Cells, Genes & Molecules

Allele mining could help improve forage grasses

Botanists demonstrate a novel, effective approach to allele discovery in diverse accessions using a draft reference genome from a single species.

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Raising cattle takes land that could be used in other ways. If land could be improved, less would be required to sustain cattle, but how to do this? Steve Hanley and colleagues propose that improving pasture grass could help. If they could improve the digestibility, then cattle would not need to graze quite so much. They also argue that enhancing the lipid content could decrease methane emissions from cattle. In a new paper in Annals of Botany the scientists show how allele mining could provide the answer.

Cattle in Africa. Image: Canva.

The team examined the genes of the C4Urochloa species (syn. Brachiaria) and Megathyrsus maximus (syn. Panicum maximum). These are grasses used as pasture in Africa and South America. Loss-of-function (LOF) alleles are in known gene targets are predicted to improve traits for these grasses. Hanley and colleagues searched for these alleles, or gene variants, among the accessions of Urochloa species and Megathyrsus maximus in the genebank collection held at the CIAT.

“We developed a new methodology for allele discovery of candidate genes in a collection of diploid and polyploid accessions with only a draft genome sequence for one diploid species as reference,” write Hanley and colleagues. “Our approach of combining RNAseq and bait capture provides a means of avoiding pseudogenes and resolving complexities. As part of the process, we improved gene models for 18 key genes and confirmed two more as accurate in the U. ruziziensis v1 genome. Our approach could be adapted for allele discovery in other plant collections or populations.”

“In future, the allele mining approach we describe here could be applied to other genes and need not be confined to alleles detrimental to molecular function. For example, candidate genes underlying apomixis… and spittlebug resistance… traits have recently been identified in Urochloa; with improving ability to predict consequences of variants in these, an allele mining approach could be of value. Also, for gene targets such as these where dominant alleles may affect phenotype, candidate gene association genetics could be a useful approach, as successfully applied for the FT gene and flowering time in Lolium perenne… As knowledge of genes improves, allele mining of diverse germplasm will become an increasingly powerful tool to identify lines that could be beneficially brought into many crop breeding programmes.”

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