We are interested in how human genomes vary from person to person and shape the biology of neurons and other brain cell populations on their way to affecting key events in normal brain development and brain illness. We develop new experimental and computational approaches, then use them together in almost every project.

Human biology from sequencing

Human biology from sequencingTens of thousands of human genomes are being sequenced every year. We believe such data can be used in new ways to teach us novel things about human biology. In recent studies, we used sequencing data to discover that DNA replication varies from person to person; to find genes hiding in and around centromeres; and to discover a common pre-cancerous condition that puts people at twelve-fold greater risk of future cancer.

Koren et al., Genetic variation in human DNA replication timing. Cell, 2014.
Genovese et al., Clonal hematopoiesis and blood cancer risk inferred from blood DNA sequence. New England Journal of Medicine, 2014.
Genovese et al., Using human population mixture to help complete maps of the human genome. Nature Genetics, 2013.

Genome structural variation

Genome structural variationWe have found that a substantial and biologically important fraction of human genome variation arises from complex and large-scale forms of variation that human genetics hadn’t had the tools and approaches to understand. We are working to figure out how these edgier parts of the human genome evolve in human populations and shape human phenotypes.

Handsaker et al., Large multiallelic copy number variations in humans. Nature Genetics, 2015.
Genovese et al., Using human population mixture to help complete maps of the human genome. Nature Genetics, 2013.
Boettger et al., Structural haplotypes and recent evolution of the human 17q21.31 locus. Nature Genetics, 2012.
Handsaker et al., Discovery and genotyping of genome structural variation by sequencing on a population scale. Nature Genetics, 2011.

Single-cell biology

Single-cell biologyWe recently developed a new technology for profiling RNA expression genome-wide in thousands of individual cells at once.  We do this by separating cells into millions of nanoliter-sized droplets, lysing the cells in droplets, and massively barcoding the contents of these droplets to remember the cell-of-origin of each RNA. In a single sequencing reaction, we routinely profile gene expression genome-wide in thousands of individual cells. We call this technology Drop-seq. We are beginning to use Drop-seq to ascertain things like: the cell types that populate the brain; the pathophysiology involved in schizophrenia, autism and other illnesses; and the ways in which genetic variation acts at the level of specific cell populations within complex tissues.

Macosko et al.,  Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets.  Cell, 2015.

Genetics and neurobiology in brain illness

Genetics and neurobiology in brain illnessWe combine the above approaches in work to understand the genetic and biological basis of brain illnesses. We pursue this through:

  • Analyzing the genomes of tens of thousands of individuals to identify genes in which common and rare variants shape risk of illness.
  • Biological experiments and computational data analysis to understand how these genes and alleles affect the function of neurons, glia, and other brain cell types.

For example, we are mapping genetic influences to specific cell populations (interneurons, excitatory neurons, microglia, astrocytes) and working to understand how genetic variation perturbs the biology of those cell populations. This work involves genomic study of brain tissue from humans and mice and of cell culture models in which neurons are interacting with microglia and other kinds of cells. Our goal is to identify the key molecular and cellular events in the etiology of illness.

McCarroll, Feng and Hyman, Genome-scale neurogenetics.  Nature Neuroscience, 2014.
McCarroll and Hyman, The genetics of polygenetic brain disorders present new challenges for neurobiology.  Neuron, 2013.
Purcell et al., A polygenic burden of rare disruptive mutations in schizophrenia.  Nature, 2014.