Genetic Gains in IRRI’s Rice Salinity Breeding and Elite Panel Development as a Future Breeding Resource

Author:

Khanna Apurva,Ramos Joie,Sta. Cruz Ma Teresa,Catolos Margaret,Anumalla Mahender,Godwin Andres,Gregorio Glenn,Singh Rakesh Kumar,Dixit Shalabh,Ali Jauhar,Islam Md Rafiqul,Singh Vikas Kumar,Rahman Akhlasur,Khatun Hasina,Pisano Daniel Joseph,Bhosale Sankalp,Hussain WaseemORCID

Abstract

AbstractGenetic gain is a crucial parameter to check the breeding program’s success and help optimize future breeding strategies for enhanced genetic gains. In this work, IRRI’s historical data from the Philippines and Bangladesh of the salinity breeding program was used to estimate the genetic gains and identify the best lines based on higher breeding values for yield as a future genetic resource. Two-stage mixed-model approach accounting for experimental design factors and pedigrees was adopted to obtain the breeding values for yield and estimate genetic trends under the salinity conditions. A positive genetic trend of 0.1% per annum with a yield advantage of 1.52 kg/ha for the Philippines and 0.31% per annum with a yield advantage of 14.02 kg/ha for Bangladesh datasets was observed. For the released varieties, genetic gain was 0.12% per annum with a yield advantage of 2.2 kg/ha/year and 0.14% per annum with a yield advantage of 5.9 kg/ha/year, respectively. Further, based on higher breeding values for grain yield, a core set of the top 145 genotypes with higher breeding values of >2400 kg/ha in the Philippines and >3500 kg/ha in Bangladesh with a selection accuracy >0.4 were selected for formulating the elite breeding panel as a future breeding resource. Conclusively, higher genetic gains are pivotal in IRRI’s rice salinity breeding program, which requires a holistic breeding approach with a major paradigm shift in breeding strategies to enhance genetic gains.Key MessageEstimating genetic gains and formulating a future salinity elite breeding panel for rice pave the way for developing better high-yielding salinity tolerant lines with enhanced genetic gains.

Publisher

Cold Spring Harbor Laboratory

Reference43 articles.

1. Harnessing the hidden genetic diversity for improving multiple abiotic stress tolerance in rice (Oryza sativa L;PLoS One,2017

2. AGHmatrix: R package to construct relationship matrices for autotetraploid and diploid species: A blueberry example;Plant Genome,2016

3. Outlier detection methods for generalized lattices: a case study on the transition from ANOVA to REML;Theor Appl Genet,2016

4. Butler DG , Cullis BR , Gilmour AR , Gogel BG , Thompson R (2017) ASReml-R reference manual version 4. VSN International Ltd, Hemel Hempstead, HP1 1ES, UK.

5. Architectural and Physiological Features to Gain High Yield in an Elite Rice Line YLY1;Rice,2020

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