Serum levels of mature microRNAs in DICER1-mutated pleuropulmonary blastoma.

DICER1 is a critical gene in the biogenesis of mature microRNAs, short non-coding RNAs that derive from either -3p or -5p precursor microRNA strands. Germline mutations of DICER1 are associated with a range of human malignancies, including pleuropulmonary blastoma (PPB). Additional somatic 'hotspot' mutations in the microRNA processing ribonuclease IIIb (RNase IIIb) domain of DICER1 are reported in cancer, and which affect microRNA biogenesis, resulting in a -3p mature microRNA strand bias. Here, in a germline (exon11 c.1806_1810insATTGA) DICER1-mutated PPB, we first confirmed the presence of an additional somatic RNase IIIb hotspot mutation (exon25 c.5425G>A [p.G1809R]) by conventional sequencing. Second, we investigated serum levels of mature microRNAs at the time of PPB diagnosis, and compared the findings with serum results from a comprehensive range of pediatric cancer patients and controls (n=52). We identified a panel of 45 microRNAs that were present at elevated levels in the serum at the time of PPB diagnosis, with a significant majority noted be derived from the -3p strand (P=0.013). In addition, we identified a subset of 10 serum microRNAs (namely miR-125a-3p, miR-125b-2-3p, miR-380-5p, miR-125b-1-3p, let-7f-2-3p, let-7a-3p, let-7b-3p, miR-708-3p, miR-138-1-3p and miR-532-3p) that were most abundant in the PPB case. Serum levels of two representative microRNAs, miR-125a-3p and miR-125b-2-3p, were not elevated in DICER1 germline-mutated relatives. In the PPB case, serum levels of miR-125a-3p and miR-125b-2-3p increased before chemotherapy, and then showed an early reduction following treatment. These microRNAs may offer future utility as serum biomarkers for screening patients with known germline DICER1 mutations for early detection of PPB, and for potential disease-monitoring in cases with confirmed PPB.We would like to thank the following for providing financial support: SPARKS (NC, MJM), Medical Research Council Fellowship (MJM), TD Bank/LDI scholarship (LdK), Alex’s Lemonade Stand Foundation (WDF), Cancer Research UK (NC) and European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement No. 310018 (MT).This is the final published version. It first appeared at http://www.nature.com/oncsis/journal/v3/n2/full/oncsis20141a.html

Detecting microRNA binding and siRNA off-target effects from expression data.

Sylamer is a method for detecting microRNA target and small interfering RNA off-target signals in 3' untranslated regions from a ranked gene list, sorted from upregulated to downregulated, after a microRNA perturbation or RNA interference experiment. The output is a landscape plot that tracks occurrence biases using hypergeometric P-values for all words across the gene ranking. We demonstrated the utility, speed and accuracy of this approach on several datasets

MCL-CAw: A refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure

Abstract Background The reconstruction of protein complexes from the physical interactome of organisms serves as a building block towards understanding the higher level organization of the cell. Over the past few years, several independent high-throughput experiments have helped to catalogue enormous amount of physical protein interaction data from organisms such as yeast. However, these individual datasets show lack of correlation with each other and also contain substantial number of false positives (noise). Over these years, several affinity scoring schemes have also been devised to improve the qualities of these datasets. Therefore, the challenge now is to detect meaningful as well as novel complexes from protein interaction (PPI) networks derived by combining datasets from multiple sources and by making use of these affinity scoring schemes. In the attempt towards tackling this challenge, the Markov Clustering algorithm (MCL) has proved to be a popular and reasonably successful method, mainly due to its scalability, robustness, and ability to work on scored (weighted) networks. However, MCL produces many noisy clusters, which either do not match known complexes or have additional proteins that reduce the accuracies of correctly predicted complexes. Results Inspired by recent experimental observations by Gavin and colleagues on the modularity structure in yeast complexes and the distinctive properties of "core" and "attachment" proteins, we develop a core-attachment based refinement method coupled to MCL for reconstruction of yeast complexes from scored (weighted) PPI networks. We combine physical interactions from two recent "pull-down" experiments to generate an unscored PPI network. We then score this network using available affinity scoring schemes to generate multiple scored PPI networks. The evaluation of our method (called MCL-CAw) on these networks shows that: (i) MCL-CAw derives larger number of yeast complexes and with better accuracies than MCL, particularly in the presence of natural noise; (ii) Affinity scoring can effectively reduce the impact of noise on MCL-CAw and thereby improve the quality (precision and recall) of its predicted complexes; (iii) MCL-CAw responds well to most available scoring schemes. We discuss several instances where MCL-CAw was successful in deriving meaningful complexes, and where it missed a few proteins or whole complexes due to affinity scoring of the networks. We compare MCL-CAw with several recent complex detection algorithms on unscored and scored networks, and assess the relative performance of the algorithms on these networks. Further, we study the impact of augmenting physical datasets with computationally inferred interactions for complex detection. Finally, we analyse the essentiality of proteins within predicted complexes to understand a possible correlation between protein essentiality and their ability to form complexes. Conclusions We demonstrate that core-attachment based refinement in MCL-CAw improves the predictions of MCL on yeast PPI networks. We show that affinity scoring improves the performance of MCL-CAw.http://deepblue.lib.umich.edu/bitstream/2027.42/78256/1/1471-2105-11-504.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/2/1471-2105-11-504-S1.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/3/1471-2105-11-504-S2.ZIPhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/4/1471-2105-11-504.pdfPeer Reviewe

