Y, Wen Y. Identification of QTNs, QTN-by-environment interactions and genes for yield-related traits in rice using 3VmrMLM. FRONTIERS IN PLANT SCIENCE 2022; 13:995609. [PMID: 36325550 PMCID: PMC9618716 DOI: 10.3389/fpls.2022.995609] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Accepted: 09/27/2022] [Indexed: 06/16/2023]
Abstract
Rice, which supports more than half the population worldwide, is one of the most important food crops. Thus, potential yield-related quantitative trait nucleotides (QTNs) and QTN-by-environment interactions (QEIs) have been used to develop efficient rice breeding strategies. In this study, a compressed variance component mixed model, 3VmrMLM, in genome-wide association studies was used to detect QTNs for eight yield-related traits of 413 rice accessions with 44,000 single nucleotide polymorphisms. These traits include florets per panicle, panicle fertility, panicle length, panicle number per plant, plant height, primary panicle branch number, seed number per panicle, and flowering time. Meanwhile, QTNs and QEIs were identified for flowering times in three different environments and five subpopulations. In the detections, a total of 7~23 QTNs were detected for each trait, including the three single-environment flowering time traits. In the detection of QEIs for flowering time in the three environments, 21 QTNs and 13 QEIs were identified. In the five subpopulation analyses, 3~9 QTNs and 2~4 QEIs were detected for each subpopulation. Based on previous studies, we identified 87 known genes around the significant/suggested QTNs and QEIs, such as LOC_Os06g06750 (OsMADS5) and LOC_Os07g47330 (FZP). Further differential expression analysis and functional enrichment analysis identified 30 candidate genes. Of these candidate genes, 27 genes had high expression in specific tissues, and 19 of these 27 genes were homologous to known genes in Arabidopsis. Haplotype difference analysis revealed that LOC_Os04g53210 and LOC_Os07g42440 are possibly associated with yield, and LOC_Os04g53210 may be useful around a QEI for flowering time. These results provide insights for future breeding for high quality and yield in rice.
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Affiliation(s)
- Jin Zhang
- College of Science, Nanjing Agricultural University, Nanjing, China
- Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Shengmeng Wang
- College of Science, Nanjing Agricultural University, Nanjing, China
| | - Xinyi Wu
- College of Science, Nanjing Agricultural University, Nanjing, China
| | - Le Han
- College of Science, Nanjing Agricultural University, Nanjing, China
| | - Yuan Wang
- College of Science, Nanjing Agricultural University, Nanjing, China
| | - Yangjun Wen
- College of Science, Nanjing Agricultural University, Nanjing, China
- Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
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Pincot DDA, Feldmann MJ, Hardigan MA, Vachev MV, Henry PM, Gordon TR, Bjornson M, Rodriguez A, Cobo N, Famula RA, Cole GS, Coaker GL, Knapp SJ. Novel Fusarium wilt resistance genes uncovered in natural and cultivated strawberry populations are found on three non-homoeologous chromosomes. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:2121-2145. [PMID: 35583656 PMCID: PMC9205853 DOI: 10.1007/s00122-022-04102-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 04/11/2022] [Indexed: 05/05/2023]
Abstract
Several Fusarium wilt resistance genes were discovered, genetically and physically mapped, and rapidly deployed via marker-assisted selection to develop cultivars resistant to Fusarium oxysporum f. sp. fragariae, a devastating soil-borne pathogen of strawberry. Fusarium wilt, a soilborne disease caused by Fusarium oxysporum f. sp. fragariae, poses a significant threat to strawberry (Fragaria [Formula: see text] ananassa) production in many parts of the world. This pathogen causes wilting, collapse, and death in susceptible genotypes. We previously identified a dominant gene (FW1) on chromosome 2B that confers resistance to race 1 of the pathogen, and hypothesized that gene-for-gene resistance to Fusarium wilt was widespread in strawberry. To explore this, a genetically diverse collection of heirloom and modern cultivars and octoploid ecotypes were screened for resistance to Fusarium wilt races 1 and 2. Here, we show that resistance to both races is widespread in natural and domesticated populations and that resistance to race 1 is conferred by partially to completely dominant alleles among loci (FW1, FW2, FW3, FW4, and FW5) found on three non-homoeologous chromosomes (1A, 2B, and 6B). The underlying genes have not yet been cloned and functionally characterized; however, plausible candidates were identified that encode pattern recognition receptors or other proteins known to confer gene-for-gene resistance in plants. High-throughput genotyping assays for SNPs in linkage disequilibrium with FW1-FW5 were developed to facilitate marker-assisted selection and accelerate the development of race 1 resistant cultivars. This study laid the foundation for identifying the genes encoded by FW1-FW5, in addition to exploring the genetics of resistance to race 2 and other races of the pathogen, as a precaution to averting a Fusarium wilt pandemic.
