WO2001029268A2 - Method for identifying interacting gene products - Google Patents
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- WO2001029268A2 WO2001029268A2 PCT/US2000/041279 US0041279W WO0129268A2 WO 2001029268 A2 WO2001029268 A2 WO 2001029268A2 US 0041279 W US0041279 W US 0041279W WO 0129268 A2 WO0129268 A2 WO 0129268A2
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- G—PHYSICS
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- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
- G01N33/6803—General methods of protein analysis not limited to specific proteins or families of proteins
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- G16B25/00—ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
- G16B25/10—Gene or protein expression profiling; Expression-ratio estimation or normalisation
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- G16B25/00—ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
Definitions
- One representation of gene and protein interactions is to build a network in which functionally related genes are connected by links. This representation has been used to demonstrate protein-protein interactions in, e.g., metabolic pathways and signal transduction pathways.
- the invention provides a method for identifying interacting proteins.
- the invention is based in part upon the discovery of that correlation in mR A expression levels is significantly higher for transcripts that correspond to interacting proteins than for transcripts that correspond to non-interacting proteins.
- the method can be used to identify gene products that interact directly Alternatively, the method can be used to identify gene products that do not interact directly but nevertheless have a linked or coordinated function For example, the gene products may interact indirectly via an intervening gene product
- Expiession of the first gene and expression of the reference gene is typically compared by measuring mRNA levels, for the first and second proteins
- expression can be detected in Northern blot hybridization analyses or methods which specifically, and, preferably, quantitatively amplify specific nucleic acid sequences
- expiession is detected using reverse-transcription based polymerase chain reaction
- sequence comparisons in test and reference populations can be made by comparing relative amounts of the examined DNA sequences in the test and reference cell populations
- the /// ⁇ tit o protein-protein interaction can be detected in, e g , a yeast two-hybrid system as described in Uetz et al , Nature 403 623-31, 2000 and in published PCT application WO00/60066.
- Yeast two-hybrid systems provide a more direct method of mapping interactions between protein domains
- pairs of protein domains are expressed as fusion proteins embedded in the yeast transcriptional apparatus
- the system is engineered to re-quire an biochemical interaction between the domains for proper function
- Yeast two-hybrid systems have been conventionally used to identify proteins that interact with a single known protein More recently, this technique has been applied with a high-throughput screening (ETS) approach on a genome-wide scale in an attempt to build a comprehensive map of the protein-protein interactions within a cell
- ETS high-throughput screening
- Also provided by the invention is a method for identifying a first gene product and a second gene product that interact in vivo
- the method includes companng the expression of a fust gene encoding a first gene product and a second gene encoding a second gene product, and then determining whether the expression of the first gene correlates with the expression of the second gene A correlation in expression indicates that the first gene product interacts with the second gene product
- the method includes an additional step of determining whether a product of the test gene and a product of the reference gene interact m an in vitro protem- protein interaction system
- the presence of the interacting pair indicates the first polypeptide and second polypeptide interact in vivo
- the in vitro protein-protein interaction can be detected in, e g , a yeast two-hybrid system
- the method can querying a database of in vitro protein-protein interactions
- the gene product is typically a polypeptide
- the gene product is an RN e g a stable RNA associated with ⁇ bosomes, sphceosomes, or other maciomolecular RNA-contaimng complexes
- a method for determining whether two proteins are in the same pathway by establishing links between at least a first and second piotein, and identifying continuous links from the first and second protein, where identifying a continuous link between the first and second protein indicates that the first and second proteins are in the same pathway
- the link is established based on information obtained from an in vitro protein-interaction system
- the link is established based on co-regulation of mRNA transcripts encoding said first protein and second protein
- co-regulation is determined by measuring the levels of transcnpts of the first gene encoding the first protein and a second gene encoding the second protein, calculating a number representing the correlation in expression levels of the first and second genes, and determining whether the number is statistically significant, where a statistically significant number representing the correlation in expression levels of the first and second genes indicates co-regulation
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Abstract
Disclosed are methods for identifying interacting gene products, such as members of protein-protein complexes.
Description
METHOD FOR IDENTIFYING INTERACTING GENE PRODUCTS
FIELD OF THE INVENTION
The present invention relates in general to nucleic acids and polypeptides and more specifically to methods for identifying interacting gene products, including interacting polypeptides.
BACKGROUND OF THE INVENTION
Whole genome sequencing efforts can identify numerous genes. Many gene products interact, e.g., as members of a protein complex and/or as members of a metabolic pathway.
Identifying interacting gene products can be useful in understanding how individual genes and proteins interact to carry out complex biological activities.
