A Novel Field-Deployable Method for Sequencing and Analyses of Henipavirus Genomes From Complex Samples on the MinION Platform.

Viruses in the genus Henipavirus encompass 2 highly pathogenic emerging zoonotic pathogens, Hendra virus (HeV) and Nipah virus (NiV). Despite the impact on human health, there is currently limited full-genome sequence information available for henipaviruses. This lack of full-length genomes hampers our ability to understand the molecular drivers of henipavirus emergence. Furthermore, rapidly deployable viral genome sequencing can be an integral part of outbreak response and epidemiological investigations to study transmission chains. In this study, we describe the development of a reverse-transcription, long-range polymerase chain reaction (LRPCR) assay for efficient genome amplification of NiV, HeV, and a related non-pathogenic henipavirus, Cedar virus (CedPV). We then demonstrated the utility of our method by amplifying partial viral genomes from 6 HeV-infected tissue samples from Syrian hamsters and 4 tissue samples from a NiV-infected African green monkey with viral loads as low as 52 genome copies/mg. We subsequently sequenced the amplified genomes on the portable Oxford Nanopore MinION platform and analyzed the data using a newly developed field-deployable bioinformatic pipeline. Our LRPCR assay allows amplification and sequencing of 2 or 4 amplicons in semi-nested reactions. Coupled with an easy-to-use bioinformatics pipeline, this method is particularly useful in the field during outbreaks in resource-poor environments.

Nephele: a cloud platform for simplified, standardized and reproducible microbiome data analysis.

Motivation: Widespread interest in the study of the microbiome has resulted in data proliferation and the development of powerful computational tools. However, many scientific researchers lack the time, training, or infrastructure to work with large datasets or to install and use command line tools. Results: The National Institute of Allergy and Infectious Diseases (NIAID) has created Nephele, a cloud-based microbiome data analysis platform with standardized pipelines and a simple web interface for transforming raw data into biological insights. Nephele integrates common microbiome analysis tools as well as valuable reference datasets like the healthy human subjects cohort of the Human Microbiome Project (HMP). Nephele is built on the Amazon Web Services cloud, which provides centralized and automated storage and compute capacity, thereby reducing the burden on researchers and their institutions. Availability and implementation: https://nephele.niaid.nih.gov and https://github.com/niaid/Nephele. Contact: darrell.hurt@nih.gov.

Evolution of early embryogenesis in rhabditid nematodes.

The cell-biological events that guide early-embryonic development occur with great precision within species but can be quite diverse across species. How these cellular processes evolve and which molecular components underlie evolutionary changes is poorly understood. To begin to address these questions, we systematically investigated early embryogenesis, from the one- to the four-cell embryo, in 34 nematode species related to C. elegans. We found 40 cell-biological characters that captured the phenotypic differences between these species. By tracing the evolutionary changes on a molecular phylogeny, we found that these characters evolved multiple times and independently of one another. Strikingly, all these phenotypes are mimicked by single-gene RNAi experiments in C. elegans. We use these comparisons to hypothesize the molecular mechanisms underlying the evolutionary changes. For example, we predict that a cell polarity module was altered during the evolution of the Protorhabditis group and show that PAR-1, a kinase localized asymmetrically in C. elegans early embryos, is symmetrically localized in the one-cell stage of Protorhabditis group species. Our genome-wide approach identifies candidate molecules-and thereby modules-associated with evolutionary changes in cell-biological phenotypes.

UTRome.org: a platform for 3'UTR biology in C. elegans.

Three-prime untranslated regions (3'UTRs) are widely recognized as important post-transcriptional regulatory regions of mRNAs. RNA-binding proteins and small non-coding RNAs such as microRNAs (miRNAs) bind to functional elements within 3'UTRs to influence mRNA stability, translation and localization. These interactions play many important roles in development, metabolism and disease. However, even in the most well-annotated metazoan genomes, 3'UTRs and their functional elements are not well defined. Comprehensive and accurate genome-wide annotation of 3'UTRs and their functional elements is thus critical. We have developed an open-access database, available at http://www.UTRome.org, to provide a rich and comprehensive resource for 3'UTR biology in the well-characterized, experimentally tractable model system Caenorhabditis elegans. UTRome.org combines data from public repositories and a large-scale effort we are undertaking to characterize 3'UTRs and their functional elements in C. elegans, including 3'UTR sequences, graphical displays, predicted and validated functional elements, secondary structure predictions and detailed data from our cloning pipeline. UTRome.org will grow substantially over time to encompass individual 3'UTR isoforms for the majority of genes, new and revised functional elements, and in vivo data on 3'UTR function as they become available. The UTRome database thus represents a powerful tool to better understand the biology of 3'UTRs.