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Affiliation(s)
- Dominique D. A. Pincot
- Department of Plant Sciences, One Shields Avenue, University of California, Davis, CA 95616 USA
| | - Mitchell J. Feldmann
- Department of Plant Sciences, One Shields Avenue, University of California, Davis, CA 95616 USA
| | - Michael A. Hardigan
- Horticultural Crops Research Unit, United States Department of Agriculture, Agricultural Research Service, Corvallis, OR 97331 USA
| | - Mishi V. Vachev
- Department of Plant Sciences, One Shields Avenue, University of California, Davis, CA 95616 USA
| | - Peter M. Henry
- United States Department of Agriculture Agricultural Research Service, 1636 East Alisal Street, Salinas, CA 93905 USA
| | - Thomas R. Gordon
- Department of Plant Pathology, One Shields Avenue, University of California, Davis, CA 95616 USA
| | - Marta Bjornson
- Department of Plant Sciences, One Shields Avenue, University of California, Davis, CA 95616 USA
| | - Alan Rodriguez
- Department of Plant Sciences, One Shields Avenue, University of California, Davis, CA 95616 USA
| | - Nicolas Cobo
- Departamento de Producción, Agropecuaria Universidad de La Frontera, Temuco, Chile
| | - Randi A. Famula
- Department of Plant Sciences, One Shields Avenue, University of California, Davis, CA 95616 USA
| | - Glenn S. Cole
- Department of Plant Sciences, One Shields Avenue, University of California, Davis, CA 95616 USA
| | - Gitta L. Coaker
- Department of Plant Sciences, One Shields Avenue, University of California, Davis, CA 95616 USA
| | - Steven J. Knapp
- Department of Plant Sciences, One Shields Avenue, University of California, Davis, CA 95616 USA
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Feldmann MJ, Piepho HP, Knapp SJ. Average semivariance directly yields accurate estimates of the genomic variance in complex trait analyses. G3 GENES|GENOMES|GENETICS 2022; 12:6571389. [PMID: 35442424 PMCID: PMC9157152 DOI: 10.1093/g3journal/jkac080] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Accepted: 03/17/2022] [Indexed: 11/23/2022]
Abstract
Many important traits in plants, animals, and microbes are polygenic and challenging to improve through traditional marker-assisted selection. Genomic prediction addresses this by incorporating all genetic data in a mixed model framework. The primary method for predicting breeding values is genomic best linear unbiased prediction, which uses the realized genomic relationship or kinship matrix (K) to connect genotype to phenotype. Genomic relationship matrices share information among entries to estimate the observed entries’ genetic values and predict unobserved entries’ genetic values. One of the main parameters of such models is genomic variance (σg2), or the variance of a trait associated with a genome-wide sample of DNA polymorphisms, and genomic heritability (hg2); however, the seminal papers introducing different forms of K often do not discuss their effects on the model estimated variance components despite their importance in genetic research and breeding. Here, we discuss the effect of several standard methods for calculating the genomic relationship matrix on estimates of σg2 and hg2. With current approaches, we found that the genomic variance tends to be either overestimated or underestimated depending on the scaling and centering applied to the marker matrix (Z), the value of the average diagonal element of K, and the assortment of alleles and heterozygosity (H) in the observed population. Using the average semivariance, we propose a new matrix, KASV, that directly yields accurate estimates of σg2 and hg2 in the observed population and produces best linear unbiased predictors equivalent to routine methods in plants and animals.
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Affiliation(s)
- Mitchell J Feldmann
- Department of Plant Sciences, University of California , Davis, CA 95616, USA
| | - Hans-Peter Piepho
- Biostatistics Unit, Institute of Crop Science, University of Hohenheim , 70593 Stuttgart, Germany
| | - Steven J Knapp
- Department of Plant Sciences, University of California , Davis, CA 95616, USA
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Li M, Zhang YW, Zhang ZC, Xiang Y, Liu MH, Zhou YH, Zuo JF, Zhang HQ, Chen Y, Zhang YM. A compressed variance component mixed model for detecting QTNs and QTN-by-environment and QTN-by-QTN interactions in genome-wide association studies. MOLECULAR PLANT 2022; 15:630-650. [PMID: 35202864 DOI: 10.1016/j.molp.2022.02.012] [Citation(s) in RCA: 47] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2021] [Revised: 01/26/2022] [Accepted: 02/19/2022] [Indexed: 05/25/2023]
Abstract
Although genome-wide association studies are widely used to mine genes for quantitative traits, the effects to be estimated are confounded, and the methodologies for detecting interactions are imperfect. To address these issues, the mixed model proposed here first estimates the genotypic effects for AA, Aa, and aa, and the genotypic polygenic background replaces additive and dominance polygenic backgrounds. Then, the estimated genotypic effects are partitioned into additive and dominance effects using a one-way analysis of variance model. This strategy was further expanded to cover QTN-by-environment interactions (QEIs) and QTN-by-QTN interactions (QQIs) using the same mixed-model framework. Thus, a three-variance-component mixed model was integrated with our multi-locus random-SNP-effect mixed linear model (mrMLM) method to establish a new methodological framework, 3VmrMLM, that detects all types of loci and estimates their effects. In Monte Carlo studies, 3VmrMLM correctly detected all types of loci and almost unbiasedly estimated their effects, with high powers and accuracies and a low false positive rate. In re-analyses of 10 traits in 1439 rice hybrids, detection of 269 known genes, 45 known gene-by-environment interactions, and 20 known gene-by-gene interactions strongly validated 3VmrMLM. Further analyses of known genes showed more small (67.49%), minor-allele-frequency (35.52%), and pleiotropic (30.54%) genes, with higher repeatability across datasets (54.36%) and more dominance loci. In addition, a heteroscedasticity mixed model in multiple environments and dimension reduction methods in quite a number of environments were developed to detect QEIs, and variable selection under a polygenic background was proposed for QQI detection. This study provides a new approach for revealing the genetic architecture of quantitative traits.
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Affiliation(s)
- Mei Li
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Ya-Wen Zhang
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; State Key Laboratory of Cotton Biology, Anyang 455000, China
| | - Ze-Chang Zhang
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Yu Xiang
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Ming-Hui Liu
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Ya-Hui Zhou
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Jian-Fang Zuo
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Han-Qing Zhang
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Ying Chen
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Yuan-Ming Zhang
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
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