Image_1_Compressed variance component mixed model reveals epistasis associated with flowering in Arabidopsis.pdf

IntroductionEpistasis is currently a topic of great interest in molecular and quantitative genetics. Arabidopsis thaliana, as a model organism, plays a crucial role in studying the fundamental biology of diverse plant species. However, there have been limited reports about identification of epistasis related to flowering in genome-wide association studies (GWAS). Therefore, it is of utmost importance to conduct epistasis in Arabidopsis.MethodIn this study, we employed Levene’s test and compressed variance component mixed model in GWAS to detect quantitative trait nucleotides (QTNs) and QTN-by-QTN interactions (QQIs) for 11 flowering-related traits of 199 Arabidopsis accessions with 216,130 markers.ResultsOur analysis detected 89 QTNs and 130 pairs of QQIs. Around these loci, 34 known genes previously reported in Arabidopsis were confirmed to be associated with flowering-related traits, such as SPA4, which is involved in regulating photoperiodic flowering, and interacts with PAP1 and PAP2, affecting growth of Arabidopsis under light conditions. Then, we observed significant and differential expression of 35 genes in response to variations in temperature, photoperiod, and vernalization treatments out of unreported genes. Functional enrichment analysis revealed that 26 of these genes were associated with various biological processes. Finally, the haplotype and phenotypic difference analysis revealed 20 candidate genes exhibiting significant phenotypic variations across gene haplotypes, of which the candidate genes AT1G12990 and AT1G09950 around QQIs might have interaction effect to flowering time regulation in Arabidopsis.DiscussionThese findings may offer valuable insights for the identification and exploration of genes and gene-by-gene interactions associated with flowering-related traits in Arabidopsis, that may even provide valuable reference and guidance for the research of epistasis in other species.</p

Table_1_Compressed variance component mixed model reveals epistasis associated with flowering in Arabidopsis.xlsx

IntroductionEpistasis is currently a topic of great interest in molecular and quantitative genetics. Arabidopsis thaliana, as a model organism, plays a crucial role in studying the fundamental biology of diverse plant species. However, there have been limited reports about identification of epistasis related to flowering in genome-wide association studies (GWAS). Therefore, it is of utmost importance to conduct epistasis in Arabidopsis.MethodIn this study, we employed Levene’s test and compressed variance component mixed model in GWAS to detect quantitative trait nucleotides (QTNs) and QTN-by-QTN interactions (QQIs) for 11 flowering-related traits of 199 Arabidopsis accessions with 216,130 markers.ResultsOur analysis detected 89 QTNs and 130 pairs of QQIs. Around these loci, 34 known genes previously reported in Arabidopsis were confirmed to be associated with flowering-related traits, such as SPA4, which is involved in regulating photoperiodic flowering, and interacts with PAP1 and PAP2, affecting growth of Arabidopsis under light conditions. Then, we observed significant and differential expression of 35 genes in response to variations in temperature, photoperiod, and vernalization treatments out of unreported genes. Functional enrichment analysis revealed that 26 of these genes were associated with various biological processes. Finally, the haplotype and phenotypic difference analysis revealed 20 candidate genes exhibiting significant phenotypic variations across gene haplotypes, of which the candidate genes AT1G12990 and AT1G09950 around QQIs might have interaction effect to flowering time regulation in Arabidopsis.DiscussionThese findings may offer valuable insights for the identification and exploration of genes and gene-by-gene interactions associated with flowering-related traits in Arabidopsis, that may even provide valuable reference and guidance for the research of epistasis in other species.</p

DataSheet_1_Compressed variance component mixed model reveals epistasis associated with flowering in Arabidopsis.zip

IntroductionEpistasis is currently a topic of great interest in molecular and quantitative genetics. Arabidopsis thaliana, as a model organism, plays a crucial role in studying the fundamental biology of diverse plant species. However, there have been limited reports about identification of epistasis related to flowering in genome-wide association studies (GWAS). Therefore, it is of utmost importance to conduct epistasis in Arabidopsis.MethodIn this study, we employed Levene’s test and compressed variance component mixed model in GWAS to detect quantitative trait nucleotides (QTNs) and QTN-by-QTN interactions (QQIs) for 11 flowering-related traits of 199 Arabidopsis accessions with 216,130 markers.ResultsOur analysis detected 89 QTNs and 130 pairs of QQIs. Around these loci, 34 known genes previously reported in Arabidopsis were confirmed to be associated with flowering-related traits, such as SPA4, which is involved in regulating photoperiodic flowering, and interacts with PAP1 and PAP2, affecting growth of Arabidopsis under light conditions. Then, we observed significant and differential expression of 35 genes in response to variations in temperature, photoperiod, and vernalization treatments out of unreported genes. Functional enrichment analysis revealed that 26 of these genes were associated with various biological processes. Finally, the haplotype and phenotypic difference analysis revealed 20 candidate genes exhibiting significant phenotypic variations across gene haplotypes, of which the candidate genes AT1G12990 and AT1G09950 around QQIs might have interaction effect to flowering time regulation in Arabidopsis.DiscussionThese findings may offer valuable insights for the identification and exploration of genes and gene-by-gene interactions associated with flowering-related traits in Arabidopsis, that may even provide valuable reference and guidance for the research of epistasis in other species.</p

