Previous Article | Next Article 
Molecular and Cellular Biology, October 1999, p. 6710-6719, Vol. 19, No. 10
Laboratories of Genetics and Molecular
Biology, University of Wisconsin, Madison, Wisconsin 53706
Received 5 March 1999/Returned for modification 10 May
1999/Accepted 16 June 1999
mRNAs are monitored for errors in gene expression by RNA
surveillance, in which mRNAs that cannot be fully translated are degraded by the nonsense-mediated mRNA decay pathway (NMD). RNA surveillance ensures that potentially deleterious truncated proteins are seldom made. NMD pathways that promote surveillance have been found
in a wide range of eukaryotes. In Saccharomyces cerevisiae, the proteins encoded by the UPF1, UPF2, and
UPF3 genes catalyze steps in NMD and are required for RNA
surveillance. In this report, we show that the Upf proteins are also
required to control the total accumulation of a large number of mRNAs
in addition to their role in RNA surveillance. High-density
oligonucleotide arrays were used to monitor global changes in the yeast
transcriptome caused by loss of UPF gene function. Null
mutations in the UPF genes caused altered accumulation of
hundreds of mRNAs. The majority were increased in abundance, but some
were decreased. The same mRNAs were affected regardless of which of the
three UPF gene was inactivated. The proteins encoded by
UPF-dependent mRNAs were broadly distributed by function
but were underrepresented in two MIPS (Munich Information Center for
Protein Sequences) categories: protein synthesis and protein
destination. In a UPF+ strain, the average
level of expression of UPF-dependent mRNAs was threefold
lower than the average level of expression of all mRNAs in the
transcriptome, suggesting that highly abundant mRNAs were
underrepresented. We suggest a model for how the abundance of hundreds
of mRNAs might be controlled by the Upf proteins.
Nonsense and frameshift mutations
cause premature termination of translation. In conjunction with this,
they also trigger nonsense-mediated mRNA decay (NMD), which greatly
accelerates the rate of degradation of the mRNA. By decreasing the
half-life of the mRNA, nonsense mRNA accumulation is severely limited
(15, 16). The phenomenon whereby mRNAs that would otherwise
code for potentially deleterious protein fragments are degraded is called RNA surveillance (7, 26). Surveillance occurs in
fungi (21), plants (29), nematodes
(26), and vertebrates (22).
In Saccharomyces cerevisiae, three genes, UPF1,
UPF2, and UPF3, are required for NMD (6, 11,
14-16). Sequence homologs of UPF1, an RNA helicase
(8, 30), have been identified in Schizosaccharomyces
pombe (4), Caenorhabditis elegans
(26), Mus musculus (25), and
Homo sapiens (1, 25). Comparison of the
Upf1p-like proteins shows that they are related by a common central
region containing conserved cysteine-rich and ATP-helicase domains
flanked by divergent sequences at both ends. These results suggest that
NMD pathways in eukaryotic organisms utilize at least one protein in
common. This provides a measure of confidence that further studies of
NMD in yeast will shed light on NMD in humans as well.
The biological purpose of RNA surveillance is to limit the accumulation
of aberrant proteins that arise through errors in gene expression.
Inefficient splicing of introns is one of the most frequent natural
source of errors in gene expression, leading to the production of
nonsense mRNAs that code for aberrant proteins. Expression of the
CYH2 gene, which codes for a ribosomal protein in S. cerevisiae, is a good example where the consequences of inefficient splicing have been examined (12). The intron in CYH2 pre-mRNA, which contains stop codons, is inefficiently
spliced. In wild-type cells, unspliced pre-mRNA is exported
(19), translated up to the premature stop codon, and then
rapidly degraded by the NMD pathway. When the NMD pathway is
inactivated by a null mutation in any of the three UPF
genes, the CYH2 pre-mRNA fails to be rapidly degraded and
accumulates to a much higher level. The rapid decay of the pre-mRNA
prevents the accumulation of a truncated protein that might assemble
with ribosomal subunits and impair function.
Evidence that the Upf proteins in S. cerevisiae may serve a
second purpose in addition to surveillance for errors in gene expression has been mounting. Several naturally occurring, intronless mRNAs whose normal level of accumulation depends on the presence of
functional UPF genes have been identified. The accumulation of mRNAs coding for the transcriptional activator Ppr1p and several downstream target genes in the uracil biosynthetic pathway have been
reported to be sensitive to inactivation of UPF1 (15,
24). Also, the mRNA encoding Ctf13p, a subunit of the
kinetochore, depends on the presence of functional UPF genes
(9). The mechanism through which the abundance of naturally
occurring mRNAs are controlled by the Upf proteins is not clear.
Prior to this study, it was not known how many naturally occurring
mRNAs might be affected by loss of UPF function. To assess the global
effects of Upf proteins on gene expression, high-density oligonucleotide arrays (HDOA) representing over 6,000 open reading frames (ORFs) in S. cerevisiae were screened for their
effects on mRNA accumulation with UPF1, UPF2, and
UPF3 were individually inactivated or when all three genes
were simultaneously inactivated. Our results indicate that the level of
accumulation of hundreds of mRNAs is dependent on the presence of
functional UPF genes.
Construction of isogenic upf
0270-7306/99/$04.00+0
Copyright © 1999, American Society for Microbiology. All rights reserved.
Yeast Upf Proteins Required for RNA Surveillance
Affect Global Expression of the Yeast Transcriptome
ABSTRACT
Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
INTRODUCTION
Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
MATERIALS AND METHODS
Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
strains.
To eliminate variation due to genetic background, we
constructed a set of five isogenic strains for use in HDOA analysis
that differ only at the three UPF loci. LRSy307
(MATa his3-11,15 ura3-52 trp1-
1 leu2
upf1-1::URA3 upf21::HIS3
upf3-1::TRP1) (3) was transformed with
single-copy plasmids expressing pairwise combinations of the three
wild-type UPF alleles. LRSy307 was transformed as follows:
with pRS316 (CEN6 ARSH4 URA3) and pML2 (CEN6 ARSH4 LEU2 UPF2 UPF3) to generate a upf1
strain, with pRS316-UPF1 (CEN6 ARSH4 URA3 UPF1) and pLS74
(CEN6 ARSH4 LEU2 UPF3) to generate a
upf2 strain, with pLS80 (CEN6 ARSH4 URA3
UPF1 UPF2) and pRS315 (CEN6 ARSH4 LEU2) to generate a
upf3 strain, with pRS316 (CEN6 ARSH4
URA3) and pRS315 (CEN6 ARSH4 LEU2) to generate a
upf1 upf2 upf3
strain, and with pRS316 (CEN6 ARSH4 URA3) and pML1
(CEN6 ARSH4 LEU2 UPF1 UPF2 UPF3) to generate a wild-type
UPF1 UPF2 UPF3 strain. For convenience, we refer to the
wild-type UPF1 UPF2 UPF3 genotype as
UPF+ and the triple-mutation
upf1 upf2 upf3
genotype as upf123.
ura3-52::URA3) and ML51 (MAT
ura3-52::URA3 upf1-5), was constructed to monitor mRNA levels by HDOA analysis and Northern blotting in a strain background different from LRSy307. ML51 carries the
upf1-5 allele, which contains the same deletion as the
upf1-2 allele (15) except that it lacks the
insertion of URA3 in the UPF1 coding region. To
construct upf1-5, a DNA fragment containing the
upf1-2 allele from pPL64 (16) but lacking the
URA3 insertion was subcloned into the integrative plasmid
pRS306 (28), resulting in pML3 (URA3 upf1-5).
pML3 was used to replace the wild-type UPF1 allele with
upf1-5 by two-step gene replacement (10) in
strain ML27 (MAT ura3-52), resulting in strain ML49
(MAT ura3-52 upf1-5). ML27 and ML49 were made
prototrophic for uracil by integrating URA3 near the
ura3-52 locus, to generate ML34 and ML51.
his4-38 SUF1-1
ura3-52 leu2 trp1-1 lys1-1), BSY1001 (MAT his4-38
SUF1-1 ura3-52 leu2 trp1-1 lys1-1 upf3-1) (14),
YJB195 (MAT ade2-1 his3-11,-15 leu2-3,-112 trp1-1 ura3-1 can1-100,) and YJB1471 (MATa ade2-1
his3-11,-15 leu2-3,-112 trp1-1 ura3-1 can1-100
NMD2::HIS3 (17). NMD2 and UPF2 are synonymous (11).
