Biology subjects

Donovan, M. K. R.

Publications and source records attributed to Donovan, M. K. R..

8 recordsLinked to original sources

bioRxiv2023

Protein Coronas on Functionalized Nanoparticles Enable Quantitative and Precise Large-Scale Deep Plasma Proteomics

BackgroundThe wide dynamic range of circulating proteins coupled with the diversity of proteoforms present in plasma has historically impeded comprehensive and quantitative characterization of the plasma proteome at scale. Automated nanoparticle (NP) protein corona-based proteomics workflows can efficiently compress the dynamic range of protein abundances into a mass spectrometry (MS)-accessible detection range. This enhances the depth and scalability of quantitative MS-based methods, which can elucidate the molecular mechanisms of biological processes, discover new protein biomarkers, and improve comprehensiveness of MS-based diagnostics. MethodsInvestigating multi-species spike-in experiments and a cohort, we investigated fold-change accuracy, linearity, precision, and statistical power for the using the Proteograph Product Suite, a deep plasma proteomics workflow, in conjunction with multiple MS instruments. ResultsWe show that NP-based workflows enable accurate identification (false discovery rate of 1%) of more than 6,000 proteins from plasma (Orbitrap Astral) and, compared to a gold standard neat plasma workflow that is limited to the detection of hundreds of plasma proteins, facilitate quantification of more proteins with accurate fold-changes, high linearity, and precision. Furthermore, we demonstrate high statistical power for the discovery of biomarkers in small- and large-scale cohorts. ConclusionsThe automated NP workflow enables high-throughput, deep, and quantitative plasma proteomics investigation with sufficient power to discover new biomarker signatures with a peptide level resolution.

biochemistry↗

bioRxiv2022

Peptide-centric analyses of human plasma enable increased resolution of biological insights into non-small cell lung cancer relative to protein-centric analysis

Advancements in deep plasma proteomics are enabling high-resolution measurement of plasma proteoforms, which may reveal a rich source of novel biomarkers previously concealed by aggregated protein methods. Here, we analyze 188 plasma proteomes from non-small cell lung cancer subjects (NSCLC) and controls to identify NSCLC-associated protein isoforms by examining differentially abundant peptides as a proxy for isoform-specific exon usage. We find four proteins comprised of peptides with opposite patterns of abundance between cancer and control subjects. One of these proteins, BMP1, has known isoforms that can explain this differential pattern, for which the abundance of the NSCLC-associated isoform increases with stage of NSCLC progression. The presence of cancer and control-associated isoforms suggests differential regulation of BMP1 isoforms. The identified BMP1 isoforms have known functional differences, which may reveal insights into mechanisms impacting NSCLC disease progression.

cancer biology↗

bioRxiv2021

In heart failure reactivation of RNA-binding proteins drives the transcriptome into a fetal state

Transcriptome-wide expression changes occur during heart failure, including reactivation of fetal-specific isoforms. However, the underlying molecular mechanisms and the extent to which a fetal gene program switch occurs remains unclear. Limitations hindering transcriptome-wide analyses of alternative splicing differences (i.e. isoform switching) in cardiovascular system (CVS) tissues between fetal and adult (healthy and diseased) stages have included both cellular heterogeneity across bulk RNA-seq samples and limited availability of fetal tissue for research. To overcome these limitations, we have deconvoluted the cellular compositions of 996 RNA-seq samples representing heart failure, healthy adult (heart and arteria), and fetal-like (iPSC-derived cardiovascular progenitor cells) CVS tissues. Comparison of the expression profiles revealed that RNA-binding proteins (RBPs) are highly overexpressed in fetal-like compared with healthy adult and are reactivated in heart failure, which results in expression of thousands fetal-specific isoforms. Of note, isoforms for 20 different RBPs were among those that reverted in heart failure to the fetal-like expression pattern. We determined that, compared with adult-specific isoforms, fetal-specific isoforms are more likely to bind RBPs, have canonical sequences at their splice sites and encode proteins with more functions. Our findings suggest targeting RBP fetal-specific isoforms could result in novel therapeutics for heart failure.

genomics↗

bioRxiv2021

iPSC-derived pancreatic progenitors are an optimal model system to study T2D regulatory variants active during fetal development of the pancreas

The impact of genetic regulatory variation active in early pancreatic development on adult pancreatic disease and traits is not well understood. Here, we generate a panel of 107 fetal-like iPSC-derived pancreatic progenitor cells (iPSC-PPCs) from whole genome-sequenced individuals and identify 4,065 genes and 4,016 isoforms whose expression and/or alternative splicing are affected by regulatory variation. We integrate eQTLs identified in adult islets and whole pancreas samples, which reveal 1,805 eQTL associations that are unique to the fetal-like iPSC-PPCs and 1,043 eQTLs that exhibit regulatory plasticity across the fetal-like and adult pancreas tissues. Colocalization with GWAS risk loci for pancreatic diseases and traits show that some putative causal regulatory variants are active only in the fetal-like iPSC-PPCs and likely influence disease by modulating expression of disease-associated genes in early development, while others with regulatory plasticity likely exert their effects in both the fetal and adult pancreas by modulating expression of different disease genes in the two developmental stages.

