Advances in Applied Bioinformatics in Crops

Collections of plant genetic resources stored in genebanks are an important source of genetic diversity for improvement in plant breeding programs and for conservation of natural variation. The establishment of reduced representative collections from a large set of genotypes is a valuable tool that provides cost-effective access to the diversity present in the whole set. Software like Core Hunter 3 is available to generate high quality core sets. In addition, general clustering approaches, e.g., k-medoids, are available to subdivide a large data set into small groups with maximum genetic diversity between groups.

Illumina genotyping platforms are a very efficient tool for the assessment of genetic diversity of plant genetic resources. The accumulation of genotyping data over time using commercial genotyping platforms raises the question of how such huge amount of information can be efficiently used for creating core collections. In the present study, after developing a 15K wheat Infinium array with 12,908 SNPs and genotyping a set of 479 hexaploid winter wheat lines (Triticum aestivum), a larger data set was created by merging 411 lines previously genotyped with the 90K iSelect array. Overlaying the markers from the 15K and 90K arrays enabled the identification of a common set of 12,806 markers, suggesting that the 15K array is a valuable and cost-effective resource for plant breeding programs.

Finally, we selected genetically diverse core sets out of these 890 wheat genotypes derived from five collections based on the common markers from the 15K and 90K SNP arrays. Two different approaches, k-medoids and Core Hunter 3 were compared,and k-medoids was identified as an efficient method for selecting small core sets out of a large collection of genotypes while retaining the genetic diversity of the original population.

Much of the world’s population growth will occur in regions where food insecurity is prevalent, with large increases in food demand projected in regions of Africa and South Asia. While improving food security in these regions will require a multi-faceted approach, improved performance of crop varieties in these regions will play a critical role. Current rates of genetic gain in breeding programs serving Africa and South Asia fall below rates achieved in other regions of the world. Given resource constraints, increased genetic gain in these regions cannot be achieved by simply expanding the size of breeding programs. New approaches to breeding are required. The Genomic Open-source Breeding informatics initiative (GOBii) and Excellence in Breeding Platform (EiB) are working with public sector breeding programs to build capacity, develop breeding strategies, and build breeding informatics capabilities to enable routine use of new technologies that can improve the efficiency of breeding programs and increase genetic gains. Simulations evaluating breeding strategies indicate cost-effective implementations of genomic selection (GS) are feasible using relatively small training sets, and proof-of-concept implementations have been validated in the International Maize and Wheat Improvement Center (CIMMYT) maize breeding program. Progress on GOBii, EiB, and implementation of GS in CIMMYT and International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) breeding programs are discussed, as well as strategies for routine implementation of GS in breeding programs serving Africa and South Asia.