Genome-wide SNPs and candidate genes underlying the genetic variations for protein and amino acids in pearl millet (Pennisetum glaucum) germplasm.

MAIN CONCLUSION: A total of 544 significant marker-trait associations and 286 candidate genes associated with total protein and 18 amino acids were identified. Thirty-three candidate genes were found near the strong marker trait associations (- log10P ≥ 5.5). Pearl millet (Pennisetum glaucum) is largely grown as a subsistence crop in South Asia and sub-Saharan Africa. It serves as a major source of daily protein intake in these regions. Despite its importance, no systematic effort has been made to study the genetic variations of protein and amino acid content in pearl millet germplasm. The present study was undertaken to dissect the global genetic variations of total protein and 18 essential and non-essential amino acids in pearl millet, using a set of 435 K Single Nucleotide Polymorphisms (SNPs) and 161 genotypes of the Pearl Millet Inbred Germplasm Association Panel (PMiGAP). A total of 544 significant marker-trait associations (at P < 0.0001; - log10P ≥ 4) were detected and 23 strong marker-trait associations were identified using Bonferroni's correction method. Forty-eight pleiotropic loci were found in the genome for the studied traits. In total, 286 candidate genes associated with total protein and 18 amino acids were identified. Thirty-three candidate genes were found near strongly associated SNPs. The associated markers and the candidate genes provide an insight into the genetic architecture of the traits studied and are going to be useful in breeding improved pearl millet varieties in the future. Availabilities of improved pearl millet varieties possessing higher protein and amino acid compositions will help combat the rising malnutrition problem via diet.

Genomic selection strategies to increase genetic gain in tea breeding programs.

Tea [Camellia sinensis (L.) O. Kuntze] is mainly grown in low- to middle-income countries (LMIC) and is a global commodity. Breeding programs in these countries face the challenge of increasing genetic gain because the accuracy of selecting superior genotypes is low and resources are limited. Phenotypic selection (PS) is traditionally the primary method of developing improved tea varieties and can take over 16 yr. Genomic selection (GS) can be used to improve the efficiency of tea breeding by increasing selection accuracy and shortening the generation interval and breeding cycle. Our main objective was to investigate the potential of implementing GS in tea-breeding programs to speed up genetic progress despite the low cost of PS in LMIC. We used stochastic simulations to compare three GS-breeding programs with a Pedigree and PS program. The PS program mimicked a practical commercial tea-breeding program over a 40-yr breeding period. All the GS programs achieved at least 1.65 times higher genetic gains than the PS program and 1.4 times compared with Seed-Ped program. Seed-GSc was the most cost-effective strategy of implementing GS in tea-breeding programs. It introduces GS at the seedlings stage to increase selection accuracy early in the program and reduced the generation interval to 2 yr. The Seed-Ped program outperformed PS by 1.2 times and could be implemented where it is not possible to use GS. Our results indicate that GS could be used to improve genetic gain per unit time and cost even in cost-constrained tea-breeding programs.