Chemistry: molecular biology and microbiology – Measuring or testing process involving enzymes or... – Involving nucleic acid
Reexamination Certificate
2001-05-15
2004-01-13
Horlick, Kenneth R. (Department: 1637)
Chemistry: molecular biology and microbiology
Measuring or testing process involving enzymes or...
Involving nucleic acid
C435S091200, C536S023100, C536S024200, C536S024300
Reexamination Certificate
active
06677121
ABSTRACT:
BACKGROUND OF THE INVENTION
The disclosed invention is generally in the field of nucleic acid characterization and analysis, and specifically in the area of analysis and comparison of gene expression patterns and genomes.
The study of differences in gene-expression patterns is one of the most promising approaches for understanding mechanisms of differentiation and development. In addition, the identification of disease-related target molecules opens new avenues for rational pharmaceutical intervention. Currently, there are two main approaches to the analysis of molecular expression patterns: (1) the generation of mRNA-expression maps and (2) examination of the ‘proteome’, in which the expression profile of proteins is analyzed by techniques such as two-dimensional gel electrophoresis, mass spectrometry [matrix-assisted-desorption-ionization-time-of-flight (MALDI-TOF) or electrospray] and by the ability to sequence sub-picomole amounts of protein. Classical approaches to transcript imaging, such as northern blotting or plaque hybridization, are time-consuming and material-intensive ways to analyze mRNA-expression patterns. For these reasons, other methods for high-throughput screening in industrial and clinical research have been developed.
A breakthrough in the analysis of gene expression was the development of the northern-blot technique in 1977 (Alwine et al.,
Proc. NatL. Acad. Sci. U.S.A.
74:5350-5354 (1977)). With this technique, labeled cDNA or RNA probes are hybridized to RNA blots to study the expression patterns of mRNA transcripts. Alternatively, RNase-protection assays can detect the expression of specific RNAs. These assays allow the expression of mRNA subsets to be determined in a parallel manner. For RNase-protection assays, the sequence of the analyzed mRna has to be known in order to synthesize a labeled cDNA that forms a hybrid with the selected mRNA; such hybrids resist RNA degradation by a single-strand-specific nuclease and can be detected by gel electrophoresis. As a third approach, differential plaque-filter hybridization allows the identification of specific differences in the expression of cloned cDNAs (Maniatis et al
Cell
15:687-701 (1978)). Although all of these techniques are excellent tools for studying differences in gene expression, the limiting factor of these classical methods is that expression patterns can be analyzed only for known genes.
The analysis of gene-expression patterns made a significant advance with the development of subtractive cDNA libraries, which are generated by hybridizing an mRna pool of one origin to an mRNA pool of a different origin. Transcripts that do not find a complementary strand in the hybridization step are then used for the construction of a cDNA library (Hedrick et al.,
Nature
308:149-153 (1984)). A variety of refinements to this method have been developed to identify specific mRNAs (Swaroop et al.,
Nucleic Acids Res.
25:1954 (1991); Diatchenko et at,
Proc. Natl. Acad. Sci. U.S.A
93:6025-6030 (1996)). One of these is the selective amplification of differentially expressed mRNAs via biotin- and restriction-mediated enrichment (SABRE; Lavery et al.,
Proc. Natl. Acad. Sci. U.S.A.
94:6831-6836 (1997)), cDNAs derived from a tester population are hybridized against the cDNAs of a driver (control) population. After a purification step specific for tester-cDNA-containing hybrids, tester—tester homohybrids are specifically amplified using an added linker, thus allowing the isolation of previously unknown genes.
The technique of differential display of eukaryotic mRNA was the first one-tube method to analyze and compare transcribed genes systematically in a bi-directional fashion; subtractive and differential hybridization techniques have only been adapted for the unidirectional identification of differentially expressed genes (Liang and Pardee,
Science
257:967-971 (1992)). Refinements have been proposed to strengthen reproducibility, efficiency, and performance of differential display (Bauer et al.,
Nucleic Acids Res.
