Rui Chen

Personal Omics Profiling Reveals Dynamic Molecular and Medical Phenotypes

Personalized medicine is expected to benefit from combining genomic information with regular monitoring of physiological states by multiple high-throughput methods. Here, we present an integrative personal omics profile (iPOP), an analysis that combines genomic, transcriptomic, proteomic, metabolomic, and autoantibody profiles from a single individual over a 14 month period. Our iPOP analysis revealed various medical risks, including type 2 diabetes. It also uncovered extensive, dynamic changes in diverse molecular components and biological pathways across healthy and diseased conditions. Extremely high-coverage genomic and transcriptomic data, which provide the basis of our iPOP, revealed extensive heteroallelic changes during healthy and diseased states and an unexpected RNA editing mechanism. This study demonstrates that longitudinal iPOP can be used to interpret healthy and diseased states by connecting genomic information with additional dynamic omics activity.

Performance comparison of exome DNA sequencing technologies

Whole exome sequencing by high-throughput sequencing of target-enriched genomic DNA (exome-seq) has become common in basic and translational research as a means of interrogating the interpretable part of the human genome at relatively low cost. We present a comparison of three major commercial exome sequencing platforms from Agilent, Illumina and Nimblegen applied to the same human blood sample. Our results suggest that the Nimblegen platform, which is the only one to use high-density overlapping baits, covers fewer genomic regions than the other platforms but requires the least amount of sequencing to sensitively detect small variants. Agilent and Illumina are able to detect a greater total number of variants with additional sequencing. Illumina captures untranslated regions, which are not targeted by the Nimblegen and Agilent platforms. We also compare exome sequencing and whole genome sequencing (WGS) of the same sample, demonstrating that exome sequencing can detect additional small variants missed by WGS.

Patient-Specific Induced Pluripotent Stem Cells as a Model for Familial Dilated Cardiomyopathy

Human induced pluripotent stem cells generated from patients with familial dilated cardiomyopathy model cardiovascular disease in these patients. iPSCs Make the Heart Beat Faster Mutations in genes expressed in the heart can cause dilated cardiomyopathy (DCM), a form of heart disease in which a weakened and enlarged heart is unable to pump sufficient blood for the body’s needs. DCM can lead to progressive heart failure that eventually requires heart transplantation. This disease has been challenging to study because cardiomyocytes from the hearts of DCM patients are difficult to obtain and do not survive long. Mouse models of DCM are established and have provided important clues about the disease mechanisms for DCM. However, the mouse heart is very different in physiology compared to the human heart; for example, the mouse heart rate is 10 times faster than that of human. In a new study, Sun et al. generated induced pluripotent stem cells (iPSCs) from skin cells of patients in a family with inherited DCM. This family carries a deleterious mutation in TNNT2, a gene that is expressed specifically in the heart and regulates cardiomyocyte contraction. Using iPSCs, the authors generated a large number of individual-specific cardiomyocytes carrying the specific TNNT2 mutation and analyzed their functional properties. Compared to cardiomyocytes derived from iPSCs of healthy controls in the same family, cardiomyocytes derived from iPSCs of DCM patients exhibited an increased heterogeneous myofilament organization, susceptibility to stress, compromised ability to regulate calcium flux, and decreased contraction force. These results suggest that the mutation in TNNT2 causes abnormalities in the cardiomyocytes and contributes to the development of DCM disease. Using these DCM iPSC–derived cardiomyocytes, the researchers also showed that several current treatments that clinically benefit DCM disease improved DCM cardiomyocyte function in culture. The current study shows that human iPSC-derived cardiomyocytes could provide an important platform to investigate the specific disease mechanisms of DCM as well as other inherited cardiovascular disorders and for screening new drugs for cardiovascular disease. Characterized by ventricular dilatation, systolic dysfunction, and progressive heart failure, dilated cardiomyopathy (DCM) is the most common form of cardiomyopathy in patients. DCM is the most common diagnosis leading to heart transplantation and places a significant burden on healthcare worldwide. The advent of induced pluripotent stem cells (iPSCs) offers an exceptional opportunity for creating disease-specific cellular models, investigating underlying mechanisms, and optimizing therapy. Here, we generated cardiomyocytes from iPSCs derived from patients in a DCM family carrying a point mutation (R173W) in the gene encoding sarcomeric protein cardiac troponin T. Compared to control healthy individuals in the same family cohort, cardiomyocytes derived from iPSCs from DCM patients exhibited altered regulation of calcium ion (Ca2+), decreased contractility, and abnormal distribution of sarcomeric α-actinin. When stimulated with a β-adrenergic agonist, DCM iPSC–derived cardiomyocytes showed characteristics of cellular stress such as reduced beating rates, compromised contraction, and a greater number of cells with abnormal sarcomeric α-actinin distribution. Treatment with β-adrenergic blockers or overexpression of sarcoplasmic reticulum Ca2+ adenosine triphosphatase (Serca2a) improved the function of iPSC-derived cardiomyocytes from DCM patients. Thus, iPSC-derived cardiomyocytes from DCM patients recapitulate to some extent the morphological and functional phenotypes of DCM and may serve as a useful platform for exploring disease mechanisms and for drug screening.

