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Methods and systems for identification of causal genomic variants

A variant, user-friendly technology for applications in genomics, biochemical devices and methods, combinatorial chemistry, etc. to address issues affecting phenotypes

Inactive Publication Date: 2014-10-08
QIAGEN REDWOOD CITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Whole-genome sequencing provides information about the 6 billion base pairs in the human genome, however, analysis of this massive amount of information has proven challenging
For example, there is a large amount of variation between genomes, but only some variants actually affect the phenotype

Method used

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  • Methods and systems for identification of causal genomic variants
  • Methods and systems for identification of causal genomic variants
  • Methods and systems for identification of causal genomic variants

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0392] Example 1: Analysis of Comparative Whole Genome Sequencing Results by Using the Original Knowledge Base Results, identifying the role of IL11RA in craniosynostosis

[0393] Identify variants. The complete human genome sequences of four subjects were loaded into the system: two genomes from children with the inherited form of craniosynostosis, and two genomes from their parents who were not affected by the disease. The genome of affected child 1 included 3,714,700 variants, the genome of affected child 2 included 3,607,874 variants, the genome of the unaffected father included 3,677,130 variants, and the genome of the uninfected mother included 3,779,223 Variants. In the combination of the four genomes, a total of 5,394,638 variants were found.

[0394] Apply the common variants filter. Subtracting the variants observed in one or more subjects in the entire Genomics 69 Genomes database or in 1000 Genomes Project subjects not observed to have the disease, brought t...

Embodiment 2

[0402] Example 2: Identification of prospective driver variants for glioblastoma

[0403] The entire or partial human genome sequence of a glioblastoma patient's tumor and another similar genome sequence from the patient's healthy tissue are loaded into the system.

[0404] Subtracting the variants observed in one or more subjects in the Entire Genomics 69 Genomes database or in one or more subjects in the 1000 Genomes Project not observed to have the disease, reduced the total number of variants to 933,866 ( Figure 14 ). These eliminated DNA variants tend to be common in populations and, therefore, are considered unlikely to cause rare genetic diseases.

[0405] The knowledge base was used to identify and subtract variants that were not previously observed to disrupt biological function or were not predicted to do so, reducing the number of remaining variants to 10,527. Excluded variants met one or more of the following criteria:

[0406] ●Not directly related to resul...

Embodiment 3

[0417] Example 3: Identification of DNA variants for the development of RNA cocktails for personalized cancer therapy

[0418] Figure 15 Example uses a cascade of filters to identify variants for use in cancer therapeutic RNA cocktails. The entire human genome of the patient's tumor and the patient's normal tissue were loaded into the system providing ~25,000 variants between the two datasets.

[0419] The number of variants was reduced to ~2,000 by retaining variants that were unique to the tumor and not present in normal tissue and removing the rest.

[0420] Nonsynonymous variants are candidates for protein-coding differences that a patient's immune system would potentially use to recognize tumor cells as distinct from normal cells, and thus "foreign". Keeping these non-synonymous variants and removing the rest reduced the number of variants to ~700.

[0421] Tumor-specific antigens recognized by the patient's immune system provide potential candidates for the immune ...

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PUM

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Abstract

Methods and systems for filtering variants in data sets comprising genomic information are provided herein.

Description

[0001] Cross References to Related Applications [0002] This application claims U.S. Provisional Patent Application No. 61 / 556,599, filed November 7, 2011, entitled "Methods and Systems for Identifying Causal Genomic Variants," and filed November 7, 2011, The benefit and priority of US Provisional Patent Application No. 61 / 556,758, entitled "Methods and Systems for Identifying Causal Genomic Variants," which is incorporated by reference in its entirety for all purposes. Background technique [0003] Whole-genome sequencing can provide information about the 6 billion base pairs in the human genome, however, analysis of this massive amount of information has proven challenging. For example, there is a large amount of variation between genomes, but only some variants actually affect the phenotype. Among phenotype-affecting variants, only a subset of these are associated with a particular phenotype, eg a disease. Currently, clinicians or researchers obtaining whole-genome seque...

Claims

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Application Information

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IPC IPC(8): G06F19/22G06F19/28C40B60/04G16B20/00G16B50/10C12Q1/68G16B20/10G16B20/20G16B20/30G16B30/00G16B40/00G16B45/00G16B50/00
CPCG06F19/18G06F19/28G06F19/22G16B20/00G16B30/00G16B50/00G16B20/30G16B50/10G16B20/20G16B20/10
Inventor 小道格拉斯·E·巴斯特丹尼尔·R·理查森
Owner QIAGEN REDWOOD CITY
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