#ASHG21 BMG: Bailey Martin-Giacalone.
Germline variants in cancer predisposition genes predict survival for children with rhabdomyosarcoma (RMS) #ASHG21 BMG: RMS most common soft tissue cancer of childhood. Usually two subtypes. alveolar RMS (ARMS) ~80% have a PAX3/7-FOX01 fusion. Embryonal RMS (ERMS) have heterogeneous somatic mutation landscape.

#ASHG21 EDF: Elisa De Franco.
loss of the primate specific gene ZNF808 causes pancreatic disease. #ASHG21 EDF: studying human development to better understand common and rare diseases. specifically interested in diabetes.

#ASHG21 JS: Jonathan Sebat.
a phenotypic spectrum of autisim attributable to... [ too fast I missed it ] #ASHG21 JS: combined 3 cohorts. Two WGS cohorts and the SPARK study. 11k families. 37,375 individuals. Called with GATK best practices. Imputed genotypes from SPARK combined with PLINK. Calculated polygenic scores.

#ASHG21 WL: Wenhan Lu.
quantifying the extent of pleiotropy using rare variant association data in 281k human exomes #ASHG21 WL: have large scale rare variant association in UKBB exomes.
Preprint - medrxiv.org/content/10.110…
Explorer at - genebass.org

#ASHG21 RB: Richard Border.
Widespread evidence of systematic bias in estimates of genetic correlation due to assortative mating.
[ I think this is the preprint. Don't hold me to it. ]
biorxiv.org/content/10.110… #ASHG21 RB: interested in characterizing what extent two traits share similarity across traits.

#ASHG21 MO: Meritxell Oliva.
Genetic regulation of DNA methylation across tissues reveals thousands of molecular links to complex traits. #ASHG21 MO: GTEx looks at gene expression, regulation, and its relationship to genetic variation. The v8 set has eQTL data. 15,201 RNA-Seq samples from 838 post-mortem donors. 49 tissues.

#ASHG21 NC: Nicholas Cheng.
Early detection of cancers using plasma cell-free DNA methylomes up to 7 years prior to clinical diagnosis. #ASHG21 NC: cancer development is a mostly evolutionary process involving sequenctial somatic mutation and methylation / accessibility changes.

#ASHG21 ALP: Alkes L Price.
Identifying disease-critical cell types and cellular processes across the human body by integration of single-cell profiles and human genetics.
Preprint - biorxiv.org/content/10.110… #ASHG21 ALP: Cellular dysfunction leads to disease. We can use GWAS data to find the critical cell types.

#ASHG21 YH: Yingbo Huang.
Sex differences in the expression and genetic regulation of drug metabolism and transporter genes in human liver.
@YingboHuang #ASHG21 YH: sex differences exist in many different traits. this includes drug responses.

#ASHG21 AN: Aparna Nathan.
Modeling eQTLs at single-cell resolution identifies 2000 eQTLs with differential effects across continuous T cell states. #ASHG21 AN: cell-state dependent eQTLs means that the same genetic variant may have an effect or no effect depending on cell type and activation. How do you find state-dependent QTLs?

#ASHG21 FW: Frank Wessely.
Understanding cell-type-specific drug effects while controlling for genotype. #ASHG21 FW: there are databases of gene expression responses to perturbation. Such as Cmap and CLUE.

#ASHG21 AT: Adelaide Tovar.
A modular massively parallel reporter assay uncovers context-specific allelic activity of GWAS variants. #ASHG21 AT: GWAS hits often not in coding sequence [though plenty are in gene bodies] and suggests that the promoter / enhancer / other non-coding sites may affect gene regulation and therefore disease risk.

#ASHG21 ML: Mischa Lundberg.
Integrative analysis of human genetic association studies, single cell transcriptomics, and knockout mouse models identifies cell types and genes involved in skeletal disease. #ASHG21 ML: Lack of 'omics data for skeletal disorders. Use murine 'omics to try and fill this gap since the data aren't always available for human samples.

#ASHG21 EP: Evin Padhi.
Computational and functional characterization of the hs737 enhancer in autism #ASHG21 EP: Noncoding de novo variants are enriched in individuals with autism. How does that work? hs737 enhancer reaches significance in discovery and replication cohorts.

#ASHG21 SK: Samuel Kim.
Leveraging single-cell ATAC-seq to identify disease-critical fetal and adult brain cell types.
biorxiv.org/content/10.110… #ASHG21 SK: need to go from disease-critical cell type identification to disease mechanism.

#ASHG21 OEG: Omar El Garwany.
Genetic determinants of alternative splicing in stimulated iPSC-derived macrophages enhance the understanding of immune-mediated disease risk.
@oelgarwany @oelgarwany #ASHG21 OEG: macrophages respond quickly to environmental stimuli, and these stimuli may cause substantial changes to their gene expression.

#ASHG21 KG: Kiran Girdhar.
Acetylated chromatin domains link chromosomal organization to cell and circuit level dysfunction in schizophrenia and bipolar disorder. #ASHG21 KG: Generated cell specific histone modified regions from controls postmortem brain samples. Enrichment of neuron specific histone peaks.

#ASHG21 BJS: Benjamin J Strober.
Uncovering context-specific genetic regulation of gene expression from single-cell RNA-sequencing using latent-factor models. #ASHG21 BJS: Many contexts modulate gene expression. Such as cell type, developmental stage, environmental stimulus.
One way to study is to look at eQTLs. Especially context-specific eQTLs. Example might be an eQTL in B cells that isn't an eQTL in T cells.

#ASHG21 TA: Tiffany Amariuta.
Modeling tissue co-regulation to quantify tissue-specific contributions to disease heritability. [ dropping in the middle of it ] #ASHG21 TA: TCSC applied to real traits. 25 GTEx v8 tissues. 350-550 meta tissues and singular tissues. analyze 82 GWAS summary statistics. TCSC identifies 67 tissue trait pairs with non-zero heritability at 10% FDR.

#ASHG21 KR: Kathleen Reed.
High-resolution structural and temporal mapping illuminates relationships between 3D chromatin structure, enhancer activity, and gene regulation during macrophage activation. #ASHG21 KR: Most of the human genome is non-coding, and a substantial fraction of non-coding space includes regulatory regions that can act in cis and trans, and may involve chromatin looping.

#ASHG21 JDB: Joshua D Backman [Regeneron].
Rare variant associations from exome sequencing of 454,787 individuals in the UK Biobank. #ASHG21 JDB: >500k adults in the UK 40-69 years old at enrollment. 12.3M coding variants. ~1M loss-of-function variants. Most of the rare variants aren't imputable. 3,994 traits ExWAS. 492 traits with rare variant association. 8,865 rare variant associations total.