An Improved Genotyping by Sequencing (GBS) Approach Offering Increased Versatility and Efficiency of SNP Discovery and Genotyping

Abstract

Highly parallel SNP genotyping platforms have been developed for some important crop species, but these platforms typically carry a high cost per sample for first-time or small-scale users. In contrast, recently developed genotyping by sequencing (GBS) approaches offer a highly cost effective alternative for simultaneous SNP discovery and genotyping. In the present investigation, we have explored the use of GBS in soybean. In addition to developing a novel analysis pipeline to call SNPs and indels from the resulting sequence reads, we have devised a modified library preparation protocol to alter the degree of complexity reduction. We used a set of eight diverse soybean genotypes to conduct a pilot scale test of the protocol and pipeline. Using ApeKI for GBS library preparation and sequencing on an Illumina GAIIx machine, we obtained 5.5 M reads and these were processed using our pipeline. A total of 10,120 high quality SNPs were obtained and the distribution of these SNPs mirrored closely the distribution of gene-rich regions in the soybean genome. A total of 39.5% of the SNPs were present in genic regions and 52.5% of these were located in the coding sequence. Validation of over 400 genotypes at a set of randomly selected SNPs using Sanger sequencing showed a 98% success rate. We then explored the use of selective primers to achieve a greater complexity reduction during GBS library preparation. The number of SNP calls could be increased by almost 40% and their depth of coverage was more than doubled, thus opening the door to an increase in the throughput and a significant decrease in the per sample cost. The approach to obtain high quality SNPs developed here will be helpful for marker assisted genomics as well as assessment of available genetic resources for effective utilisation in a wide number of species.

Genome-wide SNP discovery and genetic linkage map construction in sunflower (Helianthus annuus L.) using a genotyping by sequencing (GBS) approach

“…This was due to the high number of repetitive sequences in the genome which made tag alignments problematic (Treangen and Salzberg 2012). However, when compared with other GBS studies, the number of identified SNPs after filtering in this study (9535) was similar to the numbers reported in Rubus idaeus (9143) and soybean (10,120) (Ward et al 2013;Sonah et al 2013).…”

“…The average frequency of sunflower SNPs identified in this study was 72 kb/SNP (1 SNP every 72 kb); this is higher than soybean (100 kb/SNP) (Sonah et al 2013) and much lower than the frequency identified in oil palm (1 SNP in 0.665 kb) (Pootakham et al 2015). Again, the higher frequency of SNPs in oil palm could reflect the higher number of reads and higher coverage of the oil palm alignment (88 %).…”

Diversity and genetic analysis through DArTseq in common bean(Phaseolus vulgaris L.) germplasm from Turkey

“…DArTseq combines genome complexity reduction methods and next-generation sequencing platforms (Courtois et al, 2013;Cruz et al, 2013;Raman et al, 2014;Kilian et al, 2016). Therefore, DArTseq represents a new implementation of sequencing of complexity-reduced representations (Huang et al, 2014) and more recent applications of this concept on the nextgeneration sequencing platforms (Sonah et al, 2013;Bastien et al, 2014).…”

Perspectives on the Application of Next-generation Sequencing to the Improvement of Africa’s Staple Food Crops

“…The use of other enzyme combinations could circumvent this problem by altering the library construction [20,28]. In addition, the accuracy of base calling in complex polyploids and heterozygous individuals, of which there are several examples within the root and tuber staple crops of Africa, can also be problematic.…”

“…Sequencing DNA and RNA has become so cheap and so vast that NGS is now a basic technology for many fields of research in medicine, basic research, as well as research in agriculture. In agricultural research, NGS is applied in whole-genome sequencing (WGS), whole-genome re-sequencing (WGRS), transcriptomics, metagenomics, and reduced representation sequencing for high-throughput SNP genotyping [15,21,28,29,49]. A genome sequence becomes only useful for biological applications when the genome is annotated and genes are described and their functions revealed [50].…”