Using quantitative Northern blotting, we confirmed that all strains
displayed the expected NMD phenotype by assaying the accumulation of
CYH2 pre-mRNA relative to mature CYH2 mRNA. The
relative accumulation of CYH2 pre-mRNA serves to indicate
whether the NMD pathway is functional because a stop codon in the
intron targets the pre-mRNA for rapid decay (12). All of the
upf strains exhibited an average 5.5- ± 0.8-fold increase in the CYH2 pre-mRNA/CYH2 mRNA
accumulation ratio, which is characteristic of an inactive NMD pathway.
Growth conditions. LRSy307 transformants were grown at 30°C in synthetic complete medium (10) (Difco 0919-07 as base) with 2% dextrose supplemented with all amino acids except leucine and without the pyrimidine uracil. Strains ML34 and ML51 were grown in synthetic minimal medium with 2% dextrose without amino acids at 30°C. Overnight cultures grown in synthetic medium at 30°C were diluted 100-fold by resuspension in fresh synthetic medium and grown at 30°C to an optical density at 600 nm of 0.5 (mid-log phase), at which point total RNA was extracted as described below.
RNA methods. Total yeast RNA was isolated by hot phenol extraction (15) of cells prepared by rapid centrifugation at 23°C, resuspension of the pellet in culture medium, and recentrifugation. Cell pellets were snap-frozen in ethanol mixed with dry ice. Northern blot analysis was performed as described previously (3) except that 15 µg of total RNA was denatured with glyoxal and C2H6SO. Either DNA or antisense RNA was used as the probe. To generate antisense RNA probes, templates for in vitro transcription were created by amplifying genomic DNA via PCR with a T7 polymerase site included in the 3' oligonucleotide. Probes were labeled and used for hybridization as described previously (9). All experimental signals from Northern blot analysis were normalized against an ACT1-specific hybridization signal, which is unaffected by loss of UPF function (15). Signals were quantitated by using a Molecular Dynamics PhosphorImager (model 425) and ImageQuant software (version 3.3).
Hybridization and analysis of data from DNA microarrays. The Affymetrix Ye6100 Set HDOA is divided into features that contain oligonucleotides intended to represent all genes coding for cellular mRNAs (31). Most of the ORFs are represented by 40 25-mers, including 20 that are perfectly complementary to the mRNA and 20 that contain a single-base-pair mismatch at the position 13. Together, the 20 probe pairs constitute a probe pair set. Probe pair sets corresponding to 6,218 unique ORFs are present on the HDOA. For 97% of these, it was possible to use stringent parameters to design complete probe pair sets (31). For the remaining 3%, two or three sets of less than ideal oligonucleotides were synthesized on the HDOA. These ORFs were represented by two or three different sets of probe pairs. We included all of these probe pair sets in our analyses to avoid making arbitrary choices regarding what data to include. Consequently, the HDOA contains 6,421 probe pair sets corresponding to 6,218 yeast ORFs, with approximately 3% of the ORFs represented by two or three different probe pair sets.
The preparation of poly(A)+ mRNAs, cDNAs, and cRNAs and the conditions for hybridization were as described by Wodicka et al. (31). cRNA probes were prepared by amplification using in vitro transcription in the presence of nucleotide triphosphates conjugated to biotin and were purified by using an RNeasy column (Qiagen, Santa Clarita, Calif.). The relative concentrations of individual cRNAs were previously shown to be proportional to the abundance of each poly(A) mRNA template (31). After hybridization, the arrays were washed with streptavadin-phycoerythrin. The fluorescent signal from each feature was quantitated with an Affymetrix confocal chip reader (31). Fluorescent signals corresponding to hybridization intensities were analyzed with Affymetrix GeneChip software (version 3.0) using the following settings: difference threshold, 30; ratio threshold, 1.5; change threshold, 30; percent change threshold, 80. The parameters for the absolute decision matrix (analysis of a single HDOA) as designated by the software (detailed information on the definitions and uses of these parameters in calculations made by the software are available from Affymetrix) are Pos/Neg = (Min 3.0, Max 4.0), Pos/Total = (Min 0.33, Max 0.43), and Log Avg Ratio = (Min 0.9, Max 1.3). The parameters for the comparison decision matrix (comparison between two different HDOA) are Inc/Dec = (Min 3.0, Max 4.0), Inc/Total = (Min 0.33, Max 0.43), D Pos
D Neg Ratio = (Min 0.2, Max 0.3), and Log Avg Ratio Change = (Min 0.9, Max 1.3).
In all of our analyses, we used the "normalize to all genes"
function in GeneChip software.
To estimate the range of linearity, four different bacterial mRNAs were
added to the hybridization cocktail at the following concentrations:
BioB (1.5 pM), BioC (5 pM), BioD (25 pM), and Cre (100 pM). When plotted as a function of probe
concentration, the fluorescence intensities associated with these
transcripts were linear with respect to concentration over three log
orders as described by Lockhart et al. (18).
To compare differences in the global expression levels of mRNAs from
upf and UPF+ strains,
we used two outputs of the GeneChip software (version 3.0) as the basis
of two different analytical methods, referred to as method 1 and method
2. Method 1 is based on one of 28 numerical assessments made by the
GeneChip software. In this method, GeneChip subtracts the fluorescent
signal for each mismatched oligonucleotide (MM) from the signal for
each perfectly matched oligonucleotide (PM). The adjusted signals for
each probe pair (PM-MM) are averaged across each probe pair set,
excluding probe pairs that give signals 3 standard deviations (SD) or
more from the mean. For incomplete probe pair sets consisting of fewer
than 20 pairs (see above), GeneChip uses an algorithm to decide whether
to exclude outliers when calculating an average for the entire probe
pair set. The calculation used in method 1 yields an average adjusted
primary signal (termed "average difference" in the software) for
each probe pair set corresponding to each mRNA.
Fold changes in mRNA levels due to loss of UPF gene function
can then be calculated by dividing the average adjusted primary signal
in a mutant by the average adjusted primary signal in the wild type.
Numerators and denominators used in this calculation were rounded to 20 for values less than 20. If both values were less than 20, then the
fold change was not calculated (value = 1.0, indicating no change)
and was not included when average fold changes across multiple trials
were calculated. Average fold changes were calculated for each mRNA
independently of the difference-call assigned to each mRNA (see below).
Method 2 utilizes a summary calculation (difference-call) made by
GeneChip software version 3.0. For each mRNA, the software assigns a
difference-call for each transcript as follows: increased, marginally
increased, unchanged, marginally decreased, or decreased in a
upf strain compared to the isogenic
UPF+ strain. The software utilizes various types
of controls and numerical assessments to make adjustments in the data,
each of which carries weight in making a difference-call.
| |
RESULTS |
|---|
|
Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
|
|---|
Null mutations in UPF1, UPF2, and UPF3 have widespread effects on the transcriptome. To visualize the effects of upf null mutations on the yeast transcriptome, we compared by HDOA analysis global steady-state mRNA levels in strains carrying upf null mutations with those in a UPF wild-type strain. To ensure that changes in the transcriptome could be attributed to loss of UPF function rather than to differences in genetic background, cRNA probes were prepared from five genetically defined, isogenic, haploid strains (Materials and Methods). Three of the strains carried single null mutations in UPF1, UPF2, or UPF3, the fourth strain carried all three UPF null mutations, and the fifth carried wild-type alleles for all three UPF genes. The wild-type UPF+ alleles in these strains were expressed from single-copy, centromeric plasmids.
Biotin-labeled cRNA probes were independently prepared four times, using poly(A)+ mRNAs and cDNAs as serial templates derived from each of the five strains (upf1,
upf2, upf3,
upf123, and UPF123+)
(Materials and Methods). After hybridization to the HDOAs, sets of data
derived from digital images for each of the 20 trials (four trials per
strain) were analyzed by using GeneChip software (see Materials and
Methods). For each trial, the transcriptome of the
UPF+ strain served as the baseline for
comparison with the transcriptomes of the
ufp1, upf2,
upf3, and upf123
strains. Using method 1 (Materials and Methods), all average primary
signals for all mRNAs for all 16 trials (4 trials per upf strain) were compared with the average
primary signals for all four trials comprising the wild-type data set
Probe pair sets producing the highest and lowest primary adjusted
signals were not included in our calculations. We consistently detected
>4,500 mRNAs, whereas a small subset of mRNAs were detected more
sporadically in some but not all trials.
