Adapting Genotyping-by-Sequencing for Rice F2 Populations

Abstract

Rapid and cost-effective genotyping of large mapping populations can be achieved by sequencing a reduced representation of the genome of every individual in a given population, and using that information to generate genetic markers. A customized genotyping-by-sequencing (GBS) pipeline was developed to genotype a rice F2 population from a cross of Oryza sativa ssp. japonica cv. Nipponbare and the African wild rice species O. longistaminata. While most GBS pipelines aim to analyze mainly homozygous populations, we attempted to genotype a highly heterozygous F2 population. We show how species-and population-specific improvements of established protocols can drastically increase sample throughput and genotype quality. Using as few as 50,000 reads for some individuals (134,000 reads on average), we were able to generate up to 8154 informative SNP markers in 1081 F2 individuals. Additionally, the effects of enzyme choice, read coverage, and data postprocessing are evaluated. Using GBS-derived markers, we were able to assemble a genetic map of 1536 cM. To demonstrate the usefulness of our GBS pipeline, we determined quantitative trait loci (QTL) for the number of tillers. We were able to map four QTL to chromosomes 1, 3, 4, and 8, and partially confirm their effects using introgression lines. We provide an example of how to successfully use GBS with heterozygous F2 populations. By using the comparatively low-cost MiSeq platform, we show that the GBS method is flexible and cost-effective, even for smaller laboratories.

Diversity analysis and genome-wide association studies of grain shape and eating quality traits in rice (Oryza sativa L.) using DArT markers

“…More recently with the advances in next generation sequencing (NGS) technologies, genotyping by sequencing (GBS) has emerged as a promising genomic approach for simultaneous exploration of plant genetic diversity and molecular marker discovery [ 24 , 25 , 26 ]. Thus, GBS has effectively been used for single-nucleotide polymorphisms (SNP) marker discovery and QTL identification of tightly linked marker-trait associations [ 27 , 28 ] and in the application of genomic selection of complex traits for crop improvement [ 29 , 30 ]. The GBS approach is therefore considered an important cost-effective tool for population genetics, QTL discovery, high-resolution mapping and for genomic selection in plant breeding programs [ 25 , 29 ].…”

“…Thus, GBS has effectively been used for single-nucleotide polymorphisms (SNP) marker discovery and QTL identification of tightly linked marker-trait associations [ 27 , 28 ] and in the application of genomic selection of complex traits for crop improvement [ 29 , 30 ]. The GBS approach is therefore considered an important cost-effective tool for population genetics, QTL discovery, high-resolution mapping and for genomic selection in plant breeding programs [ 25 , 29 ].…”

A CIN-like TCP transcription factor (LsTCP4) having retrotransposon insertion associates with a shift from Salinas type to Empire type in crisphead lettuce (Lactuca sativa L.)

“…Biallelic tags having either missing value with more than half of F 2 individuals or a P-value of <0.001 based on the chi-squared test were eliminated from the genotype data. Because the genotype data from the NGS approach had the drawback of a large amount of missing data 24,25 in most cases, we applied the ABHgenotypeR package of R 25 for post-data correction and imputation. The parameter of maxHapLength in ABHgenotypeR was adjusted to five.…”

Peer Review #2 of "Characterization of introgression from the teosinte Zea mays ssp. mexicana to Mexican highland maize (v0.1)"

“…The resulting set of 10, 323 SNPs were transformed to hapmap format, and filtered to identify segregating sites (allele frequency > 0.2 and < 0.8), thinned to minimum spacing of 1 kb, and transformed to ABH format (A: PT; B: RV) using TASSEL v5.0 (Bradbury et al 2007). The data were inspected visually using ABHgenotypeR v1.0.1 (Furuta et al 2017), and passed to the ABHgenotypeR pipeline to impute missing data, corrected for under-called heterozygous sites, and corrected for single interspersed alleles using a maximum haplotype length of 6. The proportion of missing sites dropped from 0.57 to 0.02 following imputation.…”