Normalized iterative barcoding and sequencing of DNA collections

Abstract

The present invention features, inter alia, compositions and methods for preparing, from a plurality of original, nucleic acid-containing samples, a unified library of linear, non-selectively amplified DNA fragments in which the proportional representation of the fragments from each of the plurality of original samples is normalized and the library is created in a highly parallelized, pool-based fashion. The invention is particularly useful for preparing libraries in which specific information is encoded that allows shorter sequencing reads derived from high-throughput sequencing of the library to be analyzed or assembled into longer scale sequences that are fully traceable to an original, nucleic acid-containing sample within a potentially very large collection of samples. The compositions of the invention encompass the various constructs described herein, which may be variously packaged with one or more additional reagents useful in the present methods and instructions for use.

Description

TECHNICAL FIELD[0001]The present invention relates to the technical field of DNA sequencing. More specifically, the compositions and methods described herein are useful in generating DNA libraries from a plurality of sources and are useful in next generation sequencing.BACKGROUND[0002]In many different research and clinical endeavors, it is desirable to obtain nucleic acid sequence information contained in multiple, distinct samples in parallel.[0003]A ubiquitous implementation of individual-sample or single-plex DNA sequencing, commonly known as “Sanger sequencing”, is carried out using DNA polymerase to incorporate fluorescent dideoxynucleotide terminators into a series of nested extension products in a DNA template-dependent manner, after which, the extension products are separated on a capillary electrophoresis instrument coupled to a fluorometer that outputs signal corresponding to the sequential nucleotide incorporation events. Sanger sequencing is currently considered the gol...

AI Technical Summary

Benefits of technology

The present invention provides a method for preparing a unified library of linear, non-selectively amplified DNA fragments from a plurality of nucleic acid samples. The method involves tagging each sample with a unique identifiable sequence tag and pooling the samples to create a pool of sample-tagged nucleic acid molecules. The pool is then contacted with a third construct comprising a pool tag to generate a pool of sample-tagged, pool-tagged nucleic acid molecules. The pool is then amplified using oligonucleotides and the resulting amplified nucleic acid molecules are analyzed to create a normalized library of DNA fragments. This method allows for the creation of libraries in which the relative abundances of DNA fragments in each library correspond to the original sample.

Problems solved by technology

However, for sequencing many thousands of isolated or traceable samples, the conventional modes of input-indexing for molecular tagging of individual samples (sometimes called simply “barcoding”) are often prohibitively expensive.

Even as the capacity for modern sequencing instrumentation has grown, it remains relatively challenging to use the sequencing capacity of modern instruments to sequence larger numbers of distinct sample simultaneously.

However, the materials and cost associated with conventionally preparing the nucleic acid sample libraries for next generation sequencing from one thousand E. coli samples would exceed that of a single human genomic sample by at least a factor of 100.

However, these approaches add a distinct step that consumes additional time and adds material cost to NGS library preparation.

Also, samples are still processed in parallel rather than collectively, which means this disadvantage grows linearly with the number of samples.

What current methods known to the art therefore generally lack is the ability to create a multiplexed, normalized library suitable for NGS without the need for independent adjustment or parallelized normalization of input samples or resulting libraries.

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