The complexity of gene function determination remains one of the major challenges facing plant biologists today, despite the development and application of new technologies, including high throughput genotyping and next-generation sequencing. The sorghum genomics team, consisting of researchers at UQ and DAF, are using an integrated set of technologies and germplasm collections for:

  • gene mapping and gene function determination
  • marker assisted selection
  • genomic selection

Chromosome-graphData-sets generated

  • GBS whole genome SNP profiles across >6K sorghum genotypes, including breeding and mapping populations, diverse lines and ancestral genotypes, with a total of >500M data-points generated to date.

Applications:

  • high resolution genetic mapping for quantitative traits and identification of beneficial alleles
  • development of customised SNP markers for target traits for Marker Assisted Selection (e.g. KASP markers),
  • development of whole-genome prediction models for applying genomic selection for target traits
  • Whole genome sequencing data for 44 diverse sorghum lines, with excellent representation of the genetic diversity of sorghum, and with customised tools to manage, visual and analyse over 10 million sequence polymorphisms

Applications:

  • Causative SNP discovery in candidate genes facilitated by high coverage levels
  • Identification of signatures of selection and patterns of linkage disequilibrium genome-wide
  • Comparative genomics capacity to extend learnings to and from other cereal crops

Chromosome-graph2Germplasm resources developed

  • A Nested Association Mapping (NAM) resource consisting of over 5000 individuals from 100 sub-populations, associated with phenotypic data across multiple environments.
  • A sorghum association mapping panel consisting of over 1000 individuals from diverse geographic and racial origins
  • Genotyped lines from the major sorghum pre-breeding program in Australia
  • Seven genotyped conventional bi-parental recombinant inbred line (RIL) mapping populations with phenotypic data

Together these represent unique resources for enhancing gene function determination for both theoretical and applied applications, including plant improvement. Additionally, due to the critical role of the environment for gene expression, we are applying simulation modelling in combination with environment characterisation to enhance our understanding of genotype x environment interactions.

The logistical capacity of crop breeding programs to dissect complex traits and study gene expression across multiple environments is frequently unparalleled and is often not available to geneticists; by making use of information that is generated through the breeding program, we are to bridge the divide between theoretical and applied applications.

The integrated application of new technologies and resources within the sorghum breeding program is being used in a range of research projects investigating a range of crop trait characteristics including drought tolerance, grain size, photosynthesis and grain yield.