Hyeshik Chang

Currently, there is no method to distinguish between the roles of a subunit in one multisubunit protein complex from its roles in other complexes in vivo. This is because a mutation in a common subunit will affect all complexes containing that subunit. Here, we describe a unique method to discriminate...

Global target mRNA specification and regulation by the RNA-binding protein ZFP36.

Genome Biol. 2014 Jan 8;15(1):R12

Authors: Mukherjee N, Jacobs NC, Hafner M, Kennington EA, Nusbaum JD, Tuschl T, Blackshear PJ, Ohler U

Abstract
BACKGROUND: ZFP36, also known as tristetraprolin or TTP, and ELAVL1, also known as HuR, are two disease-relevant RNA-binding proteins (RBPs) that both interact with AU-rich sequences but have antagonistic roles. While ELAVL1 binding has been profiled in several studies, the precise in vivo binding specificity of ZFP36 has not been investigated on a global scale. We determined ZFP36 binding preferences using cross-linking and immunoprecipitation in human embryonic kidney cells, and examined the combinatorial regulation of AU-rich elements by ZFP36 and ELAVL1.
RESULTS: Targets bound and negatively regulated by ZFP36 include transcripts encoding proteins necessary for immune function and cancer, and transcripts encoding other RBPs. Using partial correlation analysis, we were able to quantify the association between ZFP36 binding sites and differential target RNA abundance upon ZFP36 overexpression independent of effects from confounding features. Genes with increased mRNA half-lives in ZFP36 knockout versus wild-type mouse cells were significantly enriched for our human ZFP36 targets. We identified thousands of overlapping ZFP36 and ELAVL1 binding sites, in 1,313 genes, and found that ZFP36 degrades transcripts through specific AU-rich sequences, representing a subset of the U-rich sequences ELAVL1 interacts with to stabilize transcripts.
CONCLUSIONS: ZFP36-RNA target specificities in vivo are quantitatively similar to previously reported in vitro binding affinities. ZFP36 and ELAVL1 bind an overlapping spectrum of RNA sequences, yet with differential relative preferences that dictate combinatorial regulatory potential. Our findings and methodology delineate an approach to unravel in vivo combinatorial regulation by RNA-binding proteins.

PMID: 24401661 [PubMed - as supplied by publisher]

Background: RNA-binding proteins (RBPs) play important roles in cellular homeostasis by controlling gene expression at the post-transcriptional level. Results: We explore the expression of more than 800 RBPs in sixteen healthy human tissues and their patterns of dysregulation in cancer genomes from The Cancer Genome Atlas project. We show that genes encoding RBPs are consistently and significantly highly expressed compared with other classes of genes, including those encoding regulatory components such as transcription factors, miRNAs and long non-coding RNAs. We also demonstrate that a set of RBPs, numbering approximately 30, are strongly upregulated (SUR) across at least two-thirds of the nine cancers profiled in this study. Analysis of the protein-protein interaction network properties for the SUR and non-SUR groups of RBPs suggests that path length distributions between SUR RBPs is significantly lower than those observed for non-SUR RBPs. We further find that the mean path lengths between SUR RBPs increases in proportion to their contribution to prognostic impact. We also note that RBPs exhibiting higher variability in the extent of dysregulation across breast cancer patients have a higher number of protein-protein interactions. We propose that fluctuating RBP levels might result in an increase in non-specific protein interactions, potentially leading to changes in the functional consequences of RBP binding. Finally, we show that the expression variation of a gene within a patient group is inversely correlated with prognostic impact. Conclusions: Overall, our results provide a roadmap for understanding the impact of RBPs on cancer pathogenesis.

Polycistronic transcripts are rare in the human genome as unusual mechanisms are needed to translate the downstream ORFs, including leaky scanning, IRESs, or coupled termination–reinitiation mechanisms. Here the authors have devised an algorithm to identify mRNAs in the human transcriptome with two overlapping ORFs where a coupled termination–reinitiation mechanism might be relevant. Of the thousands of such transcripts identified, 22 of 24 were seen to express a protein from the second ORF suggesting that 3' UTRs themselves have considerable coding potential. Five of these transcripts appeared to depend on a termination–reinitiation mechanism, and one of these depended on a specific aspartate-rich repeat peptide sequence at the carboxyl terminus of ORF1 for the coupling mechanism to be effective.

