Genomic selection for productive traits in biparental cassava breeding populations.

Cassava improvement using traditional breeding strategies is slow due to the species' long breeding cycle. However, the use of genomic selection can lead to a shorter breeding cycle. This study aimed to estimate genetic parameters for productive traits based on pedigree (pedigree and phenotypic...

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Main Authors: Lívia Gomes Torres, Marcos Deon Vilela de Resende, Camila Ferreira Azevedo, Fabyano Fonseca E Silva, Eder Jorge de Oliveira
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0220245
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spelling doaj-041de1446be240ef958524bcb3ce96df2021-03-03T21:19:36ZengPublic Library of Science (PLoS)PLoS ONE1932-62032019-01-01147e022024510.1371/journal.pone.0220245Genomic selection for productive traits in biparental cassava breeding populations.Lívia Gomes TorresMarcos Deon Vilela de ResendeCamila Ferreira AzevedoFabyano Fonseca E SilvaEder Jorge de OliveiraCassava improvement using traditional breeding strategies is slow due to the species' long breeding cycle. However, the use of genomic selection can lead to a shorter breeding cycle. This study aimed to estimate genetic parameters for productive traits based on pedigree (pedigree and phenotypic information) and genomic (markers and phenotypic information) analyses using biparental crosses at different stages of selection. A total of 290 clones were genotyped and phenotyped for fresh root yield (FRY), dry matter content (DMC), dry yield (DY), fresh shoot yield (FSY) and harvest index (HI). The clones were evaluated in clonal evaluation trials (CET), preliminary yield trials (PYT), advanced yield trials (AYT) and uniform yield trials (UYT), from 2013 to 2018 in ten locations. The breeding stages were analyzed as follows: one stage (CET), two stages (CET and PYT), three stages (CET, PYT and AYT) and four stages (CET, PYT, AYT and UYT). The genomic predictions were analyzed via k-fold cross-validation based on the genomic best linear unbiased prediction (GBLUP) considering a model with genetic additive effects and genotype × location interactions. Genomic and pedigree accuracies were moderate to high (0.56-0.72 and 0.62-0.78, respectively) for important starch-related traits such as DY and FRY; when considering one breeding stage (CET) with the aim of early selection, the genomic accuracies ranged from 0.60 (DMC) to 0.71 (HI). Moreover, the correlations between the genomic estimation breeding values of one-stage genomic analysis and the estimated breeding values of the four-stage (full data set) pedigree analysis were high for all traits as well as for a selection index including all traits. The results indicate great possibilities for genomic selection in cassava, especially for selection early in the breeding cycle (saving time and effort).https://doi.org/10.1371/journal.pone.0220245
collection DOAJ
language English
format Article
sources DOAJ
author Lívia Gomes Torres
Marcos Deon Vilela de Resende
Camila Ferreira Azevedo
Fabyano Fonseca E Silva
Eder Jorge de Oliveira
spellingShingle Lívia Gomes Torres
Marcos Deon Vilela de Resende
Camila Ferreira Azevedo
Fabyano Fonseca E Silva
Eder Jorge de Oliveira
Genomic selection for productive traits in biparental cassava breeding populations.
PLoS ONE
author_facet Lívia Gomes Torres
Marcos Deon Vilela de Resende
Camila Ferreira Azevedo
Fabyano Fonseca E Silva
Eder Jorge de Oliveira
author_sort Lívia Gomes Torres
title Genomic selection for productive traits in biparental cassava breeding populations.
title_short Genomic selection for productive traits in biparental cassava breeding populations.
title_full Genomic selection for productive traits in biparental cassava breeding populations.
title_fullStr Genomic selection for productive traits in biparental cassava breeding populations.
title_full_unstemmed Genomic selection for productive traits in biparental cassava breeding populations.
title_sort genomic selection for productive traits in biparental cassava breeding populations.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2019-01-01
description Cassava improvement using traditional breeding strategies is slow due to the species' long breeding cycle. However, the use of genomic selection can lead to a shorter breeding cycle. This study aimed to estimate genetic parameters for productive traits based on pedigree (pedigree and phenotypic information) and genomic (markers and phenotypic information) analyses using biparental crosses at different stages of selection. A total of 290 clones were genotyped and phenotyped for fresh root yield (FRY), dry matter content (DMC), dry yield (DY), fresh shoot yield (FSY) and harvest index (HI). The clones were evaluated in clonal evaluation trials (CET), preliminary yield trials (PYT), advanced yield trials (AYT) and uniform yield trials (UYT), from 2013 to 2018 in ten locations. The breeding stages were analyzed as follows: one stage (CET), two stages (CET and PYT), three stages (CET, PYT and AYT) and four stages (CET, PYT, AYT and UYT). The genomic predictions were analyzed via k-fold cross-validation based on the genomic best linear unbiased prediction (GBLUP) considering a model with genetic additive effects and genotype × location interactions. Genomic and pedigree accuracies were moderate to high (0.56-0.72 and 0.62-0.78, respectively) for important starch-related traits such as DY and FRY; when considering one breeding stage (CET) with the aim of early selection, the genomic accuracies ranged from 0.60 (DMC) to 0.71 (HI). Moreover, the correlations between the genomic estimation breeding values of one-stage genomic analysis and the estimated breeding values of the four-stage (full data set) pedigree analysis were high for all traits as well as for a selection index including all traits. The results indicate great possibilities for genomic selection in cassava, especially for selection early in the breeding cycle (saving time and effort).
url https://doi.org/10.1371/journal.pone.0220245
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