Image_2_Compressed variance component mixed model reveals epistasis associated with flowering in Arabidopsis.tif

IntroductionEpistasis is currently a topic of great interest in molecular and quantitative genetics. Arabidopsis thaliana, as a model organism, plays a crucial role in studying the fundamental biology of diverse plant species. However, there have been limited reports about identification of epistasis related to flowering in genome-wide association studies (GWAS). Therefore, it is of utmost importance to conduct epistasis in Arabidopsis.MethodIn this study, we employed Levene’s test and compressed variance component mixed model in GWAS to detect quantitative trait nucleotides (QTNs) and QTN-by-QTN interactions (QQIs) for 11 flowering-related traits of 199 Arabidopsis accessions with 216,130 markers.ResultsOur analysis detected 89 QTNs and 130 pairs of QQIs. Around these loci, 34 known genes previously reported in Arabidopsis were confirmed to be associated with flowering-related traits, such as SPA4, which is involved in regulating photoperiodic flowering, and interacts with PAP1 and PAP2, affecting growth of Arabidopsis under light conditions. Then, we observed significant and differential expression of 35 genes in response to variations in temperature, photoperiod, and vernalization treatments out of unreported genes. Functional enrichment analysis revealed that 26 of these genes were associated with various biological processes. Finally, the haplotype and phenotypic difference analysis revealed 20 candidate genes exhibiting significant phenotypic variations across gene haplotypes, of which the candidate genes AT1G12990 and AT1G09950 around QQIs might have interaction effect to flowering time regulation in Arabidopsis.DiscussionThese findings may offer valuable insights for the identification and exploration of genes and gene-by-gene interactions associated with flowering-related traits in Arabidopsis, that may even provide valuable reference and guidance for the research of epistasis in other species.</p

Image_1_Identification of QTN-by-environment interactions for yield related traits in maize under multiple abiotic stresses.tif

IntroductionQuantitative trait nucleotide (QTN)-by-environment interactions (QEIs) play an increasingly essential role in the genetic dissection of complex traits in crops as global climate change accelerates. The abiotic stresses, such as drought and heat, are the major constraints on maize yields. Multi-environment joint analysis can improve statistical power in QTN and QEI detection, and further help us to understand the genetic basis and provide implications for maize improvement.MethodsIn this study, 3VmrMLM was applied to identify QTNs and QEIs for three yield-related traits (grain yield, anthesis date, and anthesis-silking interval) of 300 tropical and subtropical maize inbred lines with 332,641 SNPs under well-watered and drought and heat stresses.ResultsAmong the total 321 genes around 76 QTNs and 73 QEIs identified in this study, 34 known genes were reported in previous maize studies to be truly associated with these traits, such as ereb53 (GRMZM2G141638) and thx12 (GRMZM2G016649) associated with drought stress tolerance, and hsftf27 (GRMZM2G025685) and myb60 (GRMZM2G312419) associated with heat stress. In addition, among 127 homologs in Arabidopsis out of 287 unreported genes, 46 and 47 were found to be significantly and differentially expressed under drought vs well-watered treatments, and high vs. normal temperature treatments, respectively. Using functional enrichment analysis, 37 of these differentially expressed genes were involved in various biological processes. Tissue-specific expression and haplotype difference analysis further revealed 24 candidate genes with significantly phenotypic differences across gene haplotypes under different environments, of which the candidate genes GRMZM2G064159, GRMZM2G146192, and GRMZM2G114789 around QEIs may have gene-by-environment interactions for maize yield.DiscussionAll these findings may provide new insights for breeding in maize for yield-related traits adapted to abiotic stresses.</p

Table_1_Identification of QTN-by-environment interactions for yield related traits in maize under multiple abiotic stresses.xlsx

