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Dive into the research topics where Tim R. Mercer is active.

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Featured researches published by Tim R. Mercer.


Nature Reviews Genetics | 2009

Long non-coding RNAs: insights into functions

Tim R. Mercer; Marcel E. Dinger; John S. Mattick

In mammals and other eukaryotes most of the genome is transcribed in a developmentally regulated manner to produce large numbers of long non-coding RNAs (ncRNAs). Here we review the rapidly advancing field of long ncRNAs, describing their conservation, their organization in the genome and their roles in gene regulation. We also consider the medical implications, and the emerging recognition that any transcript, regardless of coding potential, can have an intrinsic function as an RNA.


Proceedings of the National Academy of Sciences of the United States of America | 2008

Specific expression of long noncoding RNAs in the mouse brain

Tim R. Mercer; Marcel E. Dinger; Susan M. Sunkin; Mark F. Mehler; John S. Mattick

A major proportion of the mammalian transcriptome comprises long RNAs that have little or no protein-coding capacity (ncRNAs). Only a handful of such transcripts have been examined in detail, and it is unknown whether this class of transcript is generally functional or merely artifact. Using in situ hybridization data from the Allen Brain Atlas, we identified 849 ncRNAs (of 1,328 examined) that are expressed in the adult mouse brain and found that the majority were associated with specific neuroanatomical regions, cell types, or subcellular compartments. Examination of their genomic context revealed that the ncRNAs were expressed from diverse places including intergenic, intronic, and imprinted loci and that many overlap with, or are transcribed antisense to, protein-coding genes of neurological importance. Comparisons between the expression profiles of ncRNAs and their associated protein-coding genes revealed complex relationships that, in combination with the specific expression profiles exhibited at both regional and subcellular levels, are inconsistent with the notion that they are transcriptional noise or artifacts of chromatin remodeling. Our results show that the majority of ncRNAs are expressed in the brain and provide strong evidence that the majority of processed transcripts with no protein-coding capacity function intrinsically as RNAs.


Nature Structural & Molecular Biology | 2013

Structure and function of long noncoding RNAs in epigenetic regulation

Tim R. Mercer; John S. Mattick

Genomes of complex organisms encode an abundance and diversity of long noncoding RNAs (lncRNAs) that are expressed throughout the cell and fulfill a wide variety of regulatory roles at almost every stage of gene expression. These roles, which encompass sensory, guiding, scaffolding and allosteric capacities, derive from folded modular domains in lncRNAs. In this diverse functional repertoire, we focus on the well-characterized ability for lncRNAs to function as epigenetic modulators. Many lncRNAs bind to chromatin-modifying proteins and recruit their catalytic activity to specific sites in the genome, thereby modulating chromatin states and impacting gene expression. Considering this regulatory potential in combination with the abundance of lncRNAs suggests that lncRNAs may be part of a broad epigenetic regulatory network.


Genome Research | 2008

Long noncoding RNAs in mouse embryonic stem cell pluripotency and differentiation

Marcel E. Dinger; Paulo P. Amaral; Tim R. Mercer; Ken C. Pang; Stephen J. Bruce; Brooke Gardiner; Marjan E. Askarian-Amiri; Kelin Ru; Giulia Soldà; Cas Simons; Susan M. Sunkin; Mark L Crowe; Sean M. Grimmond; Andrew C. Perkins; John S. Mattick

The transcriptional networks that regulate embryonic stem (ES) cell pluripotency and lineage specification are the subject of considerable attention. To date such studies have focused almost exclusively on protein-coding transcripts. However, recent transcriptome analyses show that the mammalian genome contains thousands of long noncoding RNAs (ncRNAs), many of which appear to be expressed in a developmentally regulated manner. The functions of these remain untested. To identify ncRNAs involved in ES cell biology, we used a custom-designed microarray to examine the expression profiles of mouse ES cells differentiating as embryoid bodies (EBs) over a 16-d time course. We identified 945 ncRNAs expressed during EB differentiation, of which 174 were differentially expressed, many correlating with pluripotency or specific differentiation events. Candidate ncRNAs were identified for further characterization by an integrated examination of expression profiles, genomic context, chromatin state, and promoter analysis. Many ncRNAs showed coordinated expression with genomically associated developmental genes, such as Dlx1, Dlx4, Gata6, and Ecsit. We examined two novel developmentally regulated ncRNAs, Evx1as and Hoxb5/6as, which are derived from homeotic loci and share similar expression patterns and localization in mouse embryos with their associated protein-coding genes. Using chromatin immunoprecipitation, we provide evidence that both ncRNAs are associated with trimethylated H3K4 histones and histone methyltransferase MLL1, suggesting a role in epigenetic regulation of homeotic loci during ES cell differentiation. Taken together, our data indicate that long ncRNAs are likely to be important in processes directing pluripotency and alternative differentiation programs, in some cases through engagement of the epigenetic machinery.


