Background: Schistosomiasis is one of the most prevalent parasitic diseases worldwide and is a public health problem. Schistosoma mansoni is the most widespread species responsible for schistosomiasis in the Americas, Middle East and Africa. Adult female worms (mated to males) release eggs in the hepatic portal vasculature and are the principal cause of morbidity. Comparative separate transcriptomes of female and male adult worms were previously assessed with using microarrays and Serial Analysis of Gene Expression (SAGE), thus limiting the possibility of finding novel genes. Moreover, the egg transcriptome was analyzed only once with limited bacterially cloned cDNA libraries.
Methodology/principal Findings: To compare the gene expression of S. mansoni eggs, females, and males, we performed RNA-Seq on these three parasite forms using 454/Roche technology and reconstructed the transcriptome using Trinity de novo assembly. The resulting contigs were mapped to the genome and were cross-referenced with predicted Smp genes and H3K4me3 ChIP-Seq public data. For the first time, we obtained separate, unbiased gene expression profiles for S. mansoni eggs and female and male adult worms, identifying enriched biological processes and specific enriched functions for each of the three parasite forms. Transcripts with no match to predicted genes were analyzed for their protein-coding potential and the presence of an encoded conserved protein domain. A set of 232 novel protein-coding genes with putative functions related to reproduction, metabolism, and cell biogenesis was detected, which contributes to the understanding of parasite biology.
Conclusions/significance: Large-scale RNA-Seq analysis using de novo assembly associated with genome-wide information for histone marks in the vicinity of gene models constitutes a new approach to transcriptome analysis that has not yet been explored in schistosomes. Importantly, all data have been consolidated into a UCSC Genome Browser search- and download-tool (http://schistosoma.usp.br/). This database provides new ways to explore the schistosome genome and transcriptome and will facilitate molecular research on this important parasite.
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http://dx.doi.org/10.1371/journal.pntd.0004334 | DOI Listing |
Brief Bioinform
November 2024
Institute for Molecular Bioscience, The University of Queensland, 306 Carmody Road, St Lucia, Brisbane, QLD 4072, Australia.
Regulatory genes are critical determinants of cellular responses in development and disease, but standard RNA sequencing (RNA-seq) analysis workflows, such as differential expression analysis, have significant limitations in revealing the regulatory basis of cell identity and function. To address this challenge, we present the TRIAGE R package, a toolkit specifically designed to analyze regulatory elements in both bulk and single-cell RNA-seq datasets. The package is built upon TRIAGE methods, which leverage consortium-level H3K27me3 data to enrich for cell-type-specific regulatory regions.
View Article and Find Full Text PDFBrief Bioinform
November 2024
State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, 2 Sipailou, Xuanwu District, Nanjing 210096, China.
Spatial transcriptomics technologies have been extensively applied in biological research, enabling the study of transcriptome while preserving the spatial context of tissues. Paired with spatial transcriptomics data, platforms often provide histology and (or) chromatin images, which capture cellular morphology and chromatin organization. Additionally, single-cell RNA sequencing (scRNA-seq) data from matching tissues often accompany spatial data, offering a transcriptome-wide gene expression profile of individual cells.
View Article and Find Full Text PDFBrief Bioinform
November 2024
School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), Buk-gu, Gwangju 61005, Republic of Korea.
Combination therapies have emerged as a promising approach for treating complex diseases, particularly cancer. However, predicting the efficacy and safety profiles of these therapies remains a significant challenge, primarily because of the complex interactions among drugs and their wide-ranging effects. To address this issue, we introduce DD-PRiSM (Decomposition of Drug-Pair Response into Synergy and Monotherapy effect), a deep-learning pipeline that predicts the effects of combination therapy.
View Article and Find Full Text PDFBrief Bioinform
November 2024
Department of Electronic Engineering, Tsinghua University, 100084 Beijing, China.
Single-cell multi-omics techniques, which enable the simultaneous measurement of multiple modalities such as RNA gene expression and Assay for Transposase-Accessible Chromatin (ATAC) within individual cells, have become a powerful tool for deciphering the intricate complexity of cellular systems. Most current methods rely on motif databases to establish cross-modality relationships between genes from RNA-seq data and peaks from ATAC-seq data. However, these approaches are constrained by incomplete database coverage, particularly for novel or poorly characterized relationships.
View Article and Find Full Text PDFMol Biol Rep
January 2025
Goat Genetics and Breeding Division, ICAR-Central Institute for Research On Goats, Makhdoom, Farah, Mathura, 281 122, Uttar Pradesh, India.
Background: Extracellular matrix (ECM) proteins play a crucial role in regulating the biological properties of adherent cells. For cryopreserved fibroblasts, a favourable ECM environment can help restore their natural morphology and function more rapidly, minimizing post-thaw stress responses.
Methods And Results: This study explored the functional responses of cryopreserved enriched caprine adult dermal fibroblast (cadFibroblast) cells to structural [collagen-IV and rat tail collagen (RTC)] and adhesion ECM proteins (laminin, fibronectin, and vitronectin) under in vitro culture conditions.
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