System and Methods for Massively Parallel Analysis of Nucleic Acids in Single Cells

Inactive Publication Date: 2014-02-27
GIGAGEN
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

[0072]FIG. 31 shows a simplified workflow for high-throughput generation o

Problems solved by technology

These techniques provide useful genetic information at the cell population level, but have serious limitations for understanding biology at the single cell level.
Current biological tools also lack the capacity to assay genetic measurements in many single cells in parallel.
Conventional single cell techniques are slow, tedious, and limited in the quantity of cells that can be analyzed at once.
Applications such as PGD require time-consuming, hand-guided biopsy technology, and the largest studies include hundreds of single cells.
In another example, genetic recombination between loci of interest can be measured in s

Method used

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  • System and Methods for Massively Parallel Analysis of Nucleic Acids in Single Cells
  • System and Methods for Massively Parallel Analysis of Nucleic Acids in Single Cells
  • System and Methods for Massively Parallel Analysis of Nucleic Acids in Single Cells

Examples

Experimental program
Comparison scheme
Effect test

Example

Example 1

Methods of T-cell Analysis

[0184]The immune system responds to disease by inducing cellular responses. Nearly all immunology is involved with detection of clonotype expansion or contraction in response to an antigen and / or functional analysis of the expanded or contracted clonotypes. Described in this example are methods that leverage the information contained in immune response to diagnose and treat disease. Active and / or memory cells are particularly informative because these cells indicate a functional immune response to a disease, and therefore have high information content. Variable DNA regions and RNA transcripts were analyzed in single cells from populations of activated and / or memory immune cells, and then correlated with disease. These profiles were used to develop noninvasive diagnostics, high-value diagnostics that inform treatment regimens, and novel therapeutic agents.

[0185]T cells include T cell receptors (TCR) that recognize antigens and control immune respons...

Example

Example 2

High-Throughput Protocol for TCRβ Repertoire Library Construction

[0190]In one embodiment, a high-throughput protocol was implemented for human or mouse TCRβ repertoire library construction. The libraries were sequenced directly on the GAIIx next-gen sequencing platform (Illumina). For human samples, multiplex PCR was performed using a set of 20 primers to amplify across all 50 V segments and 10 primers to amplify across all 13 J segments. The primers libraries generated libraries that were the reverse complement of the native TCRβ sequence. This enabled sequencing from the J side of the constructs without further manipulation. The primers also had tails with the same sequence as a portion of the Illumina TruSeq library adapter. The 30 primers were pooled in a single 400 μl PCR, which contained genomic DNA from at least 5×105 cells. The reactions were then thermocycled for no more than 25 cycles, depending on the number of input cells. After thermocycling, a PCR column (Qiag...

Example

Example 3

Protocol Optimization Using 48-Plex Pool of TCRβ Plasmid Clones

[0192]The true content of any particular TCRβ repertoire is not known, so an endogenous TCRβ repertoire cannot serve as a gold standard for protocol optimization. A 48-plex pool of mouse TCRβ plasmid clones was designed to act as template for protocol optimization. First, multiplexed amplification was performed of the mouse TCRβ repertoire as described in Example 2. The PCR products were subcloned using the TOPO-TA vector (Life Technologies), transformed post ligation into TOP10 competent cells (Life Technologies), and 48 transformed colonies were picked. Next, the clones were sequenced by Sanger sequencing to identify the TCRβ clonotype sequences. All of the clones were unique, and represented a broad range of possible V-Jβ combinations. The plasmids were then mixed in a single tube, across three orders of magnitude and with six replicates at each concentration.

[0193]The 48-plex mixture was used to optimize the...

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Abstract

Methods and systems are provided for massively parallel genetic analysis of single cells in emulsion droplets or reaction containers. Genetic loci of interest are targeted in a single cell using a set of probes, and a fusion complex is formed by molecular linkage and amplification techniques. Methods are provided for high-throughput, massively parallel analysis of the fusion complex in a single cell in a population of at least 10,000 cells. Also provided are methods for tracing genetic information back to a cell using barcode sequences.

Description

CROSS REFERENCE TO RELATED APPLICATIONS[0001]This application claims the benefit of U.S. Provisional Application No. 61 / 459,600, filed Dec. 16, 2010, which is hereby incorporated in its entirety by reference.BACKGROUND OF THE INVENTION[0002]1. Field of the Invention[0003]The invention relates to the fields of molecular biology and molecular diagnostics, and more specifically to methods for massively parallel genetic analysis of nucleic acids in single cells.[0004]2. Description of the Related Art[0005]Certain quantitative genetic analyses of biological tissues and organisms are best performed at the single cell level. However, single cells only contain picograms of genetic material. Conventional methods, such as polymerase chain reaction (PCR), RNA sequencing (Mortazavi et al., 2008 Nature Methods 5:621-8), chromatin immunoprecipitation sequencing (Johnson et al., 2007 Science 316:1497-502), or whole genome sequencing (Lander et al., 2001 Nature 409:860-921), require more genetic ma...

Claims

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Application Information

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IPC IPC(8): C12Q1/68
CPCC12Q1/6837C12Q1/6846C12Q1/6886C12Q2600/156C12N15/1006C12Q2525/161C12Q2525/307C12Q2563/159C07K16/00C07K2317/622C40B50/06C12Q1/6881C12Q2600/158C12Q1/6874C12Q1/6883C12N15/1065C12N15/1075C12Q1/6888
Inventor JOHNSON, DAVID SCOTTMEYER, EVERETT HURTEAU
Owner GIGAGEN
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