Literature DB >> 28724066

Strategies for Selecting Crosses Using Genomic Prediction in Two Wheat Breeding Programs.

Bettina Lado, Sarah Battenfield, Carlos Guzmán, Martín Quincke, Ravi P Singh, Susanne Dreisigacker, R Javier Peña, Allan Fritz, Paula Silva, Jesse Poland, Lucía Gutiérrez.   

Abstract

The single most important decision in plant breeding programs is the selection of appropriate crosses. The ideal cross would provide superior predicted progeny performance and enough diversity to maintain genetic gain. The aim of this study was to compare the best crosses predicted using combinations of mid-parent value and variance prediction accounting for linkage disequilibrium (V) or assuming linkage equilibrium (V). After predicting the mean and the variance of each cross, we selected crosses based on mid-parent value, the top 10% of the progeny, and weighted mean and variance within progenies for grain yield, grain protein content, mixing time, and loaf volume in two applied wheat ( L.) breeding programs: Instituto Nacional de Investigación Agropecuaria (INIA) Uruguay and CIMMYT Mexico. Although the variance of the progeny is important to increase the chances of finding superior individuals from transgressive segregation, we observed that the mid-parent values of the crosses drove the genetic gain but the variance of the progeny had a small impact on genetic gain for grain yield. However, the relative importance of the variance of the progeny was larger for quality traits. Overall, the genomic resources and the statistical models are now available to plant breeders to predict both the performance of breeding lines per se as well as the value of progeny from any potential crosses.
Copyright © 2017 Crop Science Society of America.

Entities:  

Mesh:

Year:  2017        PMID: 28724066     DOI: 10.3835/plantgenome2016.12.0128

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


  7 in total

1.  Comparison of single-trait and multi-trait genomic predictions on agronomic and disease resistance traits in spring wheat.

Authors:  Kassa Semagn; José Crossa; Jaime Cuevas; Muhammad Iqbal; Izabela Ciechanowska; Maria Antonia Henriquez; Harpinder Randhawa; Brian L Beres; Reem Aboukhaddour; Brent D McCallum; Anita L Brûlé-Babel; Amidou N'Diaye; Curtis Pozniak; Dean Spaner
Journal:  Theor Appl Genet       Date:  2022-06-23       Impact factor: 5.574

2.  Modeling copy number variation in the genomic prediction of maize hybrids.

Authors:  Danilo Hottis Lyra; Giovanni Galli; Filipe Couto Alves; Ítalo Stefanine Correia Granato; Miriam Suzane Vidotti; Massaine Bandeira E Sousa; Júlia Silva Morosini; José Crossa; Roberto Fritsche-Neto
Journal:  Theor Appl Genet       Date:  2018-10-31       Impact factor: 5.699

3.  Combining grain yield, protein content and protein quality by multi-trait genomic selection in bread wheat.

Authors:  Sebastian Michel; Franziska Löschenberger; Christian Ametz; Bernadette Pachler; Ellen Sparry; Hermann Bürstmayr
Journal:  Theor Appl Genet       Date:  2019-07-01       Impact factor: 5.699

4.  Genetic analysis of a potato (Solanum tuberosum L.) breeding collection for southern Colombia using Single Nucleotide Polymorphism (SNP) markers.

Authors:  Jhon A Berdugo-Cely; Carolina Martínez-Moncayo; Tulio César Lagos-Burbano
Journal:  PLoS One       Date:  2021-03-18       Impact factor: 3.240

Review 5.  Genomic Selection in Sugarcane: Current Status and Future Prospects.

Authors:  Channappa Mahadevaiah; Chinnaswamy Appunu; Karen Aitken; Giriyapura Shivalingamurthy Suresha; Palanisamy Vignesh; Huskur Kumaraswamy Mahadeva Swamy; Ramanathan Valarmathi; Govind Hemaprabha; Ganesh Alagarasan; Bakshi Ram
Journal:  Front Plant Sci       Date:  2021-09-27       Impact factor: 5.753

6.  The Potential of Genome-Wide Prediction to Support Parental Selection, Evaluated with Data from a Commercial Barley Breeding Program.

Authors:  Maximilian Rembe; Yusheng Zhao; Neele Wendler; Klaus Oldach; Viktor Korzun; Jochen C Reif
Journal:  Plants (Basel)       Date:  2022-09-29

7.  Harnessing translational research in wheat for climate resilience.

Authors:  Matthew P Reynolds; Janet M Lewis; Karim Ammar; Bhoja R Basnet; Leonardo Crespo-Herrera; José Crossa; Kanwarpal S Dhugga; Susanne Dreisigacker; Philomin Juliana; Hannes Karwat; Masahiro Kishii; Margaret R Krause; Peter Langridge; Azam Lashkari; Suchismita Mondal; Thomas Payne; Diego Pequeno; Francisco Pinto; Carolina Sansaloni; Urs Schulthess; Ravi P Singh; Kai Sonder; Sivakumar Sukumaran; Wei Xiong; Hans J Braun
Journal:  J Exp Bot       Date:  2021-07-10       Impact factor: 6.992

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.