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Beyond cleaved small RNA targets: unraveling the complexity of plant RNA degradome data.

BMC Genomics. 2014 Jan 10;15(1):15

Authors: Hou CY, Wu MT, Lu SH, Hsing YI, Chen HM

Abstract
BACKGROUND: Degradation is essential for RNA maturation, turnover, and quality control. RNA degradome sequencing that integrates a modified 5[prime]-rapid amplification of cDNA ends protocol with next-generation sequencing technologies is a high-throughput approach for profiling the 5[prime]-end of uncapped RNA fragments on a genome-wide scale. The primary application of degradome sequencing has been to identify the truncated transcripts that result from endonucleolytic cleavage guided by microRNAs or small interfering RNAs. As many pathways are involved in RNA degradation, degradome data should contain other RNA species besides the cleavage remnants of small RNA targets. Nevertheless, no systematic approaches have been established to explore the hidden complexity of plant degradome.
RESULTS: Through analyzing Arabidopsis and rice RNA degradome data, we recovered 11 short motifs adjacent to predominant and abundant uncapped 5[prime]-ends. Uncapped ends associated with several of these short motifs were more prevalent than those targeted by most miRNA families especially in the 3[prime] untranslated region of transcripts. Through genome-wide analysis, five motifs showed preferential accumulation of uncapped 5[prime]-ends at the same position in Arabidopsis and rice. Moreover, the association of uncapped 5[prime]-ends with a CA-repeat motif and a motif recognized by Pumilio/Fem-3 mRNA binding factor (PUF) proteins was also found in non-plant species, suggesting that common mechanisms are present across species. Based on these motifs, potential sources of RNA ends that constitute degradome data were proposed and further examined. The 5[prime]-end of small nucleolar RNAs could be precisely captured by degradome sequencing. Position-specific enrichment of uncapped 5[prime]-ends was seen upstream of motifs recognized by several RNA binding proteins especially for the binding site of PUF proteins. False uncapped 5[prime]-ends produced from capped transcripts through non-specific PCR amplification were common artifacts among degradome datasets.
CONCLUSIONS: The complexity of plant RNA degradome data revealed in this study may contribute to the alternative applications of degradome in RNA research.

PMID: 24405808 [PubMed - as supplied by publisher]

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A biochemical landscape of A-to-I RNA editing in the human brain transcriptome.

Genome Res. 2014 Jan 9;

Authors: Sakurai M, Ueda H, Yano T, Okada S, Terajima H, Mitsuyama T, Toyoda A, Fujiyama A, Kawabata H, Suzuki T

Abstract
Inosine is an abundant RNA modification in the human transcriptome and is essential for many biological processes by modulating gene expression at the post-transcriptional level. Adenosine deaminases acting on RNA (ADARs) catalyze the hydrolytic deamination of adenosines to inosines (A-to-I editing) in double-stranded regions. We previously established a biochemical method called 'inosine chemical erasing (ICE)' to directly identify inosines on RNA strands with high reliability. Here, we have applied the ICE-method combined with deep sequencing (ICE-seq) to conduct an unbiased genome-wide screening of A-to-I editing sites in the transcriptome of human adult brain. Taken together with the sites identified by conventional ICE-method, we mapped 19,791 novel sites and newly found 1,258 edited mRNAs, including 66 novel sites in coding regions, 41 of which cause altered amino acid assignment. ICE-seq detected novel editing sites in various repeat elements as well as in short hairpins. Gene ontology analysis revealed that these edited mRNAs are associated with transcription, energy metabolism and neurological disorders, providing new insights into various aspects of human brain function.