One representation of gene and protein interactions is to build a network in which functionally related genes are connected by links. This representation has been used to demonstrate protein-protein interactions in, e.g., metabolic pathways and signal transduction pathways.
SUMMARY OF THE INVENTION
The invention provides a method for identifying interacting proteins. The invention is based in part upon the discovery of that correlation in mR A expression levels is significantly higher for transcripts that correspond to interacting proteins than for transcripts that correspond to non-interacting proteins.
In accordance with the invention, there is provided a method for identifying a member of a protein pathway by comparing the expression of a first test gene and a reference gene, where the reference gene encodes a member of a protein pathway, and determining whether the expression of the first gene correlates with the expression of the reference gene. A correlation in expression indicates that the test gene encodes a product that is a member of the protein pathway.
The invention further provides a method for identifying a first polypeptide and a second polypeptide that interact in vivo by comparing the expression of a first gene encoding a first polypeptide and a second gene encoding a second polypeptide, and determining whether the expression of the first gene correlates with the expression of the second gene. A
con elation in expression indicates that the first polypeptide interacts with the second polypeptide In one embodiment, the method further involves determining whether a product of the test gene and a product of the reference gene interact in an in vitro protem-protem interaction system, where the presence of an interacting pair indicates that the first polypeptide and second polypeptide interact in vivo In still another embodiment, the in vitro protein- piotem interaction is detected in a yeast two-hybrid system In yet another embodiment, the method further involves querying a database of in vitro protein-protem interactions
Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of the invention, suitable methods and materials are described below All publications, patent applications, patents, and other references mentioned herein aie incorpoiated by reference in their entirety In the case of conflict, the present Specification, including definitions, will contiol In addition, the materials, methods, and examples are illustrative only and not intended to be limiting
Othei features and advantages of the invention will be apparent from the following detailed description and claims
BRIEF DESCRIPTION OF THE DRAWINGS
FIG 1 is a graph depicting the probability distribution for the correlation between pairs of open reading frames (ORFs), (1) across all proteins (grey line), and (2) across pairs of piotems thought to have piotein-protein interactions Subsets of interacting pairs of proteins are shown as follows those found from high-throughput screening (triangles), those found from the literature (squares), and those found by both (filled circles)
DETAILED DESCRIPTION OF THE INVENTION
The invention provides methods for determining whether two or more gene products interact in vivo The invention is based in part on the discovery that correlation m mRNA expression levels is significantly higher for transcripts that correspond to interacting proteins than for transcripts that correspond to non-mteractmg proteins In one aspect, the invention features a method for identifying a member of a protein
?
pathway The expression of a first test gene is compared to a reference gene, which encodes a gene product that is known to be a member of the protein pathway Expression of the first test gene is compared to the expression of the reference gene, and a determination is made as to whether the expression of the first gene correlates with the expression of the reference gene A correlation in expression indicates that the test gene encodes a product that is a member of the protein pathway
The method can be used to identify gene products that interact directly Alternatively, the method can be used to identify gene products that do not interact directly but nevertheless have a linked or coordinated function For example, the gene products may interact indirectly via an intervening gene product
The test gene can be any nucleic acid sequence known to encode, or to be suspected of encoding, a protein gene product
Expiession of the first gene and expression of the reference gene is typically compared by measuring mRNA levels, for the first and second proteins For example, expression can be detected in Northern blot hybridization analyses or methods which specifically, and, preferably, quantitatively amplify specific nucleic acid sequences In some embodiments, expiession is detected using reverse-transcription based polymerase chain reaction When alteiations in gene expression are associated with gene amplification or deletion, sequence comparisons in test and reference populations can be made by comparing relative amounts of the examined DNA sequences in the test and reference cell populations
Levels of expression of the first gene and second gene can be compared using any method known the art Examples of such methods include expressed sequence tag sequencing, serial analysis of gene expression, hybridization, and differential display For example, expression can be compared using GENECALLING® methods as described in U S Patent No 5,871,697 and in Shimkets et al , Nat Biotechnol 17 798-803 Preferably, the method used has the potential to measure the expression level of every individual mRNA expressed a cell or tissue, and to generate these essentially complete data sets for a broad sample of biological states
