252 research outputs found
MicroRNAs influence reproductive responses by females to male sex peptide in Drosophila melanogaster
Across taxa, female behavior and physiology changes significantly following the receipt of ejaculate molecules during mating. For example, receipt of sex peptide (SP) in female Drosophila melanogaster significantly alters female receptivity, egg production, lifespan, hormone levels, immunity, sleep and feeding patterns. These changes are underpinned by distinct tissue- and time-specific changes in diverse sets of mRNAs. However, little is yet known about the regulation of these gene expression changes, and hence the potential role of microRNAs (miRNAs), in female post-mating responses. A preliminary screen of genomic responses in females to receipt of SP suggested that there were changes in the expression of several miRNAs. Here we tested directly whether females lacking four of the candidate miRNAs highlighted (miR-279, miR-317, miR-278 and miR-184) showed altered fecundity, receptivity and lifespan responses to receipt of SP, when mated once or continually to SP null or control males. The results showed that miRNA-lacking females mated to SP null males exhibited altered receptivity, but not reproductive output, in comparison to controls. However, these effects interacted significantly with the genetic background of the miRNA-lacking females. No significant survival effects were observed in miRNA-lacking females housed continually with SP null or control males. However, continual exposure to control males that transferred SP resulted in significantly higher variation in miRNA-lacking female lifespan than did continual exposure to SP null males. The results provide the first insight into the effects and importance of miRNAs in regulating post-mating responses in females
The role of small RNAs in Paget's associated osteosarcoma
Small RNAs (sRNAs) are a class of non-coding RNA molecules that arekey regulators of gene expression. SRNAs are also speciļ¬c biomarkersdue to their dysregulation in disease. Next generation sequencing is thegold standard for sRNA discovery, proļ¬ling and expression analysis.Bias has been found in diļ¬erent platforms of sequencing due to RNAligase preference for sequence complementarity between sRNA andadapters. We developed high deļ¬nition (HD) adapters to overcome thebias. We applied the use of HD adapters and sequencing to our studiesof bone cancer. One of these studies investigated sRNA expression inPagetās associated osteosarcoma, a rare complication of Pagetās diseaseof bone that carries a poor prognosis. We found that expression of amicroRNA, miR-16, was highly expressed in Pagetās associated osteo-sarcoma tissue when compared to controls and Pagetās disease of bone.Bioinformatics analysis revealed miR-16 directly targets the sequesto-some 1 (SQSTM1) messenger RNA. SQSTM1 protein has long been as-sociated with Pagetās disease of bone development. SQSTM1 was hy-pothesised to be involved with transformation to osteosarcoma asSQSTM1 variants are positively associated with disease severity. Wespeculated that negative regulation of SQSTM1 by miR-16 incapacitatesSQSTM1ās role in the Kelch-like ECH-associated protein 1 (KEAP1)-nuclear factor erythroid 2-like 2 (NFE2L2) pathway, a major cellulardefence mechanism against oxidative stress and cancer development.Molecular testing may help provide a robust diagnosis and is particu-larly useful in rare cancers such as Pagetās associated osteosarcomawhere transformation is often missed until late stage. We are now in-vestigating this biological data further, using single cell simultaneousgenome and transcriptome sequencing
The role of small RNAs in Paget's associated osteosarcoma
