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Minireview: Global Regulation and Dynamics
of Ribonucleic Acid
Jack D. Keene
Department of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, North
Carolina 27710
Gene expression starts with transcription and is followed by multiple posttranscriptional processes
that carry out the splicing, capping, polyadenylation, and export of each mRNA. Interest in posttranscriptional regulation has increased recently with explosive discoveries of large numbers of
noncoding RNAs such as microRNAs, yet posttranscriptional processes depend largely on the functions of RNA-binding proteins as well. Glucocorticoid nuclear receptors are classical examples of
environmentally reactive activators and repressors of transcription, but there has also been a
significant increase in studies of the role of posttranscriptional regulation in endocrine responses,
including insulin and insulin receptors, and parathyroid hormone as well as other hormonal responses, at the levels of RNA stability and translation. On the global level, the transcriptome is
defined as the total RNA complement of the genome, and thereby, represents the accumulated
levels of all expressed RNAs, because they are each being produced and eventually degraded in
either the nucleus or the cytoplasm. In addition to RNA turnover, the many underlying posttranscriptional layers noted above that follow from the transcriptome function within a dynamic
ribonucleoprotein (RNP) environment of global RNA-protein and RNA-RNA interactions. With the
exception of the spliceosome and the ribosome, thousands of heterodispersed RNP complexes
wherein RNAs are dynamically processed, trafficked, and exchanged are heterogeneous in size and
composition, thus providing significant challenges to their investigation. Among the diverse RNPs
that show dynamic features in the cytoplasm are processing bodies and stress granules as well as
a large number of smaller heterogeneous RNPs distributed throughout the cell. Although the
localization of functionally related RNAs within these RNPs are responsive to developmental and
environmental signals, recent studies have begun to elucidate the global RNA components of RNPs
that are dynamically coordinated in response to these signals. Among the factors that have been
found to affect coordinated RNA regulation are developmental signals and treatments with small
molecule drugs, hormones, and toxins, but this field is just beginning to understand the role of RNA
dynamics in these responses. (Endocrinology 151: 1391–1397, 2010)
M
uch of molecular biology and biochemistry over the
past several decades has focused on transcription, in
part, because genetics provided a practical means of elucidating gene and protein functions (1). RNA in eukaryotes, being more heterogeneous and unstable compared with DNA, was challenging to study (2). However,
the decades of the 1970s and 1980s brought advancing
progress in understanding RNA binding and regulation
that followed from the sequencing of small RNAs, including 5s RNA, transfer RNAs, and small nuclear RNAs, and
the advent of RT-PCR, the discovery of ribozymes, and the
elucidation of numerous families of RNA-binding proteins (RBPs) (3, 4). Sequencing of mammalian genomes
revealed that cellular RNA processing factors, including
RBPs, appear to outnumber transcription factors by as
much as 2-fold (2, 5). Moreover, RNA transcripts were
found to be much more diverse, heterogeneous, and of low
abundance individually than previously thought; therefore, increasing the challenge. The explosion of research
on RNA per se proceeded in parallel with new under-
ISSN Print 0013-7227 ISSN Online 1945-7170
Printed in U.S.A.
Copyright © 2010 by The Endocrine Society
doi: 10.1210/en.2009-1250 Received October 22, 2009. Accepted December 29, 2009.
Abbreviations: ELAV, Embryonic lethal abnormal vision; FMRP, fragile-X-mental retardation protein; RBP, RNA-binding protein; RIP-chip, RNP-immunoprecipitation-microchip;
RIP-seq, RIP with high-throughput sequencing; RNP, ribonucleoprotein; UTR, untranslated
region.
Endocrinology, April 2010, 151(4):1391–1397
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Endocrinology, April 2010, 151(4):1391–1397
couple transcriptional and subsequent
posttranscriptional steps by interacting
with their target transcripts (15). Although progressive coupling of these processes is widely accepted, many studies
have demonstrated that posttranscriptional events involving multiple mRNAs
are highly coordinated as well (2, 16).
