Literature DB >> 24069470

Sex-biased expression of microRNAs in Schistosoma mansoni.

Antonio Marco1, Ana Kozomara, Jerome H L Hui, Aidan M Emery, David Rollinson, Sam Griffiths-Jones, Matthew Ronshaugen.   

Abstract

Schistosomiasis is an important neglected tropical disease caused by digenean helminth parasites of the genus Schistosoma. Schistosomes are unusual in that they are dioecious and the adult worms live in the blood system. MicroRNAs play crucial roles during gene regulation and are likely to be important in sex differentiation in dioecious species. Here we characterize 112 microRNAs from adult Schistosoma mansoni individuals, including 84 novel microRNA families, and investigate the expression pattern in different sexes. By deep sequencing, we measured the relative expression levels of conserved and newly identified microRNAs between male and female samples. We observed that 13 microRNAs exhibited sex-biased expression, 10 of which are more abundant in females than in males. Sex chromosomes showed a paucity of female-biased genes, as predicted by theoretical evolutionary models. We propose that the recent emergence of separate sexes in Schistosoma had an effect on the chromosomal distribution and evolution of microRNAs, and that microRNAs are likely to participate in the sex differentiation/maintenance process.

Entities:  

Mesh:

Substances:

Year:  2013        PMID: 24069470      PMCID: PMC3772069          DOI: 10.1371/journal.pntd.0002402

Source DB:  PubMed          Journal:  PLoS Negl Trop Dis        ISSN: 1935-2727


Introduction

Human schistosomiasis is a neglected tropical disease (NTD) caused by blood flukes of the genus Schistosoma. Schistosomiasis is estimated to affect over 200 million people in developing tropical and subtropical countries, with over 90% of cases being confined to Africa [1], [2]. Schistosoma mansoni is primarily responsible for intestinal and hepatic schistosomiasis in Africa, the Arabian peninsula, parts of South America and the Caribbean Islands [3]. Unlike most other flatworms (phylum Platyhelminthes), Schistosoma species are dioecious; that is, they have two differentiated sexes. The emergence of sexual dimorphism in these species is believed to be associated with adaptation to warm-blooded vertebrates from a hermaphrodite ancestor in cold-blooded vertebrates [4]. Schistosoma mansoni has seven pairs of autosomes and one pair of sexual chromosomes with a ZW system, i.e., females are the heterogametic sex [5]. Like other species with a ZW-based system of sex determination, there is no apparent global dosage compensation in females [6]. The origin of Schistosoma sexuality has attracted much attention [4], [7]–[9]. Moreover, as the eggs laid by the female worms are primarily responsible for the pathology associated with schistosomiasis, the mechanisms associated with pairing and egg-laying, including expression of sex specific genes are of great interest. In the last years, different groups have characterized, using genomic and proteomic approaches, gene products with differential expression between males and females in Schistosoma species [10]–[13]. Since both sexes are necessary for the colonization of the host, sex-biased genes are potential targets for the infection control of schistosomes. MicroRNAs are short endogenous RNA molecules that regulate gene expression by targeting mature mRNA transcripts [14]. This mechanism of post-transcriptional regulation is conserved in animals and is likely to be involved in all aspects of cellular function [15]. The microRNA content of Schistosoma japonicum, which affects large endemic areas around the river Yangtze in China, has been studied in detail by several groups [16]–[21]. In addition, the previous characterization of microRNAs from other non dioecious species of flatworms, such as Echinococcus granulosus and the non-parasitic Schmidtea mediterranea [22], [23], provides a background against which to identify Schistosoma-specific microRNAs with a potential role in sexual development and host-parasite interactions. Current knowledge of S. mansoni microRNAs is limited and mostly based on computational predictions [24], [25]. Moreover, S. mansoni provides an excellent model to study the evolution and function of sex-biased microRNAs. Here we use deep sequencing of RNA libraries to explore the microRNA content of S. mansoni, identify microRNAs specific to the schistosomes, and study the potential impact of sex-biased microRNAs in sexual differentiation.