Of these mRNAs, 225 exhibited an average UPF-dependent fold
increase of 2- to 11-fold. The standard deviation (n = 16) for the changes in abundance of all 225 mRNAs was less than or
equal to 50% of the average Upf-dependent fold increase. These
stringent criteria having been met, the results indicate that the
minimal set of mRNAs affected by loss of UPF function is in
the range of several hundred out of the >4,500 mRNAs detected.
Method 1 is simple to execute but fails to correct for sources of
possible error that could cause an underestimate of the number of mRNA
affected by loss of UPF gene function. Also, method 1 combines all upf trials into one group and
potentially ignores any differences in gene expression between the four
upf strains. For this reason, the data were
analyzed more exhaustively by method 2 (Materials and Methods).
GeneChip software version 3.0 assigns a difference-call of increase,
marginal increase, no change, marginal decrease, or decrease (see
Materials and Methods). To analyze difference-calls from four separate
trials for each of the four upf genotypes, we
assigned numerical weights to the GeneChip difference-calls for each
trial as follows: increased signal in single upf null mutant
(+2), statistically marginal increase (+1), no change (0), statistically marginal decrease (1), and decrease (2). The
numerical values of the difference-calls across all four trials for a
single upf strain and for a single mRNA
species were summed and divided by the maximum potential score (+8) to
generate an individual-knockout index (IKI) score ranging between 1
and +1. The IKI score for a given mRNA reflects the consistency of the
change in abundance for each UPF-dependent mRNA in each
upf strain without regard to magnitude. IKI
scores near 1 or +1 represent consistent UPF-dependent
decreases or increases in the abundance of an mRNA in any of one of the
upf strains. IKI scores near zero signify that
the abundance of an mRNA is not dependent on the loss of function of a
specific UPF gene.
For each of the four upf strains, we
calculated the IKI scores for all 6,421 probe pair sets represented on
the HDOA, which represents 6,218 unique ORFs (Materials and Methods;
Table 1). When the four distributions of
IKI scores corresponding to mRNAs levels in the
upf1, upf2,
upf3, and upf123
strains were analyzed, we found that each distribution was skewed toward high scores approaching +1. This result would be expected if
loss of upf gene function, which is known to block an mRNA decay pathway, primarily causes increased abundance of a substantial number of mRNAs. At the 95th percentile of each distribution, the top
5% (321 of 6,421 probe pair sets) had IKI scores of 
0.50 (upf1), 0.75
(upf2), 0.63
(upf3), and 0.75
(upf123). In contrast, the bottom 5% of mRNAs
in all four upf strains had IKI scores of
0.25. The difference between the IKI scores at the 5th and 95th
percentiles demonstrates the positive skew in these distributions. This
supports the result obtained with method 1 that hundreds of mRNAs
increase in abundance in upf strains. Box
plots constructed for the IKI distributions revealed a close similarity
between each distribution in each upf strain
(Fig. 1), suggesting that the
upf mutations may affect a similar subset of
mRNAs regardless of which UPF gene is inactivated. In
summary, genomewide screens failed to uncover major differences that
would be expected to occur if a substantial number of mRNAs were
differentially affected by mutations in one or two but not all three of
the UPF genes.
|
|
,
upf2, and upf3
strains was calculated and rank ordered. We reasoned that if changes in
abundance for a given mRNA were similar in all three strains, then the
three associated IKI scores (one for each genotype) should be similar
and consequently have a small standard deviation. Differential
expression of an individual mRNA in one or two of the three strains in
response to a particular upf mutation would
produce a larger standard deviation for a given set of IKI scores.
Based on this, we examined 100 mRNAs that had the largest standard
deviation in IKI scores (98.5 by percentile). Then, the average
adjusted primary signal (method 1; see Materials and Methods) for each
mRNA in each relevant trial was visually inspected. We found that only
five mRNAs were consistently expressed at different levels depending on
which UPF gene was inactivated. The differentially expressed
mRNAs were YHR076W, YGR073C, UPF1 (YMR080C), UPF2
(YHR077C), and UPF3 (YGR072W).
To confirm this by another approach, we examined all RNAs represented
in each trial, using an independently derived sorting algorithm that
identifies subsets of mRNAs that are uniquely altered in only one or
two of the three upf strains. mRNAs were
designated as altered within a single upf
strain if they were assigned a difference-call of "increase" or
"decrease" in three of the four trials for that strain; otherwise, they were considered unchanged. mRNAs with difference-calls categorized as marginal were considered unchanged. This method produced a list of
104 mRNAs that changed in one or two of the three
upf strains without a corresponding change in
the other upf strains. The average adjusted
primary signals for each of these mRNAs in each relevant trial were
inspected visually. The same five mRNAs as described above were
identified as the ones most likely to exhibit differential expression
in different upf strains.
HDOA data for the five mRNAs were analyzed in greater detail (Table
2). YHR076W mRNA, which is encoded by a
gene adjacent to UPF2, was 3.5 (±0.4)- and 2.9 (±0.5)-fold
more abundant in the upf1 and
upf3 strains, respectively, than in the wild
type but was not detected in upf2 and
upf123 strains. YGR073C mRNA, which is encoded
by a gene adjacent to UPF3, was increased 1.8 (±0.2)-fold
in the upf2 strain but unchanged in all other
upf strains. We are not certain whether the
observed patterns of differential expression are related to the
locations of these genes near the upf2-1::HIS3
and upf3-1::TRP1 disruptions or to expression
of wild-type UPF genes from centromeric plasmids in the
strains, or to both factors.
|
and
upf123 strains but was two- to threefold more
abundant in the upf2 and
upf3 strains than in the
UPF+ strain. UPF2 mRNA was absent as
expected in upf2 and
upf123 strains and unchanged in the
upf3 strain but was increased 1.8 (±0.5)-fold
in the upf1 strain. UPF3 mRNA was
absent as expected in upf3 and
upf123 strains but was increased an average of
more than fivefold in upf1 and
upf2 strains. We confirmed the increased
levels of UPF1 and UPF3 mRNAs by Northern
blotting of RNA from the LRSy307-based transformants that were used for
HDOA analysis (Table 2).
To determine whether the differential expression of wild-type
UPF1 and UPF3 genes might be related to their
presence on plasmids in the LRSy307-based transformants, we used
Northern blotting to assay additional sets of
UPF+ and upf strains
that do not carry UPF genes on plasmids. The level of UPF1 mRNA was the same in strains PLy107
(UPF3+) and BSY1001
(upf3) (1.2 ± 0.1-fold increase in
upf3, n = 2). Similarly,
UPF3 mRNA levels were the same in strains ML34
(UPF1+) and ML51 (upf1)
(1.1 ± 0.6-fold increase in upf1,
n = 3).
When wild-type UPF genes were supplied on plasmids,
UPF1 mRNA was overexpressed in a
upf3 background and UPF3 mRNA was
overexpressed in a upf1 background. No
overexpression was observed when the wild-type alleles for these genes
were located at their resident positions on chromosomes. This finding
suggests that the overexpression from plasmids has no bearing on the
expression of UPF genes in wild-type. Overexpression of
UPF1 or UPF3 mRNA does not appear to cause any
change in the global profile of mRNA accumulation that results from the
disruption of a UPF gene because the same set of mRNAs was
affected in the ufp123 triple mutant (data not
shown). Barring the rare exceptions, our results suggest that loss of
function of any one of the three UPF genes causes altered
accumulation of the same subset of mRNAs.
Coincident changes in the abundance of mRNAs define the target
size.
Since the patterns of mRNA accumulation were nearly
identical in the upf1,
upf2, upf3, and
upf123 strains, we developed a method to
analyze the overall target size for UPF-dependent mRNAs by
combining all upf trials into a single set.
This provided a sample based on 16 trials (4 independent trials in each
of the four upf genotypes:
upf1, upf2,
upf3, and upf123)
normalized against four respective trials for the
UPF+ strain. We used a scoring system similar to
the IKI system to measure the consistency of the difference-calls
associated with each mRNA. This index score, termed the
combined-knockout index (CKI) score, measures the consistency of
effects detected by HDOA analysis on a given mRNA in strains carrying a
loss-of-function mutation of any or all of the UPF genes.
CKI scores were calculated in a manner similar to IKI scores except
that numerical values representing difference-calls were summed across
16 trials representing all four of the upf
strains rather than 4 trials from a single upf strain.