11:4272-4280 (1993); Liang and Pardee,
Curr. Opin. Immunol
7:274-280 (1995); Ito and Sakaki,
Methods Mol. Biol.
85:37-44 (1997); Praschar and Weissman,
Proc. Natl. Acad. Sci U.S.A.
93;659-663 (1996)). Although these approaches are more reproducible and precise than traditional PCR-based differential display, they still require the use of gel electrophoresis, and often implies the exclusion of certain DNA fragments from analysis.
Originally developed to identify differences between two complex genomes, representational difference analysis (RDA) was adapted to analyze differential gene expression by taking advantage of both subtractive hybridization and PCR (Lisitsyn et al.,
Science
259:946-951 (1993); Hubank and Schatz,
Nucleic Acids Res.
22:5640-5648 (1994)). In the first step, mRNA derived from two different populations, the tester and the driver (control), is reverse transcribed; the tester cDNA represents the cDNA population in which differential gene expression is expected to occur. Following digestion with a frequently cutting restriction endonuclease, linkers are ligated to both ends of the cDNA. A PCR step then generates the initial representation of the different gene pools. The linkers of the tester and driver cDNA are digested and a new linker is ligated to the ends of the tester cDNA. The tester and driver cDNAs are then mixed in a 1:100 ratio with an excess of driver cDNA in order to promote hybridization between single-stranded cDNAs common in both tester and driver cDNA pools. Following hybridization of the cDNAs, a PCR exponentially amplifies only those homoduplexes generated by the tester cDNA, via the priming sites on both ends of the double-stranded cDNA (O'Neill and Sinclair,
Nucleic Acids Res.
25:2681-2682 (1997); Wada et al.,
Kidney Int.
51:1629-1638 (1997); Edman et al.,
J.
323:113-118 (1997)).
The gene-expression pattern of a cell or organism determines its basic biological characteristics. In order to accelerate the discovery and characterization of mRNA-encoding sequences, the idea emerged to sequence fragments of cDNA randomly, direct from a variety of tissues (Adams et al.,
Science
252:1651-1656 (1991); Adams et al.,
Nature
377:3-16 (1995)). These expressed sequence tags (ESTs) allow the identification of coding regions in genome-derived sequences. Publicly available EST databases allow the comparative analysis of gene expression by computer. Differentially expressed genes can be identified by comparing the databases of expressed sequence tags of a given organ or cell type with sequence information from a different origin (Lee et al.,
Proc. NatL. Acad. Sci. U.S.A.
92:8303-8307 (1995); Vasmatzis et al.,
Proc. Natl. Acad. Sci. U.S.A.
95:300-304 (1998)). A drawback to sequencing of ESTs is the requirement for large-scale sequencing facilities.
Serial analysis of gene expression (SAGE) is a sequence-based approach to the identification of differentially expressed genes through comparative analyses (Velculescu et al.,
Science
270:484-487 (1995)). It allows the simultaneous analysis of sequences that derive from different cell population or tissues. Three steps form the molecular basis for SAGE: (1) generation of a sequence tag (10-14 bp) to identify expressed transcripts; (2) ligation of sequence tags to obtain concatemers that can be cloned and sequenced; and (3) comparison of the sequence data to determine differences in expression of genes that have been identified by the tags. This procedure is performed for every mRNA population to be analyzed. A major drawback of SAGE is the fact that corresponding genes can be identified only for those tags that are deposited in gene banks, thus making the efficiency of SAGE dependent on the extent of available databases. Alternatively, a major sequencing effort is required to complete a SAGE data set capable of providing 95% coverage of any given mRNA population, simply because most of the sequencing work yields repetitive reads on those tags that are present in high frequency in cellular
Feng Li
Guerra Cesar E.
Kaufman Joseph C.
Latimer Darin R.
Lizardi Paul M.
Agilix Corporation
Horlick Kenneth R.
Needle & Rosenberg P.C.
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