PMID: 24407955 [PubMed - as supplied by publisher]

Background: ZFP36, also known as tristetraprolin or TTP, and ELAVL1, also known as HuR, are two disease-relevant RNA-binding proteins (RBPs) that both interact with AU-rich sequences but have antagonistic roles. While ELAVL1 binding has been profiled in several studies, the precise in vivo binding specificity of ZFP36 has not been investigated on a global scale. We determined ZFP36 binding preferences using cross-linking and immunoprecipitation in human embryonic kidney cells, and examined the combinatorial regulation of AU-rich elements by ZFP36 and ELAVL1. Results: Targets bound and negatively regulated by ZFP36 include transcripts encoding proteins necessary for immune function and cancer, and transcripts encoding other RBPs. Using partial correlation analysis, we were able to quantify the association between ZFP36 binding sites and differential target RNA abundance upon ZFP36 overexpression independent of effects from confounding features. Genes with increased mRNA half-lives in ZFP36 knockout versus wild-type mouse cells were significantly enriched for our human ZFP36 targets. We identified thousands of overlapping ZFP36 and ELAVL1 binding sites, in 1,313 genes, and found that ZFP36 degrades transcripts through specific AU-rich sequences, representing a subset of the U-rich sequences ELAVL1 interacts with to stabilize transcripts. Conclusions: ZFP36-RNA target specificities in vivo are quantitatively similar to previously reported in vitro binding affinities. ZFP36 and ELAVL1 bind an overlapping spectrum of RNA sequences, yet with differential relative preferences that dictate combinatorial regulatory potential. Our findings and methodology delineate an approach to unravel in vivo combinatorial regulation by RNA-binding proteins.

Nature advance online publication 08 January 2014. doi:10.1038/nature12904

Authors: Frank W. Albert, Sebastian Treusch, Arthur H. Shockley, Joshua S. Bloom & Leonid Kruglyak

Variation among individuals arises in part from differences in DNA sequences, but the genetic basis for variation in most traits, including common diseases, remains only partly understood. Many DNA variants influence phenotypes by altering the expression level of one or several genes. The effects of such variants can be detected as expression quantitative trait loci (eQTL). Traditional eQTL mapping requires large-scale genotype and gene expression data for each individual in the study sample, which limits sample sizes to hundreds of individuals in both humans and model organisms and reduces statistical power. Consequently, many eQTL are probably missed, especially those with smaller effects. Furthermore, most studies use messenger RNA rather than protein abundance as the measure of gene expression. Studies that have used mass-spectrometry proteomics reported unexpected differences between eQTL and protein QTL (pQTL) for the same genes, but these studies have been even more limited in scope. Here we introduce a powerful method for identifying genetic loci that influence protein expression in the yeast Saccharomyces cerevisiae. We measure single-cell protein abundance through the use of green fluorescent protein tags in very large populations of genetically variable cells, and use pooled sequencing to compare allele frequencies across the genome in thousands of individuals with high versus low protein abundance. We applied this method to 160 genes and detected many more loci per gene than previous studies. We also observed closer correspondence between loci that influence protein abundance and loci that influence mRNA abundance of a given gene. Most loci that we detected were clustered in ‘hotspots’ that influence multiple proteins, and some hotspots were found to influence more than half of the proteins that we examined. The variants that underlie these hotspots have profound effects on the gene regulatory network and provide insights into genetic variation in cell physiology between yeast strains.

Background: RNA-binding proteins regulate a number of cellular processes, including synthesis, folding, translocation, assembly and clearance of RNAs. Recent studies have reported that an unexpectedly large number of proteins are able to interact with RNA, but partners of many RNA-binding proteins are still uncharacterized. Results: We combined prediction of ribonucleoprotein interactions, based on catRAPID calculations, with analysis of protein and RNA expression profiles from human tissues. We found strong interaction propensities for both positively- and negatively-correlated expression patterns. Our integration of in silico and ex vivo data unraveled two major types of protein-RNA interactions, with positively-correlated patterns related to cell cycle control and negatively-correlated patterns related to survival, growth and differentiation. To facilitate the investigation of protein-RNA interaction and expression networks, we developed the catRAPID express webserver. Conclusions: Our analysis sheds light on the role of RNA-binding proteins in regulating proliferation and differentiation processes, and we provide a data exploration tool to aid the design of future experimental studies.