Results

The microRNAs of Schistosoma mansoni

We have used small RNA deep sequencing to identify a total of 112 microRNAs in adult S. mansoni (Table 1, Supplementary Files S1 and S2). Valid microRNA candidates were required to have reads mapping to both arms of the precursor sequences (representing mature microRNA and microRNA* sequences) except for those with a previously validated homolog (see Materials and Methods). Our microRNA annotation procedure was intentionally conservative: we may not have detected some bona fide microRNAs, but our predictions are of high confidence.
Table 1

MicroRNAs in Schistosoma mansoni.

Read countRead countRead count
MicroRNASOMSMicroRNASOMSMicroRNASOMS
Chromosome 1 Chromosome 3 Chromosome 7
sma-mir-21955411608sma-mir-8430340sma-mir-84541370
sma-mir-81199298sma-mir-8431570sma-mir-8455230
sma-mir-8403611sma-mir-8432530sma-let-71360511621
sma-mir-8404230sma-mir-8433240sma-mir-8456380
sma-mir-125c1602725268sma-mir-8434580sma-mir-845735925
sma-mir-125a96750159980sma-mir-84353790sma-mir-84581732
sma-mir-84052530sma-mir-8436330
sma-mir-36a1633426988sma-mir-84375152411 Chromosome Z/W
sma-mir-36b255914404sma-mir-84382150sma-mir-1a61021028
sma-mir-84066680sma-mir-8439910sma-mir-7551225929358
sma-mir-84073600sma-mir-8459270
sma-mir-840815260 Chromosome 4 sma-mir-9617249234
sma-mir-8409220sma-mir-84401420sma-mir-84605780
sma-mir-8410190sma-mir-8441280sma-mir-8461380
sma-mir-84113010sma-mir-745933351888sma-mir-1b62201162
sma-mir-19035914938sma-mir-84421360sma-mir-84621200
sma-mir-8412180sma-mir-1052115104344sma-mir-8463230
sma-mir-8413360sma-mir-28129031114sma-mir-8464170
sma-mir-84141330sma-mir-8443890sma-mir-84655640
sma-mir-8415490sma-mir-8444590sma-mir-84664970
sma-mir-8416530sma-mir-71824282sma-mir-71a2448337197
sma-mir-84172720sma-mir-8445520sma-mir-2a41768707
sma-mir-84189000sma-mir-8446216790sma-mir-2b1894010956
sma-mir-8419370sma-mir-2e74263608
sma-mir-8420260 Chromosome 5 sma-mir-84672780
sma-mir-2c14591550sma-mir-8468520
Chromosome 2 sma-mir-2d644924sma-mir-84691920
sma-mir-84211010sma-mir-2f582722sma-mir-8470160
sma-mir-8422660sma-mir-71b23743860
sma-mir-842319050sma-mir-84471021484 Unplaced
sma-mir-84242880sma-mir-84712480
sma-mir-8425340 Chromosome 6 sma-mir-8472740
sma-mir-8426610sma-mir-8448880sma-mir-2162648616531
sma-mir-8427390sma-mir-3111714sma-mir-84733550
sma-mir-8428211sma-mir-8449250sma-mir-8474140
sma-mir-8429731sma-mir-84502970sma-mir-847510780
sma-mir-612135724648sma-mir-8451280sma-mir-84761830
sma-mir-12479781084sma-bantam18135175657
sma-mir-84522930sma-mir-8477250
sma-mir-8453680sma-mir-8478390
sma-mir-124b610sma-mir-84791120
sma-mir-8480740
sma-mir-84815970
sma-mir-8482520
sma-mir-8483210
sma-mir-84841870

SO: AB SOLiD sequencing; MS: Illumina MiSeq sequencing.