Small RNAs (sRNAs) are a class of non-coding RNA molecules that arekey regulators of gene expression. SRNAs are also speciļ¬c biomarkersdue to their dysregulation in disease. Next generation sequencing is thegold standard for sRNA discovery, proļ¬ling and expression analysis.Bias has been found in diļ¬erent platforms of sequencing due to RNAligase preference for sequence complementarity between sRNA andadapters. We developed high deļ¬nition (HD) adapters to overcome thebias. We applied the use of HD adapters and sequencing to our studiesof bone cancer. One of these studies investigated sRNA expression inPagetās associated osteosarcoma, a rare complication of Pagetās diseaseof bone that carries a poor prognosis. We found that expression of amicroRNA, miR-16, was highly expressed in Pagetās associated osteo-sarcoma tissue when compared to controls and Pagetās disease of bone.Bioinformatics analysis revealed miR-16 directly targets the sequesto-some 1 (SQSTM1) messenger RNA. SQSTM1 protein has long been as-sociated with Pagetās disease of bone development. SQSTM1 was hy-pothesised to be involved with transformation to osteosarcoma asSQSTM1 variants are positively associated with disease severity. Wespeculated that negative regulation of SQSTM1 by miR-16 incapacitatesSQSTM1ās role in the Kelch-like ECH-associated protein 1 (KEAP1)-nuclear factor erythroid 2-like 2 (NFE2L2) pathway, a major cellulardefence mechanism against oxidative stress and cancer development.Molecular testing may help provide a robust diagnosis and is particu-larly useful in rare cancers such as Pagetās associated osteosarcomawhere transformation is often missed until late stage. We are now in-vestigating this biological data further, using single cell simultaneousgenome and transcriptome sequencing
Paget's disease of bone-associated osteosarcoma: molecular basis, signs and symptoms, treatment and research
Darrell Green is a Big C-funded molecular biologist at the University of East Anglia, performing research towards a PhD. He works with Professor Tamas Dalmay, Head of Biological Sciences and Chair of RNA Biology at the University of East Anglia and Professor Bill Fraser who is a Trustee of The Pagetās Association, Director of The Norfolk Bone and Joint Centre, the Bioanalytical Facility and Head of Department of Medicine at Norwich Medical School and Consultant Metabolic Physician at the Norfolk and Norwich University Hospital. Here they discuss the molecular basis of Pagetās associated osteosarcoma, identifi cation of patients at risk, signs and symptoms, treatment and current research
Global discovery and characterization of small non-coding RNAs in marine microalgae
Background Marine phytoplankton are responsible for 50% of the CO2 that is fixed annually worldwide and contribute massively to other biogeochemical cycles in the oceans. Diatoms and coccolithophores play a significant role as the base of the marine food web and they sequester carbon due to their ability to form blooms and to biomineralise. To discover the presence and regulation of short non-coding RNAs (sRNAs) in these two important phytoplankton groups, we sequenced short RNA transcriptomes of two diatom species (Thalassiosira pseudonana, Fragilariopsis cylindrus) and validated them by Northern blots along with the coccolithophore Emiliania huxleyi. Results Despite an exhaustive search, we did not find canonical miRNAs in diatoms. The most prominent classes of sRNAs in diatoms were repeat-associated sRNAs and tRNA-derived sRNAs. The latter were also present in E. huxleyi. tRNA-derived sRNAs in diatoms were induced under important environmental stress conditions (iron and silicate limitation, oxidative stress, alkaline pH), and they were very abundant especially in the polar diatom F. cylindrus (20.7% of all sRNAs) even under optimal growth conditions. Conclusions This study provides first experimental evidence for the existence of short non-coding RNAs in marine microalgae. Our data suggest that canonical miRNAs are absent from diatoms. However, the group of tRNA-derived sRNAs seems to be very prominent in diatoms and coccolithophores and maybe used for acclimation to environmental conditions
Profile and functional analysis of small RNAs derived from Aspergillus fumigatus infected with double-stranded RNA mycoviruses
Background: Mycoviruses are viruses that naturally infect and replicate in fungi. Aspergillus fumigatus, an opportunistic pathogen causing fungal lung diseases in humans and animals, was recently shown to harbour several different types of mycoviruses. A well-characterised defence against virus infection is RNA silencing. The A. fumigatus genome encodes essential components of the RNA silencing machinery, including Dicer, Argonaute and RNA-dependent RNA polymerase (RdRP) homologues. Active silencing of double-stranded (ds)RNA and the generation of small RNAs (sRNAs) has been shown for several mycoviruses and it is anticipated that a similar mechanism will be activated in A. fumigatus isolates infected with