genomics↗

bioRxiv2019

Structural variant classes and short tandem repeats differentially impact gene expression and complex traits

Structural variants (SVs) and short tandem repeats (STRs) comprise a broad group of diverse DNA variants which vastly differ in their sizes and distributions across the genome. Here, we show that different SV classes and STRs differentially impact gene expression and complex traits. Functional differences between SV classes and STRs include their genomic locations relative to eGenes, likelihood of being associated with multiple eGenes, associated eGene types (e.g., coding, noncoding, level of evolutionary constraint), effect sizes, linkage disequilibrium with tagging single nucleotide variants used in GWAS, and likelihood of being associated with GWAS traits. We also identified a set of high-impact SVs/STRs associated with the expression of three or more eGenes via chromatin loops and showed they are highly enriched for being associated with GWAS traits. Our study provides insights into the genomic properties of structural variant classes and short tandem repeats that impact gene expression and human traits.

genomics↗

bioRxiv2019

Cellular deconvolution of GTEx tissues powers eQTL studies to discover thousands of novel disease and cell-type associated regulatory variants

The Genotype-Tissue Expression (GTEx) resource has contributed a wealth of novel insights into the regulatory impact of genetic variation on gene expression across human tissues, however thus far has not been utilized to study how variation acts at the resolution of the different cell types composing the tissues. To address this gap, using liver and skin as a proof-of-concept tissues, we show that readily available signature genes based on expression profiles of mouse cell types can be used to deconvolute the cellular composition of human GTEx tissues. We then deconvoluted 6,829 bulk RNA-seq samples corresponding to 28 GTEx tissues and show that we are able to quantify cellular heterogeneity, determining both the different cell types present in each of the tissues and how their proportions vary between samples of the same tissue type. Conducting eQTL analyses for GTEx liver and skin samples using cell type composition estimates as interaction terms, we identified thousands of novel genetic associations that had lower effect sizes and were cell-type-associated. We further show that cell-type-associated eQTLs in skin colocalize with melanoma, malignant neoplasm, and infection signatures, indicating variants that influence gene expression in distinct skin cell types play important roles in skin traits and disease. Overall, our study provides a framework to estimate the relative fractions of different cell types in GTEx tissues using signature genes from mouse cell types and functionally characterize human genetic variation that impacts gene expression in a cell-type-specific manner.

genetics↗

bioRxiv2019

Human iPSC gene signatures and X chromosome dosage impact response to WNT inhibition and cardiac differentiation fate

Non-genetic variability in human induced pluripotent stem cell (iPSC) lines impacts their differentiation outcome, limiting their utility for genetic studies and clinical applications. Despite the importance of understanding how non-genetic molecular variability influences iPSC differentiation outcome, large-scale studies capable of addressing this question have not yet been conducted. Here, we performed 258 directed differentiations of 191 iPSC lines using established protocols to generate iPSC-derived cardiovascular progenitor cells (iPSC-CVPCs). We observed cellular heterogeneity across the iPSC-CVPC samples due to varying fractions of two cell types: cardiomyocytes (CMs) and epicardium-derived cells (EPDCs). Analyzing the transcriptomes of CM-fated and EPDC-fated iPSCs discovered that 91 signature genes and X chromosome dosage differences influence WNT inhibition response during differentiation and are associated with cardiac fate. Analysis of an independent set of 39 iPSCs differentiated to the cardiac lineage confirmed shared sex and transcriptional differences that impact cardiac fate outcome. The scale and systematic approach of our study enabled novel insights into how iPSC transcriptional and X chromosome gene dosage differences influence WNT signaling during differentiation and hence cardiac cell fate.

genomics↗

bioRxiv2018

Using deep whole genome sequence, transcriptome and epigenome data to characterize the mutational burden of induced pluripotent stem cells

To understand the mutational burden of human induced pluripotent stem cells (iPSCs), we whole genome sequenced 18 fibroblast-derived iPSC lines and identified different classes of somatic mutations based on structure, origin and frequency. Copy number alterations affected 295 kb in each sample and strongly impacted gene expression. UV-damage mutations were present in ~45% of the iPSCs and accounted for most of the observed heterogeneity in mutation rates across lines. Subclonal mutations (not present in all iPSCs within a line) composed 10% of point mutations, and compared with clonal variants, showed an enrichment in active promoters and increased association with altered gene expression. Our study shows that, by combining WGS, transcriptome and epigenome data, we can understand the mutational burden of each iPSC line on an individual basis and suggests that this information could be used to prioritize iPSC lines for models of specific human diseases and/or transplantation therapy.

genomics↗