Snezana Drmanac

Bio: Snezana Drmanac is an academic researcher from Argonne National Laboratory. The author has contributed to research in topics: Sequencing by hybridization & DNA sequencing. The author has an hindex of 17, co-authored 27 publications receiving 2880 citations.

Human Genome Sequencing Using Unchained Base Reads on Self-Assembling DNA Nanoarrays

Abstract: Genome sequencing of large numbers of individuals promises to advance the understanding, treatment, and prevention of human diseases, among other applications. We describe a genome sequencing platform that achieves efficient imaging and low reagent consumption with combinatorial probe anchor ligation chemistry to independently assay each base from patterned nanoarrays of self-assembling DNA nanoballs. We sequenced three human genomes with this platform, generating an average of 45- to 87-fold coverage per genome and identifying 3.2 to 4.5 million sequence variants per genome. Validation of one genome data set demonstrates a sequence accuracy of about 1 false variant per 100 kilobases. The high accuracy, affordable cost of $4400 for sequencing consumables, and scalability of this platform enable complete human genome sequencing for the detection of rare variants in large-scale genetic studies.

DNA sequence determination by hybridization: A strategy for efficient large-scale sequencing

Abstract: The concept of sequencing by hybridization (SBH) makes use of an array of all possible n-nucleotide oligomers (n-mers) to identify n-mers present in an unknown DNA sequence. Computational approaches can then be used to assemble the complete sequence. As a validation of this concept, the sequences of three DNA fragments, 343 base pairs in length, were determined with octamer oligonucleotides. Possible applications of SBH include physical mapping (ordering) of overlapping DNA clones, sequence checking, DNA fingerprinting comparisons of normal and disease-causing genes, and the identification of DNA fragments with particular sequence motifs in complementary DNA and genomic libraries. The SBH techniques may accelerate the mapping and sequencing phases of the human genome project.

Accurate sequencing by hybridization for DNA diagnostics and individual genomics.

Abstract: Medical DNA diagnostics will increasingly rely on an accurate and inexpensive identification of mutations that affect the function of a gene. To validate diagnostic sequencing by hybridization (SBH), a number of p53 samples were analyzed with the complete set of 8192 noncomplementary 7-mer oligonu-cleotides. In four repeated, blind experiments we accurately sequenced 1.1 kb per each of 12 homozygote and heterozygote samples possessing base substitutions, insertions, and deletions. This SBH variant offers a high throughput platform to inexpensively sequence individual gene or pathogen genome samples within the clinical laboratory setting.

Sequencing by hybridization (SBH): advantages, achievements, and opportunities.

Abstract: Efficient DNA sequencing of the genomes of individual species and organisms is a critical task for the advancement of biological sciences, medicine and agriculture. Advances in modern sequencing methods are needed to meet the challenge of sequencing such megabase to gigabase quantities of DNA. Two possible strategies for DNA sequencing exist: direct methods, in which each base position in the DNA chain is determined individually (e.g., gel sequencing or pyrosequencing), and indirect methods, in which the DNA sequence is assembled based on experimental determination of oligonucleotide content of the DNA chain. One promising indirect method is sequencing by hybridization (SBH), in which sets of oligonucleotides are hybridized under conditions that allow detection of complementary sequences in the target nucleic acid. The unprecedented sequence search parallelism of the SBH method has allowed development of high-throughput, low-cost, miniaturized sequencing processes on arrays of DNA samples or probes. Newly developed SBH methods use DNA ligation to combine relatively small sets of short probes to score potentially tens of millions of longer oligonucleotide sequences in a target DNA. Such combinatorial approaches allow analysis of DNA samples of up to several kilobases (several times longer than allowed by current direct methods) for a variety of DNA sequence analysis applications, including de novo sequencing, resequencing, mutation/SNP discovery and genotyping, and expression monitoring. Future advances in biochemistry and implementation of detection methods that allow single-molecule sensitivity may provide the necessary miniaturization, specificity, and multiplexing efficiency to allow routine whole genome analysis in a single solution-based hybridization experiment.

Reliable hybridization of oligonucleotides as short as six nucleotides.

Abstract: Although there are many new applications for hybridizing short, synthetic oligonucleotide probes to DNA, such applications have not included determining unknown sequences of DNA. The lack of clear discrimination in hybridization of oligo probes shorter than 11 nucleotides and the lack of a theoretical understanding of factors influencing hybridization of short oligos have hampered the development of their use. We have found conditions for reliable hybridization of oligonucleotides as short as seven nucleotides to cloned DNA or to oligonucleotides attached to filters. Low-temperature hybridization and washing conditions, in contrast to the high stringency conditions currently used in hybridization experiments, have the potential for allowing the simple use of all oligos of six nucleotides or longer in meaningful hybridizations. We also present the hybridization discrimination theory that provides the conceptual framework for understanding these results.

The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data

Abstract: Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS—the 1000 Genome pilot alone includes nearly five terabases—make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

A framework for variation discovery and genotyping using next-generation DNA sequencing data

Abstract: Recent advances in sequencing technology make it possible to comprehensively catalogue genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (1) initial read mapping; (2) local realignment around indels; (3) base quality score recalibration; (4) SNP discovery and genotyping to find all potential variants; and (5) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We discuss the application of these tools, instantiated in the Genome Analysis Toolkit (GATK), to deep whole-genome, whole-exome capture, and multi-sample low-pass (~4×) 1000 Genomes Project datasets.

An integrated map of genetic variation from 1,092 human genomes

Abstract: By characterizing the geographic and functional spectrum of human genetic variation, the 1000 Genomes Project aims to build a resource to help to understand the genetic contribution to disease. Here we describe the genomes of 1,092 individuals from 14 populations, constructed using a combination of low-coverage whole-genome and exome sequencing. By developing methods to integrate information across several algorithms and diverse data sources, we provide a validated haplotype map of 38 million single nucleotide polymorphisms, 1.4 million short insertions and deletions, and more than 14,000 larger deletions. We show that individuals from different populations carry different profiles of rare and common variants, and that low-frequency variants show substantial geographic differentiation, which is further increased by the action of purifying selection. We show that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways, and that each individual contains hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites. This resource, which captures up to 98% of accessible single nucleotide polymorphisms at a frequency of 1% in related populations, enables analysis of common and low-frequency variants in individuals from diverse, including admixed, populations.

Sequencing technologies-the next generation

Abstract: Demand has never been greater for revolutionary technologies that deliver fast, inexpensive and accurate genome information. This challenge has catalysed the development of next-generation sequencing (NGS) technologies. The inexpensive production of large volumes of sequence data is the primary advantage over conventional methods. Here, I present a technical review of template preparation, sequencing and imaging, genome alignment and assembly approaches, and recent advances in current and near-term commercially available NGS instruments. I also outline the broad range of applications for NGS technologies, in addition to providing guidelines for platform selection to address biological questions of interest.