Genomics is the study of individual genomes, both at the sequence level and at the structural level. Technological advances have made genomic approaches critical for understanding basic biological processes, so that genomic research now impacts all areas of life science research.
The CSHL Genomics Program includes faculty working across disciplines and research areas. Their main interests are genomic organization, structural variation of the human genome as related to disease, computational genomics, small RNA biology, transcriptional modeling, and sequencing technology. Genomics research at CSHL benefits from state-of-the-art technology and innovative software development, with researchers both on the main CSHL campus and at the nearby CSHL Woodbury Genome Center.
Broadly, genomics research falls into three categories with significant overlap: Cognitive Genomics, Cancer Genomics and Plant Genomics. In addition, Genomics researchers works closely with researchers in other CSHL programs, particularly the Simon Center for Quantitative Biology.
CSHL is one of the founding members of the New York Genome Center, an independent, non-profit organization that is leveraging the collaborative resources of leading medical and research institutions to transform medical research and clinical care in New York.
The CSHL Cancer Genomics group seeks to understand how the cancer genome differs from the normal genome, how these differences lead to the growth and development of cancer, and how biomarkers can be used for diagnosis and prognosis. Researchers in this area are members of the CSHL Cancer Center.
Much of the research focuses on the genomic changes that occur in numerous cancer types, such as breast, prostate, lung and pancreatic cancers, as well as leukemia, glioma and melanoma. Researchers have also focused on the development and application of sophisticated tools for genome analysis that permit high resolution mapping of deletions, amplifications and changes in the sequence or epigenetic status of chromosomal loci.
Another focus area is the development and application of genomic methods in cell culture and animal models. These include sophisticated chromosome engineering techniques as well as applications of large-scale RNAi and CRISPR screens to identify both driver genes and tumor-cell-specific dependencies, as well as single cell sequencing approaches. These genetic tools/approaches allow biological validation of loci discovered by analysis of cancer genomes.
A third area of focus centers on developing tools and software that can harness large scale genomic datasets that are available to the community. Examples include the study of allelic variation in the human genome and the development of computational methods for the discovery of cancer-associated genes and diagnostic cancer markers using genomic profiles derived from different tumor types. Many of these researchers are also part of the Simons Center for Quantitative Biology at CSHL.
Schizophrenia, bipolar disorder, and major recurrent depression are cognitive disorders that create an enormous burden on patients, their families and our health care system. These disorders tend to run in families and likely have a genetic component but little is known about the genetic basis of the diseases.
With recent advances in genomic technologies, CSHL is now poised to unravel the genetic complexity of cognitive disorders. Simultaneously, advanced technologies in Neuroscience research are allowing CSHL researchers to understand how the brain assembles neural circuits to control behaviors and cognitive processes like attention and decision-making. Much of this research occurs within the CSHL Stanley Institute for Cognitive Genomics, where approaches from genomics and neuroscience are integrated to improve the diagnosis and treatment of cognitive disorders.
The CSHL Plant Genomics group is using genomic approaches with the ultimate goal of improving access to food and fuel in the future. As part of Plant Biology research at CSHL, scientists are using genomic approaches to understand everything from plant evolution to how plants grow, develop, and reproduce.
This research is challenging because many plant genomes are very large. CSHL scientists have taken part in numerous plant genome sequencing projects including Arabidopsis, rice, sorghum and maize. In addition, CSHL plant scientists have participated in epigenomic sequencing and profiling. CSHL is also part of the iPlant Cyberinfrastructure consortium and the Long Island Biofuels Alliance.
Current research projects include sequencing the wheat genome through a combination of Illumina short read sequencing and long sequence reads using the new Pacific Biosciences sequencers. The latest results for this project can be found on the CSHL wheat genome sequencing project page.
The biological landscape is made up of millions of variables that interact in complex and often seemingly random ways. I am applying principles from physical and computational sciences to the study of biology to find patterns in these interactions, to obtain insight into population genetics, human evolution, and diseases including cancer.
Of the tens of thousand of protein-coding genes in the human genome, only a small portion have an experimentally defined function. For the rest, how can we determine what they do? My lab develops computational predictions based on co-expression networks. We are applying our predictions to understand neuropsychiatric disorders.
