Does rapid sequence divergence preclude RNA structure conservation in vertebrates?

Accelerated evolution of any portion of the genome is of significant interest, potentially signaling positive selection of phenotypic traits and adaptation. Accelerated evolution remains understudied for structured RNAs, despite the fact that an RNA's structure is often key to its function. RNA structures are typically characterized by compensatory (structure-preserving) basepair changes that are unexpected given the underlying sequence variation, i.e., they have evolved through negative selection on structure. We address the question of how fast the primary sequence of an RNA can change through evolution while conserving its structure. Specifically, we consider predicted and known structures in vertebrate genomes. After careful control of false discovery rates, we obtain 13 de novo structures (and three known Rfam structures) that we predict to have rapidly evolving sequences-defined as structures where the primary sequences of human and mouse have diverged at least twice as fast (1.5 times for Rfam) as nearby neutrally evolving sequences. Two of the three known structures function in translation inhibition related to infection and immune response. We conclude that rapid sequence divergence does not preclude RNA structure conservation in vertebrates, although these events are relatively rare.

The identification and functional annotation of RNA structures conserved in vertebrates.

Structured elements of RNA molecules are essential in, e.g., RNA stabilization, localization, and protein interaction, and their conservation across species suggests a common functional role. We computationally screened vertebrate genomes for conserved RNA structures (CRSs), leveraging structure-based, rather than sequence-based, alignments. After careful correction for sequence identity and GC content, we predict ∼516,000 human genomic regions containing CRSs. We find that a substantial fraction of human-mouse CRS regions (1) colocalize consistently with binding sites of the same RNA binding proteins (RBPs) or (2) are transcribed in corresponding tissues. Additionally, a CaptureSeq experiment revealed expression of many of our CRS regions in human fetal brain, including 662 novel ones. For selected human and mouse candidate pairs, qRT-PCR and in vitro RNA structure probing supported both shared expression and shared structure despite low abundance and low sequence identity. About 30,000 CRS regions are located near coding or long noncoding RNA genes or within enhancers. Structured (CRS overlapping) enhancer RNAs and extended 3' ends have significantly increased expression levels over their nonstructured counterparts. Our findings of transcribed uncharacterized regulatory regions that contain CRSs support their RNA-mediated functionality.

Identification and characterization of novel conserved RNA structures in Drosophila.

BACKGROUND: Comparative genomics approaches have facilitated the discovery of many novel non-coding and structured RNAs (ncRNAs). The increasing availability of related genomes now makes it possible to systematically search for compensatory base changes - and thus for conserved secondary structures - even in genomic regions that are poorly alignable in the primary sequence. The wealth of available transcriptome data can add valuable insight into expression and possible function for new ncRNA candidates. Earlier work identifying ncRNAs in Drosophila melanogaster made use of sequence-based alignments and employed a sliding window approach, inevitably biasing identification toward RNAs encoded in the more conserved parts of the genome. RESULTS: To search for conserved RNA structures (CRSs) that may not be highly conserved in sequence and to assess the expression of CRSs, we conducted a genome-wide structural alignment screen of 27 insect genomes including D. melanogaster and integrated this with an extensive set of tiling array data. The structural alignment screen revealed ∼30,000 novel candidate CRSs at an estimated false discovery rate of less than 10%. With more than one quarter of all individual CRS motifs showing sequence identities below 60%, the predicted CRSs largely complement the findings of sliding window approaches applied previously. While a sixth of the CRSs were ubiquitously expressed, we found that most were expressed in specific developmental stages or cell lines. Notably, most statistically significant enrichment of CRSs were observed in pupae, mainly in exons of untranslated regions, promotors, enhancers, and long ncRNAs. Interestingly, cell lines were found to express a different set of CRSs than were found in vivo. Only a small fraction of intergenic CRSs were co-expressed with the adjacent protein coding genes, which suggests that most intergenic CRSs are independent genetic units. CONCLUSIONS: This study provides a more comprehensive view of the ncRNA transcriptome in fly as well as evidence for differential expression of CRSs during development and in cell lines.