Both coupling and coordination are important in determining how, when, and
where to translate functionally related
subpopulations of mRNAs (17). Moreover, unless the posttranscriptional pathway functions with precision, transcriptional regulatory events will become
discordant. Reports from many labs
FIG. 1. Pathway of gene expression in eukaryotic cells showing intervening steps of mRNA
have demonstrated that RBPs, includprocessing (red) that are coupled together with RBPs coordinating multiple mRNAs from
ing export proteins, provide coordinattranscription to translation. These processes are dynamic with multiple copies of each
ing functions at all steps along the postmRNA changing within and among heterogeneous RNPs in time and space (inset). The
transcriptional regulatory chain (2, 14,
approach of using microarrays or deep sequencing to identify RNP-associated subsets of
functionally related RNAs (RIP-chip or RIP-seq) is depicted, as is the use of nuclear run-on
16, 18 –21). As depicted in Fig. 1, disarray measurements to assess nascent transcripts before RNA processing. [Adapted with
crete subpopulations of mRNAs reside in
permission from J. D. Keene: Proc Natl Acad Sci USA 98:7018 –7024, 2001 (2). ©National
ribonucleoprotein (RNP) complexes (Fig.
Academy of Sciences.]
1, inset) and can be coordinately processed:
standing of RNA-protein interactions and RNA struc- spliced, transported, stabilized or degraded, localized, or
ture, whereas the discovery in Caenorhabditis elegans in translated into protein.
1993 of small regulatory RNAs by Victor Ambros’ Lab
All posttranscriptional steps require the proper func(6) and Ruvkun’s Lab (7), now called microRNAs, re- tioning of RBPs as components of RNP complexes
emerged on the global level in the late 1990s. There is whether or not noncoding regulatory RNAs are involved.
increasing evidence that microRNAs and other small Several laboratories have used RNP-immunoprecipitanoncoding RNAs are interdependent with RBPs, in tion-microchip (RIP-chip) or RIP with high-throughput
some cases cooperating and in other cases competing for sequencing (RIP-seq) to demonstrate that RBPs can interfunctional outcomes (8 –13). The entire field of post- act with distinct subsets of the global mRNA population
transcriptional gene regulation is undergoing a renais- (Fig. 1) (5, 18, 22–27). Thus, data from many laboratories
sance of discovery that is impacting on all fields of biindicate that eukaryotic gene expression is highly coordiology and medicine.
nated and that transcription factors, RBPs, and microRNAs
function together to form coherent gene expression network
modules (reviewed in Refs. 16, 20, and 21). Regardless of
Posttranscriptional Gene Regulation:
the exact mechanisms, the final outcome of protein synCoupling and Coordination
thesis is a mRNP-driven process that responds dynamiIn bacterial cells, the transcriptional apparatus is directly cally to the environment and cellular growth conditions.
RBPs are universal in living cells, and in eukaryotes,
coupled to the translational apparatus as transcripts begin
to be translated by ribosomes before their transcription are estimated to number approximately 650 in yeast and
has terminated. On the contrary, eukaryotic transcription over 2500 in mammals (2, 5, 14, 28). Although some
and translation cannot be directly coupled because of the RBPs are thought to bind RNA with little or no sequence
nuclear membrane and the compartmentalization of RNA specificity, many and possibly most RBPs are specific
diversification and processing. Therefore, the final decision for binding to distinct subpopulations of RNAs (2, 22).
as to which genes will be expressed as proteins in eukaryotes Because RBPs can bind to more than one mRNA with
is made independently in the cytoplasm, although early sig- sequence specificity, such interactions play an impornals or tags such as the Exon-Junction-Complex placed on tant role in regulating RNA localization, coexpression,
the pre-mRNA in the nucleus can influence translational and overall coordination of functionally related groups
outcomes (14). Many studies suggest that RBPs indirectly of mRNAs.
Endocrinology, April 2010, 151(4):1391–1397
Multitargeting of RNA by RBPs and
MicroRNAs
Early indications that RBPs were able to target multiple
mRNAs at specific sequence elements were demonstrated in
vitro using the embryonic lethal abnormal vision (ELAV)/
HuB RBP and the fragile-X-mental retardation protein
(FMRP). HuB is a RNA-recognition motif-containing RBP,
one of four members of the ELAV/Hu family 关HuA (aka:
HuR), HuB, HuC, HuD兴 that was shown to bind to AU-rich
elements in the 3⬘ untranslated regions (UTRs) of protooncogene and cytokine encoding transcripts (29) and to approximately 100 AU-rich human brain mRNA targets (30).
These findings were later expanded using cell extracts, and
the in vitro studied AU-rich mRNA targets confirmed, using
RIP-chip experiments with HuB, e1F4E, and HuR (22).
