Radoje Drmanac
Argonne National Laboratory
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Featured researches published by Radoje Drmanac.
Science | 2010
Radoje Drmanac; Andrew Sparks; Matthew J. Callow; Aaron L. Halpern; Norman L. Burns; Bahram Ghaffarzadeh Kermani; Paolo Carnevali; Igor Nazarenko; Geoffrey B. Nilsen; George Yeung; Fredrik Dahl; Andres Fernandez; Bryan Staker; Krishna Pant; Jonathan Baccash; Adam P. Borcherding; Anushka Brownley; Ryan Cedeno; Linsu Chen; Dan Chernikoff; Alex Cheung; Razvan Chirita; Benjamin Curson; Jessica Ebert; Coleen R. Hacker; Robert Hartlage; Brian Hauser; Steve Huang; Yuan Jiang; Vitali Karpinchyk
Toward
Science | 2010
Jared C. Roach; Gustavo Glusman; Arian Smit; Chad D. Huff; Robert Hubley; Paul Shannon; Lee Rowen; Krishna Pant; Nathan Goodman; Michael J. Bamshad; Jay Shendure; Radoje Drmanac; Lynn B. Jorde; Leroy Hood; David J. Galas
1000 Genomes The ability to generate human genome sequence data that is complete, accurate, and inexpensive is a necessary prerequisite to perform genome-wide disease association studies. Drmanac et al. (p. 78, published online 5 November) present a technique advancing toward this goal. The method uses Type IIS endonucleases to incorporate short oligonucleotides within a set of randomly sheared circularized DNA. DNA polymerase then generates concatenated copies of the circular oligonucleotides leading to formation of compact but very long oligonucleotides which are then sequenced by ligation. The relatively low cost of this technology, which shows a low error rate, advances sequencing closer to the goal of the
Nature | 2012
Brock A. Peters; Bahram Ghaffarzadeh Kermani; Andrew Sparks; Oleg Alferov; Peter Hong; Andrei Alexeev; Yuan Jiang; Fredrik Dahl; Y. Tom Tang; Juergen Haas; Kimberly Robasky; Alexander Wait Zaranek; Je-Hyuk Lee; Madeleine Ball; Joseph E. Peterson; Helena Perazich; George Yeung; Jia Liu; Linsu Chen; Michael Kennemer; Kaliprasad Pothuraju; Karel Konvicka; Mike Tsoupko-Sitnikov; Krishna Pant; Jessica Ebert; Geoffrey B. Nilsen; Jonathan Baccash; Aaron L. Halpern; George M. Church; Radoje Drmanac
1000 genome. A low-cost sequencing technique advances us closer to the goal of the
Nature Genetics | 2013
Christian P. Schaaf; Manuel L. Gonzalez-Garay; Fan Xia; Lorraine Potocki; Karen W. Gripp; Baili Zhang; Brock A. Peters; Mark A. McElwain; Radoje Drmanac; Arthur L. Beaudet; C. Thomas Caskey; Yaping Yang
1000 human genome. 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
Proceedings of the National Academy of Sciences of the United States of America | 2012
Madeleine Ball; Joseph V. Thakuria; Alexander Wait Zaranek; Tom Clegg; Abraham M. Rosenbaum; Xiaodi Wu; Misha Angrist; Jong Bhak; Jason Bobe; Matthew J. Callow; Carlos Cano; Michael F. Chou; Wendy K. Chung; Shawn M. Douglas; Preston W. Estep; Athurva Gore; Peter J. Hulick; Alberto Labarga; Je-Hyuk Lee; Jeantine E. Lunshof; Byung Chul Kim; Jong-Il Kim; Zhe Li; Michael F. Murray; Geoffrey B. Nilsen; Brock A. Peters; Anugraha M. Raman; Hugh Y. Rienhoff; Kimberly Robasky; Matthew T. Wheeler
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.
Advances in Biochemical Engineering \/ Biotechnology | 2002
Radoje Drmanac; Snezana Drmanac; Gloria Chui; Robert Diaz; Aaron Hou; Hui Jin; Paul Jin; Sunhee Kwon; Scott Lacy; Bill Moeur; Jay Shafto; Don Swanson; Tatjana Ukrainczyk; Chongjun Xu; Deane Little
Runs in the Family The power to detect mutations involved in disease by genome sequencing is enhanced when combined with the ability to discover specific mutations that may have arisen between offspring and parents. Roach et al. (p. 636, published online 10 March) present the sequence of a family with two offspring affected with two genetic disorders: Miller syndrome and primary ciliary dyskinesia. Sequence analysis of the children and their parents not only showed that the intergenerational mutation rate was lower than anticipated but also revealed recombination sites and the occurrence of rare polymorphisms. Genomic sequencing of an entire family reveals the rate of spontaneous mutations in humans and identifies disease genes. We analyzed the whole-genome sequences of a family of four, consisting of two siblings and their parents. Family-based sequencing allowed us to delineate recombination sites precisely, identify 70% of the sequencing errors (resulting in > 99.999% accuracy), and identify very rare single-nucleotide polymorphisms. We also directly estimated a human intergeneration mutation rate of ~1.1 × 10−8 per position per haploid genome. Both offspring in this family have two recessive disorders: Miller syndrome, for which the gene was concurrently identified, and primary ciliary dyskinesia, for which causative genes have been previously identified. Family-based genome analysis enabled us to narrow the candidate genes for both of these Mendelian disorders to only four. Our results demonstrate the value of complete genome sequencing in families.
