No abstract

Simple sequence repeats (SSRs), also referred to as microsatellites, are highly variable tandem DNAs that are widely used as genetic markers. The increasing availability of whole-genome and transcript sequences provides information resources for SSR marker development. However, efficient software is required to efficiently identify and display SSR information along with other gene features at a genome scale. We developed novel software package Genome-wide Microsatellite Analyzing Tool Package (GMATA) integrating SSR mining, statistical analysis and plotting, marker design, polymorphism screening and marker transferability, and enabled simultaneously display SSR markers with other genome features. GMATA applies novel strategies for SSR analysis and primer design in large genomes, which allows GMATA to perform faster calculation and provides more accurate results than existing tools. Our package is also capable of processing DNA sequences of any size on a standard computer. GMATA is user friendly, only requires mouse clicks or types inputs on the command line, and is executable in multiple computing platforms. We demonstrated the application of GMATA in plants genomes and reveal a novel distribution pattern of SSRs in 15 grass genomes. The most abundant motifs are dimer GA/TC, the A/T monomer and the GCG/CGC trimer, rather than the rich G/C content in DNA sequence. We also revealed that SSR count is a linear to the chromosome length in fully assembled grass genomes. GMATA represents a powerful application tool that facilitates genomic sequence analyses. GAMTA is freely available at http://sourceforge.net/projects/gmata/?source=navbar.

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.

Background: Low temperature restricts the planting range of all crops, but cold acclimation induces adaption to cold stress in many plants. Camellia sinensis, a perennial evergreen tree that is the source of tea, is mainly grown in warm areas. Camellia sinensis var. sinensis (CSS) has greater cold tolerance than Camellia sinensis var. assamica (CSA). To gain deep insight into the molecular mechanisms underlying cold adaptation, we investigated the physiological responses and transcriptome profiles by RNA-Seq in two tea varieties, cold resistant SCZ (classified as CSS) and cold susceptible YH9 (classified as CSA), during cold acclimation. Results: Under freezing stress, lower relative electrical conductivity and higher chlorophyll fluorescence (Fv/Fm) values were detected in SCZ than in YH9 when subjected to freezing acclimation. During cold treatment, 6072 and 7749 DEGs were observed for SCZ and YH9, respectively. A total of 978 DEGs were common for both SCZ and YH9 during the entire cold acclimation process. DEGs were enriched in pathways of photosynthesis, hormone signal transduction, and transcriptional regulation of plant-pathogen interactions. Further analyses indicated that decreased expression of Lhca2 and higher expression of SnRK2.8 are correlated with cold tolerance in SCZ. Conclusions: Compared with CSA, CSS was significantly more resistant to freezing after cold acclimation, and this increased resistance was associated with an earlier expression of cold-induced genes. Because the greater transcriptional differentiation during cold acclimation in SCZ may contribute to its greater cold tolerance, our studies identify specific genes involved in photoinhibition, ABA signal conduction, and plant immunity that should be studied for understanding the processes involved in cold tolerance. Marker-assisted breeding focused on the allelic variation at these loci provides an avenue for the possible generation of CSA cultivars that have CSS-level cold tolerance.