Based upon binding of FMRP to its own mRNA in vitro and
binding to total cell radioactive RNA to FMRP in vitro, Warren and co-workers (31) surmised that it could bind to as
many as 4% of human mRNAs, but neither the RNA targets
nor the RNA-binding sequences of FMRP were identified at
that time. However, many potential mRNA targets of FMRP
were later identified also using the RIP-chip procedure (32),
and at least one putative RNA-binding element was identified (33, 34). The RIP-chip and RIP-seq approach has since
been used with nearly 100 RBPs from different species to
examine RNA targets and specific binding sequences of RBPs
(reviewed in Refs. 16, 20, and 35). These demonstrations
that RBPs could bind to multiple mRNAs on a global level led
to the proposal that they could serve as a coordinating mechanism for posttranscriptional processes (2, 17, 22, 30). In
addition, methods were devised to assess changes in
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populations of mRNA during decay and during translational activation (Fig. 2). The results of many of these
studies suggested that the coordinated events affect specific subsets of functionally related mRNAs (reviewed in
Ref. 16).
The original discovery of microRNAs was based upon
single antisense interactions between each of two small RNA
transcripts (lin-4) and a single mRNA (lin-14) (6, 7). Only
later did the suggestion of multitargeting of microRNAs to
multiple mRNAs emerge based upon computational predictions of complementary sequences between the microRNAs and many potential mRNA targets (36 –38).
These trans-acting small RNA regulators of mRNAs, stimulated by the discovery of RNA interference by Mello and
co-workers (39), were believed, like the RBPs, to target
multiple mRNAs, leading to profound phenotypic changes.
Both experimental data and improved computational algorithms have overwhelmingly confirmed this prediction (40).
The functional relationship among the multiple targets of
microRNAs has remained unclear to date, although this
could be a result of a lack of information regarding the combinatorial interactions between microRNAs and RBPs. Also,
many articles compare microRNAs with transcription factors and leave out the analogy to RBPs entirely, whereas a
few recent reports have linked the effects of these 3⬘UTRinteracting factors (8 –10, 13). The emergence of small
noncoding RNA biology has been profound in recent
years, and in some aspects overwhelming in its impact,
because nearly every laboratory now uses RNA interference to study their respective biological systems and disease models.
FIG. 2. The complexity of transcriptomics can be reduced by probing its underlying layers. Transcriptomics has generated data with overwhelming
complexity. Polysome-arrays and decay arrays dissect layers of gene expression and can also reveal coordinated posttranscriptional events. mRNAs
identified using RIP-chip are functionally related as coordinated and dynamic RNP modules (posttranscriptional RNA operons and regulons). There
are procedures used to globally quantify RNAs at the levels of RNA stability or translation that are not otherwise evident from complex transcriptomic
analysis. Depiction of a microarray (middle) that displays transcriptomic data representing the accumulated levels of each mRNA depending upon both its
rate of synthesis and its rate of degradation. Methods such as RIP-chip (and RIP-seq), RNA decay-array analysis, and polysome gradient-array analysis have
been devised in recent years to assess these “under layers” of the transcriptome. RNA turnover due to differences in RNA stability among the RNAs is
depicted as up and down arrows below the array.
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RNA Dynamics
Along the complex pathway of gene expression from the
nucleus to the cytoplasm, the final decisions that lead to
protein production are posttranscriptional. Although
transcription is necessary to originate each mRNA, the
steps of splicing, nuclear export, RNA stability, localization, and eventually translation require precision in order
for gene expression signals at transcription to achieve their
intended expression outcome. Numerous recent studies
have demonstrated that the flow of genetic information on
these posttranscriptional levels is highly organized and
combinatorial (Fig. 3). As noted, each step of posttranscriptional gene expression is intimately connected to the
next step and the regulatory processes are coordinated by
RBPs, and noncoding RNAs are believed to particulate in
this regulation. This chain of interconnected RNA pro-
Endocrinology, April 2010, 151(4):1391–1397
cessing steps orchestrates the production of thousands of
proteins in time and space in response to cellular signals in
normal or diseased states (41– 47; for review, see Ref. 35).
