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QTL mapping of yield component traits on bin map generated from resequencing a RIL population of foxtail millet (Setaria italica)


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- 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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