Search for: All records

As sequencing and genotyping technologies evolve, crop genetics researchers accumulate increasing numbers of genomic data sets from various genotyping platforms on different germplasm panels. Imputation is an effective approach to increase marker density of existing data sets toward the goal of integrating resources for downstream applications. While a number of imputation software packages are available, the limitations to utilization for the rice community include high computational demand and lack of a reference panel. To address these challenges, we develop the Rice Imputation Server, a publicly available web application leveraging genetic information from a globally diverse rice reference panel assembled here. This resource allows researchers to benefit from increased marker density without needing to perform imputation on their own machines. We demonstrate improvements that imputed data provide to rice genome-wide association (GWA) results of grain amylose content and show that the major functional nucleotide polymorphism is tagged only in the imputed data set.

HighCO₂and high temperature have an antagonistic interaction effect on rice yield potential and present a unique challenge to adapting rice to projected future climates. Understanding how the differences in response to these two abiotic variables are partitioned across rice germplasm accessions may be key to identifying potentially useful sources of resilient alleles for adapting rice to climate change. In this study, we evaluated eleven globally diverse rice accessions under controlled conditions at two carbon dioxide concentrations (400 and 600 ppm) and four temperature environments (29 °C day/21 °C night; 29 °C day/21 °C night with additional heat stress at anthesis; 34 °C day/26 °C night; and 34 °C day/26 °C night with additional heat stress at anthesis) for a suite of traits including five yield components, five growth characteristics, one phenological trait, and four photosynthesis‐related measurements. Multivariate analyses of mean trait data from these eight treatments divide our rice panel into two primary groups consistent with the genetic classification ofINDICA/INDICA‐like andJAPONICApopulations. Overall, we find that the productivity of plants grown under elevated [CO₂] was more sensitive (negative response) to high temperature stress compared with that of plants grown under ambient [CO₂] across this diversity panel. We report differential response toCO₂× temperature interaction forINDICA/INDICA‐like andJAPONICArice accessions and find preliminary evidence for the beneficial introduction of exotic alleles into cultivated rice genomic background. Overall, these results support the idea of using wild or currently unadapted gene pools in rice to enhance breeding efforts to secure future climate change adaptation.