In some embodiments, the expression of the fust gene and the second gene is compared in cells in Icnown biologic states For example, the first gene can be measured in a cell that is the same cell type and/or developmental state as the cell type from which the reference gene is chosen
Preferably, the test gene and reference gene are provided m a data set When the reference gene and reference gene are provided in a data set, compaπng can mclude converting the data set to a matrix The matrix includes an element equal to the natural logarithm of the first test gene and an element equal to the natural logarithm of the reference gene Next, a con elation between the elements is determined by calculating a Pearson correlation between the elements corresponding to the first gene and the reference gene
While the method can be used to compare a single test gene and a single reference gene, in some embodiments the method is used to compare multiple test genes to one or more leference genes For example, the method can include comparing the expression of at least 5, 25, 50, 100, 250, 500 or more test genes to a reference gene Alternatively or in addition, the method can include comparing the expression of the one or more test genes (e g , 5, 25, 50, 100, 250, 500 or more test genes) to at least 5, 25, 50, 100, 250, 500 or more reference genes, wheiein each lefeience gene encodes a product that is a known or suspected member of a protein pathway If desπ ed, the method can further include determining whether a product of the test gene and a product of the reference gene interact in an in vitro protein-protein interaction system The presence of the interacting pair indicates the test gene encodes a member of the protein pathway This method can include querying a database of in vitro protein-protein interactions to determine if an interacting protein pair comprising a product of the test gene and a product of the reference gene is present
The /// \ tit o protein-protein interaction can be detected in, e g , a yeast two-hybrid system as described in Uetz et al , Nature 403 623-31, 2000 and in published PCT application WO00/60066. Yeast two-hybrid systems provide a more direct method of mapping interactions between protein domains In these methods, pairs of protein domains are expressed as fusion proteins embedded in the yeast transcriptional apparatus The system is engineered to re-quire an biochemical interaction between the domains for proper function Yeast two-hybrid systems have been conventionally used to identify proteins that interact with a single known protein More recently, this technique has been applied with a high-throughput screening (ETS) approach on a genome-wide scale in an attempt to build a comprehensive map of the protein-protein interactions within a cell
Also provided by the invention is a method for identifying a first gene product and a second gene product that interact in vivo The method includes companng the expression of a
fust gene encoding a first gene product and a second gene encoding a second gene product, and then determining whether the expression of the first gene correlates with the expression of the second gene A correlation in expression indicates that the first gene product interacts with the second gene product In some embodiments, the method includes an additional step of determining whether a product of the test gene and a product of the reference gene interact m an in vitro protem- protein interaction system The presence of the interacting pair indicates the first polypeptide and second polypeptide interact in vivo The in vitro protein-protein interaction can be detected in, e g , a yeast two-hybrid system The method can querying a database of in vitro protein-protein interactions
While the gene product is typically a polypeptide, in some embodiments the gene product is an RN e g a stable RNA associated with πbosomes, sphceosomes, or other maciomolecular RNA-contaimng complexes
In accordance with the invention, there is also provided a method for determining whether two proteins are in the same pathway by establishing links between at least a first and second piotein, and identifying continuous links from the first and second protein, where identifying a continuous link between the first and second protein indicates that the first and second proteins are in the same pathway In one embodiment, the link is established based on information obtained from an in vitro protein-interaction system In another embodiment, the link is established based on co-regulation of mRNA transcripts encoding said first protein and second protein In still another embodiment, co-regulation is determined by measuring the levels of transcnpts of the first gene encoding the first protein and a second gene encoding the second protein, calculating a number representing the correlation in expression levels of the first and second genes, and determining whether the number is statistically significant, where a statistically significant number representing the correlation in expression levels of the first and second genes indicates co-regulation
In yet another embodiment of the method, the number is calculated by a method selected from the following group calculating the Pearson correlation coefficient between the raw expression levels of the first and second genes, calculating the Pearson correlation coefficient between log-transforms of expression levels of the first and second genes, calculating rank-order correlation coefficients of the first and second genes, or applying the
absolute value of the correlation coefficient In a further embodiment, the statistical significance is determined by a likelihood test, where the likelihood of the measured correlation relative to the measurement expected in the absence of correlation must be larger than a thieshold value In yet a further embodiment, the statistical significance is determined by a p-value test, where the probability of measuring a correlation at least as large as the observed value must be smaller than a threshold value