Chromosomal-level assembly of the Asian Seabass genome using long sequence reads and multi-layered scaffolding

We report here the ~670 Mb genome assembly of the Asian seabass (Lates calcarifer), a tropical marine teleost. We used long-read sequencing augmented by transcriptomics, optical and genetic mapping along with shared synteny from closely related fish species to derive a chromosome-level assembly with a contig N50 size over 1 Mb and scaffold N50 size over 25 Mb that span ~90% of the genome. The population structure of L. calcarifer species complex was analyzed by re-sequencing 61 individuals representing various regions across the species' native range. SNP analyses identified high levels of genetic diversity and confirmed earlier indications of a population stratification comprising three clades with signs of admixture apparent in the South-East Asian population. The quality of the Asian seabass genome assembly far exceeds that of any other fish species, and will serve as a new standard for fish genomics

Allele-specific miRNA-binding analysis identifies candidate target genes for breast cancer risk

Most breast cancer (BC) risk-associated single-nucleotide polymorphisms (raSNPs) identified in genome-wide association studies (GWAS) are believed to cis-regulate the expression of genes. We hypothesise that cis-regulatory variants contributing to disease risk may be affecting microRNA (miRNA) genes and/or miRNA binding. To test this, we adapted two miRNA-binding prediction algorithms-TargetScan and miRanda-to perform allele-specific queries, and integrated differential allelic expression (DAE) and expression quantitative trait loci (eQTL) data, to query 150 genome-wide significant ( P≤5×10-8 ) raSNPs, plus proxies. We found that no raSNP mapped to a miRNA gene, suggesting that altered miRNA targeting is an unlikely mechanism involved in BC risk. Also, 11.5% (6 out of 52) raSNPs located in 3'-untranslated regions of putative miRNA target genes were predicted to alter miRNA::mRNA (messenger RNA) pair binding stability in five candidate target genes. Of these, we propose RNF115, at locus 1q21.1, as a strong novel target gene associated with BC risk, and reinforce the role of miRNA-mediated cis-regulation at locus 19p13.11. We believe that integrating allele-specific querying in miRNA-binding prediction, and data supporting cis-regulation of expression, improves the identification of candidate target genes in BC risk, as well as in other common cancers and complex diseases.Funding Agency Portuguese Foundation for Science and Technology CRESC ALGARVE 2020 European Union (EU) 303745 Maratona da Saude Award DL 57/2016/CP1361/CT0042 SFRH/BPD/99502/2014 CBMR-UID/BIM/04773/2013 POCI-01-0145-FEDER-022184info:eu-repo/semantics/publishedVersio

Detection of regulator genes and eQTLs in gene networks

Genetic differences between individuals associated to quantitative phenotypic traits, including disease states, are usually found in non-coding genomic regions. These genetic variants are often also associated to differences in expression levels of nearby genes (they are "expression quantitative trait loci" or eQTLs for short) and presumably play a gene regulatory role, affecting the status of molecular networks of interacting genes, proteins and metabolites. Computational systems biology approaches to reconstruct causal gene networks from large-scale omics data have therefore become essential to understand the structure of networks controlled by eQTLs together with other regulatory genes, and to generate detailed hypotheses about the molecular mechanisms that lead from genotype to phenotype. Here we review the main analytical methods and softwares to identify eQTLs and their associated genes, to reconstruct co-expression networks and modules, to reconstruct causal Bayesian gene and module networks, and to validate predicted networks in silico.Comment: minor revision with typos corrected; review article; 24 pages, 2 figure