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Differential expression analysis of RNA-seq data at single-base resolution.

Biostatistics. 2014 Jan 6;

Authors: Frazee AC, Sabunciyan S, Hansen KD, Irizarry RA, Leek JT

Abstract
RNA-sequencing (RNA-seq) is a flexible technology for measuring genome-wide expression that is rapidly replacing microarrays as costs become comparable. Current differential expression analysis methods for RNA-seq data fall into two broad classes: (1) methods that quantify expression within the boundaries of genes previously published in databases and (2) methods that attempt to reconstruct full length RNA transcripts. The first class cannot discover differential expression outside of previously known genes. While the second approach does possess discovery capabilities, statistical analysis of differential expression is complicated by the ambiguity and variability incurred while assembling transcripts and estimating their abundances. Here, we propose a novel method that first identifies differentially expressed regions (DERs) of interest by assessing differential expression at each base of the genome. The method then segments the genome into regions comprised of bases showing similar differential expression signal, and then assigns a measure of statistical significance to each region. Optionally, DERs can be annotated using a reference database of genomic features. We compare our approach with leading competitors from both current classes of differential expression methods and highlight the strengths and weaknesses of each. A software implementation of our method is available on github (https://github.com/alyssafrazee/derfinder).

PMID: 24398039 [PubMed - as supplied by publisher]

Nature Biotechnology 32, 92 (2014). doi:10.1038/nbt.2776

Authors: Lars Anders, Matthew G Guenther, Jun Qi, Zi Peng Fan, Jason J Marineau, Peter B Rahl, Jakob Lovén, Alla A Sigova, William B Smith, Tong Ihn Lee, James E Bradner & Richard A Young

A vast number of small-molecule ligands, including therapeutic drugs under development and in clinical use, elicit their effects by binding specific proteins associated with the genome. An ability to map the direct interactions of a chemical entity with chromatin genome-wide could provide important insights into chemical perturbation of cellular function. Here we describe a method that couples ligand-affinity capture and massively parallel DNA sequencing (Chem-seq) to identify the sites bound by small chemical molecules throughout the human genome. We show how Chem-seq can be combined with ChIP-seq to gain unique insights into the interaction of drugs with their target proteins throughout the genome of tumor cells. These methods will be broadly useful to enhance understanding of therapeutic action and to characterize the specificity of chemical entities that interact with DNA or genome-associated proteins.

Independent allelic transcription generates fluctuations in the single-cell transcriptome. Authors: Qiaolin Deng, Daniel Ramsköld, Björn Reinius, Rickard Sandberg

Nature Protocols 9, 263 (2014). doi:10.1038/nprot.2014.012

Authors: Michael J Moore, Chaolin Zhang, Emily Conn Gantman, Aldo Mele, Jennifer C Darnell & Robert B Darnell

The identification of sites where RNA-binding proteins (RNABPs) interact with target RNAs opens the door to understanding the vast complexity of RNA regulation. UV cross-linking and immunoprecipitation (CLIP) is a transformative technology in which RNAs purified from in vivo cross-linked RNA-protein complexes are sequenced

