DECIPHERING GENE CONTROL

Welcome to the Laboratory of Computational Biology. Our lab is part of the KU Leuven Center for Human Genetics and the VIB Center for Brain and Disease Research. We are interested in decoding the genomic regulatory code and understanding how genomic regulatory programs drive dynamic changes in cellular states, both in normal and disease processes. Transcriptional states emerge from complex gene regulatory networks. The nodes in these networks are cis-regulatory regions such as enhancers and promoters, where usually multiple transcription factors bind to regulate the expression of their target genes.

Wet lab

We apply high-throughput technologies to decipher enhancer logic and map gene regulatory networks, such as RNA-seq for transcriptomics and ATAC-seq and ChIP-seq for epigenomic profiling. To test the activities of promoters and enhancers we use massively parallel enhancer-reporter assays. Finally, to map high-resolution landscapes of possible cellular states we use single-cell transcriptomics and single-cell epigenomics. Our favorite model systems include Drosophila (the brain and the eye-antennal imaginal disc) as well as human cancer cells (short-term cultures, cell lines, primary cells, xenografts, and organ-on-chip).

Dry lab

We use bioinformatics methods for network inference and computational modeling of enhancers, such as machine learning and advanced motif discovery. Some of the bioinformatics methods we have developed and made available to the community include TOUCAN, ENDEAVOUR, iRegulon, i-cisTarget, mu-cisTarget, and SCENIC.

Tech lab

We develop microfluidics chips, including droplet microfluidics for single-cell assays. We also develop microfluidic devices to analyse 3D tumoroids (organ-on-chip) and single-cell migration, in combination with lens-free imaging.

RESEARCH

Research in our lab is focusing on gene and genome regulation, with applications in neuroscience (Drosophila melanogaster) and cancer.

Enhancer modeling

We combine machine learning with epigenome profiling to decode enhancer logic. To test enhancers we developed a massively parallel enhancer-reporter assay, called CHEQ-seq. Our enhancer modeling focuses on mammalian TFs, such as TP53, SOX10/SOX9, GRHL1/2/3, AP-1, and TEADs; as well as on Drosophila TFs involved in eye development (e.g. Glass, Optix, sine oculis), epithelial development (Grainyhead), and tumour development (AP-1, STAT92E, and Scalloped).

cis-Regulatory variation

  • cis-regulatory variation is a major driver of phenotypic diversity and is associated to many diseases. By comparing chromatin accessibility across Drosophila inbred lines we aim to further our understanding of CRM divergence and plasticity, and the consequential divergence of gene expression and regulatory networks
  • Similar techniques are applied to cancer genomes, where we sift through non-coding mutations to identify cis-regulatory driver mutations that have an impact on enhancer function and/or perturb the normal gene regulatory network in a cell.

Evolution of cis-regulation

By comparing transcriptomes, chromatin state and cis-regulatory modules across species, we learn about enhancer logic and the evolution of gene regulatory networks. We use RNA-seq, FAIRE-seq, and ATAC-seq across Drosophila species, alongside Ornstein-Uhlenbeck models to connect CRM evolution with variation in chromatin accessibility. We have also studied the evolution of epidermal and metabolic GRNs between Drosophila and Daphnia.

Melanoma phenotype switching

We are interested in deciphering regulatory programs of transcriptional state switches in mammalian systems, including human and mouse. To study the cis-regulatory code in mammalian genomes we mainly use cancer cells as model system. During cancer progression, gene expression profiles can change, causing regulatory heterogeneity in tumors. This heterogeneity has an important impact on therapy response, since some cell states may be more or less vulnerable to a particular drug therapy.

Fly brain & ageing

We study neuronal and glial cell types in the ageing Drosophila brain using single-cell RNA-seq, and compare normal cell states with disease mutations involved in Parkinson’s and Alzheimer’s disease.

Fly eye & cancer

The eye-antennal disc is a classical model system to study cellular differentiation. We use this system to unravel new genomic regulatory “recipes” that control cell fate decisions, such as photoreceptor specification and differentiation. We also perturb this system using irradiation, transcription factor perturbations, and RasV12-driven malignant transformation, to study cancer-related transcriptional changes, controlled by JNK, EGFR, and Hippo signaling pathways.

Single-cell gene regulation

Single-cell transcriptomics (scRNA-seq) and single-cell epigenomics (scATAC-seq) data revolutionize the field of regulatory genomics. We combine new computational strategies (e.g., SCENIC, cisTopic) with state-of-the-art single-cell measurements (Drop-seq, 10X, InDrops, SeqWell) to decipher cis-regulatory “programs”, to reverse engineer gene regulatory networks, and to better define cell types and cell state transitions.

Single-cell systems biology

We develop new computational approaches that exploit single-cell technologies to link genome variation with changes in epigenome, transcriptome, proteome, and phenome. We apply this to human melanoma (e.g., phenotype switching), to the mouse liver, to the developing Drosophila eye and to ageing/neurodegeneration in the Drosophila brain. See also our collaborations.

