Widespread haploid-biased gene expression enables sperm-level natural selection.

Sperm are haploid but must be functionally equivalent to distribute alleles equally among progeny. Accordingly, gene products are shared through spermatid cytoplasmic bridges that erase phenotypic differences between individual haploid sperm. Here, we show that a large class of mammalian genes are not completely shared across these bridges. We call these genes "genoinformative markers" (GIMs) and show that a subset can act as selfish genetic elements that spread alleles unevenly through murine, bovine, and human populations. We identify evolutionary pressure to avoid conflict between sperm and somatic function as GIMs are enriched for testis-specific gene expression, paralogs, and isoforms. Therefore, GIMs and sperm-level natural selection may help to explain why testis gene expression patterns are an outlier relative to all other tissues.

Common and phylogenetically widespread coding for peptides by bacterial small RNAs.

BACKGROUND: While eukaryotic noncoding RNAs have recently received intense scrutiny, it is becoming clear that bacterial transcription is at least as pervasive. Bacterial small RNAs and antisense RNAs (sRNAs) are often assumed to be noncoding, due to their lack of long open reading frames (ORFs). However, there are numerous examples of sRNAs encoding for small proteins, whether or not they also have a regulatory role at the RNA level. METHODS: Here, we apply flexible machine learning techniques based on sequence features and comparative genomics to quantify the prevalence of sRNA ORFs under natural selection to maintain protein-coding function in 14 phylogenetically diverse bacteria. Importantly, we quantify uncertainty in our predictions, and follow up on them using mass spectrometry proteomics and comparison to datasets including ribosome profiling. RESULTS: A majority of annotated sRNAs have at least one ORF between 10 and 50 amino acids long, and we conservatively predict that 409±191.7 unannotated sRNA ORFs are under selection to maintain coding (mean estimate and 95% confidence interval), an average of 29 per species considered here. This implies that overall at least 10.3±0.5% of sRNAs have a coding ORF, and in some species around 20% do. 165±69 of these novel coding ORFs have some antisense overlap to annotated ORFs. As experimental validation, many of our predictions are translated in published ribosome profiling data and are identified via mass spectrometry shotgun proteomics. B. subtilis sRNAs with coding ORFs are enriched for high expression in biofilms and confluent growth, and S. pneumoniae sRNAs with coding ORFs are involved in virulence. sRNA coding ORFs are enriched for transmembrane domains and many are predicted novel components of type I toxin/antitoxin systems. CONCLUSIONS: We predict over two dozen new protein-coding genes per bacterial species, but crucially also quantified the uncertainty in this estimate. Our predictions for sRNA coding ORFs, along with predicted novel type I toxins and tools for sorting and visualizing genomic context, are freely available in a user-friendly format at http://disco-bac.web.pasteur.fr. We expect these easily-accessible predictions to be a valuable tool for the study not only of bacterial sRNAs and type I toxin-antitoxin systems, but also of bacterial genetics and genomics.

Quantitative assessment of RNA-protein interactions with high-throughput sequencing-RNA affinity profiling.

Because RNA-protein interactions have a central role in a wide array of biological processes, methods that enable a quantitative assessment of these interactions in a high-throughput manner are in great demand. Recently, we developed the high-throughput sequencing-RNA affinity profiling (HiTS-RAP) assay that couples sequencing on an Illumina GAIIx genome analyzer with the quantitative assessment of protein-RNA interactions. This assay is able to analyze interactions between one or possibly several proteins with millions of different RNAs in a single experiment. We have successfully used HiTS-RAP to analyze interactions of the EGFP and negative elongation factor subunit E (NELF-E) proteins with their corresponding canonical and mutant RNA aptamers. Here we provide a detailed protocol for HiTS-RAP that can be completed in about a month (8 d hands-on time). This includes the preparation and testing of recombinant proteins and DNA templates, clustering DNA templates on a flowcell, HiTS and protein binding with a GAIIx instrument, and finally data analysis. We also highlight aspects of HiTS-RAP that can be further improved and points of comparison between HiTS-RAP and two other recently developed methods, quantitative analysis of RNA on a massively parallel array (RNA-MaP) and RNA Bind-n-Seq (RBNS), for quantitative analysis of RNA-protein interactions.

MicroRNA target finding by comparative genomics.

MicroRNAs (miRNAs) have been implicated in virtually every metazoan biological process, exerting a widespread impact on gene expression. MicroRNA repression is conferred by relatively short "seed match" sequences, although the degree of repression varies widely for individual target sites. The factors controlling whether, and to what extent, a target site is repressed are not fully understood. As an alternative to target prediction based on sequence alone, comparative genomics has emerged as an invaluable tool for identifying miRNA targets that are conserved by natural selection, and hence likely effective and important. Here we present a general method for quantifying conservation of miRNA seed match sites, separating it from background conservation, controlling for various biases, and predicting miRNA targets. This method is useful not only for generating predictions but also as a tool for empirically evaluating the importance of various target prediction criteria.

Direct measurement of DNA affinity landscapes on a high-throughput sequencing instrument.