SO: AB SOLiD sequencing; MS: Illumina MiSeq sequencing. De Souza Gomes et al. [25] computationally identified 42 microRNA loci in S. mansoni, significantly expanding the previous set of 6 microRNAs [16], [24]. We confirmed 20 of these (Table 1), all conserved in other species. We failed to detect the remaining 23. All but two of the unconfirmed microRNAs were not conserved in other flatworms. A second recent work characterized 211 novel microRNAs in S. mansoni by cloning of small RNA sequences from adults and schistosomulas [26]. However, the majority of the candidate microRNAs map to many positions in the genome and only a few are reported to be within putative precursor hairpin structures. Indeed, only two of the reported 211 microRNAs were confirmed in our analyses (mir-71a and let-7). We identify 92 microRNAs not previously annotated in S. mansoni, eight with obvious homologs in other species (Table 1). Amongst these, we show that the deeply-conserved mir-124 locus produces microRNAs from both genomic strands in S. mansoni (Supplementary Files S2). The remaining 84 novel predictions had no detectable similarity with any known microRNA. To characterize the microRNAs conserved in the parasitic Schistosoma genus, we compared our sequenced microRNAs with those already described for S. japonicum [17]–[19], [21]. We found that 26 out of our 112 microRNAs were conserved between these two species (Figure 1). In order to determine how many of those 26 are specific to the Schistosoma lineage, we searched the genomes of the flatworms Schmidtea mediterranea [22] and Dugesia japonica [27] for homologous sequences. Strikingly, all known microRNAs conserved between Schistosoma species were also conserved in other flatworms. We also detected a set of S. japonicum homologs for 12 of our newly identified S. mansoni sequences that were not conserved in other platyhelminthes (Figures 1A and B). Hence, these 12 microRNAs are the first instances of schistosome-specific microRNAs.
Figure 1

The origin of microRNAs of Schistosoma mansoni.

A) MicroRNAs characterized from small RNA libraries and their evolutionary origin based on homology searches. B) Example of a newly discovered microRNA in S. mansoni that is also conserved in S. japonicum. Conserved nucleotides between the two species are shown with a black background. The number of uniquely mapped reads for each sequence in S. mansoni is shown in the right, for both SOLiD and MiSeq datasets.

The origin of microRNAs of Schistosoma mansoni.

A) MicroRNAs characterized from small RNA libraries and their evolutionary origin based on homology searches. B) Example of a newly discovered microRNA in S. mansoni that is also conserved in S. japonicum. Conserved nucleotides between the two species are shown with a black background. The number of uniquely mapped reads for each sequence in S. mansoni is shown in the right, for both SOLiD and MiSeq datasets. Homology searches in other animals showed that three microRNAs are specific to platyhelminthes: mir-755, mir-2162 and mir-8451 (Figure 1A). Thirteen microRNAs are protostome-specific and the remaining 10 are conserved across the animal kingdom (Figure 1A). A total of 71 microRNAs identified in this study are not detected in any other species, and are therefore likely to be S. mansoni specific.

Sex-biased expression of microRNAs in S.mansoni

To explore potential sex-biased expression, we compared the relative expression levels of the 112 microRNAs in males and females (Figure 2A). We found 13 microRNAs that are differentially expressed between males and females. A significant excess [10] show increased expression in females (Figure 2A, Table 2). We further quantified the relative expression level of all 3 male-biased and 4 of the female-biased microRNAs by real-time PCR (see Materials and Methods). The observed fold changes in our qPCR experiments were consistent with those observed in our RNAseq analysis (Table 3), although the two least biased microRNAs by RNAseq show small and non-significant changes by qPCR.
Figure 2

Sex-biased expression of microRNAs in S. mansoni.

A) Smear plot of normalized expression levels (log fold-change) for microRNAs in male and female samples against the total read counts (log average count). Black line indicates equal expression in both sexes. Grey lines represent 2-fold changes between samples. Filled circles are microRNAs with a significant expression fold change between sexes (see Materials and Methods). B) Relative enrichment/paucity of sex-biased microRNAs in the sex chromosome (ZW). Each expression level fold-change threshold (x-axis) is plotted against the logarithm of the p-value (Fisher's exact test) for enrichment or paucity in the sex chromosome.