0.59. The frequencies of CKI scores across
for all probe pair sets are shown in a histogram (Fig. 2).
|
0.41). Using the standard deviation associated with CKI score
distribution, we divided the distribution into three sets of mRNAs:
those that exhibit UPF-dependent increases (CKI +0.55), UPF-dependent decreases (CKI 0.41), and
UPF-independent accumulation (0.41 < CKI < +0.55).
The vast majority of mRNAs were not affected by loss of UPF
function, as shown by the large accumulation of CKI scores near zero.
However, there were a significant number of mRNAs affected by
UPF loss of function. The distribution is skewed toward
positive values, suggesting that loss of UPF function may
cause a greater number of mRNAs to exhibit increased rather than
decreased accumulation. To further define and empirically test the set
of UPF-dependent mRNAs, Northern blot analysis was used to
independently verify the results from HDOA analysis and to quantitate
the changes in mRNA accumulation that result from inactivation of the
NMD pathway. To accomplish this, we selected seven mRNAs with CKI
scores near the score defined as the mean + 2 SD (+0.55). We
selected mRNAs encoded by the genes GBP2 (YCL011C),
UGA3 (YDL170W), ALR2 (YFL050C), YIL087C,
MET14 (YKL001C), YLR130C, and PHO80
(YOL001W), which had CKI scores ranging from +0.44 and +0.59
(Table 3).
|
5) (Materials and Methods). The fold increases were similar except for MET14 mRNA (CKI = 0.44), which
was not increased in ML51 (Table 3) but was increased in YJB1471
(upf2) (discussed below).
To test the efficacy of HDOA in predicting the magnitude of changes in
mRNA abundance, we examined 17 mRNAs (including the 7 discussed above)
by comparing the changes predicted by HDOA analysis and Northern
blotting (Table 3). Fifteen had CKI scores ranging from +0.44 to +1.0.
PPR1 mRNA (CKI = 0.19) was included because of prior
evidence that PPR1 mRNA abundance depends on a functional
UPF1 gene (24). PHO84 mRNA (CKI = 1.0) was included to verify that a strongly negative CKI score
corresponds to a decrease in abundance as determined Northern blotting.
Measured by both HDOA analysis and Northern blotting, the mean fold
changes had a correlation coefficient of 0.95, indicating that the mean
fold changes measured by HDOA analysis are similar to those measured by
Northern blotting. We compared these means by using Student's
t tests to determine if the mean fold change as predicted by
HDOA analysis was statistically different from that predicted by
Northern blotting. Eleven of the 17 mRNAs produced mean fold changes
that showed no evidence of a statistical difference between the two
techniques; 6 of the 17 mRNAs displayed a statistical difference with
Northern blotting typically reporting larger fold changes. However, the
change predicted by HDOA analysis always showed the same positive or
negative trend as did the change predicted by Northern blotting. When
they occurred, deviations obtained when the two methods were used were
less than a factor of 2 in magnitude.
To ensure that the UPF-dependent changes in expression were
not unique to the LRSy307-based transformants, we used Northern blotting of RNA from additional sets of strains to examine the abundance of the 17 mRNAs discussed above. ML34
(UPF1+) and ML51 (upf1-4) are
isogenic derivatives of S288C differing only at the UPF1
locus (Materials and Methods). We detected 16 of the 17 mRNAs in ML34
and ML51. PHO84 could not be consistently detected in either
ML34 or ML51. Of the 16 detectable mRNAs, 14 exhibited fold changes
comparable to those observed in derivatives of strain LRSy307. The two
mRNAs that exhibited anomalous behavior, MET14 and YIL087C,
were detected as UPF-independent mRNAs in the isogenic
strains ML34 and ML51. ML34 and ML51 were grown in a different
synthetic medium than were the derivatives of strain LRSy307, which
might account for differences in expression compared with expression in
LRSy307 transformants. However, in another isogenic pair of strains,
YJB1471 (upf2) and YJB195
(UPF2+) (Materials and Methods), which were
grown in the same synthetic medium as were strains ML34 and ML51,
MET14 exhibited a 1.6 (±0.2)-fold increase and YIL087C
exhibited a 1.9 (±0.7)-fold increase. Overall, the results indicate
that most of the changes in mRNA levels identified in the LRSy307
transformants were also observed in other strains, but some of the
mRNAs accumulated to different levels in different strains.
The Northern blotting experiments described above indicate that mRNAs
with CKI scores above +0.44 are the best candidates for those
exhibiting increased abundance when the UPF genes are inactivated. mRNAs with the highest CKI scores (+0.90) and the corresponding fold increases in abundance are shown in Table
4. CKI scores were +0.44 for 539 of the
6,421 probe pair sets, including 529 unique mRNAs and 10 mRNAs tiled
more than once on the HDOA (see Materials and Methods). Average fold
changes for these mRNAs were increased as follows: 12 from 5- to
11-fold, 29 from 4- to 5-fold, 56 from 3- to 4-fold, 234 from 2- to
3-fold, 179 from 1.5- to 2-fold, and 28 from 1.2- to 1.5-fold. One mRNA
was unchanged (CKI = 0.5).
|
0.41,
which fall 2 SD or more below the mean. Of the 40 mRNAs identified
(Table 5), 1, PHO84 mRNA
(CKI = 1.0), was decreased in abundance 4.4 (±1.4)-fold
according to HDOA analysis. Northern blotting indicated that
PHO84 mRNA was decreased 3.3 (±0.3)-fold in abundance. This
result shows that inactivation of the NMD pathway can lead to reduced
mRNA abundance. Six of the 40 mRNAs were decreased 2-fold or more in
abundance; one of these six, YOR387C mRNA, was decreased 7.1-fold
(Table 5). Overall, these results indicate that the number of mRNAs in
upf strains that increase in abundance
outnumber those that decrease in abundance at least 10-fold. Data are
available for all mRNAs on line (23b, 25a).
|
Distribution of UPF-dependent mRNAs by function and
expression level.
mRNAs that change in abundance when the NMD
pathway is inactivated were sorted according to function by using the
categories described in the MIPS (Munich Information Center for Protein
Sequences) database (23a). Table
6 shows the numbers and relative
percentages of mRNAs in each functional category assigned by MIPS for
all mRNAs and for the 529 unique UPF-dependent mRNAs that
exhibit consistent, increased accumulation ranging from 1.2- to 11-fold with CKI scores of 0.44. A substantial number of mRNAs have no known
function and are therefore are listed as "unclassified" in Table 6.
For 13 of the 15 functional categories, the mRNAs are distributed
similarly for both sets. mRNAs coding for products that function in
protein synthesis were vastly underrepresented among the
UPF-dependent mRNAs (5.5% for all mRNAs, compared to 0.9%
for UPF-dependent mRNAs). A much more modest decrease in the
frequency of representation was also observed for the "protein destination" category (8.2% for all mRNAs, compared to 3.7% for UPF-dependent mRNAs).
|
0.44 and the larger
set of 6,218 unique mRNAs tiled on the HDOA. Intron-containing mRNAs
were distributed similarly in both sets (Table 6, last row), suggesting
that the presence of an intron is probably unrelated to
UPF-mediated control of mRNA abundance in S. cerevisiae.
We assessed whether the average abundance for UPF-dependent
mRNAs with CKI scores of 0.44 was higher or lower than the average abundance for all mRNAs (Table 7). To
accomplish this, the average expression levels across the four
UPF+ trials were calculated by using the average
adjusted primary signal for each mRNA (method 1; see Materials and
Methods). The mean values were 188 fluorescent units for
UPF-dependent mRNAs with CKI scores of 0.44 and 546 fluorescent units for all mRNAs. The threefold difference is
statistically significant as measured by Student's t test
assuming equal variance at 95% confidence. To confirm this, we
examined a set of 529 mRNAs selected at random among all mRNAs and
compared the mean value in fluorescent units for this set with mean
value in fluorescent units for the set of 529 UPF-dependent
mRNAs. For all three sets of data, the medians and interquartile
regions were similar. However, the expression levels diverged at the
90th and 95th percentiles of the distribution. While there are some
statistical caveats to conclusions based on comparing different probe
pair sets (31), our results suggest that
UPF-dependent mRNAs are underrepresented among mRNAs
expressed in the upper quartile of relative expression levels. It
therefore appears that the inactivation of UPF genes
disproportionately affects the accumulation of mRNAs that are normally
present at lower than average abundance in wild-type strains.
|
Regulatory cascades among the UPF-dependent mRNAs.