The invention further provides a method for clustering proteins m a pathway by establishing a link between at least a first and a second protein, and, optionally, establishing a link between either the first protein or a second protein and a third protein, thereby clustenng pioteins in a pathway The invention will be further illustrated m the following examples, which are intended to limit the invention, except as defined in the claims appended hereto
EXAMPLE 1
The pairwise correlation of yeast genes according to expression level was obtained starting w ith a publicly available data set generated by genome-wide hybndization. The data set w as converted to a matrix with elements \„ equal to the natural loganthm of the relative expression of ORF ι in biological state / A Pearson correlation c(/ between ORFs i andy was calculated as
wheie Σ, is restricted to samples where data exists both for ORF / and ORFy, the number of such samples is nr and is defined as δx„ as xn - n, ' ∑,xπ
In computing statistics for cη, it is noted that not all proteins are represented m each of the 77 data sets that were used In order to assure that expression levels could be correlated reliably , correlations were calculated between only those pairs of ORFs that had at least 50 data sets in common This cutoff corresponds to using 93% of the pairs Raising the cutoff to 60 data sets (80% of the pans) or 70 data sets (67% of the pairs) does not cause any significant changes to the reported results
The compilation included 2355 pairs of interacting proteins The pairs were restncted to include only those for which gene expression correlations were available, as descnbed above, yielding 2246 pairs 711 found by high-throughput screening, 1587 found in the teiature, ith an overlap of 52 interactions found m both the experiments and the literature
The analysis begins with an investigation of the expression correlations between all proteins In FIG 1, the probability distribution for the correlation cη between pairs of ORFs i
≠ i is displayed as a grey line The distribution is fit well by a Gaussian with mean
0 03276±0 00005 and standard deviation 0 212 A simple model that produces a Gaussian distribution for cη is to assume that the expiession le\ els of genes / andy are completely unconelated for i ≠ j The expected value for c t is 0, and its variance when calculated over n t{ effective states is
n««
= (lM∑(δxlM:)/(δ M ) = ttef- (2) r=l
The model suggests that the number of effective states in the expression data is 0.212 2 = 22 3, rather than the 77 states for which expression data was collected
The black line in FIG 1 displays the distribution of correlations for pairs of ORFs thought to have protein-protein interactions The mean of this distribution, 0 1 1 l±O 005, is shifted significantly from the mean for all pairs of ORFs This indicates that proteins that interact are significantly more likely (one-tailed z-test/? < 106) to have positively correlated expression levels than pairs of proteins chosen at random Nevertheless, the magnitude of the shift is quite small Thus, the lack of a significant expression correlation does not indicate that the corresponding proteins do not interact
The distribution of expression correlations are shown m Fig 1 for three subsets of interacting pairs of proteins those found from high-throughput screening (triangles), those found from the literature (squares), and those found by both (filled circles) The means and standard deviations of these populations are listed m Table I Protein interactions identified from the literature yield expression correlations that are somewhat higher than the correlations for protein interactions discovered by high-throughput screening A possible explanation is
that co-expression is routinely used to verify that proteins interact, yielding a systematic bias here for finding an expression correlation.
TABLE I. C orrela itions in expression level between pairs of proteins.
Number of Pairs Mean correlation Standard deviation
All pairs 18,051,881 0.03276±0.00005 0.212
All interacting pairs 2246 0.111±0.005 0.239
From high-throu ghput screening 711 0.071±0.008 0.214
From literature 1587 0.128±0.006 0.247
From both 52 0.09±0.03 0.229
Other embodiments are within the following claims.
Claims
1. A method for identifying a member of a protein pathway, said method comprising: comparing the expression of a first test gene and a reference gene, wherein the reference gene encodes a member of said protein pathway; and determining whether the expression of the first gene correlates with the expression of the reference gene, wherein a correlation in expression indicates that said test gene encodes a product that is a member of said protein pathway.
2. The method of claim 1, wherein said the expression of said first gene and said second gene is compared at a known biologic state.
3. The method of claim 1, wherein said comparing comprises measuring the levels of transcripts of said first gene and said second gene; calculating a number representing the correlation in expression levels of said first and second genes; and detennining whether said number is statistically significant, wherein a statistically significant number representing the correlation in expression levels of said first and second genes indicates correlation of expression.
4. The method of claim 2, wherein said first test gene and reference gene are provided in a data set, and said comparing comprises measuring the levels of transcripts of said first gene and said second gene; calculating a number representing the correlation in expression levels of said first and second genes; and determining whether said number is statistically significant, wherein a statistically significant number representing the correlation in expression levels of said first and second genes indicates correlation of expression.
