The decade since the Human Genome Project ended has witnessed a remarkable sequencing technology explosion that has permitted a multitude of questions about the genome to be asked and answered, at ...unprecedented speed and resolution. Here I present examples of how the resulting information has both enhanced our knowledge and expanded the impact of the genome on biomedical research. New sequencing technologies have also introduced exciting new areas of biological endeavour. The continuing upward trajectory of sequencing technology development is enabling clinical applications that are aimed at improving medical diagnosis and treatment.
Abstract
Motivation
Although the set of currently known viruses has been steadily expanding, only a tiny fraction of the Earth’s virome has been sequenced so far. Shotgun metagenomic sequencing ...provides an opportunity to reveal novel viruses but faces the computational challenge of identifying viral genomes that are often difficult to detect in metagenomic assemblies.
Results
We describe a MetaviralSPAdes tool for identifying viral genomes in metagenomic assembly graphs that is based on analyzing variations in the coverage depth between viruses and bacterial chromosomes. We benchmarked MetaviralSPAdes on diverse metagenomic datasets, verified our predictions using a set of virus-specific Hidden Markov Models and demonstrated that it improves on the state-of-the-art viral identification pipelines.
Availability and implementation
Metaviral
SPAdes includes ViralAssembly, ViralVerify and ViralComplete modules that are available as standalone packages: https://github.com/ablab/spades/tree/metaviral_publication, https://github.com/ablab/viralVerify/ and https://github.com/ablab/viralComplete/.
Contact
d.antipov@spbu.ru
Supplementary information
Supplementary data are available at Bioinformatics online.
First FDA authorization for next-generation sequencer Collins, Francis S; Hamburg, Margaret A
New England journal of medicine/The New England journal of medicine,
12/2013, Letnik:
369, Številka:
25
Journal Article
The assembly of DNA sequences de novo is fundamental to genomics research. It is the first of many steps toward elucidating and characterizing whole genomes. Downstream applications, including ...analysis of genomic variation between species, between or within individuals critically depend on robustly assembled sequences. In the span of a single decade, the sequence throughput of leading DNA sequencing instruments has increased drastically, and coupled with established and planned large-scale, personalized medicine initiatives to sequence genomes in the thousands and even millions, the development of efficient, scalable and accurate bioinformatics tools for producing high-quality reference draft genomes is timely. With ABySS 1.0, we originally showed that assembling the human genome using short 50-bp sequencing reads was possible by aggregating the half terabyte of compute memory needed over several computers using a standardized message-passing system (MPI). We present here its redesign, which departs from MPI and instead implements algorithms that employ a Bloom filter, a probabilistic data structure, to represent a de Bruijn graph and reduce memory requirements. We benchmarked ABySS 2.0 human genome assembly using a Genome in a Bottle data set of 250-bp Illumina paired-end and 6-kbp mate-pair libraries from a single individual. Our assembly yielded a NG50 (NGA50) scaffold contiguity of 3.5 (3.0) Mbp using <35 GB of RAM. This is a modest memory requirement by today's standards and is often available on a single computer. We also investigate the use of BioNano Genomics and 10x Genomics' Chromium data to further improve the scaffold NG50 (NGA50) of this assembly to 42 (15) Mbp.
The generation and analysis of high-throughput sequencing data are becoming a major component of many studies in molecular biology and medical research. Illumina's Genome Analyzer (GA) and HiSeq ...instruments are currently the most widely used sequencing devices. Here, we comprehensively evaluate properties of genomic HiSeq and GAIIx data derived from two plant genomes and one virus, with read lengths of 95 to 150 bases.
We provide quantifications and evidence for GC bias, error rates, error sequence context, effects of quality filtering, and the reliability of quality values. By combining different filtering criteria we reduced error rates 7-fold at the expense of discarding 12.5% of alignable bases. While overall error rates are low in HiSeq data we observed regions of accumulated wrong base calls. Only 3% of all error positions accounted for 24.7% of all substitution errors. Analyzing the forward and reverse strands separately revealed error rates of up to 18.7%. Insertions and deletions occurred at very low rates on average but increased to up to 2% in homopolymers. A positive correlation between read coverage and GC content was found depending on the GC content range.
The errors and biases we report have implications for the use and the interpretation of Illumina sequencing data. GAIIx and HiSeq data sets show slightly different error profiles. Quality filtering is essential to minimize downstream analysis artifacts. Supporting previous recommendations, the strand-specificity provides a criterion to distinguish sequencing errors from low abundance polymorphisms.
