Ken Pang

Dr. Ken Pang

orcid

Research Focus & Metrics

Academic Career Length

29Years (1998-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
2 September 2005 in Science
Verified
Journal Article
Closed access
PDF file
Piero CarninciPiero Carninci
Piero Carninci
TKT. Kasukawa
T. Kasukawa
SKS. Katayama
S. Katayama
JGJ. Gough
J. Gough
MFM. C. Frith
M. C. Frith
YHY. Hayashizaki
Y. Hayashizaki
This study describes comprehensive polling of transcription start and termination sites and analysis of previously unidentified full-length complementary DNAs derived from the mouse genome. We identify the 5′ and 3′ boundaries of 181,047 transcripts with extensive variation in transcripts arising from alternative promoter usage, splicing, and polyadenylation. There are 16,247 new mouse protein-coding transcripts, including 5154 encoding previously unidentified proteins. Genomic mapping of the transcriptome reveals transcriptional forests, with overlapping transcription on both strands, separated by deserts in which few transcripts are observed. The data provide a comprehensive platform for the comparative analysis of mammalian transcriptional regulation in differentiation and development.

2 September 2005 in Science
Verified
Journal Article
Closed access
PDF file
SKS. Katayama
S. Katayama
YTY. Tomaru
Y. Tomaru
TKT. Kasukawa
T. Kasukawa
KWK. Waki
K. Waki
MNM. Nakanishi
M. Nakanishi
CWC. Wahlestedt
C. Wahlestedt
Antisense transcription (transcription from the opposite strand to a protein-coding or sense strand) has been ascribed roles in gene regulation involving degradation of the corresponding sense transcripts (RNA interference), as well as gene silencing at the chromatin level. Global transcriptome analysis provides evidence that a large proportion of the genome can produce transcripts from both strands, and that antisense transcripts commonly link neighboring “genes” in complex loci into chains of linked transcriptional units. Expression profiling reveals frequent concordant regulation of sense/antisense pairs. We present experimental evidence that perturbation of an antisense RNA can alter the expression of sense messenger RNAs, suggesting that antisense transcription contributes to control of transcriptional outputs in mammals.

30 October 2009 in The Journal of Pathology
Verified
Journal Article
Open access
PDF file
RTRyan J Taft
Ryan J Taft
KPKen Pang
Ken Pang
TMTimothy R Mercer
Timothy R Mercer
Marcel DingerMarcel Dinger
Marcel Dinger
JMJohn Mattick
John Mattick
For 50 years the term ‘gene’ has been synonymous with regions of the genome encoding mRNAs that are translated into protein. However, recent genome‐wide studies have shown that the human genome is pervasively transcribed and produces many thousands of regulatory non‐protein‐coding RNAs (ncRNAs), including microRNAs, small interfering RNAs, PIWI‐interacting RNAs and various classes of long ncRNAs. It is now clear that these RNAs fulfil critical roles as transcriptional and post‐transcriptional regulators and as guides of chromatin‐modifying complexes. Here we review the biology of ncRNAs, focusing on the fundamental mechanisms by which ncRNAs facilitate normal development and physiology and, when dysfunctional, underpin disease. We also discuss evidence that intergenic regions associated with complex diseases express ncRNAs, as well as the potential use of ncRNAs as diagnostic markers and therapeutic targets. Taken together, these observations emphasize the need to move beyond the confines of protein‐coding genes and highlight the fact that continued investigation of ncRNA biogenesis and function will be necessary for a comprehensive understanding of human disease. Copyright © 2009 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

18 June 2008 in Genome Research
Verified
Journal Article
Open access
PDF file
Marcel DingerMarcel Dinger
Marcel Dinger
PAPaulo P. Amaral
Paulo P. Amaral
TMTim R. Mercer
Tim R. Mercer
KPKen Pang
Ken Pang
SBStephen J. Bruce
Stephen J. Bruce
JMJohn Mattick
John 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.

1 January 2006 in Trends in Genetics
Verified
Journal Article
Closed access
KPKen Pang
Ken Pang
MFMartin C. Frith
Martin C. Frith
JMJohn Mattick
John Mattick

28 November 2008 in PLOS Computational Biology
Verified
Journal Article
Open access
PDF file
Marcel DingerMarcel Dinger
Marcel Dinger
KPKen Pang
Ken Pang
TMTim R. Mercer
Tim R. Mercer
JMJohn Mattick
John 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.