Literature DB >> 28464061

Use of Genomic Estimated Breeding Values Results in Rapid Genetic Gains for Drought Tolerance in Maize.

B S Vivek, Girish Kumar Krishna, V Vengadessan, R Babu, P H Zaidi, Le Quy Kha, S S Mandal, P Grudloyma, S Takalkar, K Krothapalli, I S Singh, Eureka Teresa M Ocampo, F Xingming, J Burgueño, M Azrai, R P Singh, J Crossa.   

Abstract

More than 80% of the 19 million ha of maize ( L.) in tropical Asia is rainfed and prone to drought. The breeding methods for improving drought tolerance (DT), including genomic selection (GS), are geared to increase the frequency of favorable alleles. Two biparental populations (CIMMYT-Asia Population 1 [CAP1] and CAP2) were generated by crossing elite Asian-adapted yellow inbreds (CML470 and VL1012767) with an African white drought-tolerant line, CML444. Marker effects of polymorphic single-nucleotide polymorphisms (SNPs) were determined from testcross (TC) performance of F families under drought and optimal conditions. Cycle 1 (C1) was formed by recombining the top 10% of the F families based on TC data. Subsequently, (i) C2[PerSe_PS] was derived by recombining those C1 plants that exhibited superior per se phenotypes (phenotype-only selection), and (ii) C2[TC-GS] was derived by recombining a second set of C1 plants with high genomic estimated breeding values (GEBVs) derived from TC phenotypes of F families (marker-only selection). All the generations and their top crosses to testers were evaluated under drought and optimal conditions. Per se grain yields (GYs) of C2[PerSe_PS] and that of C2[TC-GS] were 23 to 39 and 31 to 53% better, respectively, than that of the corresponding F population. The C2[TC-GS] populations showed superiority of 10 to 20% over C2[PerSe-PS] of respective populations. Top crosses of C2[TC-GS] showed 4 to 43% superiority of GY over that of C2[PerSe_PS] of respective populations. Thus, GEBV-enabled selection of superior phenotypes (without the target stress) resulted in rapid genetic gains for DT.
Copyright © 2017 Crop Science Society of America.

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Year:  2017        PMID: 28464061     DOI: 10.3835/plantgenome2016.07.0070

Source DB:  PubMed          Journal:  Plant Genome        ISSN: 1940-3372            Impact factor:   4.089


  15 in total

1.  Rapid Cycling Genomic Selection in a Multiparental Tropical Maize Population.

Authors:  Xuecai Zhang; Paulino Pérez-Rodríguez; Juan Burgueño; Michael Olsen; Edward Buckler; Gary Atlin; Boddupalli M Prasanna; Mateo Vargas; Félix San Vicente; José Crossa
Journal:  G3 (Bethesda)       Date:  2017-07-05       Impact factor: 3.154

2.  Accounting for Genotype-by-Environment Interactions and Residual Genetic Variation in Genomic Selection for Water-Soluble Carbohydrate Concentration in Wheat.

Authors:  Ben Ovenden; Andrew Milgate; Len J Wade; Greg J Rebetzke; James B Holland
Journal:  G3 (Bethesda)       Date:  2018-05-31       Impact factor: 3.154

3.  Effect of Trait Heritability, Training Population Size and Marker Density on Genomic Prediction Accuracy Estimation in 22 bi-parental Tropical Maize Populations.

Authors:  Ao Zhang; Hongwu Wang; Yoseph Beyene; Kassa Semagn; Yubo Liu; Shiliang Cao; Zhenhai Cui; Yanye Ruan; Juan Burgueño; Felix San Vicente; Michael Olsen; Boddupalli M Prasanna; José Crossa; Haiqiu Yu; Xuecai Zhang
Journal:  Front Plant Sci       Date:  2017-11-08       Impact factor: 5.753

4.  Gains through selection for grain yield in a winter wheat breeding program.

Authors:  Dennis N Lozada; Brian P Ward; Arron H Carter
Journal:  PLoS One       Date:  2020-04-28       Impact factor: 3.240

Review 5.  A review of deep learning applications for genomic selection.

Authors:  Osval Antonio Montesinos-López; Abelardo Montesinos-López; Paulino Pérez-Rodríguez; José Alberto Barrón-López; Johannes W R Martini; Silvia Berenice Fajardo-Flores; Laura S Gaytan-Lugo; Pedro C Santana-Mancilla; José Crossa
Journal:  BMC Genomics       Date:  2021-01-06       Impact factor: 3.969

6.  Maximizing efficiency of genomic selection in CIMMYT's tropical maize breeding program.

Authors:  Sikiru Adeniyi Atanda; Michael Olsen; Juan Burgueño; Jose Crossa; Daniel Dzidzienyo; Yoseph Beyene; Manje Gowda; Kate Dreher; Xuecai Zhang; Boddupalli M Prasanna; Pangirayi Tongoona; Eric Yirenkyi Danquah; Gbadebo Olaoye; Kelly R Robbins
Journal:  Theor Appl Genet       Date:  2020-10-10       Impact factor: 5.699

Review 7.  Beat the stress: breeding for climate resilience in maize for the tropical rainfed environments.

Authors:  Boddupalli M Prasanna; Jill E Cairns; P H Zaidi; Yoseph Beyene; Dan Makumbi; Manje Gowda; Cosmos Magorokosho; Mainassara Zaman-Allah; Mike Olsen; Aparna Das; Mosisa Worku; James Gethi; B S Vivek; Sudha K Nair; Zerka Rashid; M T Vinayan; AbduRahman Beshir Issa; Felix San Vicente; Thanda Dhliwayo; Xuecai Zhang
Journal:  Theor Appl Genet       Date:  2021-02-16       Impact factor: 5.699

Review 8.  Genomics-Enabled Next-Generation Breeding Approaches for Developing System-Specific Drought Tolerant Hybrids in Maize.

Authors:  Thirunavukkarsau Nepolean; Jyoti Kaul; Ganapati Mukri; Shikha Mittal
Journal:  Front Plant Sci       Date:  2018-04-11       Impact factor: 5.753

9.  Discovery and validation of genomic regions associated with resistance to maize lethal necrosis in four biparental populations.

Authors:  Manje Gowda; Yoseph Beyene; Dan Makumbi; Kassa Semagn; Michael S Olsen; Jumbo M Bright; Biswanath Das; Stephen Mugo; L M Suresh; Boddupalli M Prasanna
Journal:  Mol Breed       Date:  2018-05-10       Impact factor: 2.589

10.  A Multivariate Poisson Deep Learning Model for Genomic Prediction of Count Data.

Authors:  Osval Antonio Montesinos-López; José Cricelio Montesinos-López; Pawan Singh; Nerida Lozano-Ramirez; Alberto Barrón-López; Abelardo Montesinos-López; José Crossa
Journal:  G3 (Bethesda)       Date:  2020-11-05       Impact factor: 3.154

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