Can Cenik

Identification of Neuronal RNA Targets of TDP-43-containing Ribonucleoprotein Complexes

TAR DNA-binding protein 43 (TDP-43) is associated with a spectrum of neurodegenerative diseases. Although TDP-43 resembles heterogeneous nuclear ribonucleoproteins, its RNA targets and physiological protein partners remain unknown. Here we identify RNA targets of TDP-43 from cortical neurons by RNA immunoprecipitation followed by deep sequencing (RIP-seq). The canonical TDP-43 binding site (TG)n is 55.1-fold enriched, and moreover, a variant with adenine in the middle, (TG)nTA(TG)m, is highly abundant among reads in our TDP-43 RIP-seq library. TDP-43 RNA targets can be divided into three different groups: those primarily binding in introns, in exons, and across both introns and exons. TDP-43 RNA targets are particularly enriched for Gene Ontology terms related to synaptic function, RNA metabolism, and neuronal development. Furthermore, TDP-43 binds to a number of RNAs encoding for proteins implicated in neurodegeneration, including TDP-43 itself, FUS/TLS, progranulin, Tau, and ataxin 1 and -2. We also identify 25 proteins that co-purify with TDP-43 from rodent brain nuclear extracts. Prominent among them are nuclear proteins involved in pre-mRNA splicing and RNA stability and transport. Also notable are two neuron-enriched proteins, methyl CpG-binding protein 2 and polypyrimidine tract-binding protein 2 (PTBP2). A PTBP2 consensus RNA binding motif is enriched in the TDP-43 RIP-seq library, suggesting that PTBP2 may co-regulate TDP-43 RNA targets. This work thus reveals the protein and RNA components of the TDP-43-containing ribonucleoprotein complexes and provides a framework for understanding how dysregulation of TDP-43 in RNA metabolism contributes to neurodegeneration.

Next generation software for functional trend analysis

UNLABELLED FuncAssociate is a web application that discovers properties enriched in lists of genes or proteins that emerge from large-scale experimentation. Here we describe an updated application with a new interface and several new features. For example, enrichment analysis can now be performed within multiple gene- and protein-naming systems. This feature avoids potentially serious translation artifacts to which other enrichment analysis strategies are subject. AVAILABILITY The FuncAssociate web application is freely available to all users at http://llama.med.harvard.edu/funcassociate.

Introns in UTRs: Why we should stop ignoring them

Although introns in 5′‐ and 3′‐untranslated regions (UTRs) are found in many protein coding genes, rarely are they considered distinctive entities with specific functions. Indeed, mammalian transcripts with 3′‐UTR introns are often assumed nonfunctional because they are subject to elimination by nonsense‐mediated decay (NMD). Nonetheless, recent findings indicate that 5′‐ and 3′‐UTR intron status is of significant functional consequence for the regulation of mammalian genes. Therefore these features should be ignored no longer.

Genome analysis reveals interplay between 5'UTR introns and nuclear mRNA export for secretory and mitochondrial genes.

In higher eukaryotes, messenger RNAs (mRNAs) are exported from the nucleus to the cytoplasm via factors deposited near the 5′ end of the transcript during splicing. The signal sequence coding region (SSCR) can support an alternative mRNA export (ALREX) pathway that does not require splicing. However, most SSCR–containing genes also have introns, so the interplay between these export mechanisms remains unclear. Here we support a model in which the furthest upstream element in a given transcript, be it an intron or an ALREX–promoting SSCR, dictates the mRNA export pathway used. We also experimentally demonstrate that nuclear-encoded mitochondrial genes can use the ALREX pathway. Thus, ALREX can also be supported by nucleotide signals within mitochondrial-targeting sequence coding regions (MSCRs). Finally, we identified and experimentally verified novel motifs associated with the ALREX pathway that are shared by both SSCRs and MSCRs. Our results show strong correlation between 5′ untranslated region (5′UTR) intron presence/absence and sequence features at the beginning of the coding region. They also suggest that genes encoding secretory and mitochondrial proteins share a common regulatory mechanism at the level of mRNA export.

Integrative analysis of RNA, translation, and protein levels reveals distinct regulatory variation across humans

Elucidating the consequences of genetic differences between humans is essential for understanding phenotypic diversity and personalized medicine. Although variation in RNA levels, transcription factor binding, and chromatin have been explored, little is known about global variation in translation and its genetic determinants. We used ribosome profiling, RNA sequencing, and mass spectrometry to perform an integrated analysis in lymphoblastoid cell lines from a diverse group of individuals. We find significant differences in RNA, translation, and protein levels suggesting diverse mechanisms of personalized gene expression control. Combined analysis of RNA expression and ribosome occupancy improves the identification of individual protein level differences. Finally, we identify genetic differences that specifically modulate ribosome occupancy--many of these differences lie close to start codons and upstream ORFs. Our results reveal a new level of gene expression variation among humans and indicate that genetic variants can cause changes in protein levels through effects on translation.

