BackgroundResearch 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.ResultsUGbS-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.ConclusionsThe 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.Electronic supplementary materialThe online version of this article (10.1186/s12870-018-1316-3) contains supplementary material, which is available to authorized users.
Small millets are very promising agricultural entity to ensure global food security. They gained remarkable importance in agriculture due to their resilience to climatic changes and increasing demand for nutritious food and feed. The genetic variability in the core and mini-core germplasm of small millets was characterized for nutritional composition and capacity to tolerate abiotic stresses that can be infused in breeding programs. Other than the foxtail millet, availability of genomic information in small millets is far below the mark for use in marker-assisted breeding and other genetic improvement programs. The genome sequence of foxtail millet has recently triggered a plethora of post-genomic analysis and envisaged foxtail millet as a model organism for the C 4 grasses and bioenergy research. Recent developments in the next-generation sequencing technologies enabled us, with the simultaneous discovery of high-throughput markers and multiplexed genotyping of germplasm, to speedup markerassisted breeding. In this context, an in-depth analysis of the wealth of diverse germplasm resources and future perspectives of integrating genomics in genome-wide marker-trait association and breeding in small millets is worthy. ABBREVIATIONS cDNA D complementary DNA cM D centimorgan DREB D dehydration response element binding FAO D Food and Agricultural Organization ICAR D Indian Council of Agricultural Research ICRISAT D International Crops Research Institute for the Semi-Arid Tropics Mb D mega basepairs Mha D million hectares Mt D million tonnes Mya D million years ago NARS D National Agricultural Research System NCBI D National Center for Biotechnology Information NGS D next-generation sequencing PCR D polymerase chain reaction PGR D plant genetic resources SNP D single nucleotide polymorphism SSR D simple sequence repeat QTLs D quantitative trait loci
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