Table 2

MicroRNAs with sex-biased expression.

Male-biased expressionFemale-biased expression
microRNAlogFC male/female1 q-value2 microRNALogFC female/male1 q-value2
mir-1b1.00.064mir-84474.9<0.001
mir-611.00.061mir-2f4.1<0.001
mir-2811.00.071mir-84373.9<0.001
mir-313.40.006
bantam2.7<0.001
mir-2c2.4<0.001
mir-2d2.3<0.001
mir-71b1.8<0.001
mir-36b1.50.002
mir-7551.20.014

Log Fold Change after Upper Quartile normalization of Illumina MiSeq read counts.

False discovery rate (q-value) for a dispersion of 0.2 according to edgeR manual (see Methods).

Table 3

Real-time PCR validation of sex-biased expressed microRNAs.

microRNAqPCR logFC1 p-value2
male-biased mir-1b0.70.179
mir-611.40.008
mir-2810.10.493
female-biased mir-84374.0<0.001
bantam2.5<0.001
mir-71b1.70.022
mir-36b0.20.253

Log Fold Change for the differences between Ct values for target and control microRNAs.

P-values based on t-test of Ct value differences for three technical replicates.

Sex-biased expression of microRNAs in S. mansoni.

A) Smear plot of normalized expression levels (log fold-change) for microRNAs in male and female samples against the total read counts (log average count). Black line indicates equal expression in both sexes. Grey lines represent 2-fold changes between samples. Filled circles are microRNAs with a significant expression fold change between sexes (see Materials and Methods). B) Relative enrichment/paucity of sex-biased microRNAs in the sex chromosome (ZW). Each expression level fold-change threshold (x-axis) is plotted against the logarithm of the p-value (Fisher's exact test) for enrichment or paucity in the sex chromosome. Log Fold Change after Upper Quartile normalization of Illumina MiSeq read counts. False discovery rate (q-value) for a dispersion of 0.2 according to edgeR manual (see Methods). Log Fold Change for the differences between Ct values for target and control microRNAs. P-values based on t-test of Ct value differences for three technical replicates. We next evaluated whether microRNA loci on the sex chromosomes are biased towards differential expression between sexes. The current assembly of the S. mansoni genome does not differentiate between Z and W chromosomes. At this stage, we cannot therefore evaluate the two sexual chromosomes separately. In Figure 2B, we plot the relative enrichment of sex-chromosome-linked microRNAs for male and female-biased expression. We observed that the sex chromosome has fewer female-biased microRNAs (∼3-fold change) than expected by chance, although the difference is only marginally significant (p = 0.10). The data therefore indicate that microRNA genes with female sex-biased expression may have a tendency to move out of sex chromosomes (see Discussion). The mir-71/mir-2 microRNA cluster is highly conserved in invertebrates, and it has been shown that this cluster is duplicated in Platyhelminthes [25], [28]. Interestingly, one of the clusters (mir-71/2a/2b/2e) is on the sex chromosomes while the other (mir-71b/2f/2d/2c) is on chromosome 5 [25], [29]. This has led some authors to postulate that the mir-71/mir-2 clusters may be involved in sexual maturation in Schistosoma [25]. Our analysis reveals that all microRNAs in the autosomal cluster have female-biased expression, while the sex chromosome cluster does not show any bias (Figure 2A). Interestingly, the two clusters emerged by a duplication in the ancestral lineage leading to Schistosoma, and the multiple copies in other Platyhelminthes [29], [30] came from independent duplication events (Supplementary Files S4). This example may shed some light on how sex chromosomes evolved in dioecious species (see Discussion).