Performance comparison of whole-genome sequencing platforms

Whole-genome sequencing is becoming commonplace, but the accuracy and completeness of variant calling by the most widely used platforms from Illumina and Complete Genomics have not been reported. Here we sequenced the genome of an individual with both technologies to a high average coverage of ∼76×, and compared their performance with respect to sequence coverage and calling of single-nucleotide variants (SNVs), insertions and deletions (indels). Although 88.1% of the ∼3.7 million unique SNVs were concordant between platforms, there were tens of thousands of platform-specific calls located in genes and other genomic regions. In contrast, 26.5% of indels were concordant between platforms. Target enrichment validated 92.7% of the concordant SNVs, whereas validation by genotyping array revealed a sensitivity of 99.3%. The validation experiments also suggested that >60% of the platform-specific variants were indeed present in the genome. Our results have important implications for understanding the accuracy and completeness of the genome sequencing platforms.

The Chromosome-Centric Human Proteome Project for cataloging proteins encoded in the genome

The Chromosome-Centric Human Proteome Project for cataloging proteins encoded in the genome

Whole-genome haplotyping using long reads and statistical methods

The rapid growth of sequencing technologies has greatly contributed to our understanding of human genetics. Yet, despite this growth, mainstream technologies have not been fully able to resolve the diploid nature of the human genome. Here we describe statistically aided, long-read haplotyping (SLRH), a rapid, accurate method that uses a statistical algorithm to take advantage of the partially phased information contained in long genomic fragments analyzed by short-read sequencing. For a human sample, as little as 30 Gbp of additional sequencing data are needed to phase genotypes identified by 50× coverage whole-genome sequencing. Using SLRH, we phase 99% of single-nucleotide variants in three human genomes into long haplotype blocks 0.2–1 Mbp in length. We apply our method to determine allele-specific methylation patterns in a human genome and identify hundreds of differentially methylated regions that were previously unknown. SLRH should facilitate population-scale haplotyping of human genomes.

Promise of personalized omics to precision medicine.