Numerous subsets consisting of coregulated mRNAs were evident among the
UPF-dependent mRNAs. We examined two such mRNA subsets in
further detail. One coregulated subset consists of PPR1,
which encodes a positive transcriptional activator, and downstream
targets of Ppr1p-mediated transcriptional activation, including the
URA1, URA3, URA4, and URA10
genes (Table 8) (20, 27). It
was previously reported that PPR1 mRNA accumulation
increases threefold when UPF1 is inactivated
(24). According to HDOA data, the accumulation of
PPR1 mRNA increased 2.0 (±0.8)-fold when NMD was
inactivated. PPR1 mRNA was not included in the list of
UPF-dependent mRNAs with CKI scores of 0.44. The CKI score
was only +0.19 due to inconsistencies in the difference-calls across
trials resulting from low signal intensities. However, we confirmed by
quantitative Northern blotting that the accumulation of PPR1
mRNA increased 2.9 (±0.5)-fold when NMD was inactivated.
PPR1 mRNA also exhibited increased accumulation in the
upf strain ML51 (Table 3).
|
derivatives of strain LRSy307 and in the
upf strain ML51 (Table 3). All other mRNAs
known to code for proteins involved in phosphate utilization, were
unchanged in abundance.
| |
DISCUSSION |
|---|
|
Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
|
|---|
The goal of this study was to establish the extent to which the Upf proteins affect the expression of the >6,000 genes that comprise the transcriptome of S. cerevisiae. To address this question, we probed HDOA with cRNAs corresponding to all polyadenylated mRNAs in strains carrying functional disruptions of the UPF genes. The fluorescent signals were analyzed by using two outputs of GeneChip 3.0 software as the basis of two different analytical methods (see Materials and Methods).
We identified a minimal set of 225 mRNAs that exhibited an average
UPF-dependent fold increase of 2- to 11-fold with a standard deviation 50% of the average UPF-dependent fold increase.
To mine the data further, we devised the IKI to compare changes in different upf strains. By analyzing the
distributions of IKI scores, which range from 1 to +1, we found that
99.9% of the observed changes in mRNA abundance were common to
upf1, upf2,
upf3, and upf123
strains. There were only five exceptions: UPF1,
UPF2, UPF3, YHR076W, and YGR073C.
The UPF genes exhibited a complex pattern of overexpression
in the LRSy307 series of strains (Table 2). The anomalous behavior of
the UPF genes might be explained in part by the fact that
the genes were expressed from plasmids rather than from their normal chromosomal loci. In strains carrying UPF genes at their
normal chromosomal loci, the UPF genes were expressed at
normal levels and in a UPF-independent manner. Given this,
we do not currently attach any physiological significance to the
UPF-dependent overexpression of UPF genes from
plasmids. However, we considered whether the overexpression could
influence the number of mRNAs affected by loss of UPF
function or the magnitudes of the effects. By comparing data from the
strains that carry the single null alleles
(upf1, upf2, or
upf3) with data from the triple-null strain
(upf123), we concluded that the overexpression
of UPF genes had no effect on the number of
UPF-dependent mRNAs or on the magnitude of the observed changes.
YHR076W is located immediately adjacent to UPF2. mRNA
accumulation was increased about threefold in the
upf1 and upf3 strains
but was absent in the upf2 and
upf123 strains. YGR073C is located immediately
adjacent to UPF3. This mRNA was only marginally increased
and only in the upf1 and
upf2 strains. Possibly some of these changes
can be related to the positions of these genes near the insertions in
the upf21::HIS3 and
upf3-1::TRP1 null alleles. Although insertions
could perturb local rates of transcription through local changes in
chromatin structure, it is not clear why these mRNAs are differentially expressed depending on which of the UPF genes are being
expressed from plasmids.
Barring the exceptions noted above, our results indicate that the same
mRNAs respond to loss of UPF function regardless of which of
the UPF genes is disrupted. This finding served as the basis
for pooling all trials for all upf strains to
calculate a CKI index score for each mRNA. The CKI score measures the
consistency (but not the magnitude) of the UPF-dependent
effect on a given mRNA. This approach had the advantage of producing a
tighter distribution with a much smaller standard deviation than any of
the IKI distributions due to the increased number of trials used to
calculate the CKI scores (16 in all).
Like the IKI scores, the CKI scores range from 1 to +1 and provide a
measure of the consistency of difference-calls across all trials. CKI
scores of +0.55 were 2 SD or more above the mean score. To determine
whether mRNAs with scores near +0.55 were altered in abundance, we
analyzed by Northern blotting seven mRNAs with scores ranging from
+0.44 to +0.59. Northern blotting showed these mRNAs to be increased in
abundance, indicating that mRNAs with CKI scores in the range of +0.44
are candidates for natural targets of the UPF genes.
Overall, UPF-dependent changes in mRNA accumulation were as
high as 11.0-fold (YEL073C). Thirteen mRNAs exhibited a greater
than fivefold average increase in abundance. The average increase among
529 mRNAs with CKI scores of +0.44 was 2.4-fold.
Although most of the observed changes in the transcriptome were in the
direction of increased accumulation when UPF genes were
inactivated, a smaller number of mRNAs decreased in abundance. Forty
mRNAs had CKI scores 2 SD below the mean CKI score. Six of these had
CKI scores ranging from 0.53 to 1.0 with two- to sevenfold downward
changes in abundance. The change for one of these, PHO84
mRNA, was confirmed by Northern blotting. Overall, we detected about 10 times more mRNAs that increased in abundance as decreased in abundance.
We tested the efficacy of HDOA analysis in predicting the magnitude of changes in mRNA abundance by measuring the abundance of 17 UPF-dependent mRNAs by Northern blotting. The mean fold changes measured by HDOA analysis were similar to those measured by Northern blotting. In general, when discrepancies were observed, larger fold changes were detected by Northern blotting. These results suggest that HDOA analysis is a reasonable but not a perfect predictor of the magnitudes of change.
We know of at least two UPF-dependent mRNAs identified in previous studies, CTF13 (9) and PPR1 (15, 24), that had unexpectedly low CKI scores that would generally not be indicative of a dependence on the UPF genes. For this reason, these two mRNAs were not included in the list of UPF-dependent mRNAs predicted by HDOA analysis despite three- to fourfold increases in abundance demonstrated by Northern blotting. These mRNAs may have escaped detection by HDOA analysis because their levels of abundance in wild-type strains are near the threshold of detection. When mRNAs are present at threshold levels, errors in predicting relative abundance are more likely to occur. Consequently, greater inconsistencies between trials can lower the index score and cause an erroneous call. In addition to these false-negative calls, false-positive calls are possible at some frequency, especially for mRNAs with CKI scores that reflect borderline consistency across trials (scores near +0.44). Assuming that false-negative and false-positive calls occur with similar frequencies, on balance our results indicate that well over 500 mRNAs change in abundance when the UPF genes are inactivated; 63% of the mRNAs exhibited greater than twofold increases in abundance. The largest change in abundance was 11-fold.
The best-described function for the Upf proteins is in their role in promoting the accelerated decay of nonsense mRNAs. These mRNAs are targeted for rapid decay by the presence of a premature stop codon caused either by a mutation or by an error in gene expression. However, the Upf proteins could also cause a reduction in the overall decay rate of any mRNA as part of the normal repertoire of gene expression for that mRNA. Although naturally occurring mRNAs do not typically contain a premature stop codon, they could be targeted for rapid decay by an alternate mechanism. For example, they might contain a stop codon at the end of a translatable upstream ORF or some other sequence element that serves a targeting function, or the normal stop codon at the end of the ORF might have the atypical property of triggering rapid decay. In any case, it seems likely that the Upf proteins cause changes in the abundance of naturally occurring mRNAs through a mechanism involving RNA decay.
If this is so, then the inactivation of a UPF gene should cause increased mRNA abundance of a selective group of targeted mRNAs. While most of the UPF-dependent mRNAs exhibited increased abundance, we observed some declines in abundance and confirmed one of these (for PHO84 mRNA) by Northern blotting. Changes in abundance in both directions could be explained if mRNAs coding for either positive or negative regulatory proteins served as direct targets for accelerated decay.
In support of this view, we found that the mRNA coding for the
transcriptional activator Ppr1p was increased in
upf strains as were two mRNAs (URA1
and URA10) coding for enzymes in uracil biosynthesis that
are transcriptionally activated by Ppr1p. A third mRNA,
URA4, which has been reported to be regulated by
PPR1, did not respond to loss of UPF gene
function for unknown reasons. It was reported previously that the
half-life of PPR1 mRNA increases threefold, commensurate
with a threefold increase in PPR1 mRNA abundance
(24). One mRNA (URA3) that is regulated by
PPR1 was shown to increase in abundance due to an increased rate of transcription (15, 16). This example illustrates one way that the altered half-life of a single mRNA coding for a regulatory protein could indirectly influence the abundance of additional mRNAs.