Journal of Computational Biology | 2012
Paolo Carnevali; Jonathan M. Baccash; Aaron L. Halpern; Igor Nazarenko; Geoffrey B. Nilsen; Krishna Pant; Jessica Ebert; Anushka Brownley; Matt Morenzoni; Vitali Karpinchyk; Bruce Martin; Dennis G. Ballinger; Radoje Drmanac
Recent advances in whole-genome sequencing have brought the vision of personal genomics and genomic medicine closer to reality. However, current methods lack clinical accuracy and the ability to describe the context (haplotypes) in which genome variants co-occur in a cost-effective manner. Here we describe a low-cost DNA sequencing and haplotyping process, long fragment read (LFR) technology, which is similar to sequencing long single DNA molecules without cloning or separation of metaphase chromosomes. In this study, ten LFR libraries were made using only ∼100u2009picograms of human DNA per sample. Up to 97% of the heterozygous single nucleotide variants were assembled into long haplotype contigs. Removal of false positive single nucleotide variants not phased by multiple LFR haplotypes resulted in a final genome error rate of 1 in 10u2009megabases. Cost-effective and accurate genome sequencing and haplotyping from 10–20 human cells, as demonstrated here, will enable comprehensive genetic studies and diverse clinical applications.
Pharmacogenomics | 2014
Clint Mizzi; Brock A. Peters; Christina Mitropoulou; Konstantinos Mitropoulos; Theodora Katsila; Misha R. Agarwal; Ron H.N. van Schaik; Radoje Drmanac; Joseph A. Borg; George P. Patrinos
Prader-Willi syndrome (PWS) is caused by the absence of paternally expressed, maternally silenced genes at 15q11-q13. We report four individuals with truncating mutations on the paternal allele of MAGEL2, a gene within the PWS domain. The first subject was ascertained by whole-genome sequencing analysis for PWS features. Three additional subjects were identified by reviewing the results of exome sequencing of 1,248 cases in a clinical laboratory. All four subjects had autism spectrum disorder (ASD), intellectual disability and a varying degree of clinical and behavioral features of PWS. These findings suggest that MAGEL2 is a new gene causing complex ASD and that MAGEL2 loss of function can contribute to several aspects of the PWS phenotype.
Methods in Enzymology | 1999
Radoje Drmanac; Snezana Drmanac
Rapid advances in DNA sequencing promise to enable new diagnostics and individualized therapies. Achieving personalized medicine, however, will require extensive research on highly reidentifiable, integrated datasets of genomic and health information. To assist with this, participants in the Personal Genome Project choose to forgo privacy via our institutional review board- approved “open consent” process. The contribution of public data and samples facilitates both scientific discovery and standardization of methods. We present our findings after enrollment of more than 1,800 participants, including whole-genome sequencing of 10 pilot participant genomes (the PGP-10). We introduce the Genome-Environment-Trait Evidence (GET-Evidence) system. This tool automatically processes genomes and prioritizes both published and novel variants for interpretation. In the process of reviewing the presumed healthy PGP-10 genomes, we find numerous literature references implying serious disease. Although it is sometimes impossible to rule out a late-onset effect, stringent evidence requirements can address the high rate of incidental findings. To that end we develop a peer production system for recording and organizing variant evaluations according to standard evidence guidelines, creating a public forum for reaching consensus on interpretation of clinically relevant variants. Genome analysis becomes a two-step process: using a prioritized list to record variant evaluations, then automatically sorting reviewed variants using these annotations. Genome data, health and trait information, participant samples, and variant interpretations are all shared in the public domain—we invite others to review our results using our participant samples and contribute to our interpretations. We offer our public resource and methods to further personalized medical research.
Nature Biotechnology | 2015
Hongzhi Cao; Honglong Wu; Ruibang Luo; Shujia Huang; Yuhui Sun; Xin Tong; Yinlong Xie; Binghang Liu; H. Yang; Hancheng Zheng; Jian Li; Bo Li; Yu Wang; Fang Yang; Peng Sun; Siyang Liu; Peng Gao; Haodong Huang; Jing Sun; Dan Chen; Guangzhu He; Weihua Huang; Zheng Huang; Yue Li; Laurent C. A. M. Tellier; Xiao Liu; Qiang Feng; Xun Xu; Xiuqing Zhang; Lars Bolund
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.