Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Biological or biochemical
Reexamination Certificate
1999-11-23
2003-12-09
Brusca, John S. (Department: 1631)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Biological or biochemical
C435S004000, C435S006120, C436S518000, C436S524000, C436S525000, C436S526000, C436S527000, C436S528000, C702S019000, C702S020000
Reexamination Certificate
active
06662113
ABSTRACT:
TECHNICAL FIELD
The present invention relates to a method for efficiently screening an enormous number of test samples. More specifically, it relates to a method for efficiently detecting the correlation between test samples in groups A and B when they have material interactions between them. For example, the method of the present invention is especially useful for genomic structural analysis.
BACKGROUND ART
Research on genomic structural analysis these days can be classified as “genome mapping” and “sequencing.” In genome mapping, the chromosomal DNA structure is reconstructed by mapping the genome using various techniques and by aligning many fragmented genomic DNAs. In sequencing, the nucleotide sequence of genomic DNA is clarified by determining nucleotide sequences of aligned DNA fragments. The present invention is especially useful for genome mapping.
Previously, when test samples in groups A and B materially interacted, detecting their correlation required examining whether or not each test sample successively withdrawn one-by-one from group A corresponded to each test sample in group B in the interaction. Therefore, if group A consists of m samples and Group B consists of n test samples, (m)×(n) screenings were required.
An example of such a conventional screening method is the method for correlating Sequence Tagged Site (STS) markers (group A) with Bacterial Artificial Chromosome (BAC) clones (group B). STS is a concept for systematically marking the human genome (Olson, M. et al., Science 245: 1434-1435, 1989). STSs consist of short nucleotide sequences of about 200 to 300 bp and possess a sequence which cannot be found in other sites of the genome. Accordingly, the same STS contained in multiple clones indicates that these clones share common regions. By performing PCR using primers designed for STS with genomic DNA as the template, the amplified product of a length corresponding to the STS can be confirmed as a single band (S. B. Primrose, “Principles of Genome Analysis” Blackwell Science Ltd., 1995). In the combination of STS markers (group A) and BAC clones (group B), a BAC clone corresponding to an STS marker is used to be detected by a method based on PCR screening or hybridization screening STS markers one-by-one and BAC clones.
Physical mapping using STS has been used in a limited field by many researchers. The region of the causative gene for cystic fibrosis covered by 30 YAC clones in chromosome 7 has been integrated into a single aligned clone of more than 1.5 Mb (Green & Olson, Science 250: 94-98, 1990). Foote et al. succeeded in aligning 196 clones covering more than 98% of the euchromatin region of the human Y chromosome (Foote et al., Science 258: 60-66, 1992). A YAC-STS integrated map, a combination of physical map with genetic map, on the long arm (q) of chromosome 21 has been prepared (Chumakov et al., Nature 359, 380-387, 1991).
These days, a combination of BAC libraries or PAC (P1-derived artificial chromosome) libraries with STS markers enables covering most human genome. However, a method for efficiently detecting numerous correspondences of STSs to such large-scale libraries has not been established.
In these conventional methods, the increasing number of test samples in groups A and B results in a geometrically progressive increase in the number of screenings, requiring enormous amounts of time and labor.
For example, in genome mapping in general, screening of DNA libraries usually requires numerous repetitions of filter hybridizations or a series of PCR assays of prepared for each library(Asakawa et al., Gene 191: 69-79, 1997). Therefore, to align library clones covering the entire human genome, numerous combinations of DNA libraries and probes must be screened.
The utilization of DNA chips for genomic analysis is highly expected to facilitate more speedy screening. Since oligonucleotides of desired nucleotide sequences can be cumulated in high density on DNA chips, the hybridization assay can be carried out for numerous combinations by a single hybridization. In fact, the mapping of 256 varieties of STS markers against yeast cosmid clone using DNA chips has been reported (Sapolsky, R. J. et al., Genomics 33, 445-456, 1996). However, according to the conventional approach to these problems, the correlation must be examined for all probable combinations of DNAs and probes as before, even with DNA chips. The utilization of DNA chips as such thus does not provide a novel principle enabling the efficient detection of correlation for numerous combinations.
DISCLOSURE OF THE INVENTION
The present inventors considered that the utilization of mixed test samples might reduce the work for detecting the interaction between test samples. Naturally, the random mixing of test samples is not useful for the final clarification of correlation based on their interactions. By systematically mixing test samples in group A based on binary notation and identifying the interactions between this mixture and test samples in group B, the present inventors have found that the correlation between the groups can be more efficiently, identified than prior methods accomplishing this invention.
An objective of this invention is to efficiently detect the correlation by the following method, when test samples (Ai) in group A correlate to test samples (Bj) in group B based on material interactions. Namely, the present invention relates to the following method:
The “k” in the phrase “the k-th bit” is the integer at the “k” position in the numbering of a bit starting from the right of the figure. For example, the k-th bit of “110” where k equals 1 is “0”.
[1] a method for determining a combination of test samples out of those constituting groups A and B which correlate physically, chemically or biologically, wherein said method comprises the following steps:
(1) providing m (2
n−1
=<m=<2
n
−1 where m and n are natural numbers;, m>=3, n>=2) test samples Ai (3=<i=<m) in group A and x (x is a natural number) test samples Bj (1=<j=<x) in group B,
(2) assigning a g-bit (n=<g) ID number based on the binary notation to each test sample Ai in group A,
(3) mixing test samples Ai in group A having “1” for the first bit of ID numbers based on binary notation to make mixture C1, and similarly mixing test samples Ai in group A having “1” for the k-th (1=<k=<g) bit of ID numbers to make mixture Ck, thus obtaining g-varieties of mixtures comprising mixtures from C1 through Cg,
(4) detecting the interaction of each of g varieties of mixtures from C1 through Cg with test samples Bj in group B,
(5) determining g-bit binary numbers having “1” or “0” for the k-th bit by assigning “1” when the interaction is detected between each mixture constituting mixtures from C1 through Cg and Bj in group B, and “
0
” when no interaction is detected, and
(6) determining the correlation between test sample Ai in group A and test sample Bj in group B by referring test sample Ai in group A to the corresponding binary number obtained; (5)
[2] the method of [1], wherein the correlation between test samples involves the interaction between test samples constituting group A and group B;
[3] the method of [2], wherein the correlation based on the interaction between test samples is in the ratio of 1:1 or 1:many;
[4] the method of [1], wherein g is n;
[5] the method of [4], wherein each test samples in group A is assigned an individual ID numbers up to 2
n
1 to test samples;
[6] the method of any one of [1] through [5], wherein said method comprises steps for detecting the interaction between mixture Ca obtained by mixing all test samples in group A and test sample Bj in group B;
[7] a method for determining a combination of test samples out of those constituting groups A and B and correlating them physically, chemically or biologically, wherein said method comprise
Asakawa Shuichi
Shimizu Nobuyoshi
Brusca John S.
Fujisawa Pharmaceutical Co. Ltd.
Oblon & Spivak, McClelland, Maier & Neustadt P.C.
Zhou Shubo (Joe)
LandOfFree
Digital correlation of test samples and the screening of... does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Digital correlation of test samples and the screening of..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Digital correlation of test samples and the screening of... will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3133280