Inhibition of ß-catenin signaling respecifies anterior-like endothelium into beating human cardiomyocytes.

During vertebrate development, mesodermal fate choices are regulated by interactions between morphogens such as activin/nodal, BMPs and Wnt/ß-catenin that define anterior-posterior patterning and specify downstream derivatives including cardiomyocyte, endothelial and hematopoietic cells. We used human embryonic stem cells to explore how these pathways control mesodermal fate choices in vitro. Varying doses of activin A and BMP4 to mimic cytokine gradient polarization in the anterior-posterior axis of the embryo led to differential activity of Wnt/ß-catenin signaling and specified distinct anterior-like (high activin/low BMP) and posterior-like (low activin/high BMP) mesodermal populations. Cardiogenic mesoderm was generated under conditions specifying anterior-like mesoderm, whereas blood-forming endothelium was generated from posterior-like mesoderm, and vessel-forming CD31(+) endothelial cells were generated from all mesoderm origins. Surprisingly, inhibition of ß-catenin signaling led to the highly efficient respecification of anterior-like endothelium into beating cardiomyocytes. Cardiac respecification was not observed in posterior-derived endothelial cells. Thus, activin/BMP gradients specify distinct mesodermal subpopulations that generate cell derivatives with unique angiogenic, hemogenic and cardiogenic properties that should be useful for understanding embryogenesis and developing therapeutics.

Let-7 family of microRNA is required for maturation and adult-like metabolism in stem cell-derived cardiomyocytes.

In metazoans, transition from fetal to adult heart is accompanied by a switch in energy metabolism-glycolysis to fatty acid oxidation. The molecular factors regulating this metabolic switch remain largely unexplored. We first demonstrate that the molecular signatures in 1-year (y) matured human embryonic stem cell-derived cardiomyocytes (hESC-CMs) are similar to those seen in in vivo-derived mature cardiac tissues, thus making them an excellent model to study human cardiac maturation. We further show that let-7 is the most highly up-regulated microRNA (miRNA) family during in vitro human cardiac maturation. Gain- and loss-of-function analyses of let-7g in hESC-CMs demonstrate it is both required and sufficient for maturation, but not for early differentiation of CMs. Overexpression of let-7 family members in hESC-CMs enhances cell size, sarcomere length, force of contraction, and respiratory capacity. Interestingly, large-scale expression data, target analysis, and metabolic flux assays suggest this let-7-driven CM maturation could be a result of down-regulation of the phosphoinositide 3 kinase (PI3K)/AKT protein kinase/insulin pathway and an up-regulation of fatty acid metabolism. These results indicate let-7 is an important mediator in augmenting metabolic energetics in maturing CMs. Promoting maturation of hESC-CMs with let-7 overexpression will be highly significant for basic and applied research.

Discriminative motif analysis of high-throughput dataset.

MOTIVATION: High-throughput ChIP-seq studies typically identify thousands of peaks for a single transcription factor (TF). It is common for traditional motif discovery tools to predict motifs that are statistically significant against a naïve background distribution but are of questionable biological relevance. RESULTS: We describe a simple yet effective algorithm for discovering differential motifs between two sequence datasets that is effective in eliminating systematic biases and scalable to large datasets. Tested on 207 ENCODE ChIP-seq datasets, our method identifies correct motifs in 78% of the datasets with known motifs, demonstrating improvement in both accuracy and efficiency compared with DREME, another state-of-art discriminative motif discovery tool. More interestingly, on the remaining more challenging datasets, we identify common technical or biological factors that compromise the motif search results and use advanced features of our tool to control for these factors. We also present case studies demonstrating the ability of our method to detect single base pair differences in DNA specificity of two similar TFs. Lastly, we demonstrate discovery of key TF motifs involved in tissue specification by examination of high-throughput DNase accessibility data. AVAILABILITY: The motifRG package is publically available via the bioconductor repository. CONTACT: yzizhen@fhcrc.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Assessment and improvement of Indian-origin rhesus macaque and Mauritian-origin cynomolgus macaque genome annotations using deep transcriptome sequencing data.

