Maize originated in tropical areas and improving cold tolerance is an important breeding objective for cultivation in high latitudes. We review the main limitations in understanding and improving cold tolerance in maize and the contribution of genomics in dissecting the genetic basis of the trait and selecting better genotypes. Physiological analyses revealed that non-optimal temperature exerts detrimental effects on a multitude of metabolic functions at different growing stages, each under the control of independent gene sets. Loci controlling cold tolerance at different growing stages have been investigated by means of linkage mapping or genome-wide association, revealing that no major genes are responsible for the trait. This finding was confirmed in transcriptomic studies that always revealed multiple candidates, and a large amount of data is being collected that altogether will make it possible to obtain a more coherent picture of response to cold. To harness the increasing body of information available from the maize genome sequence and gene expression data, new bioinformatics tools will be helpful for integrating the big-data obtained from the large-scale genomics and phenomics experiments. With the enhancement of knowledge, plant science is shifting its focus from “explanatory” to “predictive” and from a plant breeding perspective the focus will be predicting the breeding value of the best genotypes by using molecular information. The future strategies for selection of cold tolerance will involve intensive genotyping, high-precision phenotyping and advanced statistical analyses to predict the optimal genotypes for more time- and cost-efficient breeding strategies.

Genomics of Cold Tolerance in Maize

Frascaroli, Elisabetta
;
2018

Abstract

Maize originated in tropical areas and improving cold tolerance is an important breeding objective for cultivation in high latitudes. We review the main limitations in understanding and improving cold tolerance in maize and the contribution of genomics in dissecting the genetic basis of the trait and selecting better genotypes. Physiological analyses revealed that non-optimal temperature exerts detrimental effects on a multitude of metabolic functions at different growing stages, each under the control of independent gene sets. Loci controlling cold tolerance at different growing stages have been investigated by means of linkage mapping or genome-wide association, revealing that no major genes are responsible for the trait. This finding was confirmed in transcriptomic studies that always revealed multiple candidates, and a large amount of data is being collected that altogether will make it possible to obtain a more coherent picture of response to cold. To harness the increasing body of information available from the maize genome sequence and gene expression data, new bioinformatics tools will be helpful for integrating the big-data obtained from the large-scale genomics and phenomics experiments. With the enhancement of knowledge, plant science is shifting its focus from “explanatory” to “predictive” and from a plant breeding perspective the focus will be predicting the breeding value of the best genotypes by using molecular information. The future strategies for selection of cold tolerance will involve intensive genotyping, high-precision phenotyping and advanced statistical analyses to predict the optimal genotypes for more time- and cost-efficient breeding strategies.
2018
The Maize Genome
287
303
Frascaroli, Elisabetta; Revilla, Pedro
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/653288
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