Gene regulation bioinformatics

We develop new bioinformatics tools for motif and CRM detection, and for gene regulatory network inference, such as i-cisTarget, iRegulon, and TOUCAN. We also maintain a large collection of curated position weight matrices (currently > 20.000). We exploit single-cell RNA-seq and single-cell ATAC-seq data to improve the identification of GRNs and enhancers, with our tools SCENIC and cisTopic.

SOFTWARE

SCope

SCope is a fast visualization tool for large-scale and high dimensional scRNA-seq datasets. Visit http://scope.aertslab.org to test out SCope on several published datasets!

Github

cisTopic

cisTopic is an R package to simultaneously identify cell states and cis-regulatory topics from single cell epigenomics data.

Github

pySCENIC

pySCENIC is a lightning-fast python implementation of the SCENIC pipeline (Single-CEll regulatory Network Inference and Clustering) which enables biologists to infer transcription factors, gene regulatory networks and cell types from single-cell RNA-seq data.

Github PyPi Read the Docs

arboreto

Arboreto is a computational framework that offers scalable implementations of Gene Regulatory Network inference algorithms. It currently supports GRNBoost2 and GENIE3 (Huynh-Thu et al., 2010).

Github PyPi Read the Docs

SCENIC

SCENIC is an R package to infer Gene Regulatory Networks and cell types from single-cell RNA-seq data.

Read more... Paper Github

i-cisTarget

i-cisTarget is an integrative genomics method for the prediction of regulatory features and cis-regulatory modules.

Website

iRegulon

iRegulon is a Cytoscape plugin that detects the TF, the targets and the motifs from a set of genes.

Website

NEWS & PUBLICATIONS

  • The transcription factor Grainy head primes epithelial enhancers for spatiotemporal activation by displacing nucleosomes.

    Jacobs J et al., Nat Genet., June 2018.

    Using ATAC-seq across a panel of Drosophila inbred strains, we found that SNPs affecting binding sites of the TF Grainy head (Grh) causally determine the accessibility of epithelial enhancers.

  • A single-cell transcriptome atlas of the ageing Drosophila brain.

    Davie K, Janssens J, Koldere D et al., Cell., June 2018.

    A single-cell atlas of the adult fly brain during aging:

    • Network inference reveals regulatory states related to oxidative phosphorylation
    • Cell identity is retained during aging despite exponential decline of gene expression
    • SCope: An online tool to explore and compare single-cell datasets across species

  • Data/Software Update

    Data & Software - Mar. 30th 2018

    • SCENIC is now available for Fly.
    • Arboreto makes GENIE3 highly parallelizable and comes with a novel and fast GRN inference algorithm as an alternative for GENIE3 for very large datasets.
    • pySCENIC is a lightning-fast python implementation of the SCENIC pipeline (Single-CEll regulatory Network Inference and Clustering).

  • Fly Cell Atlas

    Gasthuisberg campus, University of Leuven (Belgium), Dec. 8th 2017

    The Fly Cell Atlas will bring together Drosophila researchers interested in single-cell genomics, transcriptomics, and epigenomics, to build comprehensive cell atlases during different developmental stages and disease models.

  • SCENIC: single-cell regulatory network inference and clustering.

    Aibar S et al., Nat Methods., September 2017.

    We present SCENIC, a computational method for simultaneous gene regulatory network reconstruction and cell-state identification from single-cell RNA-seq data.

  • Hippo Reprograms the Transcriptional Response to Ras Signaling.

    Pascual J, Jacobs J et al., Dev Cell., Sept. 2017

    Here we show that the Hippo pathway is critical for this decision. Loss of Hippo switches Ras activation from promoting cellular differentiation to aggressive cellular proliferation.

  • Multiplex enhancer-reporter assays uncover unsophisticated TP53 enhancer logic.

    Verfaillie A et al., Genome Res., May 2016.

    Using two complementary techniques of multiplex enhancer-reporter assays, we discovered that functional enhancers could be discriminated from nonfunctional binding events by the occurrence of a single TP53 canonical motif.

  • Decoding the regulatory landscape of melanoma reveals TEADS as regulators of the invasive cell state.

    Verfaillie A et al., Nature Commun., April 2015.

    Using regulatory landscapes and in silico analysis, we show that transcriptional reprogramming underlies the distinct cellular states present in melanoma. Furthermore, it reveals an essential role for the TEADs, linking it to clinically relevant mechanisms such as invasion and resistance.

OUTREACH

Fly Cell Atlas

Together with B. Deplancke and R. Zinzen we founded the Fly Cell Atlas.

The Fly Cell Atlas will bring together Drosophila researchers interested in single-cell genomics, transcriptomics, and epigenomics, to build comprehensive cell atlases during different developmental stages and disease models.