Discussion

Although the computational prediction of microRNAs has been useful to understand the biology of small RNAs in S. mansoni [25], sequencing is required to validate the existence of these microRNAs as well as for detecting new sequences. Our work has confirmed the existence of 20 of the microRNAs predicted by de Souza Gomes et al. [25] and we have expanded the S. mansoni microRNA set to 112 loci. We specifically detect microRNAs expressed in sexually mature adults, and microRNAs specifically expressed in other developmental stages (such as schistosomulas) may have escaped our analysis. The use of deep sequencing also permits the characterization of microRNAs produced from both strands of the same locus, and we have identified sense and antisense microRNA production from the mir-124 locus. However, there is no evidence that this microRNA is also bidirectionally transcribed in other species. Indeed, bidirectionally transcribed microRNAs are rare and poorly conserved; only two cases of conserved bidirectional microRNAs are known in protostomes: iab-4 and mir-307 [31]. We observe an excess of microRNAs that exhibit female-biased expression (Figure 2A). This is in agreement with the overall female-bias observed for protein-coding genes in both S. mansoni [10] and S. japonicum [11], although a recent expression analysis in S. japonicum showed no gender bias [13]. Recently, a work in the parasitic nematode Ascaris suum showed that microRNAs are differentially expressed between males and females [32]. Although the differences were small and the targeting properties of male and female microRNAs similar, they reported a tendency of male microRNA to target extracellular proteins [32]. Another work in the bird Taeniopygia guttata (zebra finch), suggests that the male-biased expressed microRNA mir-2954 specifically target genes in the Z chromosome, and may be involved in sexual dimorphism in song behavior [33]. Together, these papers and our work point to a general mechanism of microRNA-modulation of sex-specific gene expression. A recent work shows that some microRNAs are specifically expressed in Schistosoma japonicum eggs [21]. In that work, the authors also measured the microRNA expression levels in males and females. We reanalyse their data and find that two out of our three male-biased microRNAs (mir-1 and mir-61) have a consistent bias in Schistosoma japonicum, while the third is not present in their dataset. Also, five of our female-biased microRNAs also showed a female bias in their work (mir-71b, mir-2c, mir-2d, bantam and mir-31). These findings further validate our results and show that the sex-biased pattern of microRNA expression is evolutionarily conserved between these two species. Sex-biased gene expression affects the genetic composition of chromosomes, since selection has different effects on sex-biased genes depending on whether they are located on sex chromosomes or on autosomes (reviewed in [34]). Likewise, sex chromosomes have distinctive evolutionary patterns, which affect the genes encoded within [35]. We may therefore expect to see signatures of chromosome evolution in sex-biased microRNAs. Indeed, we observed that microRNAs that are female sex-biased are depleted in the sexual chromosomes (Figure 2B). This may indicate a loss of sex-biased genes at the sex chromosomes. One interesting example is the female-biased mir-71b/2f/2c/2d autosomal microRNA cluster, which has a paralogous copy in the sex chromosome with no biased expression. If a microRNA gene that is selectively advantageous for females becomes part of a sex chromosome (by sexualisation of the chromosome, or otherwise), selection over this gene will be less efficient in the heterogametic sex (females in our case), generating a conflict between expression pattern and chromosomal location. Duplication of a gene into an autosome has been recently proposed as a way to escape such conflict (reviewed in [36]), and the mir-71/mir-2 cluster duplication appears to be an example of this. Although a more comprehensive analysis of duplicated microRNAs with sex-biased expression is required to confirm this, our analysis shows that sex-biased expressed microRNAs have an impact in shaping the genome during evolution. The study of microRNAs in the schistosomes is of both evolutionary and biomedical interest. First, the recent evolution of a sexual reproductive system from a hermaphrodite ancestor can give clues about how sexuality emerged in other species. Our data are consistent with the acquisition of sex-biased expression of conserved microRNAs soon after the species become dioecious. Second, the characterization of Schistosoma-specific microRNAs may provide new targets for infection control. In this work, we characterize for the first time 12 microRNAs conserved between S. mansoni and S. japonicum but not in other platyhelminthes (nor in other animals). Two of these sequences also showed female-biased expression (mir-8437 and mir-8447). However, some important questions remain to be answered: Are microRNAs conserved in the two studied schistosomes also conserved in other Schistosoma species or in other trematodes? Is sex-biased expression of microRNAs associated with sex-biased expression of their targets? Do other dioecious flatworms have sex-biased expression of microRNAs? The genomic sequencing of more platyhelminthes and characterization of their microRNAs will help us to answer these questions.

