Biology subjects

Guo, M. H.

Publications and source records attributed to Guo, M. H..

3 recordsLinked to original sources

bioRxiv2018

Estimating yields of prenatal carrier screening and implications for design of expanded carrier screening panels

PurposePrenatal genetic carrier screening can identify parents at risk of having a child affected by a recessive condition. However, the conditions/genes most appropriate for screening remain a matter of debate. Estimates of carrier rates across genes are needed to guide construction of carrier screening panels.\n\nMethodsWe leveraged an exome sequencing database (n=123,136) to estimate carrier rates across 6 major ancestries for 416 genes associated with severe recessive conditions.\n\nResults36.5% (East Asian) to 65% (Ashkenazi Jewish) of individuals are variant carriers in at least one of the 416 genes. For couples, screening all 416 genes would identify 0.4-2.8% of couples as being at-risk for having a child affected by one of these conditions. Screening just the 47 genes with carrier rate > 1.0% would identify more than 85% of these at-risk couples. An ancestry-specific panel designed to capture genes with carrier rates > 1.0% would include 6 to 30 genes, while a comparable pan-ethnic panel would include 47 genes.\n\nConclusionOur work guides the design of carrier screening panels and provides data to assist in counseling prospective parents. Our results highlight a high cumulative carrier rate across genes, underscoring the need for careful selection of genes for screening.

genomics↗

bioRxiv2018

The Genetic Landscape of Diamond-Blackfan Anemia

Diamond-Blackfan anemia (DBA) is a rare bone marrow failure disorder that affects 1 in 100,000 to 200,000 live births and has been associated with mutations in components of the ribosome. In order to characterize the genetic landscape of this genetically heterogeneous disorder, we recruited a cohort of 472 individuals with a clinical diagnosis of DBA and performed whole exome sequencing (WES). Overall, we identified rare and predicted damaging mutations in likely causal genes for 78% of individuals. The majority of mutations were singletons, absent from population databases, predicted to cause loss of function, and in one of 19 previously reported genes encoding for a diverse set of ribosomal proteins (RPs). Using WES exon coverage estimates, we were able to identify and validate 31 deletions in DBA associated genes. We also observed an enrichment for extended splice site mutations and validated the diverse effects of these mutations using RNA sequencing in patientderived cell lines. Leveraging the size of our cohort, we observed several robust genotype-phenotype associations with congenital abnormalities and treatment outcomes. In addition to comprehensively identifying mutations in known genes, we further identified rare mutations in 7 previously unreported RP genes that may cause DBA. We also identified several distinct disorders that appear to phenocopy DBA, including 9 individuals with biallelic CECR1 mutations that result in deficiency of ADA2. However, no new genes were identified at exome-wide significance, suggesting that there are no unidentified genes containing mutations readily identified by WES that explain > 5% of DBA cases. Overall, this comprehensive report should not only inform clinical practice for DBA patients, but also the design and analysis of future rare variant studies for heterogeneous Mendelian disorders.

genetics↗

bioRxiv2018

Interrogation of human hematopoiesis at single-cell and single-variant resolution

Incomplete annotation of cell-to-cell state variance and widespread linkage disequilibrium in the human genome represent significant challenges to elucidating mechanisms of trait-associated genetic variation. Here, using data from the UK Biobank, we perform genetic fine-mapping for 16 blood cell traits to quantify posterior probabilities of association while allowing for multiple independent signals per region. We observe an enrichment of fine-mapped variants in accessible chromatin of lineage-committed hematopoietic progenitor cells. Further, we develop a novel analytic framework that identifies \"core gene\" cell type enrichments and show that this approach uniquely resolves relevant cell types within closely related populations. Applying our approach to single cell chromatin accessibility data, we discover significant heterogeneity within classically defined multipotential progenitor populations. Finally, using several lines of empirical evidence, we identify relevant cell types, predict target genes, and propose putative causal mechanisms for fine-mapped variants. In total, our study provides an analytic framework for single-variant and single-cell analyses to elucidate putative causal variants and cell types from GWAS and high-resolution epigenomic assays.

genetics↗