Go to flycellatlas.org

BIG

  • The Leuven Bioinformatics Interest Group organises a monthly bioinformatics meeting to bring together bioinformaticians, and anybody interested in bioinformatics, across departments. It allows participants working on very different biological questions to present and discuss the technical, algorithmic, and mathematical aspects of their work. Moreover, it aims to create a meeting place for next-generation biologists to meet and discuss with bioinformaticians. Research areas include, but are not limited to : Analysis of next generation sequencing data, comparative and evolutionary genomics, data management and genome informatics, proteomics, epigenomics and gene regulation, network biology, …
  • Register on our mailing list to become a member! Visit BIG for more info.

Teaching

  • E06E2A Introduction to Bioinformatics (taught in Dutch)
  • I0D52A Bioinformatics: Structural and Comparative Genomics
  • E02N3AE Bioinformatics and Systems Biology: Sequence, Structure & Evolution
  • E02N4A Bioinformatics and Systems Biology: Expression, Regulation and Networks

Mendelcraft

MendelCraft is a MineCraft mod developed in the lab to teach children about DNA, genetics, and the laws of Mendel. You can visit the website at http://mendelcraft.aertslab.org/

Partners

  • VIB & KU Leuven
    • Our lab is part of the KU Leuven Center for Human Genetics at the KU Leuven, and the VIB Center for Brain and Disease Research
  • Genomics Core
    • The Genomics Core offers next-generation sequencing services on MiSeq, NextSeq, HiSeq2500, HiSeq4000, NovaSeq, and PacBio Sequel.
  • Vlaams Supercomputer Centrum (VSC)
  • JEDI

Press & Media

DATA & RESOURCES

JOIN US

We are always on the lookout for highly motivated scientists to join our team. If you are interested in a PhD or postdoc position to work on single-cell regulatory genomics - computational or experimental - please send your motivation letter and CV to stein.aerts@kuleuven.vib.be

Currently open positions

  • Post-doc in computational biology. You can find more info here.

Team

Stein Aerts

Stein Aerts

PRINCIPAL INVESTIGATOR
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Zeynep Kalender Atak

Zeynep Kalender Atak

STAFF SCIENTIST
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Suresh Poovathingal

Suresh Poovathingal

STAFF SCIENTIST
Sara Aibar Santos

Sara Aibar Santos

POSTDOCTORAL RESEARCHER
Jasper Wouters

Jasper Wouters

POSTDOCTORAL RESEARCHER
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David Mauduit

David Mauduit

POSTDOCTORAL RESEARCHER
Kristofer Davie

Kristofer Davie

PHD STUDENT
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Liesbeth Minnoye

Liesbeth Minnoye

PHD STUDENT
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Carmen Bravo González-Blas

Carmen Bravo González-Blas

PHD STUDENT
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Jasper Janssens

Jasper Janssens

PHD STUDENT
Duygu Koldere

Duygu Koldere

PHD STUDENT
Bram Van De Sande

Bram Van De Sande

PHD STUDENT
Valerie Christiaens

Valerie Christiaens

LAB MANAGER
Gert Hulselmans

Gert Hulselmans

TECHNICAL STAFF / BIOINFORMATICIAN
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Samira Makhazami

Samira Makhazami

TECHNICAL STAFF / LAB TECHNICIAN
Katina Spanier

Katina Spanier

TECHNICAL STAFF / BIOINFORMATICIAN
Maxime De Waegeneer

Maxime De Waegeneer

TECHNICAL STAFF / BIOINFORMATICIAN
Dafni Papasokrati

Dafni Papasokrati

MASTER STUDENT
Quinten Lauwers

Quinten Lauwers

MASTER STUDENT

Alumni

  • Marina Naval Sanchez (PhD); postdoc at CSIRO, Australia
  • Annelien Verfaillie (PhD); Research Scientist, Crick Institute, London
  • Dmitry Svetlichnyy (PhD); Research Scientist, Skoltech, Russia
  • Delphine Potier (Postdoc); postdoc CIML Marseille
  • Rekin's Janky (Postdoc); bioinformatician, VIB Nucleomics Core, Leuven
  • Mark Fiers (embedded Bioinformatics Specialist); staff scientist (De Strooper lab), VIB Leuven
  • Jelle Jacobs (Phd); postdoc at IMP (Stark lab), Vienna
  • Hana Imrichova (PhD); postdoc at CeMM (Bock lab), Vienna

  • Lab events & Pictures

    CME DAY LCB
    CME DAY LCB
    LAB RETREAT 2012
    LAB RETREAT 2012
    LCBRETREAT 2013 (1)
    LCBRETREAT 2013 (1)
    LCBRETREAT 2013 (2)
    LCBRETREAT 2013 (2)
    LCBRETREAT 2013 (3)
    LCBRETREAT 2013 (3)
    LAB LUNCH 2016
    LAB LUNCH 2016
    LAB RETREAT 2016 (1)
    LAB RETREAT 2016 (1)
    LAB RETREAT 2016 (2)
    LAB RETREAT 2016 (2)
    NEW YEARS LUNCH 2018
    NEW YEARS LUNCH 2018

    Contact

    Stein Aerts

    Herestraat 49, PO Box 602, 3000 LEUVEN, Belgium

    stein.aerts[at]kuleuven.vib.be

    +32-16-33 07 10