Absence of Evidence for MHC–Dependent Mate Selection within HapMap Populations

The major histocompatibility complex (MHC) of immunity genes has been reported to influence mate choice in vertebrates, and a recent study presented genetic evidence for this effect in humans. Specifically, greater dissimilarity at the MHC locus was reported for European-American mates (parents in HapMap Phase 2 trios) than for non-mates. Here we show that the results depend on a few extreme data points, are not robust to conservative changes in the analysis procedure, and cannot be reproduced in an equivalent but independent set of European-American mates. Although some evidence suggests an avoidance of extreme MHC similarity between mates, rather than a preference for dissimilarity, limited sample sizes preclude a rigorous investigation. In summary, fine-scale molecular-genetic data do not conclusively support the hypothesis that mate selection in humans is influenced by the MHC locus.

Identification of significantly mutated regions across cancer types highlights a rich landscape of functional molecular alterations

Cancer sequencing studies have primarily identified cancer driver genes by the accumulation of protein-altering mutations. An improved method would be annotation independent, sensitive to unknown distributions of functions within proteins and inclusive of noncoding drivers. We employed density-based clustering methods in 21 tumor types to detect variably sized significantly mutated regions (SMRs). SMRs reveal recurrent alterations across a spectrum of coding and noncoding elements, including transcription factor binding sites and untranslated regions mutated in up to ∼15% of specific tumor types. SMRs demonstrate spatial clustering of alterations in molecular domains and at interfaces, often with associated changes in signaling. Mutation frequencies in SMRs demonstrate that distinct protein regions are differentially mutated across tumor types, as exemplified by a linker region of PIK3CA in which biophysical simulations suggest that mutations affect regulatory interactions. The functional diversity of SMRs underscores both the varied mechanisms of oncogenic misregulation and the advantage of functionally agnostic driver identification.

RanBP2/Nup358 Potentiates the Translation of a Subset of mRNAs Encoding Secretory Proteins

After nuclear export, mRNAs encoding secretory proteins interact with RanBP2/Nup358 on the cytoplasmic face of the nuclear pore, a step that is required for the efficient translation of these mRNAs.

An optimized kit-free method for making strand-specific deep sequencing libraries from RNA fragments

Deep sequencing of strand-specific cDNA libraries is now a ubiquitous tool for identifying and quantifying RNAs in diverse sample types. The accuracy of conclusions drawn from these analyses depends on precise and quantitative conversion of the RNA sample into a DNA library suitable for sequencing. Here, we describe an optimized method of preparing strand-specific RNA deep sequencing libraries from small RNAs and variably sized RNA fragments obtained from ribonucleoprotein particle footprinting experiments or fragmentation of long RNAs. Our approach works across a wide range of input amounts (400 pg to 200 ng), is easy to follow and produces a library in 2–3 days at relatively low reagent cost, all while giving the user complete control over every step. Because all enzymatic reactions were optimized and driven to apparent completion, sequence diversity and species abundance in the input sample are well preserved.

ASPeak: an abundance sensitive peak detection algorithm for RIP-Seq

SUMMARY Unlike DNA, RNA abundances can vary over several orders of magnitude. Thus, identification of RNA-protein binding sites from high-throughput sequencing data presents unique challenges. Although peak identification in ChIP-Seq data has been extensively explored, there are few bioinformatics tools tailored for peak calling on analogous datasets for RNA-binding proteins. Here we describe ASPeak (abundance sensitive peak detection algorithm), an implementation of an algorithm that we previously applied to detect peaks in exon junction complex RNA immunoprecipitation in tandem experiments. Our peak detection algorithm yields stringent and robust target sets enabling sensitive motif finding and downstream functional analyses. AVAILABILITY ASPeak is implemented in Perl as a complete pipeline that takes bedGraph files as input. ASPeak implementation is freely available at https://sourceforge.net/projects/as-peak under the GNU General Public License. ASPeak can be run on a personal computer, yet is designed to be easily parallelizable. ASPeak can also run on high performance computing clusters providing efficient speedup. The documentation and user manual can be obtained from http://master.dl.sourceforge.net/project/as-peak/manual.pdf.