#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 MO: A mQTLs are variants associated with DNA methylation. GWAS-QTL colocalization can help prioritize the causal genes at a GWAS locus.
#ASHG21 MO: Looked for cis mQTLs in a 500kb window to alleles. 100k-200k mQTL CpG sites per tissue.
#ASHG21 MO: mQTLs tended to dichotomize. Either very tissue specific, or highly shared across different tissues.
#ASHG21 MO: Used pair-wise colocalization to see what the overlap was between mQTL and eQTL. 21% of mQTLs are colocalized to an eQTL., i.e. most eQTLs are not explained by a cis-colocalized mQTL.
#ASHG21 MO: Look at mQTL mechanisms to eQTLs. eQTLs are enriched in gene body and proximal regulatory elements. mQTLs are enriched in non-genic, distal regulatory regions.
#ASHG21 MO: mQTLs are linked to transcription factors involved in chromatin spatial conformation and long-range interaction. eQTLs linked to TFs involved in basal transcription.
#ASHG21 MO: GWAS for 87 traits for 8.6M variants. Looked at colocalization. 12,922 QTL-GWAS colocalizations. 81% of the GWAS study had at least one. 41% of GWAS hits overall had colocalization. 3,381 mQTLs.
#ASHG21 MO: mQTL specific cases are traits colocalized with only an mQTL, but not to an eQTL. How does that work if the expression isn't changed?
#ASHG21 MO: eQTL and mQTL colocalizations can help with fine mapping GWAS signals. May also help with identifying independent SNP effects in the same locus.
#ASHG21 MO: at TERT, mQTL in ovary colocalizes with breast cancer GWAS signal. TERT expression is undetectable in normal ovary. Expressed in stem and stem-like cells.
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#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 BMG: risk factors for survival include histology, primary site, fusion status, metastasis, age at diagnosis. tumor size. ERMS cases have better outcome. In fusion negative RMS with TP53 mutation have worse survival.
#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 JS: autism enriched in de novo mutations, rare inherited variants, and increased PRS scores.
#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 RB: Can compute the polygenic scores for each trait and see how they compare. Or correlation of effect correlations. Many ways to look at genetic correlations.