IntroductionQuantitative trait nucleotide (QTN)-by-environment interactions (QEIs) play an increasingly essential role in the genetic dissection of complex traits in crops as global climate change accelerates. The abiotic stresses, such as drought and heat, are the major constraints on maize yields. Multi-environment joint analysis can improve statistical power in QTN and QEI detection, and further help us to understand the genetic basis and provide implications for maize improvement.MethodsIn this study, 3VmrMLM was applied to identify QTNs and QEIs for three yield-related traits (grain yield, anthesis date, and anthesis-silking interval) of 300 tropical and subtropical maize inbred lines with 332,641 SNPs under well-watered and drought and heat stresses.ResultsAmong the total 321 genes around 76 QTNs and 73 QEIs identified in this study, 34 known genes were reported in previous maize studies to be truly associated with these traits, such as ereb53 (GRMZM2G141638) and thx12 (GRMZM2G016649) associated with drought stress tolerance, and hsftf27 (GRMZM2G025685) and myb60 (GRMZM2G312419) associated with heat stress. In addition, among 127 homologs in Arabidopsis out of 287 unreported genes, 46 and 47 were found to be significantly and differentially expressed under drought vs well-watered treatments, and high vs. normal temperature treatments, respectively. Using functional enrichment analysis, 37 of these differentially expressed genes were involved in various biological processes. Tissue-specific expression and haplotype difference analysis further revealed 24 candidate genes with significantly phenotypic differences across gene haplotypes under different environments, of which the candidate genes GRMZM2G064159, GRMZM2G146192, and GRMZM2G114789 around QEIs may have gene-by-environment interactions for maize yield.DiscussionAll these findings may provide new insights for breeding in maize for yield-related traits adapted to abiotic stresses.</p

Image_6_Identification of QTN-by-environment interactions for yield related traits in maize under multiple abiotic stresses.tif

IntroductionQuantitative trait nucleotide (QTN)-by-environment interactions (QEIs) play an increasingly essential role in the genetic dissection of complex traits in crops as global climate change accelerates. The abiotic stresses, such as drought and heat, are the major constraints on maize yields. Multi-environment joint analysis can improve statistical power in QTN and QEI detection, and further help us to understand the genetic basis and provide implications for maize improvement.MethodsIn this study, 3VmrMLM was applied to identify QTNs and QEIs for three yield-related traits (grain yield, anthesis date, and anthesis-silking interval) of 300 tropical and subtropical maize inbred lines with 332,641 SNPs under well-watered and drought and heat stresses.ResultsAmong the total 321 genes around 76 QTNs and 73 QEIs identified in this study, 34 known genes were reported in previous maize studies to be truly associated with these traits, such as ereb53 (GRMZM2G141638) and thx12 (GRMZM2G016649) associated with drought stress tolerance, and hsftf27 (GRMZM2G025685) and myb60 (GRMZM2G312419) associated with heat stress. In addition, among 127 homologs in Arabidopsis out of 287 unreported genes, 46 and 47 were found to be significantly and differentially expressed under drought vs well-watered treatments, and high vs. normal temperature treatments, respectively. Using functional enrichment analysis, 37 of these differentially expressed genes were involved in various biological processes. Tissue-specific expression and haplotype difference analysis further revealed 24 candidate genes with significantly phenotypic differences across gene haplotypes under different environments, of which the candidate genes GRMZM2G064159, GRMZM2G146192, and GRMZM2G114789 around QEIs may have gene-by-environment interactions for maize yield.DiscussionAll these findings may provide new insights for breeding in maize for yield-related traits adapted to abiotic stresses.</p

Image_2_Identification of QTN-by-environment interactions for yield related traits in maize under multiple abiotic stresses.tif

IntroductionQuantitative trait nucleotide (QTN)-by-environment interactions (QEIs) play an increasingly essential role in the genetic dissection of complex traits in crops as global climate change accelerates. The abiotic stresses, such as drought and heat, are the major constraints on maize yields. Multi-environment joint analysis can improve statistical power in QTN and QEI detection, and further help us to understand the genetic basis and provide implications for maize improvement.MethodsIn this study, 3VmrMLM was applied to identify QTNs and QEIs for three yield-related traits (grain yield, anthesis date, and anthesis-silking interval) of 300 tropical and subtropical maize inbred lines with 332,641 SNPs under well-watered and drought and heat stresses.ResultsAmong the total 321 genes around 76 QTNs and 73 QEIs identified in this study, 34 known genes were reported in previous maize studies to be truly associated with these traits, such as ereb53 (GRMZM2G141638) and thx12 (GRMZM2G016649) associated with drought stress tolerance, and hsftf27 (GRMZM2G025685) and myb60 (GRMZM2G312419) associated with heat stress. In addition, among 127 homologs in Arabidopsis out of 287 unreported genes, 46 and 47 were found to be significantly and differentially expressed under drought vs well-watered treatments, and high vs. normal temperature treatments, respectively. Using functional enrichment analysis, 37 of these differentially expressed genes were involved in various biological processes. Tissue-specific expression and haplotype difference analysis further revealed 24 candidate genes with significantly phenotypic differences across gene haplotypes under different environments, of which the candidate genes GRMZM2G064159, GRMZM2G146192, and GRMZM2G114789 around QEIs may have gene-by-environment interactions for maize yield.DiscussionAll these findings may provide new insights for breeding in maize for yield-related traits adapted to abiotic stresses.</p

