Genome-Wide Association Study of Nitrogen Use Efficiency and Agronomic Traits in Upland Rice
Tatiana Rakotoson,
Julie Dusserre,
Philippe Letourmy,
Julien Frouin,
Isabelle Ramonta Ratsimiala,
Noronirina Victorine Rakotoarisoa,
Tuong-Vi cao,
Kirsten Vom Brocke,
Alain Ramanantsoanirina,
Nourollah Ahmadi,
Louis-Marie Raboin
Affiliations
Tatiana Rakotoson
National Center for Applied Research on Rural Development, Regional Research Station Antsirabe, Antsirabe 110, Madagascar; Higher Education Institute of Antsirabe Vakinankaratra, University of Antananarivo, Antsirabe 110, Madagascar
Julie Dusserre
Agroecology and Sustainable Intensification of Annual Crops Research Unit, French Agricultural Research Centre for International Development (CIRAD), Avenue Agropolis, Montpellier 34398, France; University of Montpellier/CIRAD, Montpellier 34398, France
Philippe Letourmy
Agroecology and Sustainable Intensification of Annual Crops Research Unit, French Agricultural Research Centre for International Development (CIRAD), Avenue Agropolis, Montpellier 34398, France; University of Montpellier/CIRAD, Montpellier 34398, France
Julien Frouin
Genetic Improvement and Adaptation of Mediterranean and Tropical Plants Research Unit (UMR AGAP), CIRAD, Avenue Agropolis, Montpellier 34398, France; University of Montpellier/CIRAD, Montpellier 34398, France
Isabelle Ramonta Ratsimiala
Faculty of Sciences, University of Antananarivo, Antananarivo 101, Madagascar
Noronirina Victorine Rakotoarisoa
Faculty of Sciences, University of Antananarivo, Antananarivo 101, Madagascar
Tuong-Vi cao
Genetic Improvement and Adaptation of Mediterranean and Tropical Plants Research Unit (UMR AGAP), CIRAD, Avenue Agropolis, Montpellier 34398, France; University of Montpellier/CIRAD, Montpellier 34398, France
Kirsten Vom Brocke
National Center for Applied Research on Rural Development, Regional Research Station Antsirabe, Antsirabe 110, Madagascar; UMR AGAP, Highland Production Systems and Sustainability in Madagascar Platform in Partnership, CIRAD, Antsirabe 110, Madagascar; University of Montpellier/CIRAD, Montpellier 34398, France
Alain Ramanantsoanirina
National Center for Applied Research on Rural Development, Regional Research Station Antsirabe, Antsirabe 110, Madagascar
Nourollah Ahmadi
Genetic Improvement and Adaptation of Mediterranean and Tropical Plants Research Unit (UMR AGAP), CIRAD, Avenue Agropolis, Montpellier 34398, France; University of Montpellier/CIRAD, Montpellier 34398, France
Louis-Marie Raboin
Agroecology and Sustainable Intensification of Annual Crops Research Unit, French Agricultural Research Centre for International Development (CIRAD), Avenue Agropolis, Montpellier 34398, France; University of Montpellier/CIRAD, Montpellier 34398, France; Corresponding author.
Genome-wide association study (GWAS) was performed for 16 agronomic traits including nitrogen use efficiency (NUE) and yield-related components using a panel of 190 mainly japonica rice varieties and a set of 38 390 single nucleotide polymorphism (SNP) markers. This panel was evaluated under rainfed upland conditions in Madagascar in two consecutive cropping seasons with two contrasted nitrogen input levels. Using another set of five grain traits, we identified previously known genes (GW5, GS3, Awn1 and Glabrous1), thus validating the pertinence and accuracy of our datasets for GWAS. A total of 369 significant associations were detected between SNPs and agronomic traits, gathered into 46 distinct haplotype groups and 28 isolated markers. Few association signals were identified for the complex quantitative trait NUE, however, larger number of quantitative trait loci (QTLs) were detected for its component traits, with 10 and 2 association signals for nitrogen utilization efficiency and nitrogen uptake efficiency, respectively. Several detected association signals co-localized with genes involved in nitrogen transport or nitrogen remobilization within 100 kb. The present study thus confirmed the potential of GWAS to identify candidate genes and new loci associated with agronomic traits. However, because of the quantitative and complex nature of NUE-related traits, GWAS might have not captured a large number of QTLs with limited effects.
