scholarly journals Rapid whole-genome mutational profiling using next-generation sequencing technologies

2008 ◽  
Vol 18 (10) ◽  
pp. 1638-1642 ◽  
Author(s):  
D. R. Smith ◽  
A. R. Quinlan ◽  
H. E. Peckham ◽  
K. Makowsky ◽  
W. Tao ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Whole Genome ◽  
Next Generation ◽  
Sequencing Technologies ◽  
Mutational Profiling ◽  
Generation Sequencing

scholarly journals Considerations for clinical read alignment and mutational profiling using next-generation sequencing

F1000Research ◽  
2012 ◽  
Vol 1 ◽  
pp. 2 ◽  
Author(s):  
Gavin R Oliver
Keyword(s):  
Next Generation Sequencing ◽  
Basic Research ◽  
Next Generation ◽  
Sequencing Technologies ◽  
Targeted Analysis ◽  
Mutational Profiling ◽  
Reliable Assessment ◽  
Major Application ◽  
Downstream Analysis ◽  
Generation Sequencing

Next-generation sequencing technologies are increasingly being applied in clinical settings, however the data are characterized by a range of platform-specific artifacts making downstream analysis problematic and error- prone. One major application of NGS is in the profiling of clinically relevant mutations whereby sequences are aligned to a reference genome and potential mutations assessed and scored. Accurate sequence alignment is pivotal in reliable assessment of potential mutations however selection of appropriate alignment tools is a non-trivial task complicated by the availability of multiple solutions each with its own performance characteristics. Using targeted analysis of BRCA1 as an example, we have simulated and mutated a test dataset based on Illumina sequencing technology. Our findings reveal key differences in the abilities of a range of common commercial and open source alignment tools to facilitate accurate downstream detection of a range of mutations. These observations will be of importance to anyone using NGS to profile mutations in clinical or basic research.

Next generation sequencing for whole genome analysis and surveillance of influenza A viruses

2016 ◽  
Vol 79 ◽  
pp. 44-50 ◽  
Author(s):  
Jana McGinnis ◽  
Jennifer Laplante ◽  
Matthew Shudt ◽  
Kirsten St. George
Keyword(s):  
Next Generation Sequencing ◽  
Genome Analysis ◽  
Influenza A ◽  
Whole Genome ◽  
Next Generation ◽  
Influenza A Viruses ◽  
Whole Genome Analysis ◽  
Generation Sequencing

The application of next-generation sequencing technologies to drug discovery and development

2011 ◽  
Vol 16 (11-12) ◽  
pp. 512-519 ◽  
Author(s):  
Peter M. Woollard ◽  
Nalini A.L. Mehta ◽  
Jessica J. Vamathevan ◽  
Stephanie Van Horn ◽  
Bhushan K. Bonde ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Drug Discovery ◽  
Next Generation ◽  
Drug Discovery And Development ◽  
Sequencing Technologies ◽  
Generation Sequencing

High throughput crop genome genotyping by a combination of pool next generation sequencing and haplotype-based data processing

2021 ◽  
Author(s):  
Michael Schneider ◽  
Asis Shrestha ◽  
Agim Ballvora ◽  
Jens Leon
Keyword(s):  
Next Generation Sequencing ◽  
Allele Frequency ◽  
Frequency Estimation ◽  
Whole Genome ◽  
Next Generation ◽  
Conservation Genomics ◽  
High Coverage ◽  
Allele Frequency Estimation ◽  
Low Coverage ◽  
Generation Sequencing

Abstract BackgroundThe identification of environmentally specific alleles and the observation of evolutional processes is a goal of conservation genomics. By generational changes of allele frequencies in populations, questions regarding effective population size, gene flow, drift, and selection can be addressed. The observation of such effects often is a trade-off of costs and resolution, when a decent sample of genotypes should be genotyped for many loci. Pool genotyping approaches can derive a high resolution and precision in allele frequency estimation, when high coverage sequencing is utilized. Still, pool high coverage pool sequencing of big genomes comes along with high costs.ResultsHere we present a reliable method to estimate a barley population’s allele frequency at low coverage sequencing. Three hundred genotypes were sampled from a barley backcross population to estimate the entire population’s allele frequency. The allele frequency estimation accuracy and yield were compared for three next generation sequencing methods. To reveal accurate allele frequency estimates on a low coverage sequencing level, a haplotyping approach was performed. Low coverage allele frequency of positional connected single polymorphisms were aggregated to a single haplotype allele frequency, resulting in two to 271 times higher depth and increased precision. We compared different haplotyping tactics, showing that gene and chip marker-based haplotypes perform on par or better than simple contig haplotype windows. The comparison of multiple pool samples and the referencing against an individual sequencing approach revealed whole genome pool resequencing having the highest correlation to individual genotyping (up to 0.97), while transcriptomics and genotyping by sequencing indicated higher error rates and lower correlations.ConclusionUsing the proposed method allows to identify the allele frequency of populations with high accuracy at low cost. This is particularly interesting for conservation genomics in species with big genomes, like barley or wheat. Whole genome low coverage resequencing at 10x coverage can deliver a highly accurate estimation of the allele frequency, when a loci-based haplotyping approach is applied. Using annotated haplotypes allows to capitalize from biological background and statistical robustness.

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