Background: Various microRNAs (miRNAs) are up- or downregulated in tumors. However, the repression of cognate miRNA targets responsible for the phenotypic effects of this dysregulation in patients remains largely unexplored. To define miRNA targets and associated pathways, together with their relationship to outcome in breast cancer, we integrated patient-paired miRNA-mRNA expression data with a set of validated miRNA targets and pathway inference. Results: To generate a biochemically-validated set of miRNA-binding sites, we performed argonaute-2 photoactivatable-ribonucleoside-enhanced crosslinking and immunoprecipitation (AGO2-PAR-CLIP) in MCF7 cells. We then defined putative miRNA-target interactions using a computational model, which ranked and selected additional TargetScan-predicted interactions based on features of our AGO2-PAR-CLIP binding-site data. We sub-selected modeled interactions according to the abundance of their constituent miRNA and mRNA transcripts in tumors, and we took advantage of the variability of miRNA expression within molecular subtypes to detect miRNA repression. Interestingly, our data suggest that miRNA families control subtype-specific pathways; for example, miR-17, miR-19a, miR-25 and miR-200b show high miRNA regulatory activity in the triple-negative, basal-like subtype, whereas miR-22 and miR-24 do so in the HER2 subtype. An independent dataset validated our findings for miR-17 and miR-25, and showed a correlation between the expression levels of miR-182 targets and overall patient survival. Pathway analysis associated miR-17, miR-19a and miR-200b with leukocyte transendothelial migration. Conclusions: We combined PAR-CLIP data with patient expression data to predict regulatory miRNAs, revealing potential therapeutic targets and prognostic markers in breast cancer.

Although comparison of RNA-protein interaction profiles across different conditions has become increasingly important to understanding the function of RNA-binding proteins (RBPs), few computational approaches have been developed for quantitative comparison of CLIP-seq datasets. Here, we present an easy-to-use command line tool, dCLIP, for quantitative CLIP-seq comparative analysis. The two-stage method implemented in dCLIP, including a modified MA normalization method and a Hidden Markov model, is shown to be able to effectively identify differential binding regions of RBPs in four CLIP-seq datasets, generated by HITS-CLIP, iCLIP and PAR-CLIP protocols. dCLIP is freely available at http://qbrc.swmed.edu/software/.

Translational regulation contributes to plasticity in metabolism and growth that enables plants to survive in a dynamic environment. Here, we used the precise mapping of ribosome footprints (RFs) on mRNAs to investigate translational regulation under control and sublethal hypoxia stress conditions in seedlings of Arabidopsis thaliana. Ribosomes were obtained by...

Background: Sequence specific RNA binding proteins are important regulators of gene expression. Several related crosslinking-based, high-throughput sequencing methods, including PAR-CLIP, have recently been developed to determine direct binding sites of global protein-RNA interactions. However, no studies have quantitatively addressed the contribution of background binding to datasets produced by these methods. Results: We measured non-specific RNA background in PAR-CLIP data, demonstrating that covalently crosslinked background binding is common, reproducible and apparently universal among laboratories. We show that quantitative determination of background is essential for identifying targets of most RNA-binding proteins and can substantially improve motif analysis. We also demonstrate that by applying background correction to an RNA binding protein of unknown binding specificity, Caprin1, we can identify a previously unrecognized RNA recognition element not otherwise apparent in a PAR-CLIP study. Conclusions: Empirical background measurements of global RNA-protein crosslinking are a necessary addendum to other experimental controls, such as performing replicates, because covalently crosslinked background signals are reproducible and otherwise unavoidable. Recognizing and quantifying the contribution of background extends the utility of PAR-CLIP and can improve mechanistic understanding of protein-RNA specificity, protein-RNA affinity and protein-RNA association dynamics.

Although numerous approaches have been developed to map RNA-binding sites of individual RNA-binding proteins (RBPs), few methods exist that allow assessment of global RBP–RNA interactions. Here, we describe PIP-seq, a universal, high-throughput, ribonuclease-mediated protein footprint sequencing approach that reveals RNA-protein interaction sites throughout a transcriptome of interest. We apply PIP-seq to the HeLa transcriptome and compare binding sites found using different cross-linkers and ribonucleases. From this analysis, we identify numerous putative RBP-binding motifs, reveal novel insights into co-binding by RBPs, and uncover a significant enrichment for disease-associated polymorphisms within RBP interaction sites.

