A high-density genetic map and QTL analysis of agronomic traits in foxtail millet [Setaria italica (L.) P. Beauv.] using RAD-seq

Abstract

Foxtail millet (Setaria italica), a very important grain crop in China, has become a new model plant for cereal crops and biofuel grasses. Although its reference genome sequence was released recently, quantitative trait loci (QTLs) controlling complex agronomic traits remains limited. The development of massively parallel genotyping methods and next-generation sequencing technologies provides an excellent opportunity for developing single-nucleotide polymorphisms (SNPs) for linkage map construction and QTL analysis of complex quantitative traits. In this study, a high-throughput and cost-effective RAD-seq approach was employed to generate a high-density genetic map for foxtail millet. A total of 2,668,587 SNP loci were detected according to the reference genome sequence; meanwhile, 9,968 SNP markers were used to genotype 124 F2 progenies derived from the cross between Hongmiaozhangu and Changnong35; a high-density genetic map spanning 1648.8 cM, with an average distance of 0.17 cM between adjacent markers was constructed; 11 major QTLs for eight agronomic traits were identified; five co-dominant DNA markers were developed. These findings will be of value for the identification of candidate genes and marker-assisted selection in foxtail millet.

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

“…Therefore, a construction of a high-density linkage map could improve the accuracy of QTL mapping [27]. In recent years, with the development of sequencing technology and genome assemblies, SNP [12,26,27], SSR [16,29,30] [16] found similar results in the linkage map with 1013 SSRs markers constructed from F 2 population. However, the new map was constructed via RIL population with phenotypic stability, more markers (3413 bin markers), higher density (8.81 bin markers/Mb) and covered the whole genome.…”

“…A total of 69 QTLs for 21 agronomic traits were identified. Wang et al [26] mapped 11 major QTLs of eight agronomic traits using RAD-seq to detect SNP markers and screen F 2 progenies derived from the cross between Hongmiaozhangu and Changnong35. In another study, Wang et al [27] identified 57 QTLs related to 11 agronomic traits in an F 2 mapping population from a cross between Aininghuang and Jingu21.…”

Genotyping by RAD Sequencing Analysis Assessed the Genetic Distinctiveness of Experimental Lines and Narrowed down the Genomic Region Responsible for Leaf Shape in Endive (Cichorium endivia L.)

“…Since low heterozygosity values guarantee progenies with the desired genetic stability and, consequently, phenotypic uniformity [8], individuals with high homozygosity could be selected to produce precommercial varieties characterized by genetic stability and thus uniformity. The RAD-seq technique also represents an interesting tool for improving the discovery of molecular markers linked to specific traits of interest [47][48][49]. For this reason, the 4621 SNP markers were annotated through a BLASTn approach against the coding regions of Lactuca sativa, a key species in the Asteraceae family.…”

Artificially designed hybrids facilitate efficient generation of high-resolution linkage maps

“…In our study, we used 7.00 M reads per individual (Table 1 ) and utilized 587,319 (442,723 and 144,596) SNP markers for approximately 800 (400 + 400) Mb of genome sequence. The use of RAD-seq to construct linkage maps has previously required 7.28 M reads per individual (10,023 markers/1.8 Gb) in oil palm 17 , 6.70 M reads (9,968 SNP markers/423 Mb) in foxtail millet 18 , and 311.97 M reads (47,472 markers/1.1 Gb) in soybean 19 . This comparison suggests a benefit for the construction of a linkage map that has a higher precision and a lower comparative cost than RAD-seq.…”