BACKGROUND: The genome annotations of rhesus (Macaca mulatta) and cynomolgus (Macaca fascicularis) macaques, two of the most common non-human primate animal models, are limited. METHODS: We analyzed large-scale macaque RNA-based next-generation sequencing (RNAseq) data to identify un-annotated macaque transcripts. RESULTS: For both macaque species, we uncovered thousands of novel isoforms for annotated genes and thousands of un-annotated intergenic transcripts enriched with non-coding RNAs. We also identified thousands of transcript sequences which are partially or completely 'missing' from current macaque genome assemblies. We showed that many newly identified transcripts were differentially expressed during SIV infection of rhesus macaques or during Ebola virus infection of cynomolgus macaques. CONCLUSIONS: For two important macaque species, we uncovered thousands of novel isoforms and un-annotated intergenic transcripts including coding and non-coding RNAs, polyadenylated and non-polyadenylated transcripts. This resource will greatly improve future macaque studies, as demonstrated by their applications in infectious disease studies.

Compression of next-generation sequencing reads aided by highly efficient de novo assembly.

UNLABELLED: We present Quip, a lossless compression algorithm for next-generation sequencing data in the FASTQ and SAM/BAM formats. In addition to implementing reference-based compression, we have developed, to our knowledge, the first assembly-based compressor, using a novel de novo assembly algorithm. A probabilistic data structure is used to dramatically reduce the memory required by traditional de Bruijn graph assemblers, allowing millions of reads to be assembled very efficiently. Read sequences are then stored as positions within the assembled contigs. This is combined with statistical compression of read identifiers, quality scores, alignment information and sequences, effectively collapsing very large data sets to <15% of their original size with no loss of information. AVAILABILITY: Quip is freely available under the 3-clause BSD license from http://cs.washington.edu/homes/dcjones/quip.

An integrative genomic approach identifies p73 and p63 as activators of miR-200 microRNA family transcription.

Although microRNAs (miRNAs) are important regulators of gene expression, the transcriptional regulation of miRNAs themselves is not well understood. We employed an integrative computational pipeline to dissect the transcription factors (TFs) responsible for altered miRNA expression in ovarian carcinoma. Using experimental data and computational predictions to define miRNA promoters across the human genome, we identified TFs with binding sites significantly overrepresented among miRNA genes overexpressed in ovarian carcinoma. This pipeline nominated TFs of the p53/p63/p73 family as candidate drivers of miRNA overexpression. Analysis of data from an independent set of 253 ovarian carcinomas in The Cancer Genome Atlas showed that p73 and p63 expression is significantly correlated with expression of miRNAs whose promoters contain p53/p63/p73 family binding sites. In experimental validation of specific miRNAs predicted by the analysis to be regulated by p73 and p63, we found that p53/p63/p73 family binding sites modulate promoter activity of miRNAs of the miR-200 family, which are known regulators of cancer stem cells and epithelial-mesenchymal transitions. Furthermore, in chromatin immunoprecipitation studies both p73 and p63 directly associated with the miR-200b/a/429 promoter. This study delineates an integrative approach that can be applied to discover transcriptional regulatory mechanisms in other biological settings where analogous genomic data are available.

A new approach to bias correction in RNA-Seq.

MOTIVATION: Quantification of sequence abundance in RNA-Seq experiments is often conflated by protocol-specific sequence bias. The exact sources of the bias are unknown, but may be influenced by polymerase chain reaction amplification, or differing primer affinities and mixtures, for example. The result is decreased accuracy in many applications, such as de novo gene annotation and transcript quantification. RESULTS: We present a new method to measure and correct for these influences using a simple graphical model. Our model does not rely on existing gene annotations, and model selection is performed automatically making it applicable with few assumptions. We evaluate our method on several datasets, and by multiple criteria, demonstrating that it effectively decreases bias and increases uniformity. Additionally, we provide theoretical and empirical results showing that the method is unlikely to have any effect on unbiased data, suggesting it can be applied with little risk of spurious adjustment. AVAILABILITY: The method is implemented in the seqbias R/Bioconductor package, available freely under the LGPL license from http://bioconductor.org CONTACT: dcjones@cs.washington.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Transcripts with in silico predicted RNA structure are enriched everywhere in the mouse brain.