Several methods for characterizing DNA-protein interactions are available, but none have demonstrated both high throughput and quantitative measurement of affinity. Here we describe 'high-throughput sequencing'-'fluorescent ligand interaction profiling' (HiTS-FLIP), a technique for measuring quantitative protein-DNA binding affinity at unprecedented depth. In this approach, the optics built into a high-throughput sequencer are used to visualize in vitro binding of a protein to sequenced DNA in a flow cell. Application of HiTS-FLIP to the protein Gcn4 (Gcn4p), the master regulator of the yeast amino acid starvation response, yielded ~440 million binding measurements, enabling determination of dissociation constants for all 12-mer sequences having submicromolar affinity. These data revealed a complex interdependency between motif positions, allowed improved discrimination of in vivo Gcn4p binding sites and regulatory targets relative to previous methods and showed that sets of genes with different promoter affinities to Gcn4p have distinct functions and expression kinetics. Broad application of this approach should increase understanding of the interactions that drive transcription.

Hepatitis C virus infection and hepatic stellate cell activation downregulate miR-29: miR-29 overexpression reduces hepatitis C viral abundance in culture.

BACKGROUND: Chronic hepatitis C virus (HCV)-induced liver fibrosis involves upregulation of transforming growth factor (TGF)-ß and subsequent hepatic stellate cell (HSC) activation. MicroRNAs (miRNAs) regulate HCV infection and HSC activation. METHODS: TaqMan miRNA profiling identified 12 miRNA families differentially expressed between chronically HCV-infected human livers and uninfected controls. To identify pathways affected by miRNAs, we developed a new algorithm (pathway analysis of conserved targets), based on the probability of conserved targeting. RESULTS: This analysis suggested a role for miR-29 during HCV infection. Of interest, miR-29 was downregulated in most HCV-infected patients. miR-29 regulates expression of extracellular matrix proteins. In culture, HCV infection downregulated miR-29, and miR-29 overexpression reduced HCV RNA abundance. miR-29 also appears to play a role in HSCs. Hepatocytes and HSCs contribute similar amounts of miR-29 to whole liver. Both activation of primary HSCs and TGF-ß treatment of immortalized HSCs downregulated miR-29. miR-29 overexpression in LX-2 cells decreased collagen expression and modestly decreased proliferation. miR-29 downregulation by HCV may derepress extracellular matrix synthesis during HSC activation. CONCLUSIONS: HCV infection downregulates miR-29 in hepatocytes and may potentiate collagen synthesis by reducing miR-29 levels in activated HSCs. Treatment with miR-29 mimics in vivo might inhibit HCV while reducing fibrosis.

Formation, regulation and evolution of Caenorhabditis elegans 3'UTRs.

Post-transcriptional gene regulation frequently occurs through elements in mRNA 3' untranslated regions (UTRs). Although crucial roles for 3'UTR-mediated gene regulation have been found in Caenorhabditis elegans, most C. elegans genes have lacked annotated 3'UTRs. Here we describe a high-throughput method for reliable identification of polyadenylated RNA termini, and we apply this method, called poly(A)-position profiling by sequencing (3P-Seq), to determine C. elegans 3'UTRs. Compared to standard methods also recently applied to C. elegans UTRs, 3P-Seq identified 8,580 additional UTRs while excluding thousands of shorter UTR isoforms that do not seem to be authentic. Analysis of this expanded and corrected data set suggested that the high A/U content of C. elegans 3'UTRs facilitated genome compaction, because the elements specifying cleavage and polyadenylation, which are A/U rich, can more readily emerge in A/U-rich regions. Indeed, 30% of the protein-coding genes have mRNAs with alternative, partially overlapping end regions that generate another 10,480 cleavage and polyadenylation sites that had gone largely unnoticed and represent potential evolutionary intermediates of progressive UTR shortening. Moreover, a third of the convergently transcribed genes use palindromic arrangements of bidirectional elements to specify UTRs with convergent overlap, which also contributes to genome compaction by eliminating regions between genes. Although nematode 3'UTRs have median length only one-sixth that of mammalian 3'UTRs, they have twice the density of conserved microRNA sites, in part because additional types of seed-complementary sites are preferentially conserved. These findings reveal the influence of cleavage and polyadenylation on the evolution of genome architecture and provide resources for studying post-transcriptional gene regulation.

Most mammalian mRNAs are conserved targets of microRNAs.

MicroRNAs (miRNAs) are small endogenous RNAs that pair to sites in mRNAs to direct post-transcriptional repression. Many sites that match the miRNA seed (nucleotides 2-7), particularly those in 3' untranslated regions (3'UTRs), are preferentially conserved. Here, we overhauled our tool for finding preferential conservation of sequence motifs and applied it to the analysis of human 3'UTRs, increasing by nearly threefold the detected number of preferentially conserved miRNA target sites. The new tool more efficiently incorporates new genomes and more completely controls for background conservation by accounting for mutational biases, dinucleotide conservation rates, and the conservation rates of individual UTRs. The improved background model enabled preferential conservation of a new site type, the "offset 6mer," to be detected. In total, >45,000 miRNA target sites within human 3'UTRs are conserved above background levels, and >60% of human protein-coding genes have been under selective pressure to maintain pairing to miRNAs. Mammalian-specific miRNAs have far fewer conserved targets than do the more broadly conserved miRNAs, even when considering only more recently emerged targets. Although pairing to the 3' end of miRNAs can compensate for seed mismatches, this class of sites constitutes less than 2% of all preferentially conserved sites detected. The new tool enables statistically powerful analysis of individual miRNA target sites, with the probability of preferentially conserved targeting (P(CT)) correlating with experimental measurements of repression. Our expanded set of target predictions (including conserved 3'-compensatory sites), are available at the TargetScan website, which displays the P(CT) for each site and each predicted target.