Welcome to the Research Group of Harmen Bussemaker
We are based in the Department of Biological Sciences at Columbia University, and affiliated with the Department of Systems Biology and the Program in Mathematical Genomics, as well as with the New York Genome Center.
Our research focuses on how DNA-binding proteins called transcription factors read the instructions about when genes should be turned on or off that are hidden our genomes. Elucidating these gene regulatory networks is key to understanding how organisms develop and respond to changing conditions. It also provides new avenues for analyzing how genetic variation between individuals gives rise to variation in their cellular behavior. This in turn helps us understand what happens during aging and disease.
Lab News
May 2021 – Read about our new biophysically interpretable machine learning algorithm ProBound in Nature Biotechnology, and explore the associated MotifCentral website, which hosts accurate protein-DNA binding affinity models for hundreds of transcription factors from different species, with direct links to cross-platform (SELEX, PBM, ChIP-seq) validation results for each binding model. You can score your own DNA sequences using our ProBound binding model release and ProBoundTools utility. The name ProBound refers to the underlying biophysical model of whether the protein is bound, but is also intended to sound like “profound”, which alludes to deep learning, but is different and better 😉
August 2019 – Check out some of our recent collaborative publications! We reviewed the connection between functional low-affinity TF binding sites and variation in local TF concentration associated with transcriptional hubs (Kribelbauer et al., Annual Reviews, 2019); showed that the “latent specificity” for Hox proteins we uncovered using SELEX-seq indeed explains in vivo enhancer function (Sánchez-Higueras et al., Nature Communications, 2019); and extended the massively parallel SuRE-seq reporter assays to probe allelic effects on gene expression on an unprecedented scale (Van Arensbergen et al., Nature Genetics, 2019).
April 2019 – Congratulations to Maya Talukdar, an undergraduate researcher working in our lab, for being awarded a national Barry M. Goldwater Scholarship!
April 2018 – Read about No Read Left Behind (NRLB), which can characterize the DNA binding specificity of transcription factor complexes almost perfectly over the full affinity range, and allows us to predict the effect on expression of enhancers mutations that are a hundred-fold weaker than the strongest site in the genome (Rastogi et al., PNAS, 2018). See also this news story.
April 2018 – Congratulations to two former lab members for receiving an NSF graduate fellowship: Gabriella Martini, who previously was a research technician in our lab and currently is a PhD student at UC Berkeley, and Brian Trippe, who was an undergraduate researcher in our lab and is currently a PhD student at MIT.
March 2018 – Watch a 12-min presentation given at the CSHL Systems Biology Meeting about our unified approach for quantifying and interpreting DNA shape readout by transcription factors (Rube et al., MSB, 2018).
February 2018 – Our lab was awarded a two-year, $100k/year grant by the Vagelos Precision Medicine initiative for a new collaborative project with Tuuli Lappalainen’s lab at the New York Genome Center on mapping the genetic determinants of cis- and trans-acting genetic variation in human tissues. You can find an easy-to-read summary of some the work by our lab on which this project is based in the inaugural issue of Current Opinion in Systems Biology.
February 2018 – Read more about our recent research in papers describing how systematic prediction of DNA shape changes due to CpG methylation explains epigenetic effects on protein-DNA binding (Epigenetics & Chromatin, 2018), how our new SelexGLM algorithm differentiates androgen and glucocorticoid receptor DNA-binding preference over an extended binding site (Genome Research, 2018), how SELEX-seq can be extended to perform quantitative analysis of the DNA methylation sensitivity of transcription factor complexes including Hox and p53 (Cell Reports, 2017), and how we can perform genome-wide mapping of autonomous promoter activity in human cells (Nature Biotechnology, 2017).
May 2016 – Watch a talk on some of our recent methods for analyzing SELEX data at Simons Center at Berkeley University.
June 2013 – Watch a talk about our work on the intrinsic sequence and methylation sensitivity of DNase I at the Banff International Research Station.
CSHL Course
If you are an experimental biologist wondering how to analyze the large genomics dataset you just generated, consider applying for the Cold Spring Harbor summer course on Statistical Methods for Functional Genomics, where you can learn everything you always wanted to know about basic statistics and R but were afraid to ask. For 14 consecutive summers, from 2006 to 2019, our lab was intimately involved with this course, which counts many PhD students, postdocs, faculty members, and other scientists who are doing great work among its alumni. See the “roll of honor” on the CSHL page.