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Genomic selection for water use efficiency in Japonica rice and evaluation of different parameters implicated on the accuracy level. [P 0778]

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Plant and Animal Genome XXV Conference

https://pag.confex.com/pag/xxv/meetingapp.cgi/Paper/25162[07/02/2017 17:04:15]

P0778: Genomic Selection for Water Use Efficiency in japonica Rice and Evaluation of

Different Parameters Implicated on the Accuracy Level

POSTER

Conjunction of high-throughput marker technologies and new statistical methods has recently given birth to a new breeding strategy called genomic selection (GS). The method use genome-wide dense marker genotyping for the prediction of genetic values (GEBV) with enough accuracy to allow selection based on GEBV alone. We present here GS for water use efficiency in rice, in the framework of a pedigree breeding scheme. The training population (TP) was composed of 284 accessions belonging to temperate and tropical japonica rice groups. The candidate population (CP) was composed of 99 F5-F7 lines derived from 36 crosses involving 32 accessions of TP. The two populations were genotyped with an average marker density of 4.8 per kb, with MAF 2.5%. Phenotypic traits considered included flowering time (FL), grain yield (GY) and nitrogen balance index (NI) under conventional irrigation (CI) and aerobic system (AS).

Phenotypes were modeled using two statistical regression methods: genomic best linear unbiased prediction (GBLUP) and reproducing kernel Hilbert Space (RKHS). The models were tested with three incidence matrixes corresponding to densities of 4.8, 9.5 and 13.8 marker per kb, and to linkage

disequilibrium (LD) thresholds of r ≤1, r²<0.98 and r²<0.81 to investigate effect of the method and level of LD. Results of interpopulation prediction in rice breeding provided accuracies of GEBV prediction

reasonably high for GY (0.41; Sd=0.03) and for NI (0.36; Sd=0.04), low for FL (0.26; Sd = 0.07), that need to be optimized by exploring potential effect of population structure within both TP and CP.

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Authors

Manel Ben Hassen

Department of Agriculture, University of Milan Tuong-Vi Cao

CIRAD

Jaquin Lavalle CIRAD

Cinzia Colombi

Fondazione Parco Tecnologico Padano Gabriele Orasen

Department of Agriculture, University of Milan Joel Rakotomalala

FOFIFA

Lisy Razafinimpiasa FOFIFA

(2)

Plant and Animal Genome XXV Conference

https://pag.confex.com/pag/xxv/meetingapp.cgi/Paper/25162[07/02/2017 17:04:15] Department of Agriculture, University of Milan

Chiara Biselli

CREA Rice research unit Luigi Cattivelli

CREA Genomics research centre Nourollah Ahmadi

CIRAD

Giampiero Valè

CREA Rice research unit

View Related Events

Poster Category: 26 Genome Mapping, Tagging &

Characterization: Rice

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