Using similar logic, we reason that increased accumulation of a transcriptional repressor should cause a decrease in the accumulation of mRNAs regulated by a repressor. The five UPF-dependent mRNAs involved in phosphate utilization could involve negative regulation by one or more repressors given that one of the mRNAs (PHO80) was increased whereas four others (PHO84, PHO5, PHO86, and PHO8) all declined in abundance. PHO80 codes for a cyclin-dependent protein kinase that represses transcription of the PHO5 gene coding for secreted acid phosphatase by phosphorylating transcription factors encoded by PHO2 and PHO4 (2, 5, 6). Thus, the observed decline in PHO5 mRNA accumulation could be due to the increased accumulation of PHO80 mRNA. Further studies will be required to establish whether the PHO mRNAs change in abundance as a group through independent direct targeting of multiple mRNAs or indirect targeting of regulators that influence the abundance of the other mRNAs. To further support of the idea that mRNAs coding for regulatory proteins may serve as targets of UPF-mediated decay, we identified a host of additional UPF-dependent mRNAs coding for positively and negatively acting factors that influence transcription, most notably PDR3 (CKI = +0.47), RMS1 (CKI = +0.78), FZF1 (CKI = +0.63), KSS1 (CKI = +0.94), and HST1 (CKI = +0.41), and HST2 (CKI = +0.53).
We measured the half-lives of nine mRNAs selected among those that had
a CKI score of +0.44 and where the increased abundance was confirmed
by Northern blotting. None of these mRNAs appeared to have an altered
half-life (data not shown), which suggests that indirect targets may
predominant over direct targets and that the Upf proteins may cause a
change in the mRNA half-life of a small subset of the
UPF-dependent mRNAs. Further studies are in progress to
identify the direct targets of accelerated decay among naturally
occurring mRNAs and to establish the mechanism for recruiting these
mRNAs into the UPF-mediated pathway for rapid decay.
| |
ACKNOWLEDGMENTS |
|---|
We are indebted to members of the Affymetrix Academic User's Center, notably Chris Harrington and Sumathi Venkatapathy, for valuable technical expertise. We thank Renee Shirley, Amanda Ford, and Judith Berman for critical reading of the manuscript and Jeff Dahlsied and Erin O'Shea for helpful discussions.
Microarray analysis was performed by M.J.L. at the Affymetrix Academic User's Center, which is funded by NIH grant PO1 HG01323. The research was supported by the College of Agricultural and Life Sciences, University of Wisconsin, Madison, under NSF grant MCB-9870313 (M.R.C.). M.J.L. was supported by NRSA postdoctoral fellowship NIH GM19070. Additional funding was provided by the Research Committee of the University of Wisconsin Medical School.
| |
FOOTNOTES |
|---|
* Corresponding author. Mailing address: University of Wisconsin, Laboratory of Molecular Biology, 435A Bock Laboratories, 1525 Linden Dr., Madison, WI 53706. Phone: (608) 262-5388. Fax: (608) 262-4570. E-mail: mrculber{at}facstaff.wisc.edu.
Laboratory of Genetics paper 3529.
| |
REFERENCES |
|---|
|
Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
|
|---|
| 1. |
Applequist, S. E.,
M. Selg,
C. Raman, and H. M. Jack.
1997.
Cloning and characterization of HUPF1, a human homolog of the Saccharomyces cerevisiae nonsense mRNA-reducing UPF1 protein.
Nucleic Acids Res.
25:814-821 |
| 2. |
Arima, K.,
T. Oshima,
I. Kubota,
N. Nakamura,
T. Mizunaga, and A. Toh-e.
1983.
The nucleotide sequence of the yeast PHO5 gene: a putative precursor of repressible acid phosphatase contains a signal peptide.
Nucleic Acids Res.
11:1657-1672 |
| 3. |
Atkin, A. L.,
L. R. Schenkman,
M. Eastham,
J. N. Dahlseid,
M. J. Lelivelt, and M. R. Culbertson.
1997.
Relationship between yeast polyribosomes and Upf proteins required for nonsense mRNA decay.
J. Biol. Chem.
272:22163-22172 |
| 4. | Badcock, K., C. M. Churcher, B. G. Barrell, M. A. Rajandream, and S. V. Walsh. 1997. Swiss-Prot accession no. Q09820, gene name SPAC16C9.06C. |
| 5. |
Bun-Ya, M.,
M. Nishimura,
S. Harashima, and Y. Oshima.
1991.
The PHO84 gene of Saccharomyces cerevisiae encodes an inorganic phosphate transporter.
Mol. Cell. Biol.
11:3229-3238 |
| 6. |
Cui, Y.,
K. W. Hagan,
S. Zhang, and S. W. Peltz.
1995.
Identification and characterization of genes that are required for the accelerated degradation of mRNAs containing a premature translational termination codon.
Genes Dev.
9:423-436 |
| 7. | Culbertson, M. R. 1999. RNA surveillance: unforeseen consequences for gene expression, inherited genetic disorders and cancer. Trends Genet. 15:74-80[Medline]. |
| 8. | Czaplinski, K., Y. Weng, K. W. Hagan, and S. W. Peltz. 1995. Purification and characterization of the Upf1 protein: a factor involved in translation and mRNA degradation. RNA 1:610-623[Abstract]. |
| 9. |
Dahlseid, J. N.,
P. J.,
R. L. Shirley,
A. L. Atkin,
P. Hieter, and M. R. Culbertson.
1998.
Accumulation of mRNA coding for the Ctf13p kinetochore subunit of Saccharomyces cerevisiae depends on the same factors that promote rapid decay of nonsense mRNAs.
Genetics
150:1019-1035 |
| 10. | Guthrie, C., and G. R. Fink (ed.). 1991. Methods in enzymology, vol. 194. Guide to yeast genetics and molecular biology. Academic Press, San Diego, Calif. |
| 11. |
He, F., and A. Jacobson.
1995.
Identification of a novel component of the nonsense-mediated mRNA decay pathway by use of an interacting protein screen.
Genes Dev.
9:437-454 |
| 12. |
He, F.,
S. W. Peltz,
J. L. Donahue,
M. Rosbash, and A. Jacobson.
1993.
Stabilization and ribosome association of unspliced pre-mRNAs in a yeast upf1 mutant.
Proc. Natl. Acad. Sci. USA
90:7034-7038 |
| 13. |
Kaneko, Y.,
A. Toh-e, and Y. Oshima.
1982.
Identification of the genetic locus for the structural gene and a new regulatory gene for the synthesis of repressible alkaline phosphatase in Saccharomyces cerevisiae.
Mol. Cell. Biol.
2:127-137 |
| 14. |
Lee, B. S., and M. R. Culbertson.
1995.
Identification of an additional gene required for eukaryotic nonsense mRNA turnover.
Proc. Natl. Acad. Sci. USA
92:10354-10358 |
| 15. |
Leeds, P.,
S. W. Peltz,
A. Jacobson, and M. R. Culbertson.
1991.
The product of the yeast UPF1 gene is required for rapid turnover of mRNAs containing a premature translational termination codon.
Genes Dev.
5:2303-2314 |
| 16. |
Leeds, P.,
J. M. Wood,
B. S. Lee, and M. R. Culbertson.
1992.
Gene products that promote mRNA turnover in Saccharomyces cerevisiae.
Mol. Cell. Biol.
12:2165-77 |
| 17. |
Lew, J.,
S. Enomoto, and J. Berman.
1998.
Telomere length regulation and telomeric chromatin require the nonsense-mediated mRNA decay pathway.
Mol. Cell. Biol.
18:6121-6130 |
| 18. | Lockhart, D. J., H. Dong, M. C. Byrne, M. T. Follettie, M. V. Gallo, M. S. Chee, M. Mittmann, C. Wang, M. Kobayashi, H. Horton, and E. L. Brown. 1996. Expression monitoring by hybridization to high-density oligonucleotide arrays. Nat. Biotechnol. 14:1675-1680[Medline]. |
| 19. | Long, R. M., D. J. Elliott, F. Stutz, M. Rosbash, and R. H. Singer. 1995. Spatial consequences of defective processing of specific yeast mRNAs revealed by fluorescent in situ hybridization. RNA 1:1071-1078[Abstract]. |
| 20. | Losson, R., R. P. Fuchs, and F. Lacroute. 1985. Yeast promoters URA1 and URA3. Examples of positive control. J. Mol. Biol. 185:65-81[Medline]. |
| 21. |
Losson, R., and F. Lacroute.
