Using Effective Subnetworks to Predict Selected Properties of Gene Networks

BACKGROUND: Difficulties associated with implementing gene therapy are caused by the complexity of the underlying regulatory networks. The forms of interactions between the hundreds of genes, proteins, and metabolites in these networks are not known very accurately. An alternative approach is to limit consideration to genes on the network. Steady state measurements of these influence networks can be obtained from DNA microarray experiments. However, since they contain a large number of nodes, the computation of influence networks requires a prohibitively large set of microarray experiments. Furthermore, error estimates of the network make verifiable predictions impossible. METHODOLOGY/PRINCIPAL FINDINGS: Here, we propose an alternative approach. Rather than attempting to derive an accurate model of the network, we ask what questions can be addressed using lower dimensional, highly simplified models. More importantly, is it possible to use such robust features in applications? We first identify a small group of genes that can be used to affect changes in other nodes of the network. The reduced effective empirical subnetwork (EES) can be computed using steady state measurements on a small number of genetically perturbed systems. We show that the EES can be used to make predictions on expression profiles of other mutants, and to compute how to implement pre-specified changes in the steady state of the underlying biological process. These assertions are verified in a synthetic influence network. We also use previously published experimental data to compute the EES associated with an oxygen deprivation network of E.coli, and use it to predict gene expression levels on a double mutant. The predictions are significantly different from the experimental results for less than of genes. CONCLUSIONS/SIGNIFICANCE: The constraints imposed by gene expression levels of mutants can be used to address a selected set of questions about a gene network

Chimeras- Greek Mythology or Scientific Reality? Identification of Actionable Chimeric RNAs for Personalized Prevention of Breast Cancer

https://openworks.mdanderson.org/sumexp23/1080/thumbnail.jp

The repertoire and features of human platelet microRNAs

Playing a central role in the maintenance of hemostasis as well as in thrombotic disorders, platelets contain a relatively diverse messenger RNA (mRNA) transcriptome as well as functional mRNA-regulatory microRNAs, suggesting that platelet mRNAs may be regulated by microRNAs. Here, we elucidated the complete repertoire and features of human platelet microRNAs by high-throughput sequencing. More than 492 different mature microRNAs were detected in human platelets, whereas the list of known human microRNAs was expanded further by the discovery of 40 novel microRNA sequences. As in nucleated cells, platelet microRNAs bear signs of post-transcriptional modifications, mainly terminal adenylation and uridylation. In vitro enzymatic assays demonstrated the ability of human platelets to uridylate microRNAs, which correlated with the presence of the uridyltransferase enzyme TUT4. We also detected numerous microRNA isoforms (isomiRs) resulting from imprecise Drosha and/or Dicer processing, in some cases more frequently than the reference microRNA sequence, including 5′ shifted isomiRs with redirected mRNA targeting abilities. This study unveils the existence of a relatively diverse and complex microRNA repertoire in human platelets, and represents a mandatory step towards elucidating the intraplatelet and extraplatelet role, function and importance of platelet microRNAs

Chimeric RNAs reveal putative neoantigen peptides for developing tumor vaccines for breast cancer

IntroductionWe present here a strategy to identify immunogenic neoantigen candidates from unique amino acid sequences at the junctions of fusion proteins which can serve as targets in the development of tumor vaccines for the treatment of breastcancer.MethodWe mined the sequence reads of breast tumor tissue that are usually discarded as discordant paired-end reads and discovered cancer specific fusion transcripts using tissue from cancer free controls as reference. Binding affinity predictions of novel peptide sequences crossing the fusion junction were analyzed by the MHC Class I binding predictor, MHCnuggets. CD8+ T cell responses against the 15 peptides were assessed through in vitro Enzyme Linked Immunospot (ELISpot).ResultsWe uncovered 20 novel fusion transcripts from 75 breast tumors of 3 subtypes: TNBC, HER2+, and HR+. Of these, the NSFP1-LRRC37A2 fusion transcript was selected for further study. The 3833 bp chimeric RNA predicted by the consensus fusion junction sequence is consistent with a read-through transcription of the 5’-gene NSFP1-Pseudo gene NSFP1 (NSFtruncation at exon 12/13) followed by trans-splicing to connect withLRRC37A2 located immediately 3’ through exon 1/2. A total of 15 different 8-mer neoantigen peptides discovered from the NSFP1 and LRRC37A2 truncations were predicted to bind to a total of 35 unique MHC class I alleles with a binding affinity of IC50<500nM.); 1 of which elicited a robust immune response.ConclusionOur data provides a framework to identify immunogenic neoantigen candidates from fusion transcripts and suggests a potential vaccine strategy to target the immunogenic neopeptides in patients with tumors carrying the NSFP1-LRRC37A2 fusion

GASZ Is Essential for Male Meiosis and Suppression of Retrotransposon Expression in the Male Germline