The rapid development of high‐throughput technologies and computational frameworks enables the examination of biological systems in unprecedented detail. The ability to study biological phenomena at omics levels in turn is expected to lead to significant advances in personalized and precision medicine. Patients can be treated according to their own molecular characteristics. Individual omes as well as the integrated profiles of multiple omes, such as the genome, the epigenome, the transcriptome, the proteome, the metabolome, the antibodyome, and other omics information are expected to be valuable for health monitoring, preventative measures, and precision medicine. Moreover, omics technologies have the potential to transform medicine from traditional symptom‐oriented diagnosis and treatment of diseases toward disease prevention and early diagnostics. We discuss here the advances and challenges in systems biology‐powered personalized medicine at its current stage, as well as a prospective view of future personalized health care at the end of this review. WIREs Syst Biol Med 2013, 5:73–82. doi: 10.1002/wsbm.1198

Detecting and annotating genetic variations using the HugeSeq pipeline

volume 30 number 3 march 2012 nature biotechnology Liege, Belgium. 31The Babraham Institute, Cambridge, UK. 32Genomatix Software GmbH, Munich, Germany. 33Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland. 34Christian-Albrechts-Universitaet Zu Kiel, Kiel, Germany. 35Cellzome AG, Heidelberg, Germany. 36Institut National de la Sante et de la Recherche Medicale, Marseille, France. 37Weizmann Institute of Science, Rehovot, Israel. 38Barcelona Supercomputing Center, Barcelona, Spain. 39Centro Nacional de Investigaciones Oncologicas, Madrid, Spain. 40University Medical Centre Groningen, Groningen, The Netherlands. 41University of Saarland, Saarbruecken, Germany. 42Oxford Nanopore Technologies Ltd., Oxford, UK. e-mail: h.stunnenberg@ncmls.ru.nl

Whole-exome sequencing identifies tetratricopeptide repeat domain 7A (TTC7A) mutations for combined immunodeficiency with intestinal atresias

BACKGROUND Combined immunodeficiency with multiple intestinal atresias (CID-MIA) is a rare hereditary disease characterized by intestinal obstructions and profound immune defects. OBJECTIVE We sought to determine the underlying genetic causes of CID-MIA by analyzing the exomic sequences of 5 patients and their healthy direct relatives from 5 unrelated families. METHODS We performed whole-exome sequencing on 5 patients with CID-MIA and 10 healthy direct family members belonging to 5 unrelated families with CID-MIA. We also performed targeted Sanger sequencing for the candidate gene tetratricopeptide repeat domain 7A (TTC7A) on 3 additional patients with CID-MIA. RESULTS Through analysis and comparison of the exomic sequence of the subjects from these 5 families, we identified biallelic damaging mutations in the TTC7A gene, for a total of 7 distinct mutations. Targeted TTC7A gene sequencing in 3 additional unrelated patients with CID-MIA revealed biallelic deleterious mutations in 2 of them, as well as an aberrant splice product in the third patient. Staining of normal thymus showed that the TTC7A protein is expressed in thymic epithelial cells, as well as in thymocytes. Moreover, severe lymphoid depletion was observed in the thymus and peripheral lymphoid tissues from 2 patients with CID-MIA. CONCLUSIONS We identified deleterious mutations of the TTC7A gene in 8 unrelated patients with CID-MIA and demonstrated that the TTC7A protein is expressed in the thymus. Our results strongly suggest that TTC7A gene defects cause CID-MIA.

Diverse protein kinase interactions identified by protein microarrays reveal novel connections between cellular processes

Protein kinases are key regulators of cellular processes. In spite of considerable effort, a full understanding of the pathways they participate in remains elusive. We globally investigated the proteins that interact with the majority of yeast protein kinases using protein microarrays. Eighty-five kinases were purified and used to probe yeast proteome microarrays. One-thousand-twenty-three interactions were identified, and the vast majority were novel. Coimmunoprecipitation experiments indicate that many of these interactions occurred in vivo. Many novel links of kinases to previously distinct cellular pathways were discovered. For example, the well-studied Kss1 filamentous pathway was found to bind components of diverse cellular pathways, such as those of the stress response pathway and the Ccr4-Not transcriptional/translational regulatory complex; genetic tests revealed that these different components operate in the filamentation pathway in vivo. Overall, our results indicate that kinases operate in a highly interconnected network that coordinates many activities of the proteome. Our results further demonstrate that protein microarrays uncover a diverse set of interactions not observed previously.