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Aravinda Chakravarti

My laboratory focuses on the development and applications of molecular genetic, genomic and computational methods for identification of human disease genes through "genetic dissection". We use a variety of disease models to infer the features of complex disease gene architecture in birth defects (Hirschsprung disease), cardiovascular disorders (hypertension, sudden cardiac death) and mental illness (autism, bipolar disease, schizophrenia).


Common human diseases, be they birth defects, diabetes, cardiovascular disease, infectious disease, psychiatric illness or neurodegenerative disease, are familial and arise from a combination of genetic and environmental factors. The familial nature of most diseases suggests an underlying genetic susceptibility, but environmental, stochastic and epigenetic factors are also critical. Additional genetic hallmarks of complex disorders are that the underlying mutations are neither necessary nor sufficient for the development of disease, and that these mutations are common in the general population. Contemporary genomic methods and perspectives, using the human genomic sequence, comparative sequence from many other vertebrates, a genome-wide map of polymorphic sites (The International HapMap Project) are all critical elements of this genetic dissection. In particular, we are developing a paradigm for the genetics of common mutations.

Principal Investigator

Email: aravinda@jhmi.edu

My current research is aimed towards understanding the genetic biology of sudden cardiac death (SCD) and regulation of electrocardiographic QT interval. Genome-wide association screens performed by us (and others) for genes regulating QT interval duration, an important endo-phenotype for SCD, have identified more than two dozen candidate genes. I am characterizing one of these genes, NOS1AP, for its role in regulating QT interval using in vitro and in vivo models.

Research Associate

Email: ashish@jhmi.edu

Ashish Kapoor

We work and live in an era where sequence based biology is the norm rather than the exception, and sequencing has opened up the possibility of exploring our genomes to depths previously impossible. Since sequence based biology throws up mammoth amounts of data, it is imperative that we decode it and make it biologically and clinically relevant. My current research is aimed at understanding the ‘interactome’ of complex diseases like Hirschsprung disease that result from alterations in multiple genes. To achieve this, I use both the zebrafish and the mouse as model systems to sequentially or combinatorially perturb each individual gene, seeing how perturbations in genetic interactions leads to the disease state.


It is well established that ~98% of our genome does not contain protein coding genes and non-coding DNA harbors many control elements like promoters, enhancers, insulators, and micro RNA binding sites. Recently many disease-causing variants have also been mapped to these non-coding regions and it is becoming increasingly clear that loss of regulatory control is a major cause of many diseases. I am currently exploring some of the changes associated with these regulatory regions in Hirschsprung disease to get a better understanding of the underlying mechanism of action.



Publications:


  1. 1.Kapoor, A, et al. Population variation in total genetic risk of Hirschsprung disease from common RET, SEMA3 and NRG1 susceptibility polymorphisms. Hum Mol Genet. 2015; 24(10): 2997-3003.

  2. 2. Chatterjee, S, et al. In vivo genome-wide analysis of multiple tissues identifies gene regulatory networks, novel functions and downstream regulatory genes for Bapx1 and its co-regulation with Sox9 in the mammalian vertebral column. BMC Genomics. 2014;15(1): 1072.

  3. 3.Kapoor, A, et al. An enhancer polymorphism at the cardiomyocyte intercalated disc protein NOS1AP locus is a major regulator of the QT interval. Am J Hum Genet. 2014;94(6):p 854-69

  4. 4.Chatterjee, S. and T. Lufkin. Fishing for function: zebrafish BAC transgenics for functional genomics. Mol Biosyst, 2011 7(8)p. 2345-51.

  5. 5.Chatterjee, S., G. Bourque, and T. Lufkin, Conserved and non-conserved enhancers direct tissue specific transcription in ancient germ layer specific developmental control genes. BMC Dev Biol, 2011; 11: p. 63.

  6. 6.Chatterjee, S., et al. The role of post-transcriptional RNA processing and plasmid vector sequences on transient transgene expression in zebrafishT. Transgenic Res, 2010. 19(2): p. 299-304.

  7. 7.Chatterjee, S., P. Kraus, and T. Lufkin. A symphony of inner ear developmental control genes. BMC Genet, 2010. 11: p. 68.

Postdoctoral fellow

Email: sumantra@jhmi.edu

Sumantra Chatterjee

Courtney Berrios

Genetic counselors are professionals trained to help people understand and adapt to the implications of genetic contributions to disease. Genetic counselors have traditionally worked with families who had Mendelian genetic diseases with a clearly defined inheritance, but our roles have expanded to include counseling about complex diseases, where a mix of multiple genes and environmental factors may play a role in disease development.  I am excited to work in a laboratory studying complex disease genomics as we expand our understanding of these diseases. I am also particularly interested in the factors that underlie decisions about health behaviors and reproductive options for complex diseases, including the role of genetic information in making these decisions. 


My role in the laboratory includes enrolling individuals in our study of Hirschsprung disease genetics and managing all participant and medical information received.  I serve as a liaison between the laboratory and study participants, and am available to answer questions about our studies and genetics. I also handle regulatory issues for the laboratory, including Institutional Review Board (a body of faculty, staff and community members who review all research protocols for ethical standards and human subjects protections) submissions for all studies in the laboratory.

