3 resultados para Expressed sequence tag analysis
Resumo:
Schistosomiasis is a chronic and debilitating disease caused by blood flukes (digenetic trematodes) of the genus Schistosoma. Schistosomes are sexually dimorphic and exhibit dramatic morphological changes during a complex lifecycle which requires subtle gene regulatory mechanisms to fulfil these complex biological processes. In the current study, a 41,982 features custom DNA microarray, which represents the most comprehensive probe coverage for any schistosome transcriptome study, was designed based on public domain and local databases to explore differential gene expression in S. japonicum. We found that approximately 1/10 of the total annotated genes in the S. japonicum genome are differentially expressed between adult males and females. In general, genes associated with the cytoskeleton, and motor and neuronal activities were readily expressed in male adult worms, whereas genes involved in amino acid metabolism, nucleotide biosynthesis, gluconeogenesis, glycosylation, cell cycle processes, DNA synthesis and genome fidelity and stability were enriched in females. Further, miRNAs target sites within these gene sets were predicted, which provides a scenario whereby the miRNAs potentially regulate these sex-biased expressed genes. The study significantly expands the expressional and regulatory characteristics of gender-biased expressed genes in schistosomes with high accuracy. The data provide a better appreciation of the biological and physiological features of male and female schistosome parasites, which may lead to novel vaccine targets and the development of new therapeutic interventions.
Resumo:
In this study, we used IGH sequence analysis to assess the maturational status of Waldenstrom's (WM) macroglobulinemia and its putative precursor immunoglobulin (Ig)-M monoclonal gammopathy of undetermined significance (MGUS). IGH sequence analysis was performed using standard methods in 23 cases (20 WM and 3 IgM MGUS as defined by consensus panel criteria). Waldenstrom's macroglobulinemia cases were characterized by heavily mutated IGH genes (median, 6.3%; range, 3.8%-13.9%) but without intraclonal variation (ICV). IgM MGUS was similarly characterized by somatic hypermutation (median, 7.5%; range, 7%-7.7%), but ICV was evident in 1 of the 3 cases. We would therefore conclude that WM is characterized by somatic hypermutation without ICV, which supports a derivation from postgerminal center/memory B cells. IgM MGUS is also characterized by somatic hypermutation but, in a manner similar to IgA/IgG MGUS, can be associated with ICV, although the significance of this remains unclear.
Resumo:
To define specific pathways important in the multistep transformation process of normal plasma cells (PCs) to monoclonal gammopathy of uncertain significance (MGUS) and multiple myeloma (MM), we have applied microarray analysis to PCs from 5 healthy donors (N), 7 patients with MGUS, and 24 patients with newly diagnosed MM. Unsupervised hierarchical clustering using 125 genes with a large variation across all samples defined 2 groups: N and MGUS/MM. Supervised analysis identified 263 genes differentially expressed between N and MGUS and 380 genes differentially expressed between N and MM, 197 of which were also differentially regulated between N and MGUS. Only 74 genes were differentially expressed between MGUS and MM samples, indicating that the differences between MGUS and MM are smaller than those between N and MM or N and MGUS. Differentially expressed genes included oncogenes/tumor-suppressor genes (LAF4, RB1, and disabled homolog 2), cell-signaling genes (RAS family members, B-cell signaling and NF-kappaB genes), DNA-binding and transcription-factor genes (XBP1, zinc finger proteins, forkhead box, and ring finger proteins), and developmental genes (WNT and SHH pathways). Understanding the molecular pathogenesis of MM by gene expression profiling has demonstrated sequential genetic changes from N to malignant PCs and highlighted important pathways involved in the transformation of MGUS to MM.