BACKGROUND: Post-transcriptional control of gene expression is mostly conducted by specific elements in untranslated regions (UTRs) of mRNAs, in collaboration with specific binding proteins and RNAs. In several well characterized cases, these RNA elements are known to form stable secondary structures. RNA secondary structures also may have major functional implications for long noncoding RNAs (lncRNAs). Recent transcriptional data has indicated the importance of lncRNAs in brain development and function. However, no methodical efforts to investigate this have been undertaken. Here, we aim to systematically analyze the potential for RNA structure in brain-expressed transcripts. RESULTS: By comprehensive spatial expression analysis of the adult mouse in situ hybridization data of the Allen Mouse Brain Atlas, we show that transcripts (coding as well as non-coding) associated with in silico predicted structured probes are highly and significantly enriched in almost all analyzed brain regions. Functional implications of these RNA structures and their role in the brain are discussed in detail along with specific examples. We observe that mRNAs with a structure prediction in their UTRs are enriched for binding, transport and localization gene ontology categories. In addition, after manual examination we observe agreement between RNA binding protein interaction sites near the 3' UTR structures and correlated expression patterns. CONCLUSIONS: Our results show a potential use for RNA structures in expressed coding as well as noncoding transcripts in the adult mouse brain, and describe the role of structured RNAs in the context of intracellular signaling pathways and regulatory networks. Based on this data we hypothesize that RNA structure is widely involved in transcriptional and translational regulatory mechanisms in the brain and ultimately plays a role in brain function.

Polee: RNA-Seq analysis using approximate likelihood.

The analysis of mRNA transcript abundance with RNA-Seq is a central tool in molecular biology research, but often analyses fail to account for the uncertainty in these estimates, which can be significant, especially when trying to disentangle isoforms or duplicated genes. Preserving uncertainty necessitates a full probabilistic model of the all the sequencing reads, which quickly becomes intractable, as experiments can consist of billions of reads. To overcome these limitations, we propose a new method of approximating the likelihood function of a sparse mixture model, using a technique we call the Pólya tree transformation. We demonstrate that substituting this approximation for the real thing achieves most of the benefits with a fraction of the computational costs, leading to more accurate detection of differential transcript expression and transcript coexpression.

The aptamer core of SAM-IV riboswitches mimics the ligand-binding site of SAM-I riboswitches.

A novel family of riboswitches, called SAM-IV, is the fourth distinct set of mRNA elements to be reported that regulate gene expression via direct sensing of S-adenosylmethionine (SAM or AdoMet). SAM-IV riboswitches share conserved nucleotide positions with the previously described SAM-I riboswitches, despite rearranged structures and nucleotide positions with family-specific nucleotide identities. Sequence analysis and molecular recognition experiments suggest that SAM-I and SAM-IV riboswitches share similar ligand binding sites, but have different scaffolds. Our findings support the view that RNA has considerable structural versatility and reveal that riboswitches exploit this potential to expand the scope of RNA in genetic regulation.

Multiperm: shuffling multiple sequence alignments while approximately preserving dinucleotide frequencies.

SUMMARY: Assessing the statistical significance of structured RNA predicted from multiple sequence alignments relies on the existence of a good null model. We present here a random shuffling algorithm, Multiperm, that preserves not only the gap and local conservation structure in alignments of arbitrarily many sequences, but also the approximate dinucleotide frequencies. No shuffling algorithm that simultaneously preserves these three characteristics of a multiple (beyond pairwise) alignment has been available to date. As one benchmark, we show that it produces shuffled exonic sequences having folding free energy closer to native sequences than shuffled alignments that do not preserve dinucleotide frequencies. AVAILABILITY: The Multiperm GNU Cb++ source code is available at http://www.anandam.name/multiperm

Spatial modeling of prostate cancer metabolic gene expression reveals extensive heterogeneity and selective vulnerabilities.

