ALBERT

Description: Background: Streptococcus equi ssp. zooepidemicus (S. zooepidemicus) is an important pathogen causing swine streptococcosis in China. Pathogenicity islands (PAIs) of S. zooepidemicus have been transferred among bacteria through horizontal gene transfer (HGT) and play important roles in the adaptation and increased virulence of S. zooepidemicus. The present study used comparative genomics to examine the different pathogenicities of S. zooepidemicus. Results: Genome of S. zooepidemicus ATCC35246 (Sz35246) comprises 2,167,264-bp of a single circular chromosome, with a GC content of 41.65%. Comparative genome analysis of Sz35246, S. zooepidemicus MGCS10565 (Sz10565), Streptococcus equi. ssp. equi. 4047 (Se4047) and S. zooepidemicus H70 (Sz70) identified 320 Sz35246-specific genes, clustered into three toxin-antitoxin (TA) systems PAIs and one restriction modification system (RM system) PAI. These four acquired PAIs encode proteins that may contribute to the overall pathogenic capacity and fitness of this bacterium to adapt to different hosts. Analysis of the in vivo and in vitro transcriptomes of this bacterium revealed differentially expressed PAI genes and non-PAI genes, suggesting that Sz35246 possess mechanisms for infecting animals and adapting to a wide range of host environments. Analysis of the genome identified potential Sz35246 virulence genes. Genes of the Fim III operon were presumed to be involved in breaking the host-restriction of Sz35246. Conclusion: Genome wide comparisons of Sz35246 with three other strains and transcriptome analysis revealed novel genes related to bacterial virulence and breaking the host-restriction. Four specific PAIs, which were judged to have been transferred into Sz35246 genome through HGT, were identified for the first time. Further analysis of the TA and RM systems in the PAIs will improve our understanding of the pathogenicity of this bacterium and could lead to the development of diagnostics and vaccines.

Description: Background: Penicillium digitatum is one of the most destructive postharvest pathogen of citrus fruits, causing fruit decay and economic loss. The emergence of fungicide-resistant strains made the control of P. digitatum more difficult. While the genome of P. digitatum is available, there has been few reports about its resistant mechanism from the transcriptome perspective and there has been no large-scale functional annotation of the genome using expressed genes derived from transcriptomes. Methods: Total RNA of P. digitatum strain HS-F6 (prochloraz-resistant strain) and HS-E3 (prochloraz-susceptible strain) before and after prochloraz-treatment were extracted and sequenced on an Illumina Hiseq 2000 platform. The transcriptome data of four samples were compared and analyzed using differential expression analysis, novel transcripts prediction and alternative splicing analysis, SNP analysis and quantitative real-time PCR. Results: We present a large scale analysis about the transcriptome data of P. digitatum. The whole RNA was extracted from a prochloraz-resistant strain (HS-F6) and a prochloraz-susceptible strain (HS-E3) before and after prochloraz-treatment and sequenced by Illumina technology. A total of more than 100 million reads were generated and de novo assembled into 9760 transcripts that contained annotated genes after quality control and sequence assembling. 6625 single nucleotide variations (SNVs) were identified from the sequences aligned against the reference genome. Gene expression profiling analysis was performed upon prochloraz treatment in HS-F6 and HS-E3, and differential expression analysis was used to identify genes related to prochloraz-response and drug-resistance: there are 224 differentially expressed genes in HS-E3 and 1100 differentially expressed genes in HS-F6 after prochloraz-treatment. Moreover, gene expression profile in prochloraz-resistant strain HS-F6 is quite different from that in HS-E3 before prochloraz-treatment, 1520 differential expression genes were identified between the two strains. Gene ontology (GO) term enrichment and KEGG enrichment were then performed to classify the differential expression genes. Among these genes, there are a lot of transporter encoding genes including 14 MFS (Major Facilitator Superfamily) transporters, 8 ABC (ATP-binding cassette transporter) and 3 MATE (multidrug and toxic compound extrusion family) transporters. Meanwhile, the roles of typical MFS, ABC and MATE proteins in prochloraz resistance were investigated using real-time quantitative PCR. Conclusions: The sequencing-based transcriptome data of P. digitatum demonstrate differences between prochloraz-resistant and prochloraz-susceptible strains with prochloraz-treatment. The differences existed in expressed transcripts, splice isoforms and GO categories, which would contribute to our knowledge on the molecular mechanisms involved in drug resistance of P. digitatum.

Description: Grain development in maize is an essential process in the plant’s life cycle and is vital for use of the plant as a crop for animals and humans. However, little is known regarding the protein regulatory networ...

Description: Background: Cranberries (Vaccinium macrocarpon Ait.), renowned for their excellent health benefits, are an important berry crop. Here, we performed transcriptome sequencing of one cranberry cultivar, from fruits at two different developmental stages, on the Illumina HiSeq 2000 platform. Our main goals were to identify putative genes for major metabolic pathways of bioactive compounds and compare the expression patterns between white fruit (W) and red fruit (R) in cranberry. Results: In this study, two cDNA libraries of W and R were constructed. Approximately 119 million raw sequencing reads were generated and assembled de novo, yielding 57,331 high quality unigenes with an average length of 739 bp. Using BLASTx, 38,460 unigenes were identified as putative homologs of annotated sequences in public protein databases, including NCBI NR, NT, Swiss-Prot, KEGG, COG and GO. Of these, 21,898 unigenes mapped to 128 KEGG pathways, with the metabolic pathways, secondary metabolites, glycerophospholipid metabolism, ether lipid metabolism, starch and sucrose metabolism, purine metabolism, and pyrimidine metabolism being well represented. Among them, many candidate genes were involved in flavonoid biosynthesis, transport and regulation. Furthermore, digital gene expression (DEG) analysis identified 3,257 unigenes that were differentially expressed between the two fruit developmental stages. In addition, 14,473 simple sequence repeats (SSRs) were detected. Conclusions: Our results present comprehensive gene expression information about the cranberry fruit transcriptome that could facilitate our understanding of the molecular mechanisms of fruit development in cranberries. Although it will be necessary to validate the functions carried out by these genes, these results could be used to improve the quality of breeding programs for the cranberry and related species.