The Ebola virus disease epidemic in West Africa is the largest on record, responsible for over 28,599 cases and more than 11,299 deaths. Genome sequencing in viral outbreaks is desirable to ...characterize the infectious agent and determine its evolutionary rate. Genome sequencing also allows the identification of signatures of host adaptation, identification and monitoring of diagnostic targets, and characterization of responses to vaccines and treatments. The Ebola virus (EBOV) genome substitution rate in the Makona strain has been estimated at between 0.87 × 10(-3) and 1.42 × 10(-3) mutations per site per year. This is equivalent to 16-27 mutations in each genome, meaning that sequences diverge rapidly enough to identify distinct sub-lineages during a prolonged epidemic. Genome sequencing provides a high-resolution view of pathogen evolution and is increasingly sought after for outbreak surveillance. Sequence data may be used to guide control measures, but only if the results are generated quickly enough to inform interventions. Genomic surveillance during the epidemic has been sporadic owing to a lack of local sequencing capacity coupled with practical difficulties transporting samples to remote sequencing facilities. To address this problem, here we devise a genomic surveillance system that utilizes a novel nanopore DNA sequencing instrument. In April 2015 this system was transported in standard airline luggage to Guinea and used for real-time genomic surveillance of the ongoing epidemic. We present sequence data and analysis of 142 EBOV samples collected during the period March to October 2015. We were able to generate results less than 24 h after receiving an Ebola-positive sample, with the sequencing process taking as little as 15-60 min. We show that real-time genomic surveillance is possible in resource-limited settings and can be established rapidly to monitor outbreaks.
Recent scientific discoveries that resulted from the application of next-generation DNA sequencing technologies highlight the striking impact of these massively parallel platforms on genetics. These ...new methods have expanded previously focused readouts from a variety of DNA preparation protocols to a genome-wide scale and have fine-tuned their resolution to single base precision. The sequencing of RNA also has transitioned and now includes full-length cDNA analyses, serial analysis of gene expression (SAGE)-based methods, and noncoding RNA discovery. Next-generation sequencing has also enabled novel applications such as the sequencing of ancient DNA samples, and has substantially widened the scope of metagenomic analysis of environmentally derived samples. Taken together, an astounding potential exists for these technologies to bring enormous change in genetic and biological research and to enhance our fundamental biological knowledge.
We evaluated the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) variant pathogenicity guidelines for internal consistency and compatibility with ...Bayesian statistical reasoning.
The ACMG/AMP criteria were translated into a naive Bayesian classifier, assuming four levels of evidence and exponentially scaled odds of pathogenicity. We tested this framework with a range of prior probabilities and odds of pathogenicity.
We modeled the ACMG/AMP guidelines using biologically plausible assumptions. Most ACMG/AMP combining criteria were compatible. One ACMG/AMP likely pathogenic combination was mathematically equivalent to pathogenic and one ACMG/AMP pathogenic combination was actually likely pathogenic. We modeled combinations that include evidence for and against pathogenicity, showing that our approach scored some combinations as pathogenic or likely pathogenic that ACMG/AMP would designate as variant of uncertain significance (VUS).
By transforming the ACMG/AMP guidelines into a Bayesian framework, we provide a mathematical foundation for what was a qualitative heuristic. Only 2 of the 18 existing ACMG/AMP evidence combinations were mathematically inconsistent with the overall framework. Mixed combinations of pathogenic and benign evidence could yield a likely pathogenic, likely benign, or VUS result. This quantitative framework validates the approach adopted by the ACMG/AMP, provides opportunities to further refine evidence categories and combining rules, and supports efforts to automate components of variant pathogenicity assessments.
Determining the order of nucleic acid residues in biological samples is an integral component of a wide variety of research applications. Over the last fifty years large numbers of researchers have ...applied themselves to the production of techniques and technologies to facilitate this feat, sequencing DNA and RNA molecules. This time-scale has witnessed tremendous changes, moving from sequencing short oligonucleotides to millions of bases, from struggling towards the deduction of the coding sequence of a single gene to rapid and widely available whole genome sequencing. This article traverses those years, iterating through the different generations of sequencing technology, highlighting some of the key discoveries, researchers, and sequences along the way.
•We review the drastic changes to DNA sequencing technology over the last 50 years.•First-generation methods enabled sequencing of clonal DNA populations.•The second-generation massively increased throughput by parallelizing many reactions.•Third-generation methods allow direct sequencing of single DNA molecules.
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