Image_3_Identification of QTN-by-environment interactions for yield related traits in maize under multiple abiotic stresses.tif

IntroductionQuantitative trait nucleotide (QTN)-by-environment interactions (QEIs) play an increasingly essential role in the genetic dissection of complex traits in crops as global climate change accelerates. The abiotic stresses, such as drought and heat, are the major constraints on maize yields. Multi-environment joint analysis can improve statistical power in QTN and QEI detection, and further help us to understand the genetic basis and provide implications for maize improvement.MethodsIn this study, 3VmrMLM was applied to identify QTNs and QEIs for three yield-related traits (grain yield, anthesis date, and anthesis-silking interval) of 300 tropical and subtropical maize inbred lines with 332,641 SNPs under well-watered and drought and heat stresses.ResultsAmong the total 321 genes around 76 QTNs and 73 QEIs identified in this study, 34 known genes were reported in previous maize studies to be truly associated with these traits, such as ereb53 (GRMZM2G141638) and thx12 (GRMZM2G016649) associated with drought stress tolerance, and hsftf27 (GRMZM2G025685) and myb60 (GRMZM2G312419) associated with heat stress. In addition, among 127 homologs in Arabidopsis out of 287 unreported genes, 46 and 47 were found to be significantly and differentially expressed under drought vs well-watered treatments, and high vs. normal temperature treatments, respectively. Using functional enrichment analysis, 37 of these differentially expressed genes were involved in various biological processes. Tissue-specific expression and haplotype difference analysis further revealed 24 candidate genes with significantly phenotypic differences across gene haplotypes under different environments, of which the candidate genes GRMZM2G064159, GRMZM2G146192, and GRMZM2G114789 around QEIs may have gene-by-environment interactions for maize yield.DiscussionAll these findings may provide new insights for breeding in maize for yield-related traits adapted to abiotic stresses.</p

Image_5_Identification of QTN-by-environment interactions for yield related traits in maize under multiple abiotic stresses.tif

IntroductionQuantitative trait nucleotide (QTN)-by-environment interactions (QEIs) play an increasingly essential role in the genetic dissection of complex traits in crops as global climate change accelerates. The abiotic stresses, such as drought and heat, are the major constraints on maize yields. Multi-environment joint analysis can improve statistical power in QTN and QEI detection, and further help us to understand the genetic basis and provide implications for maize improvement.MethodsIn this study, 3VmrMLM was applied to identify QTNs and QEIs for three yield-related traits (grain yield, anthesis date, and anthesis-silking interval) of 300 tropical and subtropical maize inbred lines with 332,641 SNPs under well-watered and drought and heat stresses.ResultsAmong the total 321 genes around 76 QTNs and 73 QEIs identified in this study, 34 known genes were reported in previous maize studies to be truly associated with these traits, such as ereb53 (GRMZM2G141638) and thx12 (GRMZM2G016649) associated with drought stress tolerance, and hsftf27 (GRMZM2G025685) and myb60 (GRMZM2G312419) associated with heat stress. In addition, among 127 homologs in Arabidopsis out of 287 unreported genes, 46 and 47 were found to be significantly and differentially expressed under drought vs well-watered treatments, and high vs. normal temperature treatments, respectively. Using functional enrichment analysis, 37 of these differentially expressed genes were involved in various biological processes. Tissue-specific expression and haplotype difference analysis further revealed 24 candidate genes with significantly phenotypic differences across gene haplotypes under different environments, of which the candidate genes GRMZM2G064159, GRMZM2G146192, and GRMZM2G114789 around QEIs may have gene-by-environment interactions for maize yield.DiscussionAll these findings may provide new insights for breeding in maize for yield-related traits adapted to abiotic stresses.</p