Plants (Nov 2020)

Sequence Variants Linked to Key Traits in Interspecific Crosses between African and Asian Rice

  • Hayba Badro,
  • Marie-Noelle Ndjiondjop,
  • Agnelo Furtado,
  • Robert Henry

DOI
https://doi.org/10.3390/plants9121653
Journal volume & issue
Vol. 9, no. 12
p. 1653

Abstract

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Asian and African rice gene pools vary in many traits that are important in rice breeding. The genetic basis of these differences was evaluated by analysis of important agronomic traits in crosses between African and Asian rice. Trait-associated variants (TAVs) influencing three quantitative agronomic traits, heading date (Hd), tiller number at maturity (T), and 1000 grain weight (TGW), were identified by association analysis of crosses between Asian and African rice. Populations were developed by crossing WAB56-104 (Oryza sativa) and CG14 (Oryza glaberrima). DNA from plants with extremely high or low values for these phenotypes was bulked and sequenced. The reference genome of O. sativa cv Nipponbare was used in general association analysis and candidate gene analysis. A total of 5152 non-synonymous single nucleotide polymorphisms (SNPs) across 3564 genes distinguished the low and the high bulks for Hd, T, and TGW traits; 611 non-synonymous SNPs across 447 genes were found in KEGG pathways. Six non-synonymous SNPs were found in the sequences of LOC107275952, LOC4334529, LOC4326177, LOC107275432, LOC4335790, and LOC107275425 genes associated with Hd, T, and TGW traits. These genes were involved in: abscisic-acid biosynthesis, carotenoid biosynthesis, starch and sucrose metabolism, and cytokinin biosynthesis. Analysis of 24 candidate genes associated with Hd, T, and TGW traits showed seven non-synonymous variations in the sequence of Hd3a and Ehd2 from the Hd genes (not in a KEGG pathway), D10 and D53 from the T genes (strigolactones biosynthetic pathway), and Gn1a and GIF1 from the TGW genes (cytokinin biosynthetic and starch and sucrose metabolism pathways). This study identified significant differences in allele frequencies supported by high sequence depth in analysis of bulks displaying high and low values for these key traits. These trait-associated variants are likely to be useful in rice improvement.

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