No abstract

Orchardgrass (Dactylis glomerata L.) is a long-lived, cool-season forage grass that is commonly used for hay production. Despite its economic importance, orchardgrass genome remains relatively unexplored. In this study, we used Illumina RNA sequencing to identify gene-associated molecular markers, including simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs), as well as heat stress-induced differentially expressed genes (DEGs) in two orchardgrass genotypes, 'Baoxing' (heat resistant) and '01998' (heat susceptible). Approximately 163 million high-quality trimmed reads were generated from 207 million raw reads using the Illumina HiSeq 2000 platform. A total of 126,846 unigenes were obtained after de novo assembly of the trimmed reads, and 40,078 unigenes were identified as coding sequences (CDSs). Based on the assembled unigenes, 669,300 high-quality SNPs, including 416,099 transitions and 257,736 transversions, were contained in 75,875 unigenes. In addition, a total of 8475 microsatellites were detected in 7764 unigenes. When placed under heat stress, the total number of DEGs in 'Baoxing' (3527) was higher than in '01998' (2649), indicating that in comparison with heat-susceptible '01998', heat-resistant 'Baoxing' seems to have more unigenes that respond to heat stress. The high-throughput transcriptome sequencing of orchardgrass under heat stress provides useful information for gene identification and for the development of SNP and SSR molecular markers. The comparison of DEGs under different periods of heat stress allowed us to identify a wealth of candidate DEGs that can be further analysed in order to determine the genetic mechanisms underlying heat tolerance in orchardgrass.

Hemarthria R. Br. is an important genus of perennial forage grasses that is widely used in subtropical and tropical regions. Hemarthria grasses have made remarkable contributions to the development of animal husbandry and agro-ecosystem maintenance; however, there is currently a lack of comprehensive genomic data available for these species. In this study, we used Illumina high-throughput deep sequencing to characterize of two agriculturally important Hemarthria materials, H. compressa “Yaan” and H. altissima “1110.” Sequencing runs that used each of four normalized RNA samples from the leaves or roots of the two materials yielded more than 24 million high-quality reads. After de novo assembly, 137,142 and 77,150 unigenes were obtained for “Yaan” and “1110,” respectively. In addition, a total of 86,731 “Yaan” and 48,645 “1110” unigenes were successfully annotated. After consolidating the unigenes for both materials, 42,646 high-quality SNPs were identified in 10,880 unigenes and 10,888 SSRs were identified in 8330 unigenes. To validate the identified markers, high quality PCR primers were designed for both SNPs and SSRs. We randomly tested 16 of the SNP primers and 54 of the SSR primers and found that the majority of these primers successfully amplified the desired PCR product. In addition, high cross-species transferability (61.11–87.04%) of SSR markers was achieved for four other Poaceae species. The amount of RNA sequencing data that was generated for these two Hemarthria species greatly increases the amount of genomic information available for Hemarthria and the SSR and SNP markers identified in this study will facilitate further advancements in genetic and molecular studies of the Hemarthria genus.

No abstract

Identifying protein-coding genes in eukaryotic genomes remains a challenge in post-genome era due to the complex gene models. We applied a proteogenomics strategy to detect un-annotated protein-coding regions in mouse genome. High-accuracy tandem mass spectrometry (MS/MS) data from diverse mouse samples were generated by LTQ-Orbitrap mass spectrometer in house. Two searchable diagnostic proteomic datasets were constructed, one with all possible encoding exon junctions, and the other with all putative encoding exons, for the discovery of novel exon splicing events and novel uninterrupted protein-coding regions. Altogether 29,586 unique peptides were identified. Aligning backwards to the mouse genome, the translation of 4,471 annotated genes were validated by the known peptides; and 172 genic events were defined in mouse genome by the novel peptides. The approach in the current work can provide substantial evidences for eukaryote genome annotation in encoding genes.