Only a small portion of the RNAs encoded in any genome are used to make proteins. My lab investigates what these noncoding RNAs (ncRNAs) do within and outside of cells, where regulators of their expression are located in the genome, and how perturbations of ncRNAs and their regulators contribute to disease.
As organisms develop, genes turn on and off with a precise order and timing, much like the order and duration of notes in a song. My group uses model organisms to understand the molecules that control the tempo of development. We also study how changes in the timing of gene expression contribute to diseases like cancer.
To ensure that cells function normally, tens of thousands of genes must be turned on or off together. To do this, regulatory molecules - transcription factors and non-coding RNAs – simultaneously control hundreds of genes. My group studies how the resulting gene networks function and how they can be compromised in human disease.
Every gene has a job to do, but genes rarely act alone. Biologists have built models of molecular interaction networks that represent the complex relationships between thousands of different genes. I am using computational approaches to help define these relationships, work that is helping us to understand the causes of common diseases including autism, bipolar disorder, and cancer.
My lab studies genes and signals in cells that regulate the growth and shape of plants. We have discovered several genes that control plant architecture by exerting an influence on stem cells. By identifying the genes that control the number of stem cells in corn plants, for example, we’ve discovered a means of boosting the yield of that vital staple.
How does cancer arise? It evolves from innocuous beginnings, as healthy cells accumulate mutations and transform into lethal tumor cells. I am developing mathematical and statistical tools to discover key genetic elements involved in the evolution of cancer, and in particular, metastatic tumors.
Cells are amazingly complex, with the ability to sense, and remember timing, location and history. I am exploring how cells store this information, and how their surroundings influence their communication with other cells. I am also developing various imaging and molecular sequencing methods for tracking genes, molecules, and cells to understand how cancer cells arise and evolve.
We have recently come to appreciate that many unrelated diseases, such as autism, congenital heart disease and cancer, are derived from rare and unique mutations, many of which are not inherited but instead occur spontaneously. I am generating algorithms to analyze massive datasets comprising thousands of affected families to identify disease-causing mutations.
My research team studies the genes that determine when and where, and thus how many, flowers are produced on plants. Flowers form on branches called inflorescences, which originate from stem cells. By studying the genes that control how stem cells become inflorescences, we are able to manipulate flower production to improve crop yields.
My group focuses on human genetics and genomic medicine, with an emphasis on diseases with severe neuropsychiatric manifestations. We collect large family pedigrees and use whole-genome sequencing to define mutations that correlate with the syndromes. We then undertake detailed functional characterization of these mutations to discover fundamental new biology.
Chromosomes are covered with chemical modifications that help control gene expression. I study this secondary genetic code - the epigenome - and how it is guided by small mobile RNAs in plants and fission yeast. Our discoveries impact plant breeding and human health, and we use this and other genomic information to improve aquatic plants as a source of bioenergy.
Over the last two decades, revolutionary improvements in DNA sequencing technology have made it faster, more accurate, and much cheaper. We are now able to sequence up to 10 trillion DNA letters in just one month. I harness these technological advancements to assemble genomes for a variety of organisms and probe the genetic basis of neurological disorders, including autism and schizophrenia, better understand cancer progression and understand the complex structures of the genomes of higher plants.
I am a computer scientist who is fascinated by the challenge of making sense of vast quantities of genetic data. My research group focuses in particular on questions involving human evolution and transcriptional regulation.
At the growing tip of plants sits a reservoir for stem cells, called the meristem, from which new organs, such as leaves, arise. We study genetic networks that distinguish stem cells from their differentiating descendants as well as the role of mobile small RNAs as novel meristem-derived signals that pattern leaves
When we think of evolution, we often think about physical changes, like a plant developing broader leaves to collect more solar energy. Such evolution actually occurs within the plant’s DNA. I am using computational analysis and modeling to visualize how plant genomes have evolved over time, particularly those of staple crops. We are learning from this work to improve the range and yield of modern plants.
Devastating diseases like cancer and autism can be caused by spontaneous changes to our DNA—mutations first appearing in the child, or in our tissues as we age. We are developing methods to discover these changes in individuals, tumors, and even single cells, to promote early detection and treatments