Background: ADAR proteins are among the most extensively studied RNA binding proteins. They bind to their target and deaminate specific adenosines to inosines. ADAR activity is essential, and the editing of a subset of their targets is critical for viability. Recently, a huge number of novel ADAR targets were detected by analyzing next generation sequencing data. Most of these novel editing sites are located in lineage-specific genomic repeats, probably a result of overactivity of editing enzymes, thus masking the functional sites. In this study we aim to identify the set of mammalian conserved ADAR targets. Results: We used RNA sequencing data from human, mouse, rat, cow, opossum, and platypus to define the conserved mammalian set of ADAR targets. We found that the conserved mammalian editing sites are surprisingly small in number and have unique characteristics that distinguish them from non-conserved ones. The sites that constitute the set have a distinct genomic distribution, tend to be located in genes encoding neurotransmitter receptors or other synapse related proteins, and have higher editing and expression levels. We also found a high consistency of editing levels of this set within mice strains and between human and mouse. Tight regulation of editing in these sites across strains and species implies their functional importance. Conclusions: Despite the discovery of numerous editing targets, only a small number of them are conserved within mammalian evolution. These sites are extremely highly conserved and exhibit unique features, such as tight regulation, and probably play a pivotal role in mammalian biology.

Background: Long noncoding RNAs (lncRNAs) form an abundant class of transcripts, but the function of the majority of them remains elusive. While it has been shown that some lncRNAs are bound by ribosomes, it has also been convincingly demonstrated that these transcripts do not code for proteins. To obtain a comprehensive understanding of the extent to which lncRNAs bind ribosomes, we performed systematic RNA sequencing on ribosome-associated RNA pools obtained through ribosomal fractionation and compared the RNA content with nuclear and (non-ribosome bound) cytosolic RNA pools. Results: The RNA composition of the subcellular fractions differs significantly from each other, but lncRNAs are found in all locations. A subset of specific lncRNAs is enriched in the nucleus but surprisingly the majority is enriched in the cytosol and in ribosomal fractions. The ribosomal enriched lncRNAs include H19 and TUG1. Conclusions: Most studies on lncRNAs have focused on the regulatory function of these transcripts in the nucleus. We demonstrate that only a minority of all lncRNAs are nuclear enriched. Our findings suggest that many lncRNAs may have a function in cytoplasmic processes, and in particular in ribosome complexes.

Background: Sm proteins are multimeric RNA-binding factors, found in all three domains of life. Eukaryotic Sm proteins, together with their associated RNAs, form small ribonucleoprotein (RNP) complexes important in multiple aspects of gene regulation. Comprehensive knowledge of the RNA components of Sm RNPs is critical for understanding their functions. Results: We developed a multi-targeting RNA-immunoprecipitation sequencing (RIP-seq) strategy to reliably identify Sm-associated RNAs from Drosophila ovaries and cultured human cells. Using this method, we discovered three major categories of Sm-associated transcripts: small nuclear (sn)RNAs, small Cajal body (sca)RNAs and mRNAs. Additional RIP-PCR analysis showed both ubiquitous and tissue-specific interactions. We provide evidence that the mRNA-Sm interactions are mediated by snRNPs, and that one of the mechanisms of interaction is via base pairing. Moreover, the Sm-associated mRNAs are mature, indicating a splicing-independent function for Sm RNPs. Conclusions: This study represents the first comprehensive analysis of eukaryotic Sm-containing RNPs, and provides a basis for additional functional analyses of Sm proteins and their associated snRNPs outside of the context of pre-mRNA splicing. Our findings expand the repertoire of eukaryotic Sm-containing RNPs and suggest new functions for snRNPs in mRNA metabolism.

Nature Structural & Molecular Biology 21, 95 (2014). doi:10.1038/nsmb.2736

Authors: Jun-Jie Liu, Matthew A Bratkowski, Xueqi Liu, Chu-Ya Niu, Ailong Ke & Hong-Wei Wang

Nature Structural & Molecular Biology 21, 9 (2014). doi:10.1038/nsmb.2751

Authors: Michaela Müller-McNicoll & Karla M Neugebauer

Every RNA polymerase II transcript receives a 5′-end 7-methylguanosine (m7G) cap, which is rapidly bound by the nuclear cap–binding complex (CBC). Two recent studies now reveal that the CBC associates with a variety of effector proteins that enable it to interrogate nascent RNA, discriminating between distinct RNA subclasses and routing them either toward distinct maturation pathways or toward decay. Thus, the CBC has an early role in policing cellular RNA.

