Identification of SNP and SSR Markers in Finger Millet Using Next Generation Sequencing Technologies

Finger millet is an important cereal crop in eastern Africa and southern India with excellent grain storage quality and unique ability to thrive in extreme environmental conditions. Since negligible attention has been paid to improving this crop to date, the current study used Next Generation Sequencing (NGS) technologies to develop both Simple Sequence Repeat (SSR) and Single Nucleotide Polymorphism (SNP) markers. Genomic DNA from cultivated finger millet genotypes KNE755 and KNE796 was sequenced using both Roche 454 and Illumina technologies. Non-organelle sequencing reads were assembled into 207 Mbp representing approximately 13% of the finger millet genome. We identified 10,327 SSRs and 23,285 non-homeologous SNPs and tested 101 of each for polymorphism across a diverse set of wild and cultivated finger millet germplasm. For the 49 polymorphic SSRs, the mean polymorphism information content (PIC) was 0.42, ranging from 0.16 to 0.77. We also validated 92 SNP markers, 80 of which were polymorphic with a mean PIC of 0.29 across 30 wild and 59 cultivated accessions. Seventy-six of the 80 SNPs were polymorphic across 30 wild germplasm with a mean PIC of 0.30 while only 22 of the SNP markers showed polymorphism among the 59 cultivated accessions with an average PIC value of 0.15. Genetic diversity analysis using the polymorphic SNP markers revealed two major clusters; one of wild and another of cultivated accessions. Detailed STRUCTURE analysis confirmed this grouping pattern and further revealed 2 sub-populations within wild E. coracana subsp. africana. Both STRUCTURE and genetic diversity analysis assisted with the correct identification of the new germplasm collections. These polymorphic SSR and SNP markers are a significant addition to the existing 82 published SSRs, especially with regard to the previously reported low polymorphism levels in finger millet. Our results also reveal an unexploited finger millet genetic resource that can be included in the regional breeding programs in order to efficiently optimize productivity

UGbS-Flex, a novel bioinformatics pipeline for imputation-free SNP discovery in polyploids without a reference genome: finger millet as a case study

Abstract Background Research on orphan crops is often hindered by a lack of genomic resources. With the advent of affordable sequencing technologies, genotyping an entire genome or, for large-genome species, a representative fraction of the genome has become feasible for any crop. Nevertheless, most genotyping-by-sequencing (GBS) methods are geared towards obtaining large numbers of markers at low sequence depth, which excludes their application in heterozygous individuals. Furthermore, bioinformatics pipelines often lack the flexibility to deal with paired-end reads or to be applied in polyploid species. Results UGbS-Flex combines publicly available software with in-house python and perl scripts to efficiently call SNPs from genotyping-by-sequencing reads irrespective of the species’ ploidy level, breeding system and availability of a reference genome. Noteworthy features of the UGbS-Flex pipeline are an ability to use paired-end reads as input, an effective approach to cluster reads across samples with enhanced outputs, and maximization of SNP calling. We demonstrate use of the pipeline for the identification of several thousand high-confidence SNPs with high representation across samples in an F3-derived F2 population in the allotetraploid finger millet. Robust high-density genetic maps were constructed using the time-tested mapping program MAPMAKER which we upgraded to run efficiently and in a semi-automated manner in a Windows Command Prompt Environment. We exploited comparative GBS with one of the diploid ancestors of finger millet to assign linkage groups to subgenomes and demonstrate the presence of chromosomal rearrangements. Conclusions The paper combines GBS protocol modifications, a novel flexible GBS analysis pipeline, UGbS-Flex, recommendations to maximize SNP identification, updated genetic mapping software, and the first high-density maps of finger millet. The modules used in the UGbS-Flex pipeline and for genetic mapping were applied to finger millet, an allotetraploid selfing species without a reference genome, as a case study. The UGbS-Flex modules, which can be run independently, are easily transferable to species with other breeding systems or ploidy levels

Additional file 8: of UGbS-Flex, a novel bioinformatics pipeline for imputation-free SNP discovery in polyploids without a reference genome: finger millet as a case study

Table S5. Genotypic data for the MD-20 x Okhale-1 population. (XLSX 2444 kb

Additional file 5: of UGbS-Flex, a novel bioinformatics pipeline for imputation-free SNP discovery in polyploids without a reference genome: finger millet as a case study

Table S3. Number and percentage of ApeKI sites present in PstI/MspI and PstI/MspI + ApeKI digests. (DOCX 12 kb

Additional file 3: of UGbS-Flex, a novel bioinformatics pipeline for imputation-free SNP discovery in polyploids without a reference genome: finger millet as a case study

Table S1A. Summary statistics obtained for each of the three enzyme combinations for subsets of reads; Entries are grouped by read number. Table S1B. Summary statistics obtained for each of the three enzyme combinations for subsets of reads; Entries are grouped by enzyme combination. (XLSX 29 kb

Additional file 6: of UGbS-Flex, a novel bioinformatics pipeline for imputation-free SNP discovery in polyploids without a reference genome: finger millet as a case study

Figure S2. Comparison of the number of SNPs identified using different SNP callers (UG = Unified Genotyper; HC=Haplotype Caller) and different GBS references (Ref50: tags present in ≥50% of the samples; Ref70: tags present in ≥70% of the samples; Ref50_98: tags present in ≥50% of the samples and only 1 tag retained for tags with ≥98% homology; Ref70_98: tags present in ≥70% of the samples and only 1 tag retained for tags with ≥98% homology. (PPTX 7261 kb

Additional file 11: of UGbS-Flex, a novel bioinformatics pipeline for imputation-free SNP discovery in polyploids without a reference genome: finger millet as a case study

Figure S4. Comparison of genetic maps generated using MSTmap (left-hand side) and MAPMAKER (right-hand side). Nearly 65% of markers were reordered in MAPMAKER compared to MSTmap maps. The markers that occupied a different relative position in the two maps are connected by a line. (PPTX 170 kb

Additional file 9: of UGbS-Flex, a novel bioinformatics pipeline for imputation-free SNP discovery in polyploids without a reference genome: finger millet as a case study

Table S6. Genetic maps comprising all markers. (XLSX 717 kb

Additional file 1: of UGbS-Flex, a novel bioinformatics pipeline for imputation-free SNP discovery in polyploids without a reference genome: finger millet as a case study

Data S1. System requirements and UGbS-Flex commands for GBS reference generation, SNP calling and further SNP processing. (PDF 165 kb

Additional file 10: of UGbS-Flex, a novel bioinformatics pipeline for imputation-free SNP discovery in polyploids without a reference genome: finger millet as a case study

Figure S3. Effect of the presence of a deletion in a sample relative to the GBS reference allele. A gapped alignment is formed and the 3′ end extends beyond the junction of the forward and reverse reads in the GBS reference resulting in the calling of a SNP at that position. The Integrative Genomics Viewer (Robinson et al. 2011, Nature Biotechnology 29: 24–26; Thorvaldsdóttir et al. 2013, Briefings in Bioinformatics 14: 178–192) was used for visualization. (PPTX 75 kb