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2.
Genome Res ; 30(6): 898-909, 2020 06.
Artigo em Inglês | MEDLINE | ID: mdl-32540955

RESUMO

Long-range sequencing information is required for haplotype phasing, de novo assembly, and structural variation detection. Current long-read sequencing technologies can provide valuable long-range information but at a high cost with low accuracy and high DNA input requirements. We have developed a single-tube Transposase Enzyme Linked Long-read Sequencing (TELL-seq) technology, which enables a low-cost, high-accuracy, and high-throughput short-read second-generation sequencer to generate over 100 kb of long-range sequencing information with as little as 0.1 ng input material. In a PCR tube, millions of clonally barcoded beads are used to uniquely barcode long DNA molecules in an open bulk reaction without dilution and compartmentation. The barcoded linked-reads are used to successfully assemble genomes ranging from microbes to human. These linked-reads also generate megabase-long phased blocks and provide a cost-effective tool for detecting structural variants in a genome, which are important to identify compound heterozygosity in recessive Mendelian diseases and discover genetic drivers and diagnostic biomarkers in cancers.


Assuntos
Biblioteca Gênica , Sequenciamento de Nucleotídeos em Larga Escala , Análise de Sequência de DNA , Biologia Computacional/métodos , Código de Barras de DNA Taxonômico/métodos , Variação Genética , Genoma Humano , Genômica/métodos , Antígenos HLA/genética , Haplótipos , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Sequenciamento de Nucleotídeos em Larga Escala/normas , Humanos , Análise de Sequência de DNA/métodos , Análise de Sequência de DNA/normas , Fluxo de Trabalho
3.
mSystems ; 3(6)2018.
Artigo em Inglês | MEDLINE | ID: mdl-30417111

RESUMO

Next-generation sequencing technologies have enabled many advances across biology, with microbial ecology benefiting primarily through expanded sample sizes. Although the cost of running sequencing instruments has decreased substantially over time, the price of library preparation methods has largely remained unchanged. In this study, we developed a low-cost miniaturized (5-µl volume) high-throughput (384-sample) amplicon library preparation method with the Echo 550 acoustic liquid handler. Our method reduces costs of library preparation to $1.42 per sample, a 58% reduction compared to existing automated methods and a 21-fold reduction from commercial kits, without compromising sequencing success or distorting the microbial community composition analysis. We further validated the optimized method by sampling five body sites from 46 Pacific chub mackerel fish caught across 16 sampling events over seven months from the Scripps Institution of Oceanography pier in La Jolla, CA. Fish microbiome samples were processed with the miniaturized 5-µl reaction volume with 0.2 µl of genomic DNA (gDNA) and the standard 25-µl reaction volume with 1 µl of gDNA. Between the two methods, alpha diversity was highly correlated (R 2 > 0.95), while distances of technical replicates were much lower than within-body-site variation (P < 0.0001), further validating the method. The cost savings of implementing the miniaturized library preparation (going from triplicate 25-µl reactions to triplicate 5-µl reactions) are large enough to cover a MiSeq sequencing run for 768 samples while preserving accurate microbiome measurements. IMPORTANCE Reduced costs of sequencing have tremendously impacted the field of microbial ecology, allowing scientists to design more studies with larger sample sizes that often exceed 10,000 samples. Library preparation costs have not kept pace with sequencing prices, although automated liquid handling robots provide a unique opportunity to bridge this gap while also decreasing human error. Here, we take advantage of an acoustic liquid handling robot to develop a high-throughput miniaturized library preparation method of a highly cited and broadly used 16S rRNA gene amplicon reaction. We evaluate the potential negative effects of reducing the PCR volume along with varying the amount of gDNA going into the reaction. Our optimized method reduces sample-processing costs while continuing to generate a high-quality microbiome readout that is indistinguishable from the original method.

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