Dataset Information

Genome-wide identification of Schistosoma japonicum microRNAs using a deep-sequencing approach.

ABSTRACT:

Background

Human schistosomiasis is one of the most prevalent and serious parasitic diseases worldwide. Schistosoma japonicum is one of important pathogens of this disease. MicroRNAs (miRNAs) are a large group of non-coding RNAs that play important roles in regulating gene expression and protein translation in animals. Genome-wide identification of miRNAs in a given organism is a critical step to facilitating our understanding of genome organization, genome biology, evolution, and posttranscriptional regulation.

Methodology/principal findings

We sequenced two small RNA libraries prepared from different stages of the life cycle of S. japonicum, immature schistosomula and mature pairing adults, through a deep DNA sequencing approach, which yielded approximately 12 million high-quality short sequence reads containing a total of approximately 2 million non-redundant tags. Based on a bioinformatics pipeline, we identified 176 new S. japonicum miRNAs, of which some exhibited a differential pattern of expression between the two stages. Although 21 S. japonicum miRNAs are orthologs of known miRNAs within the metazoans, some nucleotides at many positions of Schistosoma miRNAs, such as miR-8, let-7, miR-10, miR-31, miR-92, miR-124, and miR-125, are indeed significantly distinct from other bilaterian orthologs. In addition, both miR-71 and some miR-2 family members in tandem are found to be clustered in a reversal direction model on two genomic loci, and two pairs of novel S. japonicum miRNAs were derived from sense and antisense DNA strands at the same genomic loci.

Conclusions/significance

The collection of S. japonicum miRNAs could be used as a new platform to study the genomic structure, gene regulation and networks, evolutionary processes, development, and host-parasite interactions. Some S. japonicum miRNAs and their clusters could represent the ancestral forms of the conserved orthologues and a model for the genesis of novel miRNAs.

SUBMITTER: Huang J

PROVIDER: S-EPMC2785426 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature

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Publications

Genome-wide identification of Schistosoma japonicum microRNAs using a deep-sequencing approach.

Huang Jian J Hao Pei P Chen Hui H Hu Wei W Yan Qing Q Liu Feng F Han Ze-Guang ZG

PloS one 20091208 12

<h4>Background</h4>Human schistosomiasis is one of the most prevalent and serious parasitic diseases worldwide. Schistosoma japonicum is one of important pathogens of this disease. MicroRNAs (miRNAs) are a large group of non-coding RNAs that play important roles in regulating gene expression and protein translation in animals. Genome-wide identification of miRNAs in a given organism is a critical step to facilitating our understanding of genome organization, genome biology, evolution, and posttr ...[more]

PMID: 19997615

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Project description:BackgroundSchistosomiasis japonica remains a major public health problem in China. Its pathogen, Schistosoma japonicum has a complex life cycle and a unique repertoire of genes expressed at different life cycle stages. Exploring schistosome gene regulation will yield the best prospects for new drug targets and vaccine candidates. MicroRNAs (miRNAs) are a highly conserved class of noncoding RNA that control many biological processes by sequence-specific inhibition of gene expression. Although a large number of miRNAs have been identified from plants to mammals, it remains no experimental proof whether schistosome exist miRNAs.Methodology and resultsWe have identified novel miRNAs from Schistosoma japonicum by cloning and sequencing a small (18-26 nt) RNA cDNA library from the adult worms. Five novel miRNAs were identified from 227 cloned RNA sequences and verified by Northern blot. Alignments of the miRNAs with corresponding family members indicated that four of them belong to a metazoan miRNA family: let-7, miR-71, bantam and miR-125. The fifth potentially new (non conserved) miRNA appears to belong to a previously undescribed family in the genus Schistosome. The novel miRNAs were designated as sja-let-7, sja-miR-71, sja-bantam, sja-miR-125 and sja-miR-new1, respectively. Expression of sja-let-7, sja-miR-71 and sja-bantam were analyzed in six stages of the life cycle, i.e. egg, miracidium, sporocyst, cercaria, schistosomulum, and adult worm, by a modified stem-loop reverse transcribed polymerase chain reaction (RT-PCR) method developed in our laboratory. The expression patterns of these miRNAs were highly stage-specific. In particular, sja-miR-71 and sja-bantam expression reach their peaks in the cercaria stage and then drop quickly to the nadirs in the schistosomulum stage, following penetration of cercaria into a mammalian host.ConclusionsAuthentic miRNAs were identified for the first time in S. japonicum, including a new schistosome family member. The different expression patterns of the novel miRNAs over the life stages of S. japonicum suggest that they may mediate important roles in Schistosome growth and development.