1979.
Interference of nonsense mutations with eukaryotic messenger RNA stability.
Proc. Natl. Acad. Sci. USA
76:5134-5137 |
| 22. | Maquat, L. E. 1995. When cells stop making sense: effects of nonsense codons on RNA metabolism in vertebrate cells. RNA 1:453-465[Abstract]. |
| 23. | Nagy, E., and L. E. Maquat. 1998. A rule for termination-codon position within intron-containing genes: when nonsense affects RNA abundance. Trends Biochem. Sci. 23:198-199[Medline]. |
| 23a. | Munich Information Centre for Protein Sequences. February 1999, revision date. [Online.] http://mips.biochem.mpg.de/. [July 1999. last date accessed.] |
| 23b. | NMD Database. October 1999, posting date. [Online.] http://144.92.19.47/default.htm. University of Wisconsin, Madison. |
| 24. | Peltz, S., and A. Jacobson. 1993. mRNA turnover in Saccharomyces cerevisiae, p. 291-328. In J. Belasco, and G. Brawerman (ed.), Control of messenger RNA stability. Academic Press, San Diego, Calif. |
| 25. |
Perlick, H. A.,
S. M. Medghalchi,
F. A. Spencer,
R. J. Kendzior, Jr., and H. C. Dietz.
1996.
Mammalian orthologues of a yeast regulator of nonsense transcript stability.
Proc. Natl. Acad. Sci. USA
93:10928-10932 |
| 25a. | Proteome, Inc. May 1999, revision date. [Online.] http://www.proteome.com/. [July 1999, last date accessed.] |
| 26. |
Pulak, R., and P. Anderson.
1993.
mRNA surveillance by the Caenorhabditis elegans smg genes.
Genes Dev.
7:1885-1897 |
| 27. |
Roy, A.,
F. Exinger, and R. Losson.
1990.
cis- and trans-acting regulatory elements of the yeast URA3 promoter.
Mol. Cell. Biol.
10:5257-5270 |
| 28. |
Sikorski, R. S., and P. Hieter.
1989.
A system of shuttle vectors and yeast host strains designed for efficient manipulation of DNA in Saccharomyces cerevisiae.
Genetics
122:19-27 |
| 29. | van Hoof, A., and P. J. Green. 1996. Premature nonsense codons decrease the stability of phytohemagglutinin mRNA in a position-dependent manner. Plant J. 10:415-424[Medline]. |
| 30. | Weng, Y., K. Czaplinski, and S. W. Peltz. 1998. ATP is a cofactor of the Upf1 protein that modulates its translation termination and RNA binding activities. RNA 4:205-214[Abstract]. |
| 31. | Wodicka, L., H. Dong, M. Mittmann, M. H. Ho, and D. J. Lockhart. 1997. Genome-wide expression monitoring in Saccharomyces cerevisiae. Nat. Biotechnol. 15:1359-1367[Medline]. |
Molecular and Cellular Biology, October 1999, p. 6710-6719, Vol. 19, No. 10
0270-7306/99/$04.00+0
Copyright © 1999, American Society for Microbiology. All rights reserved.
This article has been cited by other articles:
-
Kebaara, B. W., Atkin, A. L.
(2009). Long 3'-UTRs target wild-type mRNAs for nonsense-mediated mRNA decay in Saccharomyces cerevisiae. Nucleic Acids Res
37: 2771-2778
[Abstract] [Full Text] -
Song, H.-R., Song, J.-D., Cho, J.-N., Amasino, R. M., Noh, B., Noh, Y.-S.
(2009). The RNA Binding Protein ELF9 Directly Reduces SUPPRESSOR OF OVEREXPRESSION OF CO1 Transcript Levels in Arabidopsis, Possibly via Nonsense-Mediated mRNA Decay. Plant Cell
21: 1195-1211
[Abstract] [Full Text] -
Atkins, J. F., Bjork, G. R.
(2009). A Gripping Tale of Ribosomal Frameshifting: Extragenic Suppressors of Frameshift Mutations Spotlight P-Site Realignment. Microbiol. Mol. Biol. Rev.
73: 178-210
[Abstract] [Full Text] -
Zheng, W., Finkel, J. S., Landers, S. M., Long, R. M., Culbertson, M. R.
(2008). Nonsense-Mediated Decay of ash1 Nonsense Transcripts in Saccharomyces cerevisiae. Genetics
180: 1391-1405
[Abstract] [Full Text] -
Dall'Osso, C., Guella, I., Duga, S., Locatelli, N., Paraboschi, E. M., Spreafico, M., Afrasiabi, A., Pechlaner, C., Peyvandi, F., Tenchini, M. L., Asselta, R.
(2008). Molecular characterization of three novel splicing mutations causing factor V deficiency and analysis of the F5 gene splicing pattern. haematol
93: 1505-1513
[Abstract] [Full Text] -
Saltzman, A. L., Kim, Y. K., Pan, Q., Fagnani, M. M., Maquat, L. E., Blencowe, B. J.
(2008). Regulation of Multiple Core Spliceosomal Proteins by Alternative Splicing-Coupled Nonsense-Mediated mRNA Decay. Mol. Cell. Biol.
28: 4320-4330
[Abstract] [Full Text] -
Akimitsu, N.
(2008). Messenger RNA Surveillance Systems Monitoring Proper Translation Termination. J Biochem
143: 1-8
[Abstract] [Full Text] -
Johansson, M. J. O., He, F., Spatrick, P., Li, C., Jacobson, A.
(2007). Association of yeast Upf1p with direct substrates of the NMD pathway. Proc. Natl. Acad. Sci. USA
104: 20872-20877
[Abstract] [Full Text] -
Culbertson, M. R.
(2007). Navigating Without a Road Map. Genetics
177: 1-7
[Full Text] -
Isken, O., Maquat, L. E.
(2007). Quality control of eukaryotic mRNA: safeguarding cells from abnormal mRNA function. Genes Dev.
21: 1833-3856
[Abstract] [Full Text] -
Viegas, M. H., Gehring, N. H., Breit, S., Hentze, M. W., Kulozik, A. E.
(2007). The abundance of RNPS1, a protein component of the exon junction complex, can determine the variability in efficiency of the Nonsense Mediated Decay pathway. Nucleic Acids Res
35: 4542-4551
[Abstract] [Full Text] -
Stalder, L., Muhlemann, O.
(2007). Transcriptional Silencing of Nonsense Codon-containing Immunoglobulin {micro} Genes Requires Translation of Its mRNA. J. Biol. Chem.
282: 16079-16085
[Abstract] [Full Text] -
Longman, D., Plasterk, R. H.A., Johnstone, I. L., Caceres, J. F.
(2007). Mechanistic insights and identification of two novel factors in the C. elegans NMD pathway. Genes Dev.
21: 1075-1085
[Abstract] [Full Text] -
Jacobs, J. L., Belew, A. T., Rakauskaite, R., Dinman, J. D.
(2007). Identification of functional, endogenous programmed -1 ribosomal frameshift signals in the genome of Saccharomyces cerevisiae. Nucleic Acids Res
35: 165-174
[Abstract] [Full Text] -
Schrader, R., Young, C., Kozian, D., Hoffmann, R., Lottspeich, F.
(2006). Temperature-sensitive eIF5A Mutant Accumulates Transcripts Targeted to the Nonsense-mediated Decay Pathway. J. Biol. Chem.
281: 35336-35346
[Abstract] [Full Text] -
Rodriguez-Gabriel, M. A., Watt, S., Bahler, J., Russell, P.
(2006). Upf1, an RNA Helicase Required for Nonsense-Mediated mRNA Decay, Modulates the Transcriptional Response to Oxidative Stress in Fission Yeast.. Mol. Cell. Biol.
26: 6347-6356
[Abstract] [Full Text] -
Wittmann, J., Hol, E. M., Jack, H.-M.
(2006). hUPF2 Silencing Identifies Physiologic Substrates of Mammalian Nonsense-Mediated mRNA Decay. Mol. Cell. Biol.
26: 1272-1287
[Abstract] [Full Text] -
Behm-Ansmant, I., Izaurralde, E.
(2006). Quality control of gene expression: a stepwise assembly pathway for the surveillance complex that triggers nonsense-mediated mRNA decay.. Genes Dev.
