Lentil (Lens culinaris ssp. culinaris) is a nutritious and affordable pulse with an ancient crop domestication history. The genus Lens consists of seven taxa, however, there are many discrepancies in the taxon and gene pool classification of lentil and its wild relatives. Due to the narrow genetic basis of cultivated lentil, there is a need towards better understanding of the relationships amongst wild germplasm to assist introgression of favourable genes into lentil breeding programs. Genotyping-by-sequencing (GBS) is an easy and affordable method that allows multiplexing of up to 384 samples or more per library to generate genome-wide single nucleotide Polymorphism (SNP) markers. In this study, we aimed to characterize our lentil germplasm collection using a two-enzyme GBS approach. We constructed two 96-plex GBS libraries with a total of 60 accessions where some accessions had several samples and each sample was sequenced in two technical replicates. We developed an automated GBS pipeline and detected a total of 266,356 genome-wide SNPs. After filtering low quality and redundant SNPs based on haplotype information, we constructed a maximum-likelihood tree using 5,389 SNPs. The phylogenetic tree grouped the germplasm collection into their respective taxa with strong support. Based on phylogenetic tree and STRUCTURE analysis, we identified four gene pools, namely L. culinaris/L. orientalis/L. tomentosus, L. lamottei/L. odemensis, L. ervoides and L. nigricans which form primary, secondary, tertiary and quaternary gene pools, respectively. We discovered sequencing bias problems likely due to DNA quality and observed severe run-to-run variation in the wild lentils. We examined the authenticity of the germplasm collection and identified 17% misclassified samples. Our study demonstrated that GBS is a promising and affordable tool for screening by plant breeders interested in crop wild relatives.

BackgroundAcacia auriculiformis × Acacia mangium hybrids are commercially important trees for the timber and pulp industry in Southeast Asia. Increasing pulp yield while reducing pulping costs are major objectives of tree breeding programs. The general monolignol biosynthesis and secondary cell wall formation pathways are well-characterized but genes in these pathways are poorly characterized in Acacia hybrids. RNA-seq on short-read platforms is a rapid approach for obtaining comprehensive transcriptomic data and to discover informative sequence variants.ResultsWe sequenced transcriptomes of A. auriculiformis and A. mangium from non-normalized cDNA libraries synthesized from pooled young stem and inner bark tissues using paired-end libraries and a single lane of an Illumina GAII machine. De novo assembly produced a total of 42,217 and 35,759 contigs with an average length of 496 bp and 498 bp for A. auriculiformis and A. mangium respectively. The assemblies of A. auriculiformis and A. mangium had a total length of 21,022,649 bp and 17,838,260 bp, respectively, with the largest contig 15,262 bp long. We detected all ten monolignol biosynthetic genes using Blastx and further analysis revealed 18 lignin isoforms for each species. We also identified five contigs homologous to R2R3-MYB proteins in other plant species that are involved in transcriptional regulation of secondary cell wall formation and lignin deposition. We searched the contigs against public microRNA database and predicted the stem-loop structures of six highly conserved microRNA families (miR319, miR396, miR160, miR172, miR162 and miR168) and one legume-specific family (miR2086). Three microRNA target genes were predicted to be involved in wood formation and flavonoid biosynthesis. By using the assemblies as a reference, we discovered 16,648 and 9,335 high quality putative Single Nucleotide Polymorphisms (SNPs) in the transcriptomes of A. auriculiformis and A. mangium, respectively, thus yielding useful markers for population genetics studies and marker-assisted selection.ConclusionWe have produced the first comprehensive transcriptome-wide analysis in A. auriculiformis and A. mangium using de novo assembly techniques. Our high quality and comprehensive assemblies allowed the identification of many genes in the lignin biosynthesis and secondary cell wall formation in Acacia hybrids. Our results demonstrated that Next Generation Sequencing is a cost-effective method for gene discovery, identification of regulatory sequences, and informative markers in a non-model plant.

