Biology subjects

Peterson, A. S.

Publications and source records attributed to Peterson, A. S..

4 recordsLinked to original sources

bioRxiv2020

South Asian patient population genetics reveal strong founder effects and high rates of homozygosity - new resources for precision medicine

Population-scale genetic studies can identify drug targets and allow disease risk to be predicted with resulting benefit for management of individual health risks and system-wide allocation of health care delivery resources. Although population-scale projects are underway in many parts of the world, genetic variation between population groups means that additional projects are warranted. South Asia has a population whose genetics is the least characterized of any of the worlds major populations. Here we describe GenomeAsia studies that characterize population structure in South Asia and that create tools for economical and accurate genotyping at population-scale. Prior work on population structure characterized isolated population groups, the relevance of which to large-scale studies of disease genetics is unclear. For our studies we used whole genome sequence information from 4,807 individuals recruited in the health care delivery systems of Pakistan, India and Bangladesh to ensure relevance to population-scale studies of disease genetics. We combined this with WGS data from 927 individuals from isolated South Asian population groups, and developed a custom SNP array (called SARGAM) that is optimized for future human genetic studies in South Asia. We find evidence for high rates of reproductive isolation, endogamy and consanguinity that vary across the subcontinent and that lead to levels of homozygosity that approach 100 times that seen in outbred populations. We describe founder effects that increase the power to associate functional variants with disease processes and that make South Asia a uniquely powerful place for population-scale genetic studies.

genomics↗

bioRxiv2019

Heterogeneity of satellite cells implicates DELTA1/ NOTCH2 signaling in self-renewal

How satellite cells and their progenitors balance differentiation and self-renewal to achieve sustainable tissue regeneration is not well understood. A major roadblock to understanding satellite cell fate decisions has been the difficulty to study this process in vivo. By visualizing expression dynamics of myogenic transcription factors during early regeneration in vivo, we identified the time point at which cells undergo decisions to differentiate or self-renew. Single-cell RNA sequencing revealed heterogeneity of satellite cells during both muscle homeostasis and regeneration, including a subpopulation enriched in Notch2 receptor expression. Furthermore, we reveal that differentiating cells express the Dll1 ligand. Using antagonistic antibodies we demonstrate that the DLL1 and NOTCH2 signaling pair is required for satellite cell self-renewal. Thus, differentiating cells provide the self-renewing signal during regeneration, enabling proportional regeneration in response to injury while maintaining the satellite cell pool. These findings have implications for therapeutic control of muscle regeneration.

cell biology↗

bioRxiv2018

Evaluating the quality of the 1000 Genomes Project data

Data from the 1000 Genomes project is quite often used as a reference for human genomic analysis. However, its accuracy needs to be assessed to understand the quality of predictions made using this reference. We present here an assessment of the genotype, phasing, and imputation accuracy data in the 1000 Genomes project. We compare the phased haplotype calls from the 1000 Genomes project to experimentally phased haplotypes for 28 of the same individuals sequenced using the 10X Genomics platform. We observe that phasing and imputation for rare variants are unreliable, which likely reflects the limited sample size of the 1000 Genomes project data. Further, it appears that using a population specific reference panel does not improve the accuracy of imputation over using the entire 1000 Genomes data set as a reference panel. We also note that the error rates and trends depend on the choice of definition of error, and hence any error reporting needs to take these definitions into account.

genomics↗

bioRxiv2018

Single-Cell RNA-seq Reveals a Subpopulation of Cells Underlying β Cell Expansion in the Postnatal Islets

Pancreatic {beta} cells undergo significant expansion and maturation during human and rodent postnatal development. Here, we used single-cell RNA-seq to characterize gene expression patterns at various stages of mouse islet cell development and uncovered a population of cells that is most abundant during the early postnatal period. This cell population lacks expression of FLTP and expresses PDGF receptors. Each of these conditions have previously been associated with proliferative capacity in {beta} cells suggesting that we have identified the proliferative competent of {beta} cell mass expansion. The subpopulation co-express many endocrine lineage-specific genes and exhibits a downregulation of genes associated with mitochondrial oxidative phosphorylation and global protein synthesis. It has upregulated activity of genes in the Wnt, Hippo, PDGF, and Notch pathways and has a significantly higher proliferation potential than the more mature {beta} population. We show that activity of the Notch pathway is required in postnatal {beta} cell expansion where it serves to maintain an undifferentiated endocrine state in the polyhormonal cell population. Collectively, our study identifies a proliferative, progenitor-like cell subpopulation in the postnatal islet as the source of postnatal {beta} cell expansion.

developmental biology↗