Materials and Methods

Small RNA extraction, library construction and sequencing

For the detection of expressed microRNAs, female mice (BKW strain) were infected with Belo-Horizonte strain Schistosoma mansoni parasites by paddling in water containing 200 cercariae. Seven weeks after infection, adult schistosomes were collected from the mice post-mortem by hepatic portal perfusion. RNA was extracted from adult schistosome samples with the miRVana miRNA isolation kit (Ambion). We used two sequencing technologies, AB SOLiD and Illumina MiSeq, to sequence S. mansoni small RNA libraries. The extremely deep coverage provided by SOLiD sequencing provides high sensitivity for the discovery of novel microRNAs. We further used Illumina MiSeq sequencing of gender-specific libraries to compare the expression level of microRNAs between males and females. Library construction was performed as previous described [37] using the SOLiD Small RNA Expression Kit (Ambion). SOLiD sequencing was performed at the Center for Genomic Research at the University of Liverpool. We obtained a total of 124,341,126 SOLiD sequence reads from two libraries. For the gender-specific differential expression of microRNAs, we prepared RNA libraries with the miRVana kit from separate male and female samples (provided by Andrew MacDonald and Rinku Rajan at the University of Edinburgh), and prepared libraries for Illumina MiSeq sequencing according to the manufacturer's instructions. MiSeq samples were sequenced in the Genomics Core Facility at the University of Manchester. High-throughput datasets were deposited in Gene Expression Omnibus (GEO) at NCBI (accession number: GSE49359).

MicroRNA detection and annotation

Sequencing reads from male and female libraries were separately mapped to the S. mansoni reference genome (assembly 5.1 available at http://www.genedb.org/Homepage/Smansoni; [38], [39]) with Bowtie 0.12 using the sequential trimming strategy implemented in SeqTrimMap 1.0 [40] allowing 2 mismatches. Sequences mapping to potential rRNAs or tRNAs were first removed. Putative tRNAs were predicted in the genome sequence with tRNAscan-SE using default parameters [41] and ribosomal RNAs (rRNAs) were extracted from the SILVA database (http://www.arb-silva.de/, release 108). Mapped reads with a length of 19–25 nucleotides, matching five or fewer positions in the genome (a total of 63,771,124 sequence reads), were used to detect microRNAs as previously described [37], [40]. We further used BLAST [42] to search microRNA candidates against the S. mansoni genome and discarded those with more than 5 hits (E-value 43]) with reads mapped from our datasets but which did not pass our criteria were also retained. Homolog of our microRNA candidates were predicted in the genome sequences of S. japonicum (version 2), S. mediterranea (v. 3.1), Caenorhabditis elegans (v. 7.1), Tribolium castaneum (v. 3.0), Drosophila melanogaster (v. 5.1), Homo sapiens (v. 37.1) and Gallus gallus (v. 2.1), with parameters: −W 4, −r +2, −q −3. Only sequences with a predicted hairpin structure and conserving at least one mature sequence were considered as putative homologs.

Differential expression analyses

We mapped reads produced from MiSeq sequencing reactions to our annotated S. mansoni microRNAs and discarded all reads that map to more than one microRNA locus. Read counts were transformed with the ‘upper quartile’ normalization using the edgeR package [44], following the suggestions in [45]. Other normalization procedures (‘TMM’, ‘LOWESS’ and ‘no normalization’) did not change the results (Supplementary Files S3). Fold changes in expression levels are given in logarithms in base 2. We consider a dispersion of expression between experiments of 0.2 and a false discovery rate of 10%. With these parameters, microRNAs showing a two-fold difference in their expression levels are considered to be sex-biased, as routinely suggested [46], [47]. The expression level in males and females of seven microRNAs (mir-1b, mir-61, mir-281, mir-36b, mir-71b, bantam and mir-8437) were further validated by quantitative PCR. We used custom made TaqMan assays manufactured by Life Technologies. Fluorescent quantification was done in a Chromo 4 qPCR system (BioRad) for a log fluorescent threshold of 0.05, using mir-36a (the microRNA showing the least bias in the MiSeq experiments) as the non-sex-biased control microRNA. For each amplification, we performed three technical replicates to estimate the significance of the observed differences.