A change in the timing or rate of developmental events throughout ontogeny is referred to as heterochrony, and it is a major evolutionary process in plants and animals. We investigated the genetic basis for natural variation in the timing of vegetative phase change in the tree Eucalyptus globulus, which undergoes a dramatic change in vegetative morphology during the juvenile-to-adult transition. Quantitative trait loci analysis in an outcross F2 family derived from crosses between individuals from a coastal population of E. globulus with precocious vegetative phase change and individuals from populations in which vegetative phase change occurs several years later implicated the microRNA EglMIR156.5 as a potential contributor to this heterochronic difference. Additional evidence for the involvement of EglMIR156.5 was provided by its differential expression in trees with early and late phase change. Our findings suggest that changes in the expression of miR156 underlie natural variation in vegetative phase change in E. globulus, and may also explain interspecific differences in the timing of this developmental transition.

BackgroundNext Generation Sequencing has provided comprehensive, affordable and high-throughput DNA sequences for Single Nucleotide Polymorphism (SNP) discovery in Acacia auriculiformis and Acacia mangium. Like other non-model species, SNP detection and genotyping in Acacia are challenging due to lack of genome sequences. The main objective of this study is to develop the first high-throughput SNP genotyping assay for linkage map construction of A. auriculiformis x A. mangium hybrids.ResultsWe identified a total of 37,786 putative SNPs by aligning short read transcriptome data from four parents of two Acacia hybrid mapping populations using Bowtie against 7,839 de novo transcriptome contigs. Given a set of 10 validated SNPs from two lignin genes, our in silico SNP detection approach is highly accurate (100%) compared to the traditional in vitro approach (44%). Further validation of 96 SNPs using Illumina GoldenGate Assay gave an overall assay success rate of 89.6% and conversion rate of 37.5%. We explored possible factors lowering assay success rate by predicting exon-intron boundaries and paralogous genes of Acacia contigs using Medicago truncatula genome as reference. This assessment revealed that presence of exon-intron boundary is the main cause (50%) of assay failure. Subsequent SNPs filtering and improved assay design resulted in assay success and conversion rate of 92.4% and 57.4%, respectively based on 768 SNPs genotyping. Analysis of clustering patterns revealed that 27.6% of the assays were not reproducible and flanking sequence might play a role in determining cluster compression. In addition, we identified a total of 258 and 319 polymorphic SNPs in A. auriculiformis and A. mangium natural germplasms, respectively.ConclusionWe have successfully discovered a large number of SNP markers in A. auriculiformis x A. mangium hybrids using next generation transcriptome sequencing. By using a reference genome from the most closely related species, we converted most SNPs to successful assays. We also demonstrated that Illumina GoldenGate genotyping together with manual clustering can provide high quality genotypes for a non-model species like Acacia. These SNPs markers are not only important for linkage map construction, but will be very useful for hybrid discrimination and genetic diversity assessment of natural germplasms in the future.

Microsatellite instability (MSI) is a molecular signature of mismatch repair deficiency (dMMR), a predictive marker of immune checkpoint inhibitor therapy response. Despite its recognized pan-cancer value, most methods only support detection of this signature in colorectal cancer. In addition to the tissue-specific differences that impact the sensitivity of MSI detection in other tissues, the performance of most methods is also affected by patient ethnicity, tumor content, and other sample-specific properties. These limitations are particularly important when only tumor samples are available and restrict the performance and adoption of MSI testing. Here we introduce MSIdetect, a novel solution for NGS-based MSI detection. MSIdetect models the impact of indel burden and tumor content on read coverage at a set of homopolymer regions that we found are minimally impacted by sample-specific factors. We validated MSIdetect in 139 Formalin-Fixed Paraffin-Embedded (FFPE) clinical samples from colorectal and endometrial cancer as well as other more challenging tumor types, such as glioma or sebaceous adenoma or carcinoma. Based on analysis of these samples, MSIdetect displays 100% specificity and 96.3% sensitivity. Limit of detection analysis supports that MSIdetect is sensitive even in samples with relatively low tumor content and limited microsatellite instability. Finally, the results obtained using MSIdetect in tumor-only data correlate well (R=0.988) with what is obtained using tumor-normal matched pairs, demonstrating that the solution addresses the challenges posed by MSI detection from tumor-only data. The accuracy of MSI detection by MSIdetect in different cancer types coupled with the flexibility afforded by NGS-based testing will support the adoption of MSI testing in the clinical setting and increase the number of patients identified that are likely to benefit from immune checkpoint inhibitor therapy.