Pearl millet genome sequence provides a resource to improve agronomic traits in arid environments

Pearl millet [Pennisetum glaucum (L.) R. Br., syn. Cenchrus americanus (L.) Morrone], is a staple food for over 90 million poor farmers in arid and semi-arid regions of sub-Saharan Africa and South Asia. We report the ~1.79 Gb genome sequence of reference genotype Tift 23D2B1-P1-P5, which contains an estimated 38,579 genes. Resequencing analysis of 994 (963 inbreds of the highly cross-pollinated cultigen, and 31 wild accessions) provides insights into population structure, genetic diversity, evolution and domestication history. In addition we demonstrated the use of re-sequence data for establishing marker trait associations, genomic selection and prediction of hybrid performance and defining heterotic pools. The genome wide variations and abiotic stress proteome data are useful resources for pearl millet improvement through deploying modern breeding tools for accelerating genetic gains in pearl millet.publishersversionPeer reviewe

Phenotypic data from inbred parents can improve genomic prediction in Pearl Millet hybrids

Pearl millet is a non-model grain and fodder crop adapted to extremely hot and dry environments globally. In India, a great deal of public and private sectors’ investment has focused on developing pearl millet single cross hybrids based on the cytoplasmic-genetic male sterility (CMS) system, while in Africa most pearl millet production relies on open pollinated varieties. Pearl millet lines were phenotyped for both the inbred parents and hybrids stage. Many breeding efforts focus on phenotypic selection of inbred parents to generate improved parental lines and hybrids. This study evaluated two genotyping techniques and four genomic selection schemes in pearl millet. Despite the fact that 6× more sequencing data were generated per sample for RAD-seq than for tGBS, tGBS yielded more than 2× as many informative SNPs (defined as those having MAF > 0.05) than RAD-seq. A genomic prediction scheme utilizing only data from hybrids generated prediction accuracies (median) ranging from 0.73-0.74 (1000-grain weight), 0.87-0.89 (days to flowering time), 0.48-0.51 (grain yield) and 0.72-0.73 (plant height). For traits with little to no heterosis, hybrid only and hybrid/inbred prediction schemes performed almost equivalently. For traits with significant mid-parent heterosis, the direct inclusion of phenotypic data from inbred lines significantly (P < 0.05) reduced prediction accuracy when all lines were analyzed together. However, when inbreds and hybrid trait values were both scored relative to the mean trait values for the respective populations, the inclusion of inbred phenotypic datasets moderately improved genomic predictions of the hybrid genomic estimated breeding values. Here we show that modern approaches to genotyping by sequencing can enable genomic selection in pearl millet. While historical pearl millet breeding records include a wealth of phenotypic data from inbred lines, we demonstrate that the naive incorporation of this data into a hybrid breeding program can reduce prediction accuracy, while controlling for the effects of heterosis per se allowed inbred genotype and trait data to improve the accuracy of genomic estimated breeding values for pearl millet hybrids

Phenotypic data from inbred parents can improve genomic prediction in Pearl Millet hybrids

Pearl millet is a non-model grain and fodder crop adapted to extremely hot and dry environments globally. In India, a great deal of public and private sectors’ investment has focused on developing pearl millet single cross hybrids based on the cytoplasmic-genetic male sterility (CMS) system, while in Africa most pearl millet production relies on open pollinated varieties. Pearl millet lines were phenotyped for both the inbred parents and hybrids stage. Many breeding efforts focus on phenotypic selection of inbred parents to generate improved parental lines and hybrids. This study evaluated two genotyping techniques and four genomic selection schemes in pearl millet. Despite the fact that 6× more sequencing data were generated per sample for RAD-seq than for tGBS, tGBS yielded more than 2× as many informative SNPs (defined as those having MAF > 0.05) than RAD-seq. A genomic prediction scheme utilizing only data from hybrids generated prediction accuracies (median) ranging from 0.73-0.74 (1000-grain weight), 0.87-0.89 (days to flowering time), 0.48-0.51 (grain yield) and 0.72-0.73 (plant height). For traits with little to no heterosis, hybrid only and hybrid/inbred prediction schemes performed almost equivalently. For traits with significant mid-parent heterosis, the direct inclusion of phenotypic data from inbred lines significantly (P < 0.05) reduced prediction accuracy when all lines were analyzed together. However, when inbreds and hybrid trait values were both scored relative to the mean trait values for the respective populations, the inclusion of inbred phenotypic datasets moderately improved genomic predictions of the hybrid genomic estimated breeding values. Here we show that modern approaches to genotyping by sequencing can enable genomic selection in pearl millet. While historical pearl millet breeding records include a wealth of phenotypic data from inbred lines, we demonstrate that the naive incorporation of this data into a hybrid breeding program can reduce prediction accuracy, while controlling for the effects of heterosis per se allowed inbred genotype and trait data to improve the accuracy of genomic estimated breeding values for pearl millet hybrids

Identification of heterotic groups in South-Asian-bred hybrid parents of pearl millet

Five hundred and eighty hybrid parents, 320 R- and 260 B-lines, derived from 6 pearl millet breeding programs in India, genotyped following RAD-GBS (about 0.9 million SNPs) clustered into 12 R- and 7 B-line groups. With few exceptions, hybrid parents of all the breeding programs were found distributed across all the marker-based groups suggesting good diversity in these programs. Three hundred and twenty hybrids generated using 37 (22 R and 15 B) representative parents, evaluated for grain yield at four locations in India, showed significant differences in yield, heterosis, and combining ability. Across all the hybrids, mean mid- and better-parent heterosis for grain yield was 84.0% and 60.5%, respectively. Groups G12 B × G12 R and G10 B × G12 R had highest heterosis of about 10% over best check hybrid Pioneer 86M86. The parents involved in heterotic hybrids were mainly from the groups G4R, G10B, G12B, G12R, and G13B. Based on the heterotic performance and combining ability of groups, 2 B-line (HGB-1 and HGB-2) and 2 R-line (HGR-1 and HGR-2) heterotic groups were identified. Hybrids from HGB-1 × HGR-1 and HGB-2 × HGR-1 showed grain yield heterosis of 10.6 and 9.3%, respectively, over best hybrid check. Results indicated that parental groups can be formed first by molecular markers, which may not predict the best hybrid combination, but it can reveal a practical value of assigning existing and new hybrid pearl millet parental lines into heterotic groups to develop high-yielding hybrids from the different heterotic groups

Erratum: Pearl millet genome sequence provides a resource to improve agronomic traits in arid environments

In the version of this article initially published, in the HTML, the wrong Creative Commons Attribution license (cc-by-nc rather than cc-by) was inserted. The error has been corrected in the HTML version of the articl