Using genetic mapping and genomics approaches in understanding and improving drought tolerance in pearl millet.

Drought at the reproductive stage is a major constraint to pearl millet [Pennisetum glaucum (L.) R. Br.] productivity. Quantitative trait locus (QTL) mapping provides a means to dissect complex traits, such as drought tolerance, into their components, each of which is controlled by QTLs. Molecular marker-supported genotypic information at the identified QTLs then enables quick and accurate accumulation of desirable alleles in plant breeding programmes. Recent genetic mapping research in pearl millet has mapped several QTLs for grain yield and its components under terminal drought stress conditions. Most importantly, a major QTL associated with grain yield and for the drought tolerance of grain yield in drought stress environments has been identified on linkage group 2 (LG 2) which accounts for up to 32% of the phenotypic variation of grain yield in mapping population testcrosses. The effect of this QTL has been validated in two independent marker-assisted backcrossing programmes, where 30% improvement in grain yield general combining ability (GCA) expected of this QTL under terminal drought stress conditions was recovered in the QTL introgression lines. To transfer effectively favourable alleles of this QTL into pearl millet varieties that otherwise are high yielding and adapted to specific agricultural zones, efforts are currently underway to develop closely spaced gene-based markers within this drought tolerance (DT)-QTL. In this review, an overview is provided of information on the genetic maps developed in pearl millet for mapping drought tolerance traits and their applications in identifying and characterizing DT-QTLs. Marker-assisted transfer of desirable QTL alleles to elite parent backgrounds, and results from introgression line validation in multiple terminal drought stress environments are discussed. Current efforts undertaken towards delimiting the interval of a major DT-QTL mapping to LG 2, and towards identifying candidate genes and physiologies underlying this QTL are presented. Highly specialized genetic stocks [QTL-near-isogenic lines (NILs), a high-resolution cross, and a germplasm population] and genomic resources (gene sequences, gene-based markers, and comparative genomics information) specifically developed for these purposes are discussed.