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Faculty

David Knowles

Assistant Professor, Department of Computer Science 

Core Faculty, New York Genome Center

Assistant Professor, Department of Computer Science 

Core Faculty, New York Genome Center

Dr. Tuuli Lappalainen Science Study

The illustration above depicts with an example of four genes, how knowing how variable genes are in the normal population helps to find candidate disease genes in a patient. Above, top: Tuuli Lappalainen, PhD; bottom: Pejman Mohammadi, PhD.

For individuals with rare diseases, getting a diagnosis is often a long and complicated odyssey. Over the past few years, this has been greatly improved by genome sequencing that can pinpoint the mutation that breaks a gene and leads to a severe disease. However, this approach is still unsuccessful in the majority of patients, largely because of our inability to read the genome to identify all mutations that disrupt gene function.

In a new study published on October 10 in Science , researchers from New York Genome Center , Columbia University , and Scripps Research Institute propose a solution to this problem. Building a new computational method for analyzing genomes together with transcriptome data from RNA-sequencing, they can now identify genes where genetic variants disrupt gene expression in patients and improve the diagnosis of rare genetic disease.

The new method introduced in this study, Analysis of Expression Variation or ANEVA, first takes allele-specific expression data from a large reference sample of healthy individuals to understand how much genetic regulatory variation each gene harbors in the normal population. Then, using the ANEVA Dosage Outlier Test, researchers can analyze the transcriptome of any individual – such as a patient – to find a handful of genes where he or she carries a genetic variant with an unusually large effect compared to what healthy individuals have. By applying this test to a cohort of muscle dystrophy and myopathy patients, the researchers demonstrated  the performance of their method and diagnosed additional patients where previous methods of genome and RNA analysis had failed to find the broken genes.

Tuuli Lamport Research Award

Tuuli Lappalainen, PhD, was honored with the Lamport Research faculty award at the 2019 Commencement ceremony. Dr. Lappalainen is pictured here with Columbia University Trustee Andrew Barth (left) and Dean Lee Goldman of Columbia University Irving Medical Center. (Courtesy of CUIMC Communications)

Tuuli Lappalainen , PhD, assistant professor of systems biology at Columbia University and core faculty member at the New York Genome Center (NYGC) , has received the Harold and Golden Lamport Research award, presented on May 22 at the Vagelos College of Physicians and Surgeons Commencement Ceremony. 

The Lamport Research award is an annual prize given to junior faculty members that show promise in basic science or clinical science research. This year it recognizes Dr. Lappalainen’s ongoing research in functional genetic variation in human populations, and her work in elucidating the cellular mechanisms linked to genetic risk for various diseases and traits. Dr. Lappalainen and her lab combine computational analysis of high-throughput sequencing data, human population genetics approaches and experimental work. 

Her group at NYGC and Columbia is highly collaborative and has made important contributions to several international research consortia in human genomics, including the Genotype Tissue Expression (GTEx) Project and the TOPMed Consortium. 

Dr. Lappalainen joined the faculty at Columbia University in 2014 as part of the Department of Systems Biology and NYGC. In 2018, she received the annual Leena Peltonen Prize for Excellence in Human Genetics, which was presented to her in Milan, Italy, at the 52nd European Society of Human Genetics meeting. 

Harmen and Tuuli
Harmen Bussemaker (left) and Tuuli Lappalainen

Harmen Bussemaker, PhD, and Tuuli Lappalainen, PhD, have received an inaugural Roy and Diana Vagelos Precision Medicine Pilot Award for a collaboration that will bridge quantitative genetics and mechanistic biology to obtain a mechanistic understanding of regulatory effects of genetic variants in humans.

Drs. Bussemaker and Lappalainen, both faculty in Columbia’s Department of Systems Biology, represent one of three winning proposals out of a pool of 56 applications. Their project titled, “Elucidating the tissue-specific molecular mechanisms underlying disease associations through integrative analysis of genetic variation and molecular network data”, will help to advance Columbia University’s efforts in precision medicine basic science research. 

As reported by Columbia Precision Medicine, the investigators’ research objectives include: to dissect the molecular mechanisms underlying tissue-specificity of genetic regulatory variants and to map network-level regulatory variants that cause protein-level transcription factor (TF) activity to vary between individuals. The investigators will infer TF activity based on DNA binding specificity models of human TFs, and use it as a tissue-specific parameter of the cellular environment. They will also map trans-acting genetic variants that affect TF activity (coined ‘aQTLs’ by one of the investigators) in each tissue. The investigators hope to elucidate which transcription factors are driving the functional impact and tissue specificity of any particular eQTL, genomic loci that contribute to variation in gene expression levels. 

Faculty

Tuuli Lappalainen

Assistant Professor, Department of Systems Biology, Columbia University
Junior Investigator and Core Member, New York Genome Center

Assistant Professor, Department of Systems Biology, Columbia University
Junior Investigator and Core Member, New York Genome Center