Assessment of reference genes at six different developmental stages of Schistosoma mansoni for quantitative RT-PCR.

Reverse-transcription quantitative real-time polymerase chain reaction (RT-qPCR) is the most used, fast, and reproducible method to confirm large-scale gene expression data. The use of stable reference genes for the normalization of RT-qPCR assays is recognized worldwide. No systematic study for selecting appropriate reference genes for usage in RT-qPCR experiments comparing gene expression levels at different Schistosoma mansoni life-cycle stages has been performed. Most studies rely on genes commonly used in other organisms, such as actin, tubulin, and GAPDH. Therefore, the present study focused on identifying reference genes suitable for RT-qPCR assays across six S. mansoni developmental stages. The expression levels of 25 novel candidates that we selected based on the analysis of public RNA-Seq datasets, along with eight commonly used reference genes, were systematically tested by RT-qPCR across six developmental stages of S. mansoni (eggs, miracidia, cercariae, schistosomula, adult males and adult females). The stability of genes was evaluated with geNorm, NormFinder and RefFinder algorithms. The least stable candidate reference genes tested were actin, tubulin and GAPDH. The two most stable reference genes suitable for RT-qPCR normalization were Smp_101310 (Histone H4 transcription factor) and Smp_196510 (Ubiquitin recognition factor in ER-associated degradation protein 1). Performance of these two genes as normalizers was successfully evaluated with females maintained unpaired or paired to males in culture for 8 days, or with worm pairs exposed for 16 days to double-stranded RNAs to silence a protein-coding gene. This study provides reliable reference genes for RT-qPCR analysis using samples from six different S. mansoni life-cycle stages.

Long non-coding RNA levels can be modulated by 5-azacytidine in Schistosoma mansoni.

Schistosoma mansoni is a flatworm that causes schistosomiasis, a neglected tropical disease that affects more than 200 million people worldwide. There is only one drug indicated for treatment, praziquantel, which may lead to parasite resistance emergence. The ribonucleoside analogue 5-azacytidine (5-AzaC) is an epigenetic drug that inhibits S. mansoni oviposition and ovarian development through interference with parasite transcription, translation and stem cell activities. Therefore, studying the downstream pathways affected by 5-AzaC in S. mansoni may contribute to the discovery of new drug targets. Long non-coding RNAs (lncRNAs) are transcripts longer than 200 nucleotides with low or no protein coding potential that have been involved in reproduction, stem cell maintenance and drug resistance. We have recently published a catalog of lncRNAs expressed in S. mansoni life-cycle stages, tissues and single cells. However, it remains largely unknown if lncRNAs are responsive to epigenetic drugs in parasites. Here, we show by RNA-Seq re-analyses that hundreds of lncRNAs are differentially expressed after in vitro 5-AzaC treatment of S. mansoni females, including intergenic, antisense and sense lncRNAs. Many of these lncRNAs belong to co-expression network modules related to male metabolism and are also differentially expressed in unpaired compared with paired females and ovaries. Half of these lncRNAs possess histone marks at their genomic loci, indicating regulation by histone modification. Among a selected set of 8 lncRNAs, half of them were validated by RT-qPCR as differentially expressed in females, and some of them also in males. Interestingly, these lncRNAs are also expressed in other life-cycle stages. This study demonstrates that many lncRNAs potentially involved with S. mansoni reproductive biology are modulated by 5-AzaC and sheds light on the relevance of exploring lncRNAs in response to drug treatments in parasites.

Weighted Gene Co-Expression Analyses Point to Long Non-Coding RNA Hub Genes at Different Schistosoma mansoni Life-Cycle Stages.

Long non-coding RNAs (lncRNAs) (>200 nt) are expressed at levels lower than those of the protein-coding mRNAs, and in all eukaryotic model species where they have been characterized, they are transcribed from thousands of different genomic loci. In humans, some four dozen lncRNAs have been studied in detail, and they have been shown to play important roles in transcriptional regulation, acting in conjunction with transcription factors and epigenetic marks to modulate the tissue-type specific programs of transcriptional gene activation and repression. In Schistosoma mansoni, around 10,000 lncRNAs have been identified in previous works. However, the limited number of RNA-sequencing (RNA-seq) libraries that had been previously assessed, together with the use of old and incomplete versions of the S. mansoni genome and protein-coding transcriptome annotations, have hampered the identification of all lncRNAs expressed in the parasite. Here we have used 633 publicly available S. mansoni RNA-seq libraries from whole worms at different stages (n = 121), from isolated tissues (n = 24), from cell-populations (n = 81), and from single-cells (n = 407). We have assembled a set of 16,583 lncRNA transcripts originated from 10,024 genes, of which 11,022 are novel S. mansoni lncRNA transcripts, whereas the remaining 5,561 transcripts comprise 120 lncRNAs that are identical to and 5,441 lncRNAs that have gene overlap with S. mansoni lncRNAs already reported in previous works. Most importantly, our more stringent assembly and filtering pipeline has identified and removed a set of 4,293 lncRNA transcripts from previous publications that were in fact derived from partially processed mRNAs with intron retention. We have used weighted gene co-expression network analyses and identified 15 different gene co-expression modules. Each parasite life-cycle stage has at least one highly correlated gene co-expression module, and each module is comprised of hundreds to thousands lncRNAs and mRNAs having correlated co-expression patterns at different stages. Inspection of the top most highly connected genes within the modules' networks has shown that different lncRNAs are hub genes at different life-cycle stages, being among the most promising candidate lncRNAs to be further explored for functional characterization.