Phenomic selection: a low-cost and high-throughput alternative to genomic selection

Renaud Rincent, Jean-Paul Charpentier, Patricia Faivre-Rampant, Etienne Paux, Jacques Le Gouis, Catherine Bastien, Vincent Segura

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Received: 21st April 18

Genomic selection - the prediction of breeding values using DNA polymorphisms - is a disruptive method that has widely been adopted by animal and plant breeders to increase crop, forest and livestock productivity and ultimately secure food and energy supplies. It improves breeding schemes in different ways, depending on the biology of the species and genotyping and phenotyping constraints. However, both genomic selection and classical phenotypic selection remain difficult to implement because of the high genotyping and phenotyping costs that typically occur when selecting large collections of individuals, particularly in early breeding generations. To specifically address these issues, we propose a new conceptual framework called phenomic selection, which consists of a prediction approach based on low-cost and high-throughput phenotypic descriptors rather than DNA polymorphisms. We applied phenomic selection on two species of economic interest (wheat and poplar) using near-infrared spectroscopy on various tissues. We showed that one could reach accurate predictions in independent environments for developmental and productivity traits and tolerance to disease. We also demonstrated that under realistic scenarios, one could expect much higher genetic gains with phenomic selection than with genomic selection. Our work constitutes a proof of concept and is the first attempt at phenomic selection; it clearly provides new perspectives for the breeding community, as this approach is theoretically applicable to any organism and does not require any genotypic information.

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This is an abstract of a preprint hosted on an independent third party site. It has not been peer reviewed but is currently under consideration at Nature Communications.

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