mycoviruses. Results: To investigate the existence and nature of A. fumigatus sRNAs, sRNA-seq libraries of virus-free and virus-infected isolates were created using Scriptminer adapters and compared. Three dsRNA viruses were investigated: Aspergillus fumigatus partitivirus-1 (AfuPV-1, PV), Aspergillus fumigatus chrysovirus (AfuCV, CV) and Aspergillus fumigatus tetramycovirus-1 (AfuTmV-1, NK) which were selected because they induce phenotypic changes such as coloration and sectoring. The dsRNAs of all three viruses, which included two conventionally encapsidated ones PV and CV and one unencapsidated example NK, were silenced and yielded characteristic vsiRNAs together with co-incidental silencing of host fungal genes which shared sequence homology with the viral genomes. Conclusions: Virus-derived sRNAs were detected and characterised in the presence of virus infection. Differentially expressed A. fumigatus microRNA-like (miRNA-like) sRNAs and small interfering RNAs (siRNAs) were detected and validated. Host sRNA loci which were differentially expressed as a result of virus infection were also identified. To our knowledge, this is the first study reporting the sRNA profiles of A. fumigatus isolates
Nucleotide bias of DCL and AGO in plant anti-virus gene silencing
Plant Dicer-like (DCL) and Argonaute (AGO) are the key enzymes involved in anti-virus post-transcriptional gene silencing (AV-PTGS). Here we show that AV-PTGS exhibited nucleotide preference by calculating a relative AV-PTGS efficiency on processing viral RNA substrates. In comparison with genome sequences of dicot-infecting Turnip mosaic virus (TuMV) and monocot-infecting Cocksfoot streak virus (CSV), viral-derived small interfering RNAs (vsiRNAs) displayed positive correlations between AV-PTGS efficiency and G+C content (GC%). Further investigations on nucleotide contents revealed that the vsiRNA populations had G-biases. This finding was further supported by our analyses of previously reported vsiRNA populations in diverse plant-virus associations, and AGO associated Arabidopsis endogenous siRNA populations, indicating that plant AGOs operated with G-preference. We further propose a hypothesis that AV-PTGS imposes selection pressure(s) on the evolution of plant viruses. This hypothesis was supported when potyvirus genomes were analysed for evidence of GC elimination, suggesting that plant virus evolution to have low GC% genomes would have a unique function, which is to reduce the host AV-PTGS attack during infections
Comprehensive processing of high-throughput small RNA sequencing data including quality checking, normalization, and differential expression analysis using the UEA sRNA Workbench
Recently, high-throughput sequencing (HTS) has revealed compelling details about the small RNA (sRNA) population in eukaryotes. These 20 to 25 nt noncoding RNAs can influence gene expression by acting as guides for the sequence-specific regulatory mechanism known as RNA silencing. The increase in sequencing depth and number of samples per project enables a better understanding of the role sRNAs play by facilitating the study of expression patterns. However, the intricacy of the biological hypotheses coupled with a lack of appropriate tools often leads to inadequate mining of the available data and thus, an incomplete description of the biological mechanisms involved. To enable a comprehensive study of differential expression in sRNA data sets, we present a new interactive pipeline that guides researchers through the various stages of data preprocessing and analysis. This includes various tools, some of which we specifically developed for sRNA analysis, for quality checking and normalization of sRNA samples as well as tools for the detection of differentially expressed sRNAs and identification of the resulting expression patterns. The pipeline is available within the UEA sRNA Workbench, a user-friendly software package for the processing of sRNA data sets. We demonstrate the use of the pipeline on a H. sapiens data set; additional examples on a B. terrestris data set and on an A. thaliana data set are described in the Supplemental Information. A comparison with existing approaches is also included, which exemplifies some of the issues that need to be addressed for sRNA analysis and how the new pipeline may be used to do this
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