Huang et al 2017 Nature Overview Inflammatory bowel disease (IBD) { width=60% } Ulcerative colitis (UC): colon inflammation & ulcers Crohn’s disease (CD): colon + ileum inflammation Contributions of this study The pace of identifying associated loci outstrips that of defining specific molecular mechanisms and extracting biological insight from associations 200 IBD loci identified, few resolved to functional variants This study: 94 loci evaluated, 45 variants resolved Approach: genetic «fine-mapping» + detailed annotations Dense genotyping array of Europeans 3 fine-mapping methods Enrichment in regulatory regions 3 eQTL colocalization methods ###

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By [Joehanes and Munson, GB, 2017] Methods Framingham Heart study: 5K samples, whole blood eQTL. QC: polymorphism-in-probe effect is likely minor. Discovery of eQTL: step-wise regression to find independent eQTL. Found 19K independent cis-eQTL and 6K trans-eQTL. Sample size is important for the power: it scales linearly with cis-eQTL, but more with trans-eQTL. Double the size from 2500 to 5000 increase the trans-eQTL by 3-4 fold. Validation of eQTL: (1) Internal: 75% cis and 41% trans-eQTL are validated.

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By [Hopf and Marks, NBT, 2017] Methods Motivation: pairwise correlation measures such as mutual information cannot distinguish direct and indirect coupling. Using a model such as MRF enables this: e.g. suppose we have energy terms A-B and B-C, then this will explain away coupling of A-C. Model: given sequence alignment, treats all sequences as samples from a stationary distribution. The distribution is determined by the fitness (or energy) of the sequence.

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By Rooney and Hacohen, Cell, 2015. Cytolytic activity (CYT) Measuring cytolytic activity (CYT): using granzyme and perforin levels. CYT activity varies across tumor types: in some tumors, e.g. kidney and cervical cancer, strong induction; but in others, e.g. breast cancer, no. Correlated genes with CYT: other genes that are markers of CYT activity; also positive correlation with genes usually not expressed in CTLs and NK cells, some are immunosuppresive molecules.

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By Reddy T. et al (2012) Genome Research. First, for audience not very familiar with the context: Transcription factors: Bind specific DNA motif & controls gene expression Chromatin Immunoprecipitation Sequencing: Cartoon: ChIP-Seq with chips Differential allelic : Alleles are different versions of the same gene. To focus on allelic imbalance means to focus on heterozygotes Differential allelic TF occupancy (DATO): preference to bind one allele over another, within the same cell type Allele specific expression (ASE): Explained in part as functional consequence of differential allelic TF binding EP300: histone acetyltransferase p300, makes DNA more accessible to TF This paper was published in 2012: when exome sequencing was just becoming widely adopted.

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Biological question Mutation in monogenic disease can cause disease phenotype at various level of severity. For instance, cystic fiberosis (CF) is caused by a single gene, CFTR, the homozygous individuals with exactly the same allele $\delta$F508 present a wide range of clinical symptoms. It is due to «modifier genes», MBL2 and TGF-$\beta$. Such observation is general in many Mendelian diseases. Namely, the disease is predictable but the severity of it is highly unknown due to the variation of genetic background.

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Regulatory elements: Putting enhancers into context Principle of suboptimization The enhancer consists of low-affinity TF binding sites in a suboptimal syntax, in terms of flanking nucleotides and spacing between the sites. Optimizing the TF binding affinities can lead to ectopic expression. Experiment In sea squirt, 15 synthetic enhancers consisting of 2 ETS binding sites and a ZicL binding site. Only 2 show activities. Further manipulation confirm key roles for binding site orientation, spacing and flanking nucleotides.

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Problem infer spatial locations of various cell types which will determine the cell fate and behavior RNA staining only assays a small number of transcripts and RNA-seq can measure the global gene expression, but separates the cells from their native spatial context. they develop Seurat to localize the cells by integrating single cell RNA-seq data and in situ RNA patterns. Modeling Overview Figure 1 gives the overview of the method.

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Read-n-share

In summer 2017 during one of the Xin He lab reading group session we came up with the notion of crowdsourcing the efforts of reading papers. The gist is that we should figure out a way to not only share our literature reading notes, but also engage in discussions / debates if there are multiple people interested in the same paper. We were excited about the idea. But how do we go about implementing it?

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