Genetic Counselor

Email: cberrios@jhmi.edu

My background in medicine has helped me to understand and appreciate the complex role that genes play in health and disease.  This has helped shape my research interests, which range from understanding genes at the level of an individual’s genotype to how these genes impact an individual at the level of the phenotype. Currently, I am studying Sudden Cardiac Death (SCD).  SCD is a complex disease that can be defined as natural death from cardiac causes; it is responsible for half of all deaths due to heart disease and can affect individuals who outwardly appear to be healthy.  Much work has been devoted to understanding the causes of SCD.  In recent years, several candidate genes have been identified that are implicated in this disease. By working closely with Ashish Kapoor, my research focuses on studying the impact of these genes on the heart’s QT interval. 


One of my main responsibilities is maintaining the Chakravarti laboratory’s mouse colony.  We have developed a mouse that conditionally over-expresses one of these candidate genes, NOS1AP.  By performing experiments on these transgenic mice at the level of cells, tissues, and the whole animal, we hope to better understand the role of this gene.  Additionally, I am characterizing other genes at the in vitro level that previously have been shown to be involved in Sudden Cardiac Death.

Dallas Auer

Research Specialist

Email: dallas@jhmi.edu

To investigate the genetic causes of blood pressure (BP) variation and hypertension, I am leading specific large collaborative genome-wide association studies and sequencing studies within the Chakravarti laboratory.  Analyses within the Family Blood Pressure Program (FBPP) have permitted identification of some candidate regions containing genes influencing BP levels, hypertension and its cardiovascular complications in multiple ethnicities.  The FBPP and the Atherosclerosis Risk in Communities (ARIC) study, a prospective-cohort cardiovascular disease study of 15,792 persons, joined forces for BP analysis in 2007 for a large GWAS on blood pressure traits (FEHGAS). This effort was subsequently integrated into the CHARGE consortium (http://web.chargeconsortium.com), a collaboration of 5 large population-based cohorts.  Collectively, CHARGE BP has genome-wide genotyping data on more than 30,000 individuals.  The ICBP (International Consortium for Blood Pressure GWAS), built from CHARGE and 17 European-origin cohorts of Global BPGen, includes a total of ~70,000 participants with genome-wide marker data.  The two consortia have identified 13 loci that are reproducibly associated with BP and HTN and overall genome-wide association meta-analyses are currently conducted.  The CHARGE consortium is currently sequencing DNA from participating cohorts, either by targeted sequencing of GWAS findings or by exomic sequencing.  These results will help us to understand the contribution of rare variants to common disease.

Research Associate

Email: georg@rhone.ch

Georg Ehret

Personal Website

My current project involves the study of human mitochondrial genetics with an emphasis in characterizing heteroplasmy. The term heteroplasmy refers to the state in which, within a single cell, there’s more than one population of mitochondrial DNA (mtDNA), e.g some containing the wild-type base and others containing a mutant base. Due to the role of mtDNA in disease and its utility in population genetics, it has become of great importance to accurately sequence the complete mitochondrial genome with deep coverage to enable accurate base calling and heteroplasmy detection. With the help of next-generation sequencing technologies (NGS), we are developing a novel sequence processing and analysis algorithm for confident determination of whole human mtDNA.

Maria X Sosa

Lab Manager & Sr. Research Specialist

Email: msosa2@jhmi.edu

1 in 68 children are identified as having an autism spectrum disorder, disorders that can have a major impact on quality of life for these children and their families. There have been many large-scale efforts to understand the genetic causes of autism spectrum disorders, but these are impeded by the multitude of underlying genetic causes, several of which converge in one individual to cause disease. Because these variants are diverse and often have only a modest contribution to disease in any one individual, the standard approach to identifying causative genes has been to study very large cohorts of individuals.

We are using a different approach to this problem. Females have lower susceptibility to autism than males; therefore, females who are severely affected with autism are expected to carry genetic variants with greater effects on neurodevelopment than their male counterparts, and the same is true of families with multiple affected children. Genetic variants with greater effects are rarer but easier to identify. Therefore, I am using exome and other targeted resequencing of families containing multiple severely autistic girls to identify genes important to autism pathogenesis and to understand the mutational profile that results in severe autism in females. This approach may help us to better understand the skewed gender ratio in autism and enable us to discover additional genes that contribute to autism using a relatively small cohort. In line with this study, I am working on how to best identify and understand rare variants underlying any given genetic disorder.

Joseph Tilghman

Graduate student

Email:  jtilghm7@jhmi.edu

 Postdoctoral Fellow


Email: dwlee@jhu.edu

Dongwon Lee

Genome wide association studies (GWAS) have identified more than ten thousand single nucleotide polymorphisms (SNPs) significantly associated with a phenotypic trait or a disease (http://www.genome.gov/gwastudies).  It is generally assumed that the causal variants underlying the association lie within regulatory elements since most of the GWAS SNPs (~90%) are located in intergentic or intronic regions.  However, virtually no existing methods can aid us to find these causal regulatory SNPs from the proxy SNPs in linkage disequilibrium (LD).  To directly address this issue, I am currently developing new statistical and computational methods, based on the genome sequence and large-scale data on genomic readouts of cis-regulation, to computationally predict the functional impact of each genetic variant on all regulatory elements.