Compositions and methods for accurately identifying mutations
US-2024409996-A1 · Dec 12, 2024 · US
US9909176B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9909176-B2 |
| Application number | US-201514841981-A |
| Country | US |
| Kind code | B2 |
| Filing date | Sep 1, 2015 |
| Priority date | Sep 8, 2014 |
| Publication date | Mar 6, 2018 |
| Grant date | Mar 6, 2018 |
A practical reading order for non-experts. Skip the full description unless you need deep technical detail.
What the patent document calls the invention.
A short plain-language summary of the technical disclosure.
Who owns or filed the patent and who is credited as inventor.
Filing, priority, publication, and grant dates set the timeline.
The legal scope of protection — read this for what is actually claimed.
Technology tags used to group this patent with similar filings.
Prior art links and similar publications in this corpus.
Official abstract text for this publication.
A method for limited input whole genome sequencing of RNA viruses includes isolating a viral RNA sample, converting the viral RNA sample to a double-stranded viral cDNA sample, constructing a double-stranded viral cDNA amplicon library from the double-stranded viral cDNA sample, and sequencing the double-stranded viral cDNA amplicon library to obtain a double-stranded viral cDNA sample sequencing read.
Opening claim text (preview).
That which is claimed: 1. A method for limited input whole genome sequencing of orthomyxoviruses, noroviruses, flaviviruses, or ebola viruses, the method comprising: isolating a orthomyxovirus, norovirus, flavivirus, or ebola virus viral RNA sample; converting the viral RNA sample to a double-stranded viral cDNA sample, wherein the converting includes: priming first strand cDNA synthesis using an oligonucleotide primer specific for a highly conserved region of a viral genome, wherein the highly conserved region is common to all subtypes of the viral genome as a means of replication, synthesizing a second cDNA strand with RNase H, DNA ligase, and DNA polymerase I to form the double-stranded viral cDNA sample, and purifying the double-stranded viral cDNA sample; constructing a double-stranded viral cDNA amplicon library from the double-stranded viral cDNA sample; and sequencing the double-stranded viral cDNA amplicon library to obtain a double-stranded viral cDNA sample sequencing read. 2. The method according to claim 1 , wherein isolating the viral RNA sample comprises: extracting RNA from a supernatant to form an RNA extract sample; and depleting DNA from the RNA extract sample. 3. The method according to claim 2 , wherein extracting RNA from the supernatant comprises magnetic bead-based nucleic acid isolation. 4. The method according to claim 2 , wherein the supernatant comprises about 10 3 RNA viruses. 5. The method according to claim 2 , wherein the supernatant comprises an in vivo supernatant. 6. The method according to claim 1 , wherein constructing the double-stranded viral cDNA amplicon library comprises: performing tagmentation reactions on the double-stranded viral cDNA sample to obtain the double-stranded viral cDNA amplicon library; purifying the double-stranded viral cDNA amplicon library; quantifying the double-stranded viral cDNA amplicon library; and pooling multiplexed double-stranded viral cDNA amplicon libraries. 7. The method according to claim 6 , wherein one set of primers is effective in performing tagmentation reactions across different strains within a viral family. 8. The method according to claim 1 , wherein sequencing the double-stranded viral cDNA amplicon library comprises: denaturing the double-stranded viral cDNA amplicon library; loading the double-stranded viral cDNA amplicon library onto a sequencer; and running the sequencer to obtain the double-stranded viral cDNA sample sequencing read. 9. The method according to claim 1 , wherein sequencing the double-stranded viral cDNA amplicon library comprises sequencing from about 0.1 pg to about 10 pg converted viral genomes. 10. The method according to claim 1 , further comprising analyzing the double-stranded viral cDNA sample sequencing read with an ultrafast read classifier. 11. The method according to claim 10 , wherein analyzing the double-stranded viral cDNA sample sequencing read with an ultrafast read classifier further comprises: querying at least one database; and identifying the double-stranded viral cDNA sample sequencing read as belonging to an RNA viral species. 12. The method according to claim 11 , wherein the at least one database comprises at least one of a full metagenomics implementation, a pan-virus implementation, a virus-specific implementation, or any combination thereof. 13. The method according to claim 10 , wherein the ultrafast read classifier analyzes from about 3 million reads to about 4 million double-stranded viral cDNA sample sequencing reads in from about 1 minute to about 5 minutes and the ultrafast read classifier has a sequence alignment with existing reference genomes of from about 90% to about 100%. 14. The method according to claim 10 , wherein the ultrafast read classifier identifies nearest neighbor RNA viruses in from about 1 minute to about 15 minutes. 15. The method according to claim 1 , wherein the RNA viruses comprise non-segmented genomes. 16. The method according to claim 1 , wherein the RNA viruses comprise negative-sense single-stranded RNA viruses. 17. The method according to claim 1 , wherein the method comprises a completion time of from about 5 hours to about 15 hours and a hands-on time of from about 0.5 hours to about 5 hours. 18. The method according to claim 1 , wherein the supernatant comprises an in vitro supernatant. 19. The method according to claim 1 , wherein the RNA viruses comprise segmented genomes. 20. The method according to claim 1 , wherein the RNA viruses comprise double-stranded RNA viruses.
involving nucleic acid arrays, e.g. sequencing by hybridisation · CPC title
involving virus or bacteriophage {(immunoassay for viruses G01N33/56983)} · CPC title
Related publications grouped by family.
Answers are generated from the same data shown on this page.