High throughput screening of populations carrying naturally occurring mutations
Efficient methods are disclosed for the high throughput identification of mutations in genes in members of mutagenized populations. The methods comprise DNA isolation, pooling, amplification, creation of libraries, high throughput sequencing of libraries, preferably by sequencing-by-synthesis technologies, identification of mutations and identification of the member of the population carrying the mutation and identification of the mutation.
1. A method of detecting a genetic variation, comprising:
(a) tagging each of a plurality of nucleic acid molecules using a plurality of tags, each tag comprising a tag sequence, such that a subset of the nucleic acid molecules in the plurality have the same tag sequence, to generate a set of tagged nucleic acid molecules;
(b) subjecting the set of tagged nucleic acid molecules to amplification to generate amplification products;
(c) sequencing the amplification products with a multi-fold redundancy to generate sequence reads; and
(d) aligning the sequence reads to identify the genetic variation.
2. The method of claim 1 , wherein the genetic variation is naturally occurring.
3. The method of claim 2 , wherein the genetic variation is a single nucleotide polymorphism (SNP), a small insertion or a deletion, or a variation in microsatellite repeat number.
4. The method of claim 1 , wherein the nucleic acid molecules are human derived.
5. The method of claim 1 , wherein the nucleic acid molecules are genomic DNA molecules.
6. The method of claim 1 , wherein both ends of each of the plurality of nucleic acid molecules are tagged.
7. The method of claim 1 , wherein the multi-fold redundancy comprises a redundancy of at least 2.
8. The method of claim 1 , wherein the multi-fold redundancy permits distinction between a sequencing error and a genetic variation.
9. The method of claim 1 , wherein the identification of the genetic variation comprises identifying a sequence change multiple times.
10. The method of claim 1 , wherein the identification is performed in silico.
11. The method of claim 1 , further comprising preparing the nucleic acid molecules for sequencing by ligating adaptors to create a library of single stranded DNA.
12. The method of claim 1 , wherein the sequencing is performed using high-throughput sequencing.
13. The method of claim 1 , wherein the sequencing is bi-directional sequencing.
14. The method of claim 1 , wherein the sequencing is sequencing-by-synthesis.
15. The method of claim 1 , wherein the sequencing is performed on a solid support.
16. The method of claim 1 , wherein the sequencing comprises detecting a light signal indicative of a sequencing reaction.
17. The method of claim 1 , wherein aligning comprises comparing the sequence reads to a reference sequence.
18. The method of claim 1 , wherein aligning comprises comparing the sequence reads to a consensus sequence.
19. The method of claim 1 , wherein the genetic variation is identified without the use of an enzyme which recognizes and cuts single nucleotide sequence mismatches and without performing heteroduplex analysis.
20. The method of claim 1 , wherein the nucleic acid molecules are tagged using amplification or ligation.
21. The method of claim 1 , wherein the alignment is performed using a computer program.
22. A method of detecting a genetic variation as compared to a reference sequence, comprising:
(a) tagging each of a plurality of nucleic acid molecules using a plurality of tags, each tag comprising a tag sequence, such that a subset of the nucleic acid molecules in the plurality have the same tag sequence, to generate a set of tagged nucleic acid molecules, each of the tagged nucleic acid molecules comprising a tag at each end;
(b) subjecting the set of tagged nucleic acid molecules to amplification to generate amplification products;
(c) performing high-throughput sequencing-by-synthesis of the amplification products of step (a) to generate a set of sequence reads;
(d) aligning the set of sequence reads using the reference sequence to identify the genetic variation.