Nature Structural & Molecular Biology 21, 17 (2014). doi:10.1038/nsmb.2750

Authors: Claudia Schneider & David Tollervey

The exosome complex has key roles in RNA processing and quality control. Single-particle EM analyses now provide compelling evidence for two distinct pathways by which substrate RNAs can pass through the exosome structure to reach the catalytic site for exonuclease digestion.

MicroRNAs (miRNAs) are 20- to ~24-nucleotide (nt) small RNAs that impact a variety of biological processes, from development to age-associated events. To study the role of miRNAs in aging, studies have profiled the levels of miRNAs with time. However, evidence suggests that miRNAs show heterogeneity in length and sequence in different biological contexts. Here, by examining the expression pattern of miRNAs by Northern blot analysis, we found that Drosophila miRNAs show distinct isoform pattern changes with age. Surprisingly, an increase of some miRNAs reflects increased 2'-O-methylation of select isoforms. Small RNA deep sequencing revealed a global increase of miRNAs loaded into Ago2, but not into Ago1, with age. Our data suggest increased loading of miRNAs into Ago2, but not Ago1, with age, indicating a mechanism for differential loading of miRNAs with age between Ago1 and Ago2. Mutations in Hen1 and Ago2, which lack 2'-O-methylation of miRNAs, result in accelerated neurodegeneration and shorter life span, suggesting a potential impact of the age-associated increase of 2'-O-methylation of small RNAs on age-associated processes. Our study highlights that miRNA 2'-O-methylation at the 3' end is modulated by differential partitioning of miRNAs between Ago1 and Ago2 with age and that this process, along with other functions of Ago2, might impact age-associated events in Drosophila.

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Demystifying the nuclear function of Argonaute proteins.

RNA Biol. 2014 Jan 2;11(1)

Authors: Huang V, Li LC

Abstract
The Argonaute family of proteins is highly evolutionarily conserved and plays essential roles in small RNA-mediated gene regulatory pathways and in a wide variety of cellular processes. They were initially discovered by genetics studies in plants and have been well-characterized as key components of gene silencing pathways guided by small RNAs, a phenomenon known as RNA interference. Conventionally, guided by different classes of small RNAs, Argonautes bind to and silence homologous target sequences at the post-transcriptional level. Increasing lines of evidence support their multi-functional roles in the nucleus. Advances in high-throughput genome-wide methodologies have greatly facilitated our understanding of their functions in post-transcriptional gene silencing as well as in other nuclear events. In this point-of-view, we will summarize key findings from genome-wide analyses of the Ago subfamily of proteins in mammals and Drosophila, discuss their nuclear functions in the regulation of transcription and alternative splicing identified in recent years, and briefly touch upon their potential implications in cancer.

PMID: 24384674 [PubMed - as supplied by publisher]

By using chromosome conformation capture technology, a recent study has revealed two alternative three-dimensional folding states of the human genome during the cell cycle.

Genome-editing technology allows improved positive or negative selection screens. Authors: Tim Wang, Jenny J. Wei, David M. Sabatini, Eric S. Lander

Live offspring can be obtained from male mice in which the Y chromosome contribution is limited to only two genes. Authors: Yasuhiro Yamauchi, Jonathan M. Riel, Zoia Stoytcheva, Monika A. Ward

Nature Protocols 9, 171 (2014). doi:10.1038/nprot.2014.006

Authors: Simone Picelli, Omid R Faridani, Åsa K Björklund, Gösta Winberg, Sven Sagasser & Rickard Sandberg

Emerging methods for the accurate quantification of gene expression in individual cells hold promise for revealing the extent, function and origins of cell-to-cell variability. Different high-throughput methods for single-cell RNA-seq have been introduced that vary in coverage, sensitivity and multiplexing ability. We recently introduced Smart-seq