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Next-Gen Data Analysis

Next-Gen Data Analysis
Next-Gen Data Analysis

Next-Gen Genomics has arrived and it has changed the way the research community is looking at diseases, genetic makeup and the genome. Ocimum Biosolutions now offers Next-Gen Data Analysis on all popular Next-Gen Sequencing platforms such as Roche 454, Illumina Solexa, ABI SOLiD™ and also Sanger sequencing.

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In the past four years, high throughput DNA sequencing platforms have become widely available, leading to nose-diving in the cost of DNA sequencing. The speed and accuracy of the platforms has led to wide acceptance and empowerment among individual investigators. In fact the progress in parallel fields such as data storage and computational skills have supported the growth in next generation sequencing technology.

Next-generation DNA sequencing has changed the way genomic research is done today, by enabling comprehensive analysis of genomes, transcriptomes and epigenome without significant effort. Genetic variation, protein-DNA interaction, noncoding RNA expression profiling etc. can be assessed by Next-generation sequencing. The next gen sequencing or short read sequencing applications could range from identifying etiology and new variations that lead to increased risk of several chronic disorders and diseases, enhanced characterization of livestock genome sequence, identification of virulence markers that can cause diseases in crops and inference of population structure in microbial ecology studies. Major Next-Gen Sequencing platforms today are Roche 454, Illumina Genome Analyzer and ABI SOLiD™.

 

PlatformsRoche (454) GS-FLXIllumina Genome Analyzer II system ABI SOLiD
Starting DNA (μg) 3 – 5 0.1 – 1 0.1 – 20
Amplification Emulsion PCR Bridge PCR Emulsion PCR
Sequencing method Pyrosequencing Sequencing by synthesis Sequencing by ligation
Read length (bases) 250 32-40 35
Throughput capability (Gb per run) 0.1 1.3 4
Reagent cost per run (list prices) 8500 3000 3400
Run time 7.5 h 3 d 7 d
 
Ref: Applications and Case Studies of the Next-Generation Sequencing Technologies in Food, Nutrition and Agriculture. George E. Liu*. Recent Patents on Food, Nutrition & Agriculture, 2009, 1, 75-79

 

Some techniques in Next Generation Genomics that have transformed Genomics research are as follows:

The need for identifying causative mutations, low frequency SNP’s and genome variation within populations is the fundamental objective of targeted and whole genome resequencing. This requires analysis of millions of sequences and that the read length is sufficiently longer to be mapped onto the genome accurately. In addition the mapping process itself must be accurate and quick. The next generation sequencing platforms have a clear edge over the electrophoresis based sequencing in such cases. These systems generate gigabytes of data in a single run providing full genome coverage.

De novo sequencing allows generation of primary genetic sequence of an organism. With longer read lengths and faster data analysis, de novo sequencing is much cheaper and quicker compared to Sanger sequencing.

Small RNA can serve as important biomarkers for diagnostic purposes. Digital gene expression using next generation genomic technologies can help in discovery and analysis of RNA without the need for previous sequence information. These systems are highly accurate and suited for analyzing low RNA expression levels.

ChIP-Seq data sets analysis and annotation for identification of protein-DNA interactions of an entire genome.

Metagenomics annotations and classification requires high throughput or short read sequencing technologies in cases where DNA is purified from an environmental sample and sequenced. The sequences could be from several different species that need to be assembled.

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  • Support for all popular Next-Gen Sequencing platforms such as Roche 454, Illumina Solexa, ABI SOLiD™ and also Sanger sequencing
  • Assembly of Next-Gen sequencing data with Reference sequence mapping
  • Genome variation analysis by accurate assembly of sequences with deep coverage
  • miRNA functional annotation and target prediction
  • Metagenomics annotations and classification
  • New algorithm development, statistical assessment, data analysis & interpretation
  • Customization of proprietary tools to support Next Gen studies and talk to Next Gen instruments