Ethical statement

Laboratory animal use was within a designated facility regulated under the terms of the UK Animals (Scientific Procedures) Act, 1986, complying with all requirements therein. The experiments involving mice in this study were approved by the Natural History Museum Ethical Review Process and work was carried out under Home Office project licence 70/6834. Sequences, chromosomal location and number of reads for all Schistosoma mansoni microRNAs characterized in this study. (XLS) Click here for additional data file. Structural features of Schistosoma mansoni microRNA precursors. (TXT) Click here for additional data file. Differential expression analysis between male and female Schistosoma mansoni specimens for different normalization methods. (XLS) Click here for additional data file. Phylogenetic relationships between mir-71 sequences in Schistosoma mansoni, S. japonicum and Schmidtea mediterranea. (PDF) Click here for additional data file.
  47 in total

1.  Identification of small non-coding RNAs in the planarian Dugesia japonica via deep sequencing.

Authors:  Yun-Fei Qin; Jin-Mei Zhao; Zhen-Xia Bao; Zhao-Yu Zhu; Jia Mai; Yi-Bo Huang; Jian-Biao Li; Ge Chen; Ping Lu; San-Jun Chen; Lin-Lin Su; Hui-Min Fang; Ji-Ke Lu; Yi-Zhe Zhang; Shou-Tao Zhang
Journal:  Genomics       Date:  2012-03-08       Impact factor: 5.736

2.  tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence.

Authors:  T M Lowe; S R Eddy
Journal:  Nucleic Acids Res       Date:  1997-03-01       Impact factor: 16.971

3.  Genomic linkage map of the human blood fluke Schistosoma mansoni.

Authors:  Charles D Criscione; Claudia L L Valentim; Hirohisa Hirai; Philip T LoVerde; Timothy J C Anderson
Journal:  Genome Biol       Date:  2009-06-30       Impact factor: 13.583

4.  An "in-depth" description of the small non-coding RNA population of Schistosoma japonicum schistosomulum.

Authors:  Zhangxun Wang; Xiangyang Xue; Jun Sun; Rong Luo; Xindong Xu; Yanyan Jiang; Qingfeng Zhang; Weiqing Pan
Journal:  PLoS Negl Trop Dis       Date:  2010-02-09

5.  Paucity of genes on the Drosophila X chromosome showing male-biased expression.

Authors:  Michael Parisi; Rachel Nuttall; Daniel Naiman; Gerard Bouffard; James Malley; Justen Andrews; Scott Eastman; Brian Oliver
Journal:  Science       Date:  2003-01-02       Impact factor: 47.728

6.  Deep sequencing identifies new and regulated microRNAs in Schmidtea mediterranea.

Authors:  Yi-Chien Lu; Magda Smielewska; Dasaradhi Palakodeti; Michael T Lovci; Stefan Aigner; Gene W Yeo; Brenton R Graveley
Journal:  RNA       Date:  2009-06-24       Impact factor: 4.942

7.  Profiles of small non-coding RNAs in Schistosoma japonicum during development.

Authors:  Pengfei Cai; Nan Hou; Xianyu Piao; Shuai Liu; Haiying Liu; Fan Yang; Jianwei Wang; Qi Jin; Heng Wang; Qijun Chen
Journal:  PLoS Negl Trop Dis       Date:  2011-08-02

8.  Global expression analysis revealed novel gender-specific gene expression features in the blood fluke parasite Schistosoma japonicum.

