Identification of candidate genes for gelatinization temperature, gel consistency and pericarp color by GWAS in rice based on SLAF-sequencing

Abstract

Rice is an important cereal in the world. The study of the genetic basis of important agronomic traits in rice landraces and identification of genes will facilitate the breed improvement. Gelatinization temperature (GT), gel consistency (GC) and pericarp color (PC) are important indices of rice cooking and eating quality evaluation and potential nutritional importance, which attract wide attentions in the application of genetic and breeding. To dissect the genetic basis of GT, GC and PC, a total of 419 rice landraces core germplasm collections consisting of 330 indica lines, 78 japonica lines and 11 uncertain varieties were planted, collected, then GT, GC, PC were measured for two years, and sequenced using specific-locus amplified fragment sequencing (SLAF-seq) technology. In this study, 261,385,070 clean reads and 56,768 polymorphic SLAF tags were obtained, which a total of 211,818 single nucleotide polymorphisms (SNPs) were discovered. With 208,993 SNPs meeting the criterion of minor allele frequency (MAF) > 0.05 and integrity> 0.5, the phylogenetic tree and population structure analysis were performed for all 419 rice landraces, and the whole panel mainly separated into six subpopulations based on population structure analysis. Genome-wide association study (GWAS) was carried out for the whole panel, indica subpanel and japonica subpanel with subset SNPs respectively. One quantitative trait locus (QTL) on chromosome 6 for GT was detected in the whole panel and indica subpanel, and one QTL associated with GC was located on chromosome 6 in the whole panel and indica subpanel. For the PC trait, 8 QTLs were detected in the whole panel on chromosome 1, 3, 4, 7, 8, 10 and 11, and 7 QTLs in the indica subpanel on chromosome 3, 4, 7, 8, 10 and 11. For the three traits, no QTL was detected in japonica subpanel, probably because of the polymorphism repartition between the subpanel, or small population size of japonica subpanel. This paper provides new gene resources and insights into the molecular mechanisms of important agricultural trait of rice phenotypic variation and genetic improvement of rice quality variety breeding.

The Genetic Basis and Nutritional Benefits of Pigmented Rice Grain

“…Butardo et al (2017) used GWAS to uncover a number of single nucleotide polymorphism loci (SNPs) linked to Rc. The 763 SNPs associated with pericarp pigmentation uncovered by Yang et al (2018) mapped to 6 of the 12 rice chromosomes (chromosomes 1, 3, 4, 8, 10, and 11); some of the most significantly associated SNPs lying close to previously identified structural or regulatory genes, but others map to regions not previously associated with variation in rice grain pigmentation.…”

Genetic Analysis for Cooking and Eating Quality of Super Rice and Fine Mapping of a Novel Locus qGC10 for Gel Consistency

“…As quantitative traits, they are determined mainly by genetic factors and affected by environmental conditions (Fan et al, 2005). Series of QTLs have been reported for AC, GT and GC (Sun S. -Y. et al, 2005;Su et al, 2011;Ponce et al, 2018;Yang et al, 2018). However, only few QTLs have been fine mapped or cloned.…”

Using hyperspectral analysis as a potential high throughput phenotyping tool in GWAS for protein content of rice quality

“…In order to construct a hyperspectral index that could be applied for AC, a bigger sample size would be selected in the future. In addition, because the GC is a complex trait and the nature of the GC data set was not a measurement of the content of a certain chemical/compound, but the length of flow distance [48], which makes it not suitable for hyperspectral technology, because hyperspectral signal was relating to the resonance of certain chemical bonds [25]. There is not any published research on using hyperspectral technology to dissect GC of rice seeds.…”