A new costing tool is helping national breeding programs get the financial data needed to improve their efficiency, effectiveness and transparency. And now, in its first in-person event since the beginning of the pandemic, CGIAR Excellence in Breeding (EiB) has prepped six African National Agricultural Research and Extension Systems (NARES) to fully cost their programs.
Genomic selection/prediction is becoming an important tool to maximize genetic gain in breeding programs. The method covers multiple ways to improve different aspects of the breeders’ equation.
Parthiban Prakash presents the current state of genomic prediction application in the rice program at IRRI located in the Philippines. Prakash covers the application of GS to increase accuracy and change selection intensity in the IRRI rice program, discusses current plans to reduce cycle time and the challenges of implementing GS in an ongoing program.
Giovanny Covarrubias-Pazaran (EiB) presents the genomic prediction workshop and outlines the topics to be covered and guest speakers.
About this training:
Giovanny Covarrubias-Pazaran presents how to implement genomic prediction to properly manage genetic variance. The logistical challenges that will be faced during adoption are then discussed, along with a summary of the different uses of genomic selection (GS).
Yoseph Beyene presents the current state of genomic prediction application in the CIMMYT maize breeding program in East Africa. Yoseph presents the use of GS to increase accuracy and change selection intensity in the maize program and discusses the challenges of implementation in an ongoing breeding program.
Eng Hwa Ng and Rajaguru Bohar present the current genotyping shared services available from EiB to enable low, mid and high-density genotyping for the application in genomic selection. The link to trait augmentation is presented and the logistical challenges involved in starting to genotype the early-stage materials from programs is discussed. A network strategy for genotyping is presented to breeders. Costs, workflows, panels available and crop status are discussed by Rajaguru.
Giovanny Covarrubias-Pazaran presents how to implement genomic prediction to change selection intensity. It is possible to increase selection intensity at an additional cost (although lower than the cost of phenotyping) or maintain the same intensity and accuracy with reduced costs.
Additionally, Covarrubias-Pazaran presents how to implement genomic prediction to reduce cycle time. This implies predicting individuals that have not been observed before while also predicting haplotypes that have not been observed before.
Giovanny Covarrubias-Pazaran presents how to implement genomic prediction to increase the accuracy of field trials by using a genomic relationship matrix to predict haplotypes and individuals. This is especially useful when heritabilities in field trials are low.
This session is focused on the basics of what genomic prediction implies in terms of data and models and applications. Common questions raised by CGIAR programs during interactions with the EiB platform are also covered.