Jesse Engreitz

@jengreitz

Junior Fellow Society of Fellows. Exploring regulatory code of the human genome . Asst Professor starting Spring 2020

Cambridge, MA
Vrijeme pridruživanja: kolovoz 2010.

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  1. Prikvačeni tweet
    15. lis 2019.

    I am excited to announce that my lab will launch at Stanford in Spring 2020! I will be an Assistant Professor in Genetics and the Children’s Heart Center. We aim to map the regulatory wiring of the genome to discover mechanisms of heart diseases. 1/

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  2. proslijedio/la je Tweet
    prije 17 sati

    Fantastic to see this work out in led by and from , as well as and from our group. Wonderful collaboration with , the doyenne of blood cell genetics! Great tweetorial from the team!👇

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  3. 30. sij

    Proteomics across hundreds of cell lines in CCLE — very interesting analyses of protein-RNA correlation!

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  4. proslijedio/la je Tweet
    9. pro 2019.

    1/ Four years ago, our lab set out to predict and control the loss of mesendoderm competence during ectoderm differentiation in human stem cells. Along the way, we showed that we could shape the Waddington landscape (remember intro dev bio?). Thread 👇

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  5. proslijedio/la je Tweet
    18. pro 2019.

    Ultra-high throughput scRNA-seq from Christoph Bock's lab! Combines combinatorial barcoding with droplet microfluidics to sequence >150,000 cells on a single lane:

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  6. proslijedio/la je Tweet
    7. pro 2019.

    Just updated! Our massive database of PhD fellowships for research anywhere. We have found 117 funding opportunities for graduate students in all fields of research. We provide deadline, dollar amount, link to funder, number of pages, eligibility.

    , , i još njih 7
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  7. proslijedio/la je Tweet
    5. pro 2019.

    See theory/comp preprint on model for disordered proteins, led by our Princeton collaborator Thanos, w/ 1st authors Antonia (now fac @ UIUC) and undergrad Helena (now doing PhD @ Harvard). *Beautifully* complex & highly sequence-dependent phase behavior!

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  8. proslijedio/la je Tweet
    5. pro 2019.

    After two years on the BioRxiv and now including 2 years of progress, our paper making the case for random DNA genomics is now available! We found all sorts of cool things, but, to me, the most important is the sheer abundance of transcription factor binding sites. thread->

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  9. 5. pro 2019.

    Fascinating connection between splicing and promoter selection

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  10. 3. pro 2019.
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  11. 2. pro 2019.
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  12. 2. pro 2019.

    Congratulations to our awesome ABC team! Joe Nasser @mc_monte_cristo and others And: We are hiring! 10/10

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  13. 2. pro 2019.

    ABC also has implications for understanding the 3D genome. Estimating 3D contact as a function of genomic distance predicts CRISPR data nearly as well as using Hi-C. So, contact freq from distance (not CTCF loops, domains, etc.) appear to be key feature for most enhancers. 9/

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  14. 2. pro 2019.

    ABC maps can help to connect common disease variants to their target genes. Ex: Here is the SORT1 locus from . ABC maps in hepatocytes connect to SORT1 — matching eQTL and CRISPR data. (Note though that variant regulates multiple genes!) 8/

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  15. 2. pro 2019.

    Now we have a simple way to predict enhancer-gene connections — for any gene in any cell type! At minimum, computing ABC requires ATAC-seq and H3K27ac ChIP-seq. Download the code here: 7/

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  16. 2. pro 2019.

    This Activity-by-Contact (ABC) model works remarkably well at predicting our CRISPR data – including in K562 and in other cell types. 6/

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  17. 2. pro 2019.

    So, we explored other prediction methods. Our best model was surprisingly simple: Effect of enhancer = Activity (count ATAC+H3K27ac reads) x Contact (count Hi-C reads) This encodes the notion that enhancers act on promoters upon 3D contact, with different strengths. 5/

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  18. 2. pro 2019.

    With gold-standard CRISPR data in hand, we checked whether any existing models could predict enhancer-gene regulation. In fact, the answer was no! Existing methods (Hi-C loops, contact domains, nearest gene, DHS E-P correlation, and others) all performed poorly. 4/

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  19. 2. pro 2019.

    To answer this, we first experimentally mapped many thousands of potential enhancer-gene connections, using a new method combining CRISPRi with RNA FISH and flow cytometry (CRISPRi-FlowFISH). 3/

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  20. 2. pro 2019.

    Enhancers tune gene expression in each cell type in the body. We know enhancers can control multiple genes over long distances, with cell-type specific effects. But, are there simple rules to explain this network of millions of enhancers x 21000 genes x 1000s of cell types? 2/

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  21. 2. pro 2019.

    I am excited to share our latest work, in which we tackle the question: How can we predict which enhancers regulate which genes in which cell types? Thread 👇 1/

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