Identification of epistasis loci underlying rice flowering time by controlling population stratification and polygenic effect

Abstract

Flowering time is an important agronomic trait, attributed by multiple genes, gene-gene interactions and environmental factors. Population stratification and polygenic effects might confound genetic effects of the causal loci underlying this complex trait. We proposed a two-step approach for detecting epistasis interactions underlying rice flowering time by accounting population structure and polygenic effects. Simulation studies showed that the approach used in this study performs better than classical and PC-linear approaches in terms of powers and false discovery rates in the case of population stratification and polygenic effects. Whole genome epistasis analyses identified 589 putative genetic interactions for flowering time. Eighteen of these interactions are located within 10 kilobases of regions of known protein-protein interactions. Thirty-seven SNPs near to twenty-five genes involve in rice or/and Arabidopsis (orthologue) flowering pathway. Bioinformatics analysis showed that 66.55% pairwise genes of the identified interactions (392 out of the 589 interactions) have similarity in various genomic features. Moreover, significant numbers of detected epistatic genes have high expression in different floral tissues. Our findings highlight the importance of epistasis analysis by controlling population stratification and polygenic effect and provided novel insights into the genetic architecture of rice flowering which could assist breeding programmes.

Keywords: GWAS; epistasis analysis; polygenic effect; population stratification; rice flowering.

Figure 1

Model comparisons under structured population. (a) Power and (b) FDR comparison at different genetic heritability for structured population and samples were considered from three different populations (1,000 sample size with 400, 300 and 300 sample for three populations, respectively). This figure is available in black and white in print and in colour at DNARES online.

Figure 2

Model comparisons under assumption of (i) polygenic effect (ii) both population structure and polygenic effect. Power and FRD for (a, b) 15% fixed epistatic variance and; (c, d) 40% fixed error variance under the assumption of polygenic effect. Power and FRD for (e, f) 15% fixed epistatic variance and; (g, h) 40% fixed error variance under the assumption of both population stratification and polygenic effect. Different proportions of polygenic effects (0–40%) were varied presented in x-axis. In all cases the additive variance and epistatic variance were equal. With fixed epistatic variance to 15%, the error variance was 70% when the polygenic variance was 0% and error variance was 30% when polygenic variance was 40% (Supplementary Table S8). Again with fixed error variance to 40%, the epistatic variance was 30% when polygenic variance was 0% and epistatic variance was 10% when polygenic variance was 40% (Supplementary Table S9). This figure is available in black and white in print and in colour at DNARES online.

Figure 3

Overview of the identified epistatic loci for rice flowering time. (a) The Circos plot represents the interaction of the 499 unique SNPs that comprise the 589 epistatic interactions. The outer track shows 12 chromosomes levelled by different colours. The other tracks present (1) line plot of the location of the candidate genes of identified SNPs, (2) Line plot of the minor allele frequency (MAF) of the SNPs. The range of the MAFs are 0.015–0.5 and more than half of the SNPs are in the range between 0.1 and 0.3 (Supplementary Fig. S2). Track (3) presents the detected interactions through all chromosomes. (b) The distribution of the minor allele frequency. (c) The distribution of interactions through all chromosomes. Chromosome wise (d) and overall (e) distribution of location of the identified epistatic SNPs. This figure is available in black and white in print and in colour at DNARES online.

Figure 4

Gene ontology biological process treemap. Gene ontology biological process treemap of the annotated genes for rice flowering time. Sizes of the rectangles are adjusted on the basis of the frequency of the GO terms (Supplementary Data S6) . This figure is available in black and white in print and in colour at DNARES online.

Figure 5

Network of epistasis interaction for rice flowering time. (a) A Cytoscape network generated from SNPs interactions inferred following proposed method for the rice flowering time. The nodes are represented to the SNPs and the shape of the nodes are symbolised on the basis of annotated genes those involve in the rice or Arabidopsis flower related pathway: octagon (involved in rice flowering time or seed development pathway), diamond (involved in Arabidopsis flowering time or flower development pathway) and rectangle (involved in both rice and Arabidopsis flower related pathway). The edges are coloured on the basis of the connected genes located in similar subcellular location or overlap with same GO terms and/or predicted for PPI and/or overlap of the three genomic features (Supplementary Fig. S7, Data S8 and S9). Solid line for the edge indicating early flowering and dash line indicating delay flowering. (b) Rice and Arabidopsis genes involved in flower pathway. (c) The overlap of GO domain and epistatic genes (d) the overlap of interacting genes in subcellular location, gene ontology and PPI. This figure is available in black and white in print and in colour at DNARES online.

Figure 6

Subcellular location and tissue-specific expression. Subcellular location and tissue-specific expression of the candidate genes involved in G1 of the network. Colour strip represents for chromosome, dot plot for predicted subcellular locations (cytosol, plastid, vacuole, extracellular, mitochondria, membrane, nuclear, ER: endoplasmic reticulum, Golgi, golgi apparatus and peroxisome) and heatmap for six floral tissues (E1: Post-emergence inflor, E2: Pre-emergence inflor, E3: Embryo-25DAP, E4: Anther, E5: Pistil and E6: Panicle) specific expression. Dendrogram showing clustering (hierarchical clustering) of genes in heatmap is on the basis of tissue-specific expression. The colour scale bar of the figure represents log2 transformed FPKM values. Square on the dendrogram represents the corresponding annotated genes of the SNPs in Table 1. This figure is available in black and white in print and in colour at DNARES online.