Nuage are amorphous ultrastructural granules in the cytoplasm of male germ cells as divergent as Drosophila, Xenopus, and Homo sapiens. Most nuage are cytoplasmic ribonucleoprotein structures implicated in diverse RNA metabolism including the regulation of PIWI-interacting RNA (piRNA) synthesis by the PIWI family (i.e., MILI, MIWI2, and MIWI). MILI is prominent in embryonic and early post-natal germ cells in nuage also called germinal granules that are often associated with mitochondria and called intermitochondrial cement. We find that GASZ (Germ cell protein with Ankyrin repeats, Sterile alpha motif, and leucine Zipper) co-localizes with MILI in intermitochondrial cement. Knockout of Gasz in mice results in a dramatic downregulation of MILI, and phenocopies the zygotene–pachytene spermatocyte block and male sterility defect observed in MILI null mice. In Gasz null testes, we observe increased hypomethylation and expression of retrotransposons similar to MILI null testes. We also find global shifts in the small RNAome, including down-regulation of repeat-associated, known, and novel piRNAs. These studies provide the first evidence for an essential structural role for GASZ in male fertility and epigenetic and post-transcriptional silencing of retrotransposons by stabilizing MILI in nuage

Identification of differentially expressed miRNAs in chicken lung and trachea with avian influenza virus infection by a deep sequencing approach

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) play critical roles in a wide spectrum of biological processes and have been shown to be important effectors in the intricate host-pathogen interaction networks. Avian influenza virus (AIV) not only causes significant economic losses in poultry production, but also is of great concern to human health. The objective of this study was to identify miRNAs associated with AIV infections in chickens.</p> <p>Results</p> <p>Total RNAs were isolated from lung and trachea of low pathogenic H5N3 infected and non-infected SPF chickens at 4 days post-infection. A total of 278,398 and 340,726 reads were obtained from lung and trachea, respectively. And 377 miRNAs were detected in lungs and 149 in tracheae from a total of 474 distinct chicken miRNAs available at the miRBase, respectively. Seventy-three and thirty-six miRNAs were differentially expressed between infected and non-infected chickens in lungs and tracheae, respectively. There were more miRNAs highly expressed in non-infected tissues than in infected tissues. Interestingly, some of these differentially expressed miRNAs, including miR-146, have been previously reported to be associated with immune-related signal pathways in mammals.</p> <p>Conclusion</p> <p>To our knowledge, this is the first study on miRNA gene expression in AIV infected chickens using a deep sequencing approach. During AIV infection, many host miRNAs were differentially regulated, supporting the hypothesis that certain miRNAs might be essential in the host-pathogen interactions. Elucidation of the mechanism of these miRNAs on the regulation of host-AIV interaction will lead to the development of new control strategies to prevent or treat AIV infections in poultry.</p

Identification of a pan-cancer oncogenic microRNA superfamily anchored by a central core seed motif

MicroRNAs modulate tumorigenesis through suppression of specific genes. As many tumour types rely on overlapping oncogenic pathways, a core set of microRNAs may exist, which consistently drives or suppresses tumorigenesis in many cancer types. Here we integrate The Cancer Genome Atlas (TCGA) pan-cancer data set with a microRNA target atlas composed of publicly available Argonaute Crosslinking Immunoprecipitation (AGO-CLIP) data to identify pan-tumour microRNA drivers of cancer. Through this analysis, we show a pan-cancer, coregulated oncogenic microRNA ‘superfamily’ consisting of the miR-17, miR-19, miR-130, miR-93, miR-18, miR-455 and miR-210 seed families, which cotargets critical tumour suppressors via a central GUGC core motif. We subsequently define mutations in microRNA target sites using the AGO-CLIP microRNA target atlas and TCGA exome-sequencing data. These combined analyses identify pan-cancer oncogenic cotargeting of the phosphoinositide 3-kinase, TGFβ and p53 pathways by the miR-17-19-130 superfamily members

Discovery of Novel MicroRNAs in Female Reproductive Tract Using Next Generation Sequencing

MicroRNAs (miRNAs) are small non-coding RNAs that mediate post-transcriptional gene silencing. Over 700 human miRNAs have currently been identified, many of which are mutated or de-regulated in diseases. Here we report the identification of novel miRNAs through deep sequencing the small RNAome (<30 nt) of over 100 tissues or cell lines derived from human female reproductive organs in both normal and disease states. These specimens include ovarian epithelium and ovarian cancer, endometrium and endometriomas, and uterine myometrium and uterine smooth muscle tumors. Sequence reads not aligning with known miRNAs were each mapped to the genome to extract flanking sequences. These extended sequence regions were folded in silico to identify RNA hairpins. Sequences demonstrating the ability to form a stem loop structure with low minimum free energy (<−25 kcal) and predicted Drosha and Dicer cut sites yielding a mature miRNA sequence matching the actual sequence were considered putative novel miRNAs. Additional confidence was achieved when putative novel hairpins assembled a collection of sequences highly similar to the putative mature miRNA but with heterogeneous 3′-ends. A confirmed novel miRNA fulfilled these criteria and had its “star” sequence in our collection. We found 7 distinct confirmed novel miRNAs, and 51 additional novel miRNAs that represented highly confident predictions but without detectable star sequences. Our novel miRNAs were detectable in multiple samples, but expressed at low levels and not specific to any one tissue or cell type. To date, this study represents the largest set of samples analyzed together to identify novel miRNAs