Project description:This dataset includes RNAseq data of 7 tissues/developmental stages of Lathyrus sativus genotype LSWT11 and 2 tissues with drought- and well-watered treatments of Lathyrus sativus genotypes LS007 and Mahateora. These data were used in the functional annotation pipeline of the Rbp1.0 genome assembly of LS007. The multi-tissue transcriptome was also used to support gene candidate identification by mRNA abundance. Also included is Hi-C sequencing data used to scaffold the assembly into pseudochromosomes
Project description:To gain insights into the molecular mechnism governing the drug resistance of Eimeria tenella, two drug-resistant strains of E. tenella, maduramicin-resistant (MRR) strain and diclazuril-resistant (DZR) strain were induced.We carried out comparative transcriptome analyses of a drug-sensitive strain (DS) and two drug-resistant strains (MRR and DZR) of E. tenella by RNA-seqencing. A total of 1070 DEGs, 672 upregulated and 398 downregulated, were identified in MRR vs. DS; and 379 DEGs, 330 upregulated and 49 downregulated, were detected in DZR vs. DS. Functional annotation analysis identified several DEGs coding for proteins associated with catalytic activity in the DZR strain that were involved in glycolysis and the tricarboxylic acid (TCA) cycle. Other DEGs were associated with ion binding and ion transmembrane transporter activity in the MRR strain. Some DEGs coded for surface antigens that were downregulated in two drug-resistant strains involved invasion, pathogenesis, and host–parasite interactions.These results contribute to developing rapid molecular methods to detect drug resistance of Eimeria spp. in poultry.
Project description:With the emergence of zebrafish as an important model organism, a concerted effort has been made to study its transcriptome. This effort is limited by gaps in zebrafish annotation, which is especially pronounced concerning transcripts dynamically expressed during zygotic genome activation (ZGA). To date, short read sequencing has been the principal technology for zebrafish transcriptome annotation. In part because these sequence reads are too short for assembly methods to resolve the full complexity of the transcriptome, the current annotation is rudimentary. By providing direct observation of full-length transcripts, recently refined long-read sequencing platforms can dramatically improve annotation coverage and accuracy. Here, we leveraged the SMRT platform to study the early ZGA-stage zebrafish transcriptome. Our analysis revealed additional novelty and complexity in the zebrafish transcriptome, identifying 2748 high confidence novel transcripts that originated from previously unannotated loci and 1835 new isoforms in previously annotated genes.
Project description:Purpose: The goal of this study is to provided a comprehensive genomic information for functional genomic studies in Q. mongolica. Methods:The Quercus mongolica leaves were generated by deep sequencing, using Illumina Hiseq 4000. The high-quality reads were obtained by removing the reads that contained adaptor contamination, low quality bases and undetermined bases.The transcriptome were de novo assembly. Results:A total of 52934562 raw reads were obtained from Illumina sequencing platform. After filtering out the low quality reads, we obtained 52076914 clean reads, which assembled into 39130 transcripts with a mean length of 742 bp and GC content of 42.12%, and 24196 unigenes with a mean length of 732 bp and GC content of 42.34%, based on Trinity assembly platform. Conclusions:RNA-Seq was applied to polyadenylate-enriched mRNAs from leaves of Q. mongolica to obtain the transcriptome. De novo assembly was then applied followed by gene annotation and functional classification. The SSRs and SNPs were also obtained using assembled transcripts as reference sequences. The results of this study lay the foundation for further research on genetic diversity of Quercus.
Project description:The horse, like a majority of animal species, has a limited amount of species-specific expressed sequence data available in public databases. As a result, structural models for a majority of genes defined in the equine genome are predictions based on ab initio sequence analysis or the projection of gene structures from other mammalian species. The current study used Illumina-based sequencing of messenger RNA (RNA-seq) to help refine structural annotation of equine protein-coding genes and for a preliminary assessment of gene expression patterns. Sequencing of mRNA from eight equine tissues generated 293,758,105 thirty five-base sequence tags, equaling 10.28 giga-basepairs of total sequence data. The tag alignments represent approximately 208X coverage of the equine mRNA transcriptome and confirmed transcriptional activity for roughly 90% of the protein-coding gene structures predicted by Ensembl and NCBI. Tag coverage was sufficient to define structural annotation for 11,356 genes, while also identifying an additional 456 transcripts with exon/intron features that are not listed by either Ensembl or NCBI. Genomic locus data and intervals for the protein-coding genes predicted by the Ensembl and NCBI annotation pipelines were combined with 75,116 RNA-seq derived transcriptional units to generate a consensus equine protein-coding gene set of 20,302 defined loci. Gene ontology annotation was used to compare the functional and structural categories of genes expressed in either a tissue-restricted pattern or broadly across all tissue samples. Examination of 8 equine RNA samples representing 6 distinct tissues