Spatial heterogeneity is a fundamental feature of the tumor microenvironment (TME), and tackling spatial heterogeneity in neoplastic metabolic aberrations is critical for tumor treatment. Genome-scale metabolic network models have been used successfully to simulate cancer metabolic networks. However, most models use bulk gene expression data of entire tumor biopsies, ignoring spatial heterogeneity in the TME. To account for spatial heterogeneity, we performed spatially-resolved metabolic network modeling of the prostate cancer microenvironment. We discovered novel malignant-cell-specific metabolic vulnerabilities targetable by small molecule compounds. We predicted that inhibiting the fatty acid desaturase SCD1 may selectively kill cancer cells based on our discovery of spatial separation of fatty acid synthesis and desaturation. We also uncovered higher prostaglandin metabolic gene expression in the tumor, relative to the surrounding tissue. Therefore, we predicted that inhibiting the prostaglandin transporter SLCO2A1 may selectively kill cancer cells. Importantly, SCD1 and SLCO2A1 have been previously shown to be potently and selectively inhibited by compounds such as CAY10566 and suramin, respectively. We also uncovered cancer-selective metabolic liabilities in central carbon, amino acid, and lipid metabolism. Our novel cancer-specific predictions provide new opportunities to develop selective drug targets for prostate cancer and other cancers where spatial transcriptomics datasets are available.

Metabolic Control over mTOR-Dependent Diapause-like State.

Regulation of embryonic diapause, dormancy that interrupts the tight connection between developmental stage and time, is still poorly understood. Here, we characterize the transcriptional and metabolite profiles of mouse diapause embryos and identify unique gene expression and metabolic signatures with activated lipolysis, glycolysis, and metabolic pathways regulated by AMPK. Lipolysis is increased due to mTORC2 repression, increasing fatty acids to support cell survival. We further show that starvation in pre-implantation ICM-derived mouse ESCs induces a reversible dormant state, transcriptionally mimicking the in vivo diapause stage. During starvation, Lkb1, an upstream kinase of AMPK, represses mTOR, which induces a reversible glycolytic and epigenetically H4K16Ac-negative, diapause-like state. Diapause furthermore activates expression of glutamine transporters SLC38A1/2. We show by genetic and small molecule inhibitors that glutamine transporters are essential for the H4K16Ac-negative, diapause state. These data suggest that mTORC1/2 inhibition, regulated by amino acid levels, is causal for diapause metabolism and epigenetic state.

A widespread riboswitch candidate that controls bacterial genes involved in molybdenum cofactor and tungsten cofactor metabolism.

We have identified a highly conserved RNA motif located upstream of genes encoding molybdate transporters, molybdenum cofactor (Moco) biosynthesis enzymes, and proteins that utilize Moco as a coenzyme. Bioinformatics searches have identified 176 representatives in gamma-Proteobacteria, delta-Proteobacteria, Clostridia, Actinobacteria, Deinococcus-Thermus species and DNAs from environmental samples. Using genetic assays, we demonstrate that a Moco RNA in Escherichia coli associated with the Moco biosynthetic operon controls gene expression in response to Moco production. In addition, we provide evidence indicating that this conserved RNA discriminates against closely related analogues of Moco. These results, together with extensive phylogenetic conservation and typical gene control structures near some examples, indicate that representatives of this structured RNA represent a novel class of riboswitches that sense Moco. Furthermore, we identify variants of this RNA that are likely to be triggered by the related tungsten cofactor (Tuco), which carries tungsten in place of molybdenum as the metal constituent.

Finding non-coding RNAs through genome-scale clustering.