Project description:BackgroundSmall endogenous non-coding RNAs (sncRNAs) such as small interfering RNA (siRNA), microRNA and other small RNA transcripts are derived from distinct loci in the genome and play critical roles in RNA-mediated gene silencing mechanisms in plants and metazoa. They are approximately 22 nucleotides long; regulate mRNA stability through perfect or imperfect match to the targets. The biological activities of sncRNAs have been related to many biological events, from resistance to microbe infections to cellular differentiation. The development of the zoonotic parasite Schistosoma japonicum parasite includes multiple steps of morphological alterations and biological differentiations, which provide a unique model for studies on the functions of small RNAs. Characterization of the genome-wide transcription of the sncRNAs will be a major step in understanding of the parasite biology. The objective of this study is to investigate the transcriptional profile and potential function of the small non-coding RNAs in the development of S. japanicum.ResultsThe endogenous siRNAs were found mainly derived from transposable elements (TE) or transposons and the natural antisense transcripts (NAT). In contrast to other organisms, the TE-derived siRNAs in S. japonicum were more predominant than other sncRNAs including microRNAs (miRNAs). Further, there were distinct length and 3'end variations in the sncRNAs, which were associated with the developmental differentiation of the parasite. Among the identified miRNA transcripts, there were 38 unique to S. japonicum and 16 that belonged to 13 miRNA families are common to other metazoan lineages. These miRNAs were either ubiquitously expressed, or they exhibited specific expression patterns related to the developmental stages or sex. Genes that encoded miRNAs are mainly located in clusters within the genome of S. japonicum. However, genes within one cluster could be differentially transcribed, which suggested that individual genes might be regulated by distinct mechanisms during parasite development.ConclusionsMany miRNA and endogenous siRNA transcripts were identified in S. japonicum and the amount of siRNA was at least 4.4 and 1.6 times more than that of miRNA in both schistosomulum and adult worm stages respectively. SiRNAs are mainly derived from transposable elements (or transposons); while natural antisense transcripts (NAT)-derived siRNAs were much less. A majority of miRNA transcripts identified in the parasite were species-specific and the expression of certain miRNAs was found developmentally regulated. Both miRNA and siRNAs are potentially important regulators in the development of schistosomal parasites.

Project description:BackgroundIn areas where schistosomiasis control programs have been implemented, morbidity and prevalence have been greatly reduced. However, to sustain these reductions and move towards interruption of transmission, new tools for disease surveillance are needed. Genomic methods have the potential to help trace the sources of new infections, and allow us to monitor drug resistance. Large-scale genotyping efforts for schistosome species have been hindered by cost, limited numbers of established target loci, and the small amount of DNA obtained from miracidia, the life stage most readily acquired from humans. Here, we present a method using next generation sequencing to provide high-resolution genomic data from S. japonicum for population-based studies.Methodology/principal findingsWe applied whole genome amplification followed by double digest restriction site associated DNA sequencing (ddRADseq) to individual S. japonicum miracidia preserved on Whatman FTA cards. We found that we could effectively and consistently survey hundreds of thousands of variants from 10,000 to 30,000 loci from archived miracidia as old as six years. An analysis of variation from eight miracidia obtained from three hosts in two villages in Sichuan showed clear population structuring by village and host even within this limited sample.Conclusions/significanceThis high-resolution sequencing approach yields three orders of magnitude more information than microsatellite genotyping methods that have been employed over the last decade, creating the potential to answer detailed questions about the sources of human infections and to monitor drug resistance. Costs per sample range from $50-$200, depending on the amount of sequence information desired, and we expect these costs can be reduced further given continued reductions in sequencing costs, improvement of protocols, and parallelization. This approach provides new promise for using modern genome-scale sampling to S. japonicum surveillance, and could be applied to other schistosome species and other parasitic helminthes.

Dataset Information

Genome-wide identification of Schistosoma japonicum microRNAs using a deep-sequencing approach.

Background

Methodology/principal findings

Conclusions/significance

Publications

Genome-wide identification of Schistosoma japonicum microRNAs using a deep-sequencing approach.

Similar Datasets

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