20: 391-398
[Full Text] -
Ford, A. S., Guan, Q., Neeno-Eckwall, E., Culbertson, M. R.
(2006). Ebs1p, a Negative Regulator of Gene Expression Controlled by the Upf Proteins in the Yeast Saccharomyces cerevisiae. Eukaryot Cell
5: 301-312
[Abstract] [Full Text] -
Taylor, R., Kebaara, B. W., Nazarenus, T., Jones, A., Yamanaka, R., Uhrenholdt, R., Wendler, J. P., Atkin, A. L.
(2005). Gene Set Coregulated by the Saccharomyces cerevisiae Nonsense-Mediated mRNA Decay Pathway. Eukaryot Cell
4: 2066-2077
[Abstract] [Full Text] -
REHWINKEL, J., LETUNIC, I., RAES, J., BORK, P., IZAURRALDE, E.
(2005). Nonsense-mediated mRNA decay factors act in concert to regulate common mRNA targets. RNA
11: 1530-1544
[Abstract] [Full Text] -
CULBERTSON, M. R., NEENO-ECKWALL, E.
(2005). Transcript selection and the recruitment of mRNA decay factors for NMD in Saccharomyces cerevisiae. RNA
11: 1333-1339
[Abstract] [Full Text] -
Hieronymus, H., Silver, P. A.
(2004). A systems view of mRNP biology. Genes Dev.
18: 2845-2860
[Abstract] [Full Text] -
HARGER, J. W., DINMAN, J. D.
(2004). Evidence against a direct role for the Upf proteins in frameshifting or nonsense codon readthrough. RNA
10: 1721-1729
[Abstract] [Full Text] -
Grigull, J., Mnaimneh, S., Pootoolal, J., Robinson, M. D., Hughes, T. R.
(2004). Genome-Wide Analysis of mRNA Stability Using Transcription Inhibitors and Microarrays Reveals Posttranscriptional Control of Ribosome Biogenesis Factors. Mol. Cell. Biol.
24: 5534-5547
[Abstract] [Full Text] -
Bates, M. E., Liu, L. Y., Esnault, S., Stout, B. A., Fonkem, E., Kung, V., Sedgwick, J. B., Kelly, E. A. B., Bates, D. M., Malter, J. S., Busse, W. W., Bertics, P. J.
(2004). Expression of Interleukin-5- and Granulocyte Macrophage-Colony-Stimulating Factor-Responsive Genes in Blood and Airway Eosinophils. Am. J. Respir. Cell Mol. Bio.
30: 736-743
[Abstract] [Full Text] -
KEELING, K. M., LANIER, J., DU, M., SALAS-MARCO, J., GAO, L., KAENJAK-ANGELETTI, A., BEDWELL, D. M.
(2004). Leaky termination at premature stop codons antagonizes nonsense-mediated mRNA decay in S. cerevisiae. RNA
10: 691-703
[Abstract] [Full Text] -
Enomoto, S., Glowczewski, L., Lew-Smith, J., Berman, J. G.
(2004). Telomere Cap Components Influence the Rate of Senescence in Telomerase-Deficient Yeast Cells. Mol. Cell. Biol.
24: 837-845
[Abstract] [Full Text] -
Blaxall, B. C., Spang, R., Rockman, H. A., Koch, W. J.
(2003). Differential myocardial gene expression in the development and rescue of murine heart failure. Physiol. Genomics
15: 105-114
[Abstract] [Full Text] -
Das, B., Butler, J. S., Sherman, F.
(2003). Degradation of Normal mRNA in the Nucleus of Saccharomyces cerevisiae. Mol. Cell. Biol.
23: 5502-5515
[Abstract] [Full Text] -
Kebaara, B., Nazarenus, T., Taylor, R., Forch, A., Atkin, A. L.
(2003). The Upf-dependent decay of wild-type PPR1 mRNA depends on its 5'-UTR and first 92 ORF nucleotides. Nucleic Acids Res
31: 3157-3165
[Abstract] [Full Text] -
Dahlseid, J. N., Lew-Smith, J., Lelivelt, M. J., Enomoto, S., Ford, A., Desruisseaux, M., McClellan, M., Lue, N., Culbertson, M. R., Berman, J.
(2003). mRNAs Encoding Telomerase Components and Regulators Are Controlled by UPF Genes in Saccharomyces cerevisiae. Eukaryot Cell
2: 134-142
[Abstract] [Full Text] -
Shirley, R. L., Ford, A. S., Richards, M. R., Albertini, M., Culbertson, M. R.
(2002). Nuclear Import of Upf3p Is Mediated by Importin-{alpha}/-{beta} and Export to the Cytoplasm Is Required for a Functional Nonsense-Mediated mRNA Decay Pathway in Yeast. Genetics
161: 1465-1482
[Abstract] [Full Text] -
Clark, T. A., Sugnet, C. W., Ares, M. Jr.
(2002). Genomewide Analysis of mRNA Processing in Yeast Using Splicing-Specific Microarrays. Science
296: 907-910
[Abstract] [Full Text] -
Cohen, Y., Dardalhon, M., Averbeck, D.
(2002). Homologous recombination is essential for RAD51 up-regulation in Saccharomyces cerevisiae following DNA crosslinking damage. Nucleic Acids Res
30: 1224-1232
[Abstract] [Full Text] -
Wagner, E., Lykke-Andersen, J.
(2002). mRNA surveillance: the perfect persist. J. Cell Sci.
115: 3033-3038
[Abstract] [Full Text] -
Lucchini, S., Thompson, A., Hinton, J. C. D.
(2001). Microarrays for microbiologists. Microbiology
147: 1403-1414
[Full Text] -
He, F., Jacobson, A.
(2001). Upf1p, Nmd2p, and Upf3p Regulate the Decapping and Exonucleolytic Degradation of both Nonsense-Containing mRNAs and Wild-Type mRNAs. Mol. Cell. Biol.
21: 1515-1530
[Abstract] [Full Text] -
Hendrick, J. L., Wilson, P. G., Edelman, I. I., Sandbaken, M. G., Ursic, D., Culbertson, M. R.
(2001). Yeast Frameshift Suppressor Mutations in the Genes Coding for Transcription Factor Mbf1p and Ribosomal Protein S3: Evidence for Autoregulation of S3 Synthesis. Genetics
157: 1141-1158
[Abstract] [Full Text] -
Medghalchi, S. M., Frischmeyer, P. A., Mendell, J. T., Kelly, A. G., Lawler, A. M., Dietz, H. C.
(2001). Rent1, a trans-effector of nonsense-mediated mRNA decay, is essential for mammalian embryonic viability. Hum Mol Genet
10: 99-105
[Abstract] [Full Text] -
GONZALEZ, C.I., WANG, W., PELTZ, S.W.
(2001). Nonsense-mediated mRNA Decay in Saccharomyces cerevisiae: A Quality Control Mechanism That Degrades Transcripts Harboring Premature Termination Codons. Cold Spring Harb Symp Quant Biol
66: 321-328
[Abstract] -
Mendell, J. T., Medghalchi, S. M., Lake, R. G., Noensie, E. N., Dietz, H. C.
(2000). Novel Upf2p Orthologues Suggest a Functional Link between Translation Initiation and Nonsense Surveillance Complexes. Mol. Cell. Biol.
20: 8944-8957
[Abstract] [Full Text] -
Mitrovich, Q. M., Anderson, P.
(2000). Unproductively spliced ribosomal protein mRNAs are natural targets of mRNA surveillance in C. elegans. Genes Dev.
14: 2173-2184
[Abstract] [Full Text] -
Lyons, T. J., Gasch, A. P., Gaither, L. A., Botstein, D., Brown, P. O., Eide, D. J.
(2000). Genome-wide characterization of the Zap1p zinc-responsive regulon in yeast. Proc. Natl. Acad. Sci. USA
97: 7957-7962
[Abstract] [Full Text] -
Denning, G., Jamieson, L., Maquat, L. E., Thompson, E. A., Fields, A. P.
(2001). Cloning of a Novel Phosphatidylinositol Kinase-related Kinase. CHARACTERIZATION OF THE HUMAN SMG-1 RNA SURVEILLANCE PROTEIN. J. Biol. Chem.
276: 22709-22714
[Abstract] [Full Text]
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Copyright © 2009 by the American Society for Microbiology. For an alternate route to Journals.ASM.org, visit: http://intl-journals.asm.org | More Info»