RNAs are highly dynamic, and multitargeting by RBPs
plays an important role in generating as well as regulating
dynamic RNA networks. Because RNA can be generated,
used, and then destroyed over relatively short intervals, it
can serve multiple transient functions and be replaced
when needed. Whether being acted upon in cis, or acting
as a trans-combinatorial regulator of other RNAs, the dynamic interactions can be exceedingly brief. Indeed, the
multiple copies of each mRNA allow each individual species to have multiple lives in that each is capable of joining
together with any functionally related group of mRNAs as
long as it contains the appropriate RNA binding element
that is also present in the other RNAs in the subset (14, 17,
FIG. 3. Multiple copies allow multiple combinations of mRNAs. Illustration of the multiple lives of each mRNA based on the posttranscriptional
RNA operon/regulon model (16). Functionally related mRNAs are “clustered” in time and space such that the proteins encoded by them can be
coordinately produced in concert. Each of the four mRNAs has the potential to be a member of more than one subset because the protein it
encodes serves multiple functional roles in different cellular processes. The colored circles represent different RBPs or different posttranslationally
modified isoforms of a given RBP that bind to the colored bars in the 3⬘ or 5⬘ UTRs. Noncoding RNAs that bind in combination with RBPs to
sequences in these mRNAs can affect posttranscriptional outcomes such as RNA stability and translation. Posttranscriptional RNA Operons (PTRos)
are coordinated subsets of functionally related mRNAs in association with regulatory RBPs and noncoding RNAs that are spliced, transported,
stabilized, localized, or translated in a coherent manner. Multiple PTRos can share certain mRNAs to form overlapping posttranscriptional regulons
that coordinate the production of several related subsets of functionally related proteins.
Endocrinology, April 2010, 151(4):1391–1397
18, 20). For example, in the case of hormonal responses,
one can imagine how rapidly responding changes at the
level of RNA stability provide an advantage to multicellular systems (48).
An important feature of RNA networks is that a significant proportion of cellular proteins encode RBPs that
in turn regulate the mRNAs encoding other RBPs. This
property of the ribonome forms a “regulators of regulators” feature that can serve to coordinate upstream and
downstream functions of gene expression. Indeed, there is
massive feedback from translation to transcription and
from translation to other posttranscriptional processes
providing stability and resilience to global RNA networks
by making them interdependent (49, 50). Thus, at least
two gene expression networks, one transcriptionally derived and one or more posttranscriptionally derived, are
linked in a dynamic network of cross talk because every
transcription factor must be translated and every translation factor must be transcribed. In any case, translation is
the final decision along the chain of gene expression and
it has recently been found to have its own overarching
mode of modular coordination that we have termed posttranscriptional RNA operons and regulons (see Fig. 3)
(reviewed in Refs. 16, 20, and 35).
Most cellular events are dynamic in time and space as
is readily apparent in time-lapse imaging of cells and embryos. Although all molecules and macromolecules are
dynamic in their local shapes and allostery, traditional
molecular biological and biochemical experiments do not
generally consider events in both time and space; certainly
not on a global basis. Moreover, molecular structural
studies have only recently been designed to look beyond
static crystallographic analysis and are beginning to use
nuclear magnetic resonance and liquid imaging of increasingly larger peptides and DNA and RNA to understand
molecular dynamics (51, 52). The field that investigates
transient molecular complexes is rapidly emerging and has
broad implications for understanding the structural and
functional dynamics of molecules at all levels of cell regulation. RNAs are known to be dynamic on multiple levels
as detected, for example, by time-lapse experiments using
florescent probes and molecular tags (51). However,
global analyses that assess RNA dynamics have not been
extensively used. Yet most developmental processes and
chemical activation events are believed to alter the levels
and locations of RNAs. Hormonal and inflammatory responses as well as genotoxic effects on cells are examples
of cellular activation events that involve both transcriptional activation as well as posttranscriptional regulation
of RNA stability and translation (28, 53–58). Also, see
accompanying minireviews in this issue (59, 60). This is a
field of active investigation because these important cel-
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lular responses underlie many normal physiological and
pathological processes.
