Date Published: February 2, 2017
Publisher: Public Library of Science
Author(s): Tanguy Lafarge, Crisanta Bueno, Julien Frouin, Laval Jacquin, Brigitte Courtois, Nourollah Ahmadi, Aimin Zhang.
Fertilization sensitivity to heat in rice is a major issue within climate change scenarios in the tropics. A panel of 167 indica landraces and improved varieties was phenotyped for spikelet sterility (SPKST) under 38°C during anthesis and for several secondary traits potentially affecting panicle micro-climate and thus the fertilization process. The panel was genotyped with an average density of one marker per 29 kb using genotyping by sequencing. Genome-wide association analyses (GWAS) were conducted using three methods based on single marker regression, haplotype regression and simultaneous fitting of all markers, respectively. Fourteen loci significantly associated with SPKST under at least two GWAS methods were detected. A large number of associations was also detected for the secondary traits. Analysis of co-localization of SPKST associated loci with QTLs detected in progenies of bi-parental crosses reported in the literature allowed to narrow -down the position of eight of those QTLs, including the most documented one, qHTSF4.1. Gene families underlying loci associated with SPKST corresponded to functions ranging from sensing abiotic stresses and regulating plant response, such as wall-associated kinases and heat shock proteins, to cell division and gametophyte development. Analysis of diversity at the vicinity of loci associated with SPKST within the rice three thousand genomes, revealed widespread distribution of the favourable alleles across O. sativa genetic groups. However, few accessions assembled the favourable alleles at all loci. Effective donors included the heat tolerant variety N22 and some Indian and Taiwanese varieties. These results provide a basis for breeding for heat tolerance during anthesis and for functional validation of major loci governing this trait.
Spikelet sterility in the rice crop is becoming a burning issue in the context of global warming since it may occur as soon as air temperature reaches 33°C at time of anthesis  even if it is for less than an hour of exposure , a situation which can already be encountered in many rice growing areas . Meanwhile, the linear tendency of global warming was 0.74°C for the period 1906–2005 . Because of higher recurrence of extreme high-temperature events and a projected global average surface temperature increase of 1.5 to 4.8°C by 2100 [5, 6], yield decrease in the 2nd half of the century is predicted to be even stronger in the tropics than in the temperate areas . Considering also a simulated increase in annual mean of maximum temperature during the period 1990–2050 of 0.5 to 1.0°C in the northern and central part of South-East Asia, and of 1.0 to 1.5°C in the southern part , spikelet sterility due to heat in rice will become more dramatic worldwide in the near future.
The aim of this work was to explore the phenotypic diversity for rice spikelet sensitivity to high temperature, and the associated allelic variations, and to draw a unified picture of the genetic bases of this important trait in the context of climate change, by connecting QTLs previously mapped in bi-parental crosses to the underlying genes. Given the recent development of new GWAS methodologies, we also explored the added value of two methods that resort to more complex models than the classical single marker regression to detect SNP loci associated with phenotypic variation. During our phenotyping experiment for spikelet sensitivity to high temperature, several other traits have also been measured. Some of these traits were related to the plant ability to reduce panicle temperature through transpiration, via either large leaf area (LFAR, SLA, GLFDW, DLFDW, LFSNS 16, LFSNS 21, SLA) or appropriate architecture (PTHT, PNPOS, FLFAG, LFAG), others related to plant potential performance (PNNB, TINB, PNLT, PNEX, SHDW, ST+PNDW), and one related to the duration during which the plant may be susceptible to heat (HDLT). Although we could not find any direct relationship between these traits and SPKST, we included them in our GWAS work with the aim of (i) further ascertaining the suitability of our diversity panel for GWAS analysis and (ii) enriching existing QTL data bases for those traits.