Science | 2008

The Eukaryotic Genome as an RNA Machine

Paulo P. Amaral; Marcel E. Dinger; Tim R. Mercer; John S. Mattick

The past few years have revealed that the genomes of all studied eukaryotes are almost entirely transcribed, generating an enormous number of non–protein-coding RNAs (ncRNAs). In parallel, it is increasingly evident that many of these RNAs have regulatory functions. Here, we highlight recent advances that illustrate the diversity of ncRNA control of genome dynamics, cell biology, and developmental programming.


Cell | 2011

The Human Mitochondrial Transcriptome

Tim R. Mercer; Shane Neph; Marcel E. Dinger; Joanna Crawford; Martin A. Smith; Anne Marie J Shearwood; Eric Haugen; Cameron P. Bracken; Oliver Rackham; John A. Stamatoyannopoulos; Aleksandra Filipovska; John S. Mattick

The human mitochondrial genome comprises a distinct genetic system transcribed as precursor polycistronic transcripts that are subsequently cleaved to generate individual mRNAs, tRNAs, and rRNAs. Here, we provide a comprehensive analysis of the human mitochondrial transcriptome across multiple cell lines and tissues. Using directional deep sequencing and parallel analysis of RNA ends, we demonstrate wide variation in mitochondrial transcript abundance and precisely resolve transcript processing and maturation events. We identify previously undescribed transcripts, including small RNAs, and observe the enrichment of several nuclear RNAs in mitochondria. Using high-throughput in vivo DNaseI footprinting, we establish the global profile of DNA-binding protein occupancy across the mitochondrial genome at single-nucleotide resolution, revealing regulatory features at mitochondrial transcription initiation sites and functional insights into disease-associated variants. This integrated analysis of the mitochondrial transcriptome reveals unexpected complexity in the regulation, expression, and processing of mitochondrial RNA and provides a resource for future studies of mitochondrial function (accessed at http://mitochondria.matticklab.com).


Nature Biotechnology | 2012

Targeted RNA sequencing reveals the deep complexity of the human transcriptome

Tim R. Mercer; Daniel J. Gerhardt; Marcel E. Dinger; Joanna Crawford; Cole Trapnell; Jeffrey A. Jeddeloh; John S. Mattick; John L. Rinn

Transcriptomic analyses have revealed an unexpected complexity to the human transcriptome, whose breadth and depth exceeds current RNA sequencing capability. Using tiling arrays to target and sequence select portions of the transcriptome, we identify and characterize unannotated transcripts whose rare or transient expression is below the detection limits of conventional sequencing approaches. We use the unprecedented depth of coverage afforded by this technique to reach the deepest limits of the human transcriptome, exposing widespread, regulated and remarkably complex noncoding transcription in intergenic regions, as well as unannotated exons and splicing patterns in even intensively studied protein-coding loci such as p53 and HOX. The data also show that intermittent sequenced reads observed in conventional RNA sequencing data sets, previously dismissed as noise, are in fact indicative of unassembled rare transcripts. Collectively, these results reveal the range, depth and complexity of a human transcriptome that is far from fully characterized.


PLOS Computational Biology | 2008

Differentiating protein-coding and noncoding RNA: challenges and ambiguities.

