| Literature DB >> 21698376 |
Chandra Shekhar Pareek1, Rafal Smoczynski, Andrzej Tretyn.
Abstract
The high-throughput - next generation sequencing (HT-NGS) technologies are currently the hottest topic in the field of human and animals genomics researches, which can produce over 100 times more data compared to the most sophisticated capillary sequencers based on the Sanger method. With the ongoing developments of high throughput sequencing machines and advancement of modern bioinformatics tools at unprecedented pace, the target goal of sequencing individual genomes of living organism at a cost of $1,000 each is seemed to be realistically feasible in the near future. In the relatively short time frame since 2005, the HT-NGS technologies are revolutionizing the human and animal genome researches by analysis of chromatin immunoprecipitation coupled to DNA microarray (ChIP-chip) or sequencing (ChIP-seq), RNA sequencing (RNA-seq), whole genome genotyping, genome wide structural variation, de novo assembling and re-assembling of genome, mutation detection and carrier screening, detection of inherited disorders and complex human diseases, DNA library preparation, paired ends and genomic captures, sequencing of mitochondrial genome and personal genomics. In this review, we addressed the important features of HT-NGS like, first generation DNA sequencers, birth of HT-NGS, second generation HT-NGS platforms, third generation HT-NGS platforms: including single molecule Heliscope™, SMRT™ and RNAP sequencers, Nanopore, Archon Genomics X PRIZE foundation, comparison of second and third HT-NGS platforms, applications, advances and future perspectives of sequencing technologies on human and animal genome research.Entities:
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Year: 2011 PMID: 21698376 PMCID: PMC3189340 DOI: 10.1007/s13353-011-0057-x
Source DB: PubMed Journal: J Appl Genet ISSN: 1234-1983 Impact factor: 3.240
An overviews of impact HT-NGS technology on human genome researches (Only year 2010 and first issues of 2011 literatures were included)
| Applications | Description | References |
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| 1. Whole genome genotyping |
| Lind et al. |
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| Raymond et al. | |
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| Burgess | |
| 2. De Novo assembling and re-assembling of the human genome. |
| Bansal |
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| Dames et al. | |
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| Li et al. | |
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| Nagarajan and Pop | |
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| Shapiro and Hofreiter | |
| Epigenetics |
| Bormann et al. |
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| Fouse et al. | |
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| Bhaijee et al. | |
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| Hackenberg et al. | |
| ChIP-seq |
| Costa et al. |
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| Jiao et al. | |
| Genome wide structural variation detection in human population |
| Durbin et al. |
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| Henn et al. | |
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| Bowne et al. | |
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| Xi et al. | |
| Mutation detection and carrier screening | " | Senapathy et al. |
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| Vermeer et al. | |
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| Amstutz et al. | |
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| Bell et al. | |
| Detection of inherited disorders |
| Kuhlenbäumer et al. |
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| Zoghbi and Warren | |
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| Bashamboo et al. | |
| Complex human diseases |
| Day-Williams and Zeggini |
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| Singleton et al. | |
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| Voelkerding et al. | |
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| Kingsley | |
| Cancer research |
| Ding et al. |
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| Katsios et al. | |
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| Meyerson et al. | |
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| Pfeifer and Hainaut | |
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| Fang et al. | |
| RNA sequencing |
| Buermans et al. |
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| Costa et al. | |
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| Erhard and Zimmer | |
