- QTL mapping of yield component traits on bin map generated from resequencing a RIL population of foxtail millet ( Setaria italica. - Background: Foxtail millet (Setaria italica) has been developed into a model genetical system for deciphering architectural evolution, C 4 photosynthesis, nutritional properties, abiotic tolerance and bioenergy in cereal grasses because of its advantageous characters with the small genome size, self-fertilization, short growing cycle, small growth stature, efficient genetic transformation and abundant diverse germplasm resources. - Therefore, excavating QTLs of yield component traits, which are closely related to aspects mentioned above, will further facilitate genetic research in foxtail millet and close cereal species.. - Conclusions: A high-density genetic map with 3413 bin markers was constructed and three stable QTLs and 9 QTL clusters for yield component traits were identified. - The results laid a powerful foundation for fine mapping, identifying candidate genes, elaborating molecular mechanisms and application in foxtail millet breeding programs by marker- assisted selection.. - Keywords: Foxtail millet (Setaria italica), Yield component traits, SNP, Bin map, QTL. - Foxtail millet (S. - Straw weight per plant (SWP), panicle weight per plant (PWP), grain weight per plant (GWP) and 1000-grain weight (TGW) are the most important traits to foxtail millet as a food and forage crop or model genetic system and closely related with agricultural. - [16] scanned the whole genome sequence of foxtail millet and developed and 10,598 simple se- quence repeat (SSRs) makers, respectively, that were used to construct genetic or physical map for foxtail millet. - [22] identified eight SSR markers on different chromosomes showing significant associations with nine agronomic traits in a natural popula- tion consisting of 184 foxtail millet accessions from diverse geographical locations.. - With the availability of high-throughput genotyping technology, the rapid investigation of genomic variation in both natural populations and segregating populations of foxtail millet is now feasible by genotyping using SNPs. - [23] sequenced 916 diverse foxtail millet varieties and identified 2,584,083 SNPs and used 845,787 common SNPs to construct a haplotype map of the fox- tail millet genome. - Wang et al. - The results will be valuable for further research on fine mapping, identifying candidate genes, elaborating molecular mechanisms and marker-assisted selection (MAS) in foxtail millet.. - 0.01) for all measured traits (Table 3), which suggested that environmental factors had great effect on foxtail millet yield component traits.. - These bins were regarded as genetic bin makers for the construction of the linkage map that spanned 1222.26 cM of the foxtail millet genome with 0.36 cM/bin. - 0.05) (Additional file 8: Figure S2, Additional file 5: Table S5) accounting for 89.10% of the total. - QTL mapping of yield component traits. - 2018-GG . - 2018-HN . - Twelve QTLs for grain weight per plant were mapped on seven chromosomes, explaining 5.5–12.2% of the phenotypic variance (Table 4). - Four QTLs for 1000-grain weight were identified on Chr4, Chr6 and Chr8, which explained 6.0–6.9% of the phenotypic variance (Table 4). - Wang et al.. - Thus, it can be used in better dissecting the genetic mechanism of di- verse traits in foxtail millet.. - 2 Recombination bin map of 164 foxtail millet RILs. - Table 4 QTL identified for four yield component traits under multi-environments based on bin markers genetic map. - SWP qSWP1.1 2017-WW 1 Bin . - qSWP1.2 2017-WW 1 Bin . - qSWP2.1 2017-DH 2 Bin . - qSWP3.1 2018-GG 3 Bin . - qSWP3.2 2017-DH 3 Bin . - qSWP6.1 2018-GG 6 Bin . - qSWP6.2 2017-HN 6 Bin . - qSWP7.1 2017-HN 7 Bin . - qSWP7.2 2017-WW 7 Bin . - qSWP7.3 2017-HN 7 Bin . - qSWP7.4 2018-GG 7 Bin . - qSWP7.5 2017-HN 7 Bin . - qSWP8.1 2018-GG 8 Bin . - qSWP8.2 2017-WW 8 Bin . - qSWP8.3 2018-GG 8 Bin . - qSWP9.1 2017-HN 