Electrostatic charging of jumping droplets

With the broad interest in and development of superhydrophobic surfaces for self-cleaning, condensation heat transfer enhancement and anti-icing applications, more detailed insights on droplet interactions on these surfaces have emerged. Specifically, when two droplets coalesce, they can spontaneously jump away from a superhydrophobic surface due to the release of excess surface energy. Here we show that jumping droplets gain a net positive charge that causes them to repel each other mid-flight. We used electric fields to quantify the charge on the droplets and identified the mechanism for the charge accumulation, which is associated with the formation of the electric double layer at the droplet–surface interface. The observation of droplet charge accumulation provides insight into jumping droplet physics as well as processes involving charged liquid droplets. Furthermore, this work is a starting point for more advanced approaches for enhancing jumping droplet surface performance by using external electric fields to control droplet jumping.United States. Dept. of Energy. Office of Basic Energy Sciences (Solid-State Solar-Thermal Energy Conversion Center Award DE-FG02-09ER46577)United States. Office of Naval ResearchNational Science Foundation (U.S.) (Major Research Instrumentation Grant for Rapid Response Research (MRI- RAPID))National Science Foundation (U.S.) (Award ECS-0335765)National Science Foundation (U.S.). Graduate Research Fellowship Program (Grant 1122374

High sample throughput genotyping for estimating C-lineage introgression in the dark honeybee: an accurate and cost-effective SNP-based tool

The natural distribution of the honeybee (Apis mellifera L.) has been changed by humans in recent decades to such an extent that the formerly widest-spread European subspecies, Apis mellifera mellifera, is threatened by extinction through introgression from highly divergent commercial strains in large tracts of its range. Conservation efforts for A. m. mellifera are underway in multiple European countries requiring reliable and cost-efficient molecular tools to identify purebred colonies. Here, we developed four ancestry-informative SNP assays for high sample throughput genotyping using the iPLEX Mass Array system. Our customized assays were tested on DNA from individual and pooled, haploid and diploid honeybee samples extracted from different tissues using a diverse range of protocols. The assays had a high genotyping success rate and yielded accurate genotypes. Performance assessed against whole-genome data showed that individual assays behaved well, although the most accurate introgression estimates were obtained for the four assays combined (117 SNPs). The best compromise between accuracy and genotyping costs was achieved when combining two assays (62 SNPs). We provide a ready-to-use cost-effective tool for accurate molecular identification and estimation oinfo:eu-repo/semantics/publishedVersio

Genomic analysis of Sparus aurata reveals the evolutionary dynamics of sex-biased genes in a sequential hermaphrodite fish

Sexual dimorphism is a fascinating subject in evolutionary biology and mostly results from sex-biased expression of genes, which have been shown to evolve faster in gonochoristic species. We report here genome and sex-specific transcriptome sequencing of Sparus aurata, a sequential hermaphrodite fish. Evolutionary comparative analysis reveals that sex-biased genes in S. aurata are similar in number and function, but evolved following strikingly divergent patterns compared with gonochoristic species, showing overall slower rates because of stronger functional constraints. Fast evolution is observed only for highly ovary-biased genes due to female-specific patterns of selection that are related to the peculiar reproduction mode of S. aurata, first maturing as male, then as female. To our knowledge, these findings represent the first genome-wide analysis on sex-biased loci in a hermaphrodite vertebrate species, demonstrating how having two sexes in the same individual profoundly affects the fate of a large set of evolutionarily relevant genes.European Union KBBE.2013.1.2-10 European Community 311920 Fondazione Cassa di Risparmio Padova e Rovigo FCT - Foundation for Science and Technology research grant SPARCOMP under the Call ARISTEIA I of the National Strategic Reference Framework - by the EU 36 Hellenic Republic through the European Social Fundinfo:eu-repo/semantics/publishedVersio

A novel member of the let-7 microRNA family is associated with developmental transitions in filarial nematode parasites

Background: Filarial nematodes are important pathogens in the tropics transmitted to humans via the bite of blood sucking arthropod vectors. The molecular mechanisms underpinning survival and differentiation of these parasites following transmission are poorly understood. microRNAs are small non-coding RNA molecules that regulate target mRNAs and we set out to investigate whether they play a role in the infection event. Results: microRNAs differentially expressed during the early post-infective stages of Brugia pahangi L3 were identified by microarray analysis. One of these, bpa-miR-5364, was selected for further study as it is upregulated ~12-fold at 24 hours post-infection, is specific to clade III nematodes, and is a novel member of the let-7 family, which are known to have key developmental functions in the free-living nematode Caenorhabditis elegans. Predicted mRNA targets of bpa-miR-5364 were identified using bioinformatics and comparative genomics approaches that relied on the conservation of miR-5364 binding sites in the orthologous mRNAs of other filarial nematodes. Finally, we confirmed the interaction between bpa-miR-5364 and three of its predicted targets using a dual luciferase assay. Conclusions: These data provide new insight into the molecular mechanisms underpinning the transmission of third stage larvae of filarial nematodes from vector to mammal. This study is the first to identify parasitic nematode mRNAs that are verified targets of specific microRNAs and demonstrates that post-transcriptional control of gene expression via stage-specific expression of microRNAs may be important in the success of filarial infection