Authors:  Xianyu Piao; Pengfei Cai; Shuai Liu; Nan Hou; Lili Hao; Fan Yang; Heng Wang; Jianwei Wang; Qi Jin; Qijun Chen
Journal:  PLoS One       Date:  2011-04-06       Impact factor: 3.240

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

Authors:  Jian Huang; Pei Hao; Hui Chen; Wei Hu; Qing Yan; Feng Liu; Ze-Guang Han
Journal:  PLoS One       Date:  2009-12-08       Impact factor: 3.240

10.  edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.

Authors:  Mark D Robinson; Davis J McCarthy; Gordon K Smyth
Journal:  Bioinformatics       Date:  2009-11-11       Impact factor: 6.937

View more
  37 in total

Review 1.  Sex-biased gene expression and sexual conflict throughout development.

Authors:  Fiona C Ingleby; Ilona Flis; Edward H Morrow
Journal:  Cold Spring Harb Perspect Biol       Date:  2014-11-06       Impact factor: 10.005

2.  ATP synthase: an identified target gene of bantam in paired female Schistosoma japonicum.

Authors:  Jun Sun; Su-Wen Wang; Chen Li
Journal:  Parasitol Res       Date:  2014-11-20       Impact factor: 2.289

Review 3.  Multifunctional Roles of MicroRNAs in Schistosomiasis.

Authors:  Haoran Zhong; Yamei Jin
Journal:  Front Microbiol       Date:  2022-06-09       Impact factor: 6.064

4.  Epigenetic Markers Associated with Schistosomiasis.

Authors:  R A Gomes Assenço; E Alves Mota; V F De Oliveira; W De Castro Borges; R Guerra-Sá
Journal:  Helminthologia       Date:  2021-02-10       Impact factor: 1.184

5.  microRNAs and the evolution of complex multicellularity: identification of a large, diverse complement of microRNAs in the brown alga Ectocarpus.

Authors:  James E Tarver; Alexandre Cormier; Natalia Pinzón; Richard S Taylor; Wilfrid Carré; Martina Strittmatter; Hervé Seitz; Susana M Coelho; J Mark Cock
Journal:  Nucleic Acids Res       Date:  2015-06-22       Impact factor: 16.971

6.  Identification of microRNA genes in three opisthorchiids.

Authors:  Vladimir Y Ovchinnikov; Dmitry A Afonnikov; Gennady V Vasiliev; Elena V Kashina; Banchob Sripa; Viacheslav A Mordvinov; Alexey V Katokhin
Journal:  PLoS Negl Trop Dis       Date:  2015-04-21

7.  Selection Against Maternal microRNA Target Sites in Maternal Transcripts.

Authors:  Antonio Marco
Journal:  G3 (Bethesda)       Date:  2015-08-24       Impact factor: 3.154

8.  Protein and small non-coding RNA-enriched extracellular vesicles are released by the pathogenic blood fluke Schistosoma mansoni.

Authors:  Fanny C Nowacki; Martin T Swain; Oleg I Klychnikov; Umar Niazi; Alasdair Ivens; Juan F Quintana; Paul J Hensbergen; Cornelis H Hokke; Amy H Buck; Karl F Hoffmann
Journal:  J Extracell Vesicles       Date:  2015-10-05

9.  Clusters of microRNAs emerge by new hairpins in existing transcripts.

Authors:  Antonio Marco; Maria Ninova; Matthew Ronshaugen; Sam Griffiths-Jones
Journal:  Nucleic Acids Res       Date:  2013-06-17       Impact factor: 16.971

10.  Parasite-derived microRNAs in host serum as novel biomarkers of helminth infection.

Authors:  Anna M Hoy; Rachel J Lundie; Alasdair Ivens; Juan F Quintana; Norman Nausch; Thorsten Forster; Frances Jones; Narcis B Kabatereine; David W Dunne; Francisca Mutapi; Andrew S Macdonald; Amy H Buck
Journal:  PLoS Negl Trop Dis       Date:  2014-02-20
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.