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| Lee et al. | |
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| Morin et al. | |
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| Nagalakshmi | |
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| Marguerat and Bähler | |
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| Ramsingh et al. | |
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| Werner | |
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| Yang et al. | |
| Library preparation, paired ends and genomic captures for NGS platforms |
| Farias-Hesson et al. |
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| Hajirasouliha et al. | |
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| Hestand et al. | |
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| Walsh | |
| Sequencing of mitochondrial genome |
| Jex et al. |
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| McComish et al. | |
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| Soroka and Burzynski | |
| Personal genomics |
| Hong et al. |
Fig. 1Advanced technological features of three leading second generation HT-NGS platforms
Fig. 2Advanced technological features of four leading third generation HT-NGS platforms
Comparison of second and third HT NGS platforms
| Companies | Roche GS FLX | Illumina-Sollexa | Life Technologies | Helicos Biosciences | Pacific Biosciences |
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| Platforms | GS FLX Titanium, GS Junior | HiSeq 2000, Genome Analyzer IIX, Genome Analyzer IIE, iScanSQ | ABI SOLiD, SOLiD 4 | HeliScope | SMRT |
| Template preparation | Clonal-ePCR on bead surface | Clonal bridge enzymatic amplification on glass surface | Clonal-ePCR on bead surface | Single molecule detection | Single molecule detection |
| Sample requirements | 1 μg for shotgun library, 5 μg for paired end | <1 g for single or paired-end libraries | <2 μg for shotgun library, 5–20 μg for paired end | <2 μg, single end only | Not available (NA) |
| Detection method | Light emitted from secondary reactions initiated by release of pyrophosphate | Fluorescent emission from incorporated dye-labelled nucleotides | Fluorescent emission from ligated dye-labelled oligonucleotides | Real time detection of fluorescent dye in polymerase active site during incorporation | Real time detection of fluorescent dye in polymerase active site during incorporation |
| Length of library prep/feature generation (days) | 3–4 | 2 | 2–4.5 | 1 | NA |
| Method of feature generation | Bead-based/emulsion PCR | Isothermal ‘ | Bead-based/emulsion PCR | Single molecule sequencing | Single molecule real time sequencing by synthesis |
| Paired ends/separation | 3 kb(2 × 110 p) | 200 bp (2 × 36 bp) | 3 kb(2 × 25 bp) | 25–55 bp | NA |
| Chemistry | Pyrosequencing | Reversible Dye Terminators | Oligonucleotide Probe Ligation | Reversible Dye Terminators | Phospho-linked Fluorescent Nucleotides |
| Bases/template | ∼400 | ∼75 (35–100) | 35–50 | 35 | 800–1000 |
Templates run | 1,000,000 | 40,000,000 | 85,000,000 | NA | NA |
| Data production/day | 400 MB/run/7.5 hr | 3,000 MB/run/6.5 days | 4,000 MB/run/6 days | 8 days | 0.02 days |
| Maximum samples | 16 regions/plate | 8 channels/flow cell | 16chambers/2 slides | NA | NA |
| Raw accuracy | 99.5% | >98.5% | 99.94% | >99% | NA |
| Sequencing method | Pyrosequencing | Reversible dye terminators | Sequencing by ligation | One base-at-a-time | Sequencing by synthesis |
| Read lengths | 400 bases | 36 bases | 35 bases | Longer than 1000 | Longer than 1000 |
| Sequencing run time | 10 h | 2-5 days | 6 days | 12 | <1 |
| Total Throughput bases/run (Gb) | 0.40–0.60 Gb, 0.035 Gb | 3–6 Gb | 10–20 Gb | 28 GB | 100 Gb per hour |
| Throughput/day (Gb) | ~1 | 1.5 | 1.7–2 | 2.5 | ~1 |
| Estimated system cost | $500,000 | ∼$400,000 | $525,000 | Lower than second NGS | Lower than second NGS |
| Consumable cost per single-end run (paired-end run) | $5000 | $3000 | $4000 | Lower than second NGS | Lower than second NGS |
| Cost per run (total direct) | $8439 | $8950 | $17,447 | Lower than second NGS | Lower than second NGS |
| Cost per Mb | $84.39 | $5.97 | $5.81 | Lower than second NGS | Lower than second NGS |
Fig. 3Changes in instrument capacity over the past decade, and the timing of major sequencing projects (Figure updated from Madris, 2011). On top: increasing scale of data output per run plotted on a logarithmic scale. At middle: timeline representing major milestones in massively parallel sequencing platform introduction and instrument revisions. On bottom: the time lines of several projects, milestones and publications citing different sequencing technologies
