Unraveling the secrets of yam genomes to improve breeding

Unraveling the secrets of yam genomes to improve breeding

Despite yam’s importance as a food security and cash crop, knowledge of its genome lags far behind that of other crops. RTB is helping to bridge this gap through genomic and metabolomic research to better understand yam diversity, and provide breeders with knowledge to accelerate and enhance the development of improved varieties.

When RTB began work, no reference genome existed for any of the six economically important yam species and little genetic research had been done on the crop. During RTB’s first phase, IITA contributed to the completion of reference genome sequences for the two most cultivated yam species, Dioscorea rotundata and D. alata, in partnership with Iwate Biotechnology Research Center and Earlham Institute. IITA researchers planted 840 D. rodundata accessions for phenotyping and sent them to Cornell University for genotyping by sequencing (GBS) in order to identify genes linked to important traits. IITA also sent 100 D. alata accessions from Africa to CIRAD for GBS, together with approximately 900 D. alata accessions from Asia and the South Pacific for genomic research on that species. In addition, metabolite profiles were completed for 49 genotypes from the five different yam species routinely used in breeding.

“There are a lot of issues that we don’t understand about yam,” said Ranjana Bhattacharjee, a molecular breeder at IITA.

Yam was completely neglected, and it is still a neglected crop, but thanks to RTB we’re making important progress.

She explained that IITA has prioritized genomic research on D. rotundata because it is the most commonly grown species in West Africa and constitutes most of the yam produced worldwide. Of the 840 D. rotundata accessions that underwent GBS and phenotyping, 500 were from IITA’s core collection, 300 were elite breeding lines, and 40 were collected at Nigerian markets. Researchers analyzed GBS data to assess genetic diversity and population structures, and completed a hierarchical cluster analysis that revealed three major clusters: elite breeding lines clustered separately from the landraces, whereas the third cluster likely represents triploid yams, though Bhattacharjee said a ploidy analysis is needed to confirm this.

Upon analyzing the GBS data, researchers realized that many accessions labeled as different varieties were actually genetically identical. They identified 240 unique clones among the many duplicates and planted them for further phenotyping and characterization. These accessions will be used as a training population for genome wide association studies, and for testing the use of genomic selection to accelerate yam improvement.

Traits of interest include flowering, tuber weight, oxidation, earliness, resistance to anthracnose disease, and quality characteristics such as dry matter and ‘poundability’, which is important for West African women, since they pound boiled tuber flesh for traditional dishes.

“Earliness, tuber oxidation and flowering are important traits that genomic data could make a big difference in breeding for,” observed Bhattacharjee. She explained that a scarcity of female flowers makes it difficult to cross yams, and she hopes to use genetic and metabolite data to determine which parents will produce enough flowers to facilitate breeding.

Researchers at Royal Holloway University of London have completed metabolite profiles of 49 genotypes of D. rotundata, D. alata, D. cayenensis, D. bulbifera and D. dumetorum. Combined analysis of leaf and tuber material identified a subset of metabolites that allow accurate species classification and highlighted the potential of predicting tuber composition from leaf profiles. “Metabolite data can provide deeper insight into genes of interest,” said Bhattacharjee, who hopes to use it to better understand the metabolic pathways that control important traits. She added that she would like to have metabolite profiles for the 240 accessions in the training population in order to use the data for high-throughput phenotyping. This could complement genomic data by accelerating the selection of offspring, which would help breeders to develop new varieties faster.

Photo: Yam in vitro cultures at IITA’s genebank in Ibadan, Nigeria. IITA

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