The accumulated global levels of mRNAs in cells, referred to as the transcriptome, represent the balance between on-going transcription and on-going changes in
RNA stability (Figs. 1 and 2) (2). This important fact has
generally been overlooked in gene expression profiling
studies because the results obtained from total cellular or
tumor RNA using microarrays is frequently assumed to
represent RNA production. However, without a means to
determine global changes in the stability of these RNAs as
well as their levels of translation, we are left with a very
incomplete understanding of the pathway of gene expression and the eventual outcomes. Thus, a variety of experimental approaches emerged, including nuclear run-on en
masse (Fig. 1, inset), RNA decay-array analysis and polysome gradient-array analysis (Fig. 2). For example, a study
that used nuclear run-on analysis of nascent transcripts globally during T-cell activation and compared the changes in
RNA abundance demonstrated that more than one half of
the changes in RNA were due to effects of RNA stability (61).
Unfortunately, this very important aspect of transcriptomics
analysis has been largely disregarded in many studies that
seek to understand disease states using gene expression signatures. Moreover, most experiments that assess global transcription do so by measuring mRNA production, and those
transcripts were very likely subjected to the effects of RNA
stability. Therefore, interpretations of transcriptional outcomes need to consider this fact in determining mechanisms
that coordinate global gene expression.
Coordinated Gene Expression and the
Posttranscriptional Operon Model
As noted above, molecular events in gene expression from
transcription to translation are closely interconnected to
one another (Fig. 1). Jacob and Monod discovered prokaryotic DNA operons in which genes are expressed in
functionally related units. The DNA operon model demonstrated that the initiation of transcription usually results in the production of long polycistronic mRNAs that
contain multiple gene transcripts in tandem. This polycistronic architecture allows multiple genes to be expressed
in concert and to be regulated sequentially as groups. Although a high percentage of bacterial genes are contained in
operons, functionally related genes are not physically clustered on the genomes of eukaryotes. In fact, DNA operons
have not been found in human cells, suggesting that other
mechanisms of gene coordination may exist. In addition,
with minor exceptions, polycistronic mRNAs are not common in mammalian cells, but instead, mRNA transcripts are
monocistronic. Despite these facts, it is still generally as-
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sumed by most scientists that gene expression in mammalian
cells is coordinated solely at the level of transcription.
Our laboratory demonstrated that during the induction
of neuronal differentiation, Hu proteins bind to mRNA
subpopulations within RNPs that change combinatorially
in a dynamic pattern, indicating coordinated remodeling
of mRNPs (17, 22). As noted above, the demonstration
that ELAV/Hu proteins are multitargeted to bind discrete
subsets of mRNAs in neurons and other cells led to the
theory of posttranscriptional RNA operons (or regulons)
(Fig. 3) (17). This concept has been supported by data
from many laboratories in many species by using RIP-chip
and other experimental and bioinformatics procedures
(summarized in Ref. 35). Recent studies with activated T
cells have examined the dynamics of global mRNA populations using a probabilistic approach applying Gaussian
mixture modeling and related statistical methods (27, 47).
One of the benefits of this approach is that one can assign a
continuous metric to each mRNA in the population after
cellular perturbation. Data representing these values allowed
a database to be queried from the drug-gene-disease connectivity map (62) to identify small molecule drugs that affect
posttranscriptional regulators and thereby generated a drug
phenotype of HuR-mediated RNA stability during T-cell activation (47). Overall, the field of global RNA dynamics is at
its beginnings and can provide insights into responses to developmental and environmental signals as well as hormone
receptor functions and other endocrine systems in which
rapid responses of the gene expression apparatus have provided an important physiological adaptation.
Future Perspectives
Novel approaches to understanding responses to hormones
and other endocrine mediators at the posttranscriptional
level of gene expression are developing at a rapid pace. Although many of these systems remain poorly understood,
investigative methods to elucidate the underlying bases using
quantitative cellular dynamics will be necessary (63). The
advent of microarrays set forth an opportunity to analyze
RNA regulatory factors on a global basis, and more recently,
the introduction of high-throughput “deep” sequencing procedures has provided a powerful means to derive even more
global information such as the roles of noncoding RNAs in
posttranscriptional regulation. It will be important to exploit
these strategies to better understand gene expression dynamics after hormone treatments and physiological responses.
Acknowledgments
Address all correspondence and requests for reprints to: Jack D.
Keene, Department of Molecular Genetics and Microbiology,
Endocrinology, April 2010, 151(4):1391–1397
Duke University Medical Center, Durham, North Carolina
27710. E-mail: [email protected].
Disclosure Summary: The author has a financial relationship
with Ribonomics, Inc., and MBL, Inc., which hold licenses to
RIP-chip technologies mentioned in this article.
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