Fig. 4Two strategies for generating the first complete human genome sequence: On right, the Human Genome Project (HGP) map-based strategy (Lander et al. 2001) showing the localizing bacterial artificial chromosomes (BACs) containing large fragments of human DNA within the framework of a landmark-based physical map. On left, the Celera’s strategy (Venter et al. 2001) showing the whole genome shotgun sequencing approach
Characteristics of assembled domestic animal genomes
| Assembly and Gene-build features | Cat ( | Chicken ( | Cow ( | Dog ( | Horse ( | Pig ( | Sheep ( | Turkey ( |
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| Sequencing strategy (fold coverage) | Whole-genome shotgun (1.87×) | Whole-genome shotgun/BAC and other clones (6.6×) | Whole-genome shotgun/BAC and other clones (7.1×) | Whole-genome shotgun/BAC and other clones (7.5×) | Whole-genome shotgun/BAC and other clones (6.8×) | Whole-genome shotgun (0.66×) and Minimal tile-path BAC by BAC (6×) | Whole-genome shotgun (3×) | BAC/other large clone shotgun (−) |
| Genome length (Assembly) | 1.64 Gb (CAT) | 1.05 Gb (WASHUC2) | 2.91 Gb (Btau4.0) | 2.38 Gb (CanFam2.0 | 2.47 Gb (EquCab 2) | ~2.1 and 2.26 Gbs (Sscrofa9) | 2.78 Gb (OAR1.0) | 1.08 Gb (UMD2) |
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| Refrences | Pontius et al. | Hillier et al. | Elsik et al. | Lindblad-Toh et al. | Wade et al. | Wernersson et al. |
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| Sequencing organization | Agencourt Bioscience/ Broad Institute | Washington University Genome Sequencing Center | Baylor HGSC: The Bovine Genome Sequencing and Analysis Consortium. 2009 | Broad Institute/MIT Center for Genome Research | Broad Institute/MIT Center for Genome Research | The Sino-Danish pig genome sequencing project and Wellcome Trust Sanger Institute | AgResearch/Baylor HGSC/CSIRO/University of Otago | Virginia Bioinformatics Institute/ USDA Beltsville/ University of Maryland |
| Release year | 2006 | 2004 | 2009 | 2005 | 2009 | 2005 and 2009 | 2008 | 2009 |
| Database version | 60.1i | 60.2p | 60.4i | 60.2p | 60.2 g | 60.9 d | 57 | 57 |
| Base Pairs | 1,642,698,377 | 1,050,947,331 | 3,247,516,410 | 2,384,996,543 | 2,428,773,513 | 2,389,078,169 | 1,201,946,309 | 941,191,869 |
| Golden Path Length | 4,055,847,588 | 1,100,480,441 | 2,918,205,644 | 2,531,673,953 | 2,474,912,402 | 2,262,596,414 | 2,860,496,367 | 1,087,496,503 |
| Known protein-coding genes | 231 | 14,923 | 19,241 | 2,321 | 15,355 | 621 | Not available (NA) | 11,145 |
| Projected protein-coding genes | 13,061 | 1,544 | 1,416 | 13,512 | 2,275 | 11,899 | NA | NA |
| Novel protein-coding genes | 1,756 | 269 | 391 | 3,472 | 2,806 | 4,973 | NA | NA |
| Pseudogenes | 1,284 | 96 | 686 | 1,742 | 4,400 | 520 | NA | NA |
| RNA genes | 2,930 | 1102 | 3,936 | 3,613 | 2,118 | 2,447 | NA | NA |
| Gene exons | 195,263 | 182,492 | 225,837 | 216,305 | 211,815 | 159,909 | NA | NA |
| Gene transcripts | 19,262 | 23,392 | 31,599 | 30,914 | 29,159 | 22,050 | NA | NA |
An overview of impact HT NGS technology on domestic animals genome research
| Domestic animals | Description | References |
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| Cow |
| Van Tassell et al. |
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| Eck et al. | |
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| Liu et al. | |
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| MacHugh et al. | |
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| Zimin et al. | |
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| Drögemüller et al. | |
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| Wright et al. | |
| Water buffalo ( |
| Michelizzi et al |
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| Michelizzi et al. | |
| Aurochs ( |
| Edwards et al. |
| Pig |
| Wiedmann et al. |
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| Amaral et al. | |
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| Ramos et al. | |
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| Isom et al. | |
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| Leifer et al. | |
| Poultry ( |
| Marklund and Carlborg |
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| Dalloul et al. | |
| Horse ( |
| Bright et al. |
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| Coleman et al. | |
| Sheep ( |
| Archibald et al. |
| Giant Panda ( |
| Li et al. |
| General review |
| Green et al. |
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| Turner et al. | |
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| Pérez-Enciso and Ferretti | |
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| Shah et al. |