Whole Genome Sequencing of Elite Rice Cultivars as a Comprehensive Information Resource for Marker Assisted Selection

Abstract

Current advances in sequencing technologies and bioinformatics revealed the genomic background of rice, a staple food for the poor people, and provided the basis to develop large genomic variation databases for thousands of cultivars. Proper analysis of this massive resource is expected to give novel insights into the structure, function, and evolution of the rice genome, and to aid the development of rice varieties through marker assisted selection or genomic selection. In this work we present sequencing and bioinformatics analyses of 104 rice varieties belonging to the major subspecies of Oryza sativa. We identified repetitive elements and recurrent copy number variation covering about 200 Mbp of the rice genome. Genotyping of over 18 million polymorphic locations within O. sativa allowed us to reconstruct the individual haplotype patterns shaping the genomic background of elite varieties used by farmers throughout the Americas. Based on a reconstruction of the alleles for the gene GBSSI, we could identify novel genetic markers for selection of varieties with high amylose content. We expect that both the analysis methods and the genomic information described here would be of great use for the rice research community and for other groups carrying on similar sequencing efforts in other crops.

The sole introduction of two single-point mutations establishes glycerol utilization in Saccharomyces cerevisiae CEN.PK derivatives

“…Manual inspection of the variants within the filtered dataset revealed a large number of heterozygous genotype calls that are generally unexpected for haploid strains. Because these heterozygous genotypes could only be the product of differences between repetitive elements or genotype errors [31, 39, 40], we further removed variants in which at least one sample showed a heterozygous genotype and variants in which copy number variation was predicted for the three samples. Only 10 variants (7 SNPs and 3 Indels) remained after applying these filters (Table 3).…”

Identification of new sources of resistance to RHBV- rice hoja blanca virus

“…The genomic region spanning from 2.81 Mbp to 3.8 Mbp was compared between Fedearroz 2000, the five new sources, and Colombia 1 (intermediate), Fedearroz 50 (highly antibiotic effect against the vector), and Bluebonnet 50 (RHBV-susceptible check). The whole genome sequences (WGS) of the former three genotypes were obtained from previous work (Duitama, Silva, Sanabria, Cruz, Quintero, Ballen… & Tohme, 2015); the WGS of Colombia 1 (IRGC 116970-1-1) and Bluebonnet 50 (IRGC 1799-1-1) were obtained from the 3K RGP (Li, Wang & Zeigler, 2014). The reads were analyzed using NGSEP (Next Generation Sequencing Eclipse Plugin) software with the parameters recommended in Duitama, Quintero, Cruz, Quintero, Hubmann, Foulquié-Moreno,... & Tohme.…”

Robust phenotyping strategies for evaluation of stem non-structural carbohydrates (NSC) in rice

“…The burgeoning availability of open-access genetic resources for rice (IRGSP, 2005; Jacquemin et al , 2013; Li et al , 2014; Schatz et al , 2014; Duitama et al , 2015; McCouch et al , 2016) supports systematic large-scale studies to dissect the genetic architecture underlying stem NSC dynamics. The MSUv7 genome assembly () has been annotated with gene models across the 12 rice chromosomes, and over 100 predicted enzyme-coding genes have putative catalytic involvement in starch and sucrose biosynthesis, degradation, and transport (Dharmawardhana et al , 2013).…”