November 26, 2020
Digital breeding can be expected with barley
An international joint research group of Okayama University, RIKEN CSRS, and other researchers constructed chromosome-scale sequence assemblies for 20 barley accessions. The group first selected 20 accessions from more than 20,000 barley accessions by genetic fingerprinting with genome-wide genotyping. Then the group assembled sequence datasets from each of the 20 varieties through multiple sequencing and bioinformatics methods.
The haploid genome size of barley is as large as 5 billion base pairs, 1.7 times larger than humans and 13 times larger than rice. In barley, there was one reference genome sequence information from a single variety. Therefore, it was difficult to analyze genetic codes not identified in the reference variety.
in this study, the group performed a "Pan Genome" analysis in which 20 wild and cultivated barley accessions were analyzed to construct chromosome-scale sequence assemblies and compare their entire genomic structures. As the result, the group found that 63% of genic regions were common among the 20 varieties, and the remaining 37% were specific. The group also revealed that chromosomal translocations that occurred during the breeding history in barley.
The “Pan Genome” analysis in barley with multiple accessions will be applied to identify its useful genes associated with important traits for breeding. Moreover, it will enable us to realize digital breeding techniques to design target varieties in barley.
M. Jayakodi, S. Padmarasu, G. Haberer, V. S. Bonthala, H. Gundlach, C. Monat, T. Lux, N. Kamal, D. Lang, A. Himmelbach, J. Ens, X.-Q. Zhang, T. T. Angessa, G. Zhou, C. Tan, C. Hill, P. Wang, M. Schreiber, L. B. Boston, C. Plott, J. Jenkins, Y. Guo, A. Fiebig, H. Budak, D. Xu, . Zhang, C. Wang, J. Grimwood, J. Schmutz, G. Guo, G. Zhang, K. Mochida, T. Hirayama, K. Sato, K. J. Chalmers, P. Langridge, R. Waugh, C. J. Pozniak, U. Scholz, K. F. X. Mayer, M. Spannag, C. Li, M. Mascher, N. Stein,
"The barley pan-genome reveals the hidden legacy of mutation breeding".
Bioproductivity Informatics Research Team