9 Bin . - qSWP9.2 2017-WW 9 Bin . - PWP qPWP2.1 2018-HN 2 Bin . - qPWP3.1 2018-GG 3 Bin . - qPWP3.2 2018-GG 3 Bin . - qPWP3.3 2018-GG 3 Bin . - qPWP5.1 2018-HN 5 Bin . - qPWP6.1 2018-GG 6 Bin . - qPWP6.2 2017-DH 6 Bin . - qPWP6.3 2017-HN 6 Bin . - qPWP7.1 2018-GG 7 Bin . - qPWP7.2 2018-HN 7 Bin . - qPWP8.1 2018-HN 8 Bin . - qPWP9.1 2017-WW 9 Bin . - qPWP9.2 2018-HN 9 Bin . - qPWP9.3 2018-HN 9 Bin . - QTL regions for yield component traits. - Straw weight per plant, panicle weight per plant, grain weight per plant and 1000 grain weight are the main yield component traits of foxtail millet. - This sug- gests that qGWP3.3 might be new and major loci that was associated with grain weight of foxtail millet. - Table 4 QTL identified for four yield component traits under multi-environments based on bin markers genetic map (Continued). - GWP qGWP2.1 2017-HN 2 Bin . - qGWP2.2 2018-HN 2 Bin . - qGWP3.1 2018-GG 3 Bin . - qGWP3.2 2018-GG 3 Bin . - qGWP3.3 2018-GG 3 Bin . - qGWP6.1 2017-HN 6 Bin . - qGWP7.1 2018-HN 7 Bin . - qGWP7.2 2018-GG 7 Bin . - qGWP8.1 2018-HN 8 Bin . - qGWP9.1 2017-WW 9 Bin . - qGWP9.2 2017-HN 9 Bin . - qGWP9.3 2018-HN 9 Bin . - TGW qTGW4.1 2017-WW 4 Bin . - qTGW6.1 2017-HN 6 Bin . - qTGW8.1 2017-WW 8 Bin . - qTGW8.2 2017-WW 8 Bin . - But the functions of these genes were still unknown in foxtail millet. - Taken together, these stable and QTL clusters laid a foundation for fine mapping, identifying candidate genes, elaborating molecular mechanisms and application in foxtail millet molecular breeding.. - Three stable QTLs and nine QTL clusters on the chromosome and 9 were identified, which could be applied preferentially for fine mapping, candidate genes identification and application in foxtail millet breeding programs by marker-assisted selection.. - 3 QTL controlling yield component traits on nine chromosomes. - Bin markers and genotypes of 164 RILs.. - A high-density linkage map based on resequencing a RIL population in foxtail millet.. - Genome-Wide Association study of Major Agronomic traits in Foxtail Millet (Setaria italica L.) Using ddRAD sequencing. - Population structure and linkage disequilibrium of ICRISAT foxtail millet (Setaria italica (L.) P. - Foxtail millet: a model crop for genetic and genomic studies in bioenergy grasses. - reference genome sequence of the model plant Setaria. - Genome sequence of foxtail millet (Setaria italica) provides insights into grass evolution and biofuel potential. - Genome-wide development and use of microsatellite markers for large- scale genotyping applications in foxtail millet [Setaria italica (L. - Development of highly polymorphic simple sequence repeat markers using genome-wide microsatellite variant analysis in foxtail millet [Setaria italica (L.) P. - A high density genetic map and QTL for agronomic and yield traits in Foxtail millet [Setaria italica (L.) P. - Genetic control of branching in foxtail millet. - Construction of a foxtail millet linkage map and mapping of spikelet-tipped bristles 1 (stb1) by using transposon display markers and simple sequence repeat markers with genome sequence information. - Population structure and association mapping of yield contributing agronomic traits in foxtail millet. - A haplotype map of genomic variations and genome-wide association studies of agronomic traits in foxtail millet (Setaria italica). - Updated foxtail millet genome assembly and gene mapping of nine key agronomic traits by resequencing a RIL population. - A high-density genetic map and QTL analysis of agronomic traits in foxtail millet [Setaria italica (L.) P. - QTL mapping for 11 agronomic traits based on a genome-wide Bin-map in a large F 2 population of foxtail millet (Setaria italica (L.) P. - Development and genetic mapping of SSR markers in foxtail millet [Setaria italica (L.) P.. - Genetic analysis and preliminary mapping of a highly male-sterile gene in foxtail millet (Setaria italica L
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