Marcel E. Dinger; Ken C. Pang; Tim R. Mercer; John S. Mattick

The assumption that RNA can be readily classified into either protein-coding or non-protein–coding categories has pervaded biology for close to 50 years. Until recently, discrimination between these two categories was relatively straightforward: most transcripts were clearly identifiable as protein-coding messenger RNAs (mRNAs), and readily distinguished from the small number of well-characterized non-protein–coding RNAs (ncRNAs), such as transfer, ribosomal, and spliceosomal RNAs. Recent genome-wide studies have revealed the existence of thousands of noncoding transcripts, whose function and significance are unclear. The discovery of this hidden transcriptome and the implicit challenge it presents to our understanding of the expression and regulation of genetic information has made the need to distinguish between mRNAs and ncRNAs both more pressing and more complicated. In this Review, we consider the diverse strategies employed to discriminate between protein-coding and noncoding transcripts and the fundamental difficulties that are inherent in what may superficially appear to be a simple problem. Misannotations can also run in both directions: some ncRNAs may actually encode peptides, and some of those currently thought to do so may not. Moreover, recent studies have shown that some RNAs can function both as mRNAs and intrinsically as functional ncRNAs, which may be a relatively widespread phenomenon. We conclude that it is difficult to annotate an RNA unequivocally as protein-coding or noncoding, with overlapping protein-coding and noncoding transcripts further confounding this distinction. In addition, the finding that some transcripts can function both intrinsically at the RNA level and to encode proteins suggests a false dichotomy between mRNAs and ncRNAs. Therefore, the functionality of any transcript at the RNA level should not be discounted.


BioEssays | 2009

RNA regulation of epigenetic processes.

John S. Mattick; Paulo P. Amaral; Marcel E. Dinger; Tim R. Mercer; Mark F. Mehler

There is increasing evidence that dynamic changes to chromatin, chromosomes and nuclear architecture are regulated by RNA signalling. Although the precise molecular mechanisms are not well understood, they appear to involve the differential recruitment of a hierarchy of generic chromatin modifying complexes and DNA methyltransferases to specific loci by RNAs during differentiation and development. A significant fraction of the genome‐wide transcription of non‐protein coding RNAs may be involved in this process, comprising a previously hidden layer of intermediary genetic information that underpins developmental ontogeny and the differences between species, ecotypes and individuals. It is also evident that RNA editing is a primary means by which hardwired genetic information in animals can be altered by environmental signals, especially in the brain, indicating a dynamic RNA‐mediated interplay between the transcriptome, the environment and the epigenome. Moreover, RNA‐directed regulatory processes may also transfer epigenetic information not only within cells but also between cells and organ systems, as well as across generations.


BMC Neuroscience | 2010

Long noncoding RNAs in neuronal-glial fate specification and oligodendrocyte lineage maturation

Tim R. Mercer; Irfan A. Qureshi; Solen Gokhan; Marcel E. Dinger; Guangyu Li; John S. Mattick; Mark F. Mehler

BackgroundLong non-protein-coding RNAs (ncRNAs) are emerging as important regulators of cellular differentiation and are widely expressed in the brain.ResultsHere we show that many long ncRNAs exhibit dynamic expression patterns during neuronal and oligodendrocyte (OL) lineage specification, neuronal-glial fate transitions, and progressive stages of OL lineage elaboration including myelination. Consideration of the genomic context of these dynamically regulated ncRNAs showed they were part of complex transcriptional loci that encompass key neural developmental protein-coding genes, with which they exhibit concordant expression profiles as indicated by both microarray and in situ hybridization analyses. These included ncRNAs associated with differentiation-specific nuclear subdomains such as Gomafu and Neat1, and ncRNAs associated with developmental enhancers and genes encoding important transcription factors and homeotic proteins. We also observed changes in ncRNA expression profiles in response to treatment with trichostatin A, a histone deacetylase inhibitor that prevents the progression of OL progenitors into post-mitotic OLs by altering lineage-specific gene expression programs.ConclusionThis is the first report of long ncRNA expression in neuronal and glial cell differentiation and of the modulation of ncRNA expression by modification of chromatin architecture. These observations explicitly link ncRNA dynamics to neural stem cell fate decisions, specification and epigenetic reprogramming and may have important implications for understanding and treating neuropsychiatric diseases.

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John S. Mattick

Garvan Institute of Medical Research

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Marcel E. Dinger

Garvan Institute of Medical Research

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Ira W. Deveson

Garvan Institute of Medical Research

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Michael B. Clark

Garvan Institute of Medical Research

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Tommaso Leonardi

European Bioinformatics Institute

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Simon A. Hardwick

Garvan Institute of Medical Research

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Ted Wong

Garvan Institute of Medical Research

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