A genome-wide map of conserved microRNA targets in C. elegans.

BACKGROUND: Metazoan miRNAs regulate protein-coding genes by binding the 3' UTR of cognate mRNAs. Identifying targets for the 115 known C. elegans miRNAs is essential for understanding their function. RESULTS: By using a new version of PicTar and sequence alignments of three nematodes, we predict that miRNAs regulate at least 10% of C. elegans genes through conserved interactions. We have developed a new experimental pipeline to assay 3' UTR-mediated posttranscriptional gene regulation via an endogenous reporter expression system amenable to high-throughput cloning, demonstrating the utility of this system using one of the most intensely studied miRNAs, let-7. Our expression analyses uncover several new potential let-7 targets and suggest a new let-7 activity in head muscle and neurons. To explore genome-wide trends in miRNA function, we analyzed functional categories of predicted target genes, finding that one-third of C. elegans miRNAs target gene sets are enriched for specific functional annotations. We have also integrated miRNA target predictions with other functional genomic data from C. elegans. CONCLUSIONS: At least 10% of C. elegans genes are predicted miRNA targets, and a number of nematode miRNAs seem to regulate biological processes by targeting functionally related genes. We have also developed and successfully utilized an in vivo system for testing miRNA target predictions in likely endogenous expression domains. The thousands of genome-wide miRNA target predictions for nematodes, humans, and flies are available from the PicTar website and are linked to an accessible graphical network-browsing tool allowing exploration of miRNA target predictions in the context of various functional genomic data resources.

Combinatorial microRNA target predictions.

MicroRNAs are small noncoding RNAs that recognize and bind to partially complementary sites in the 3' untranslated regions of target genes in animals and, by unknown mechanisms, regulate protein production of the target transcript. Different combinations of microRNAs are expressed in different cell types and may coordinately regulate cell-specific target genes. Here, we present PicTar, a computational method for identifying common targets of microRNAs. Statistical tests using genome-wide alignments of eight vertebrate genomes, PicTar's ability to specifically recover published microRNA targets, and experimental validation of seven predicted targets suggest that PicTar has an excellent success rate in predicting targets for single microRNAs and for combinations of microRNAs. We find that vertebrate microRNAs target, on average, roughly 200 transcripts each. Furthermore, our results suggest widespread coordinate control executed by microRNAs. In particular, we experimentally validate common regulation of Mtpn by miR-375, miR-124 and let-7b and thus provide evidence for coordinate microRNA control in mammals.

RNAiDB and PhenoBlast: web tools for genome-wide phenotypic mapping projects.

RNA interference (RNAi) is being used in large-scale genomic studies as a rapid way to obtain in vivo functional information associated with specific genes. How best to archive and mine the complex data derived from these studies provides a series of challenges associated with both the methods used to elicit the RNAi response and the functional data gathered. RNAiDB (RNAi Database; http://www. rnai.org) has been created for the archival, distribution and analysis of phenotypic data from large-scale RNAi analyses in Caenorhabditis elegans. The database contains a compendium of publicly available data and provides information on experimental methods and phenotypic results, including raw data in the form of images and streaming time-lapse movies. Phenotypic summaries together with graphical displays of RNAi to gene mappings allow quick intuitive comparison of results from different RNAi assays and visualization of the gene product(s) potentially inhibited by each RNAi experiment based on multiple sequence analysis methods. RNAiDB can be searched using combinatorial queries and using the novel tool PhenoBlast, which ranks genes according to their overall phenotypic similarity. RNAiDB could serve as a model database for distributing and navigating in vivo functional information from large-scale systematic phenotypic analyses in different organisms.