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Gene-expression profiling with reduced numbers of transcript measurements

A technology of genome-wide expression and transcripts, which is applied in the direction of analysis materials, measurement devices, biological tests, etc.

Inactive Publication Date: 2013-06-19
MASSACHUSETTS INST OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the overall success and widespread use of these methods is severely constrained by the high cost and low throughput of existing transcriptome analysis techniques

Method used

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  • Gene-expression profiling with reduced numbers of transcript measurements
  • Gene-expression profiling with reduced numbers of transcript measurements
  • Gene-expression profiling with reduced numbers of transcript measurements

Examples

Experimental program
Comparison scheme
Effect test

Embodiment I

[0177] Example I: Identification of Cluster Centroid Landmark Transcripts and Building a Correlation Matrix

[0178] This example describes a method for identifying cluster centroid landmark transcripts with inferred relationships.

[0179] The 35,867 transcriptome-wide gene expression profiles generated with the Affymetrix U133 family of oligonucleotide microarrays were downloaded as .cel files from NCBI’s Gene Expression Omnibus (GEO) repository. For each probe set, the .cel files were preprocessed using MAS5 (Affymetrix) to generate mean difference values ​​(ie expression levels). The expression level of each expression profile was then increased or decreased relative to the expression levels of 350 previously determined invariant probes whose expression levels collectively spanned the range of expression levels observed. The smallest common feature space in the dataset was determined to be 22,268 probe sets.

[0180] The quality of each profile was evaluated by referri...

Embodiment II

[0187] Example II: Determining an Appropriate Number of Cluster Centroid Landmark Transcripts

[0188] This example describes a method for selecting the number of cluster centroid landmark transcripts required to build a useful transcriptome-wide gene expression profile. The method uses a large collection of transcriptome-wide gene expression profiles generated from Affymetrix oligonucleotide microarrays from cultured human cells treated with small molecule disruptors, provided in the public connectivity map resource build02 (broadinstitute.org / cmap) . One use of connectivity graphs is to identify similarities between the biological effects of small molecule interferents. This can be done by examining the similarity of gene expression profiles produced by treatment of cells with these disruptors (Lamb et al., "The Connectivity Map: using gene-expression signatures to connect small molecules, genes and disease (Connectivity Map: Using gene-expression signatures to connect s...

Embodiment III

[0192] Example III: Platform-specific selection of cluster centroid landmark transcripts

[0193] This example describes a method for validating the performance of cluster centroid landmark transcripts on selected moderately multiplexed assay platforms. This example relates in particular to the measurement of expression levels of cluster centroid landmark transcripts derived from gene expression profiles established with Affymetrix microarrays using the LMF method of Peck et al., "A method for high-throughput gene expression signature analysis (using method for high-throughput gene expression marker analysis)” Genome Biology 7: R61 (2006). see image 3 .

[0194] Probe pairs were designed for the 1,000 cluster centroid landmark transcripts selected according to Example 1 (above) as described by Peck et al. The expression levels of these transcripts were measured by LMF in a collection of 384 biological samples including unperturbed cell lines, cell lines treated with b...

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Abstract

The present invention provides compositions and methods for making and using a transcriptome-wide gene-expression profiling platform that measures the expression levels of only a select subset of the total number of transcripts. Because gene expression is believed to be highly correlated, direct measurement of a small number (for example, 1,000) of appropriately- selected transcripts allows the expression levels of the remainder to be inferred. The present invention, therefore, has the potential to reduce the cost and increase the throughput of full- transcriptome gene-expression profiling relative to the well-known conventional approaches that require all transcripts to be measured.

Description

[0001] Statement of Government Funding [0002] This invention was made with government support under Grant Number CA133834 awarded by the National Institutes of Health. The US Government has certain rights in this invention. field of invention [0003] The present invention relates to the fields of genome informatics and gene expression profiling. Gene expression profiles provide complex molecular fingerprints about the relevant state of a cell or tissue. Similarity of gene expression profiles between states of an organism (ie, eg, normal and diseased cells and / or tissues) provides molecular taxonomy, classification and diagnosis. Similarity in gene expression profiles due to various external perturbations (i.e., e.g., ablation or forced expression of specific genes and / or small molecule and / or environmental changes) reveals functional similarities between these perturbators, which are important in pathways and Valuable in the elucidation of the mechanism of action. Simil...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): C40B30/00C40B40/06C40B40/08G01N33/48G01N33/50G01N31/00G16B25/10G16B25/20G16B40/30
CPCC12Q1/6809G16B25/00G16B40/00G16B40/30G16B25/20G16B25/10
Inventor D.D.佩克J.兰布T.R.戈卢布A.苏布拉马尼安
Owner MASSACHUSETTS INST OF TECH