5. The method of claim 1 , wherein said method further comprises comparing the expression of said first test gene to at least 5 reference genes, wherein each reference gene encodes a product that is a known member of a protein pathway
6 The method of claim 1, wherein said method further comprises comparing the expression of at least five test genes to said reference gene
7 The method of claim 1, wherein said method further comprises comparing the expiession of said at least five test genes to at least 5 reference genes, wherein each reference gene encodes a product that is a known member of a protein pathway
8 The method of claim 7, wherein said method further comprises determining whether a product of the test gene and a product of the reference gene intei ct in an in vitto protein-protein interaction system, wherein the presence of said tei acting pan indicates said test gene encodes a member of said protein pathway
9 The method of claim 8, wherein the in vitro protem-protein interaction is detected in a yeast two-hybrid system
10 The method of claim 1 , wherein said method further comprises querying a database of in vitro protem-protein interactions to determine if an interacting protein pair comprising a product of the test gene and a product of the reference gene is present, wherein the presence of said interacting pair indicates said test gene encodes a member of said protein pathway
1 1 The method of claim 8, wherein said database is constructed using interactions established with a yeast two-hybrid system
12 The method of claim 1 , wherein the product of the first test gene interacts directly with the pioduct of the first reference gene
13 The method of claim 1, wherein expression of the first gene and expression of the reference gene is compared by measuring mRNA levels for the first and second proteins 14 A method for identifying a first polypeptide and a second polypeptide that interact in o, the method comprising comparing the expression of a first gene encoding a first polypeptide and a second gene encoding a second polypeptide, and determining whether the expression of the first gene correlates with the expression of the second gene, wherein a correlation in expression indicates that the first polypeptide interacts with the second polypeptide
15 The method of claim 14, wherein said method further composes determining whether a product of the test gene and a product of the reference gene interact in an in vitro protein-protein interaction system, wherein the presence of said interacting pair indicates the first polypeptide and second polypeptide interact in vivo
16 The method of claim 15, wherein the in vitro protem-protein interaction is detected in a yeast two-hybrid system
17 The method of claim 14, wherein said method further comprises querying a database of in iti o protem-protem interactions
18 A method for determining whether two proteins are in the same pathway, the method comprising establishing links between at least a first and second protein, and identifying continuous links from the first and second protein, wherein identifying a continuous link between the first and second protein indicates the first and second proteins are m the same pathway
19 The method of claim 18, wherein the link is established based on information obtained from an in vitro protem-mteraction system
20 The method of claim 18, wherein the link is established based on co-regulation of mRNA transcripts encoding said first protein and second protein
21 The method of claim 20, wherein co-regulation is determined by measuring the levels of transcnpts of said a first gene encoding said first protein and a second gene encoding said second protein, calculating a number representing the correlation in expression levels of said first and second genes, and determining whether said number is statistically significant, wherein a statistically significant number representing the correlation in expression levels of said first and second genes indicates co-regulation
22 The method of claim 21, wherein said number is calculated by a method selected from the gioup consisting of calculating the Pearson correlation coefficient between the raw expression levels of said first and second gene, calculating the Pearson correlation coefficient between log-transforms of expression levels of said fust gene and second gene, calculating rank-order correlation coefficients of said first gene and said second gene, and applying the absolute value of the correlation coefficient
23 The method of claim 21 , wherein the statistical significance is determined by a likelihood test, wherein the likelihood of the measured correlation relative to the measurement expected m the absence of correlation must be larger than a threshold value
24 The method of claim 22, wherein the statistical significance is determined by a p-value test, wherein the probability of measuring a correlation at least as large as the observed value must be smaller than a threshold value
25 A method for clustering proteins m a pathway, the method comprising establishing a link between at least a first and second protein, and optionally, establishing a link between either said first protein or second protein and a third protein, thereby clustering proteins in said pathway.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7914990B2 (en) | 2005-01-13 | 2011-03-29 | Progenika Biopharma, S.A. | Methods and products for in vitro genotyping |
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| WO1999058720A1 (en) * | 1998-05-12 | 1999-11-18 | Acacia Biosciences, Inc. | Quantitative methods, systems and apparatuses for gene expression analysis |
| WO2000058521A2 (en) * | 1999-03-31 | 2000-10-05 | Rosetta Inpharmatics, Inc. | Methods for the identification of reporter and target molecules using comprehensive gene expression profiles |
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2000
- 2000-10-18 WO PCT/US2000/041279 patent/WO2001029268A2/en active Search and Examination
- 2000-10-18 AU AU29161/01A patent/AU2916101A/en not_active Abandoned
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO1999058720A1 (en) * | 1998-05-12 | 1999-11-18 | Acacia Biosciences, Inc. | Quantitative methods, systems and apparatuses for gene expression analysis |
| WO2000058521A2 (en) * | 1999-03-31 | 2000-10-05 | Rosetta Inpharmatics, Inc. | Methods for the identification of reporter and target molecules using comprehensive gene expression profiles |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7914990B2 (en) | 2005-01-13 | 2011-03-29 | Progenika Biopharma, S.A. | Methods and products for in vitro genotyping |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2001029268A3 (en) | 2002-01-31 |
| AU2916101A (en) | 2001-04-30 |
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