Non-coding RNAs (ncRNAs) are transcripts that do not code for proteins. Recent findings have shown that RNA-mediated regulatory mechanisms influence a substantial portion of typical microbial genomes. We present an efficient method for finding potential ncRNAs in bacteria by clustering genomic sequences based on homology inferred from both primary sequence and secondary structure. We evaluate our approach using a set of predominantly Firmicutes sequences. Our results showed that, though primary sequence based-homology search was inaccurate for diverged ncRNA sequences, through our clustering method, we were able to infer motifs that recovered nearly all members of most known ncRNA families. Hence, our method shows promise for discovering new families of ncRNA.

MicroRNA discovery and profiling in human embryonic stem cells by deep sequencing of small RNA libraries.

We used massively parallel pyrosequencing to discover and characterize microRNAs (miRNAs) expressed in human embryonic stem cells (hESC). Sequencing of small RNA cDNA libraries derived from undifferentiated hESC and from isogenic differentiating cultures yielded a total of 425,505 high-quality sequence reads. A custom data analysis pipeline delineated expression profiles for 191 previously annotated miRNAs, 13 novel miRNAs, and 56 candidate miRNAs. Further characterization of a subset of the novel miRNAs in Dicer-knockdown hESC demonstrated Dicer-dependent expression, providing additional validation of our results. A set of 14 miRNAs (9 known and 5 novel) was noted to be expressed in undifferentiated hESC and then strongly downregulated with differentiation. Functional annotation analysis of predicted targets of these miRNAs and comparison with a null model using non-hESC-expressed miRNAs identified statistically enriched functional categories, including chromatin remodeling and lineage-specific differentiation annotations. Finally, integration of our data with genome-wide chromatin immunoprecipitation data on OCT4, SOX2, and NANOG binding sites implicates these transcription factors in the regulation of nine of the novel/candidate miRNAs identified here. Comparison of our results with those of recent deep sequencing studies in mouse and human ESC shows that most of the novel/candidate miRNAs found here were not identified in the other studies. The data indicate that hESC express a larger complement of miRNAs than previously appreciated, and they provide a resource for additional studies of miRNA regulation of hESC physiology. Disclosure of potential conflicts of interest is found at the end of this article.

Macronuclear genome sequence of the ciliate Tetrahymena thermophila, a model eukaryote.

The ciliate Tetrahymena thermophila is a model organism for molecular and cellular biology. Like other ciliates, this species has separate germline and soma functions that are embodied by distinct nuclei within a single cell. The germline-like micronucleus (MIC) has its genome held in reserve for sexual reproduction. The soma-like macronucleus (MAC), which possesses a genome processed from that of the MIC, is the center of gene expression and does not directly contribute DNA to sexual progeny. We report here the shotgun sequencing, assembly, and analysis of the MAC genome of T. thermophila, which is approximately 104 Mb in length and composed of approximately 225 chromosomes. Overall, the gene set is robust, with more than 27,000 predicted protein-coding genes, 15,000 of which have strong matches to genes in other organisms. The functional diversity encoded by these genes is substantial and reflects the complexity of processes required for a free-living, predatory, single-celled organism. This is highlighted by the abundance of lineage-specific duplications of genes with predicted roles in sensing and responding to environmental conditions (e.g., kinases), using diverse resources (e.g., proteases and transporters), and generating structural complexity (e.g., kinesins and dyneins). In contrast to the other lineages of alveolates (apicomplexans and dinoflagellates), no compelling evidence could be found for plastid-derived genes in the genome. UGA, the only T. thermophila stop codon, is used in some genes to encode selenocysteine, thus making this organism the first known with the potential to translate all 64 codons in nuclear genes into amino acids. We present genomic evidence supporting the hypothesis that the excision of DNA from the MIC to generate the MAC specifically targets foreign DNA as a form of genome self-defense. The combination of the genome sequence, the functional diversity encoded therein, and the presence of some pathways missing from other model organisms makes T. thermophila an ideal model for functional genomic studies to address biological, biomedical, and biotechnological questions of fundamental importance.