Biology subjects

Schmidt, C. J.

Publications and source records attributed to Schmidt, C. J..

4 recordsLinked to original sources

bioRxiv2023

Single Nucleus Transcriptomics Reveals Pervasive Glial Activation in Opioid Overdose Cases

Dynamic interactions of neurons and glia in the ventral midbrain (VM) mediate reward and addiction behavior. We studied gene expression in 212,713 VM single nuclei from 95 human opioid overdose cases and drug-free controls. Chronic exposure to opioids left numerical proportions of VM glial and neuronal subtypes unaltered, while broadly affecting glial transcriptomes, involving 9.5 - 6.2% of expressed genes within microglia, oligodendrocytes, and astrocytes, with prominent activation of the immune response including interferon, NFkB signaling, and cell motility pathways, sharply contrasting with down-regulated expression of synaptic signaling and plasticity genes in VM non-dopaminergic neurons. VM transcriptomic reprogramming in the context of opioid exposure and overdose included 325 genes with genetic variation linked to substance use traits in the broader population, thereby pointing to heritable risk architectures in the genomic organization of the brains reward circuitry.

neuroscience↗

bioRxiv2023

Proteomic insight into human directed evolution of the domesticated chicken Gallus gallus.

Chicken domestication began at least 3,500 years ago for purposes of divination, cockfighting, and food. Prior to industrial scale chicken production, domestication selected larger birds with increased egg production. In the mid-20th century companies began intensive selection with the broiler (meat) industry focusing on improved feed conversion, rapid growth, and breast muscle yield. Here we present proteomic analysis comparing the Ross 708 modern broiler line with the UIUC legacy line. Comparing the breast muscle proteome between modern broilers and legacy lines not selected for these growth traits identifies cellular processes that have responded to human directed evolution. Mass spectrometry was used to identify differences in protein levels in the breast muscle of 6-day old chicks from Modern and Legacy lines. The results highlighted elevated levels of stress proteins, ribosomal proteins, and proteins that participate in the innate immune pathway in the Modern chickens. Furthermore, the comparative analyses indicated differences in the levels of proteins involved in multiple biochemical pathways. In particular, the Modern line had elevated levels of proteins affecting the pentose phosphate pathway, TCA cycle, and fatty acid oxidation and reduced protein levels of the first phase of glycolysis. These analyses provide hypotheses linking the morphometric changes driven by human directed selection to biochemical pathways. The results also have implications for the onset of Wooden Breast disease that arose due to selection for rapid breast muscle growth and is a major problem in the poultry industry.

evolutionary biology↗

bioRxiv2019

VARIANT ANALYSIS PIPELINE FOR ACCURATE DETECTION OF GENOMIC VARIANTS FROM TRANSCRIPTOME SEQUENCING DATA.

The wealth of information deliverable from transcriptome sequencing (RNA-seq) is significant, however current applications for variant detection still remain a challenge due to the complexity of the transcriptome. Given the ability of RNA-seq to reveal active regions of the genome, detection of RNA-seq SNPs can prove valuable in understanding the phenotypic diversity between populations. Thus, we present a novel computational workflow named VAP (Variant Analysis Pipeline) that takes advantage of multiple RNA-seq splice aware aligners to call SNPs in non-human models using RNA-seq data only. We applied VAP to RNA-seq from a highly inbred chicken line and achieved >97% precision and >99% sensitivity when compared with the matching whole genome sequencing (WGS) data. Over 65% of WGS coding variants were identified from RNA-seq. Further, our results discovered SNPs resulting from post translational modifications, such as RNA editing, which may reveal potentially functional variation that would have otherwise been missed in genomic data. Even with the limitation in detecting variants in expressed regions only, our method proves to be a reliable alternative for SNP identification using RNA-seq data.

bioinformatics↗

bioRxiv2018

Identifying Mechanisms of Regulation to Model Carbon Flux During Heat Stress And Generate Testable Hypotheses

Understanding biological response to stimuli requires identifying mechanisms that coordinate changes across pathways. One of the promises of multi-omics studies is achieving this level of insight by simultaneously identifying different levels of regulation. However, computational approaches to integrate multiple types of data are lacking. An effective systems biology approach would be one that uses statistical methods to detect signatures of relevant network motifs and then builds metabolic circuits from these components to model shifting regulatory dynamics. For example, transcriptome and metabolome data complement one another in terms of their ability to describe shifts in physiology. Here, we extend a previously described method used to identify single nucleotide polymorphism (SNPs) associated with metabolic changes (Gieger et al., 2008). We apