Time-Related QTL Mapping with a Next-Generation Platform for Cotton

The development of superior heat tolerant and water-use efficient cotton cultivars has been slowed by the polygenic inheritance, low heritability, and time-dependence of adaptive traits in stress environments. Moreover, there is limited knowledge of the key genes that underpin physiological and biochemical traits that relate to improved productivity under high temperatures and water deficit. To that end, we developed genotyping-by-sequencing (GBS) and field-based, high-throughput phenotyping (HTP) approaches for dissecting the genetic architecture of adaptive traits that are potentially important for increased cotton fiber yield and quality in the southwestern United States. We tested these approaches on a cotton recombinant inbred line (RIL) population (TM-1×NM24016) grown under replicated well-watered and water-deficit treatments in Arizona. We present results from a QTL analysis of phenotypic data that were predominantly collected by tractor-mounted sensors at three time points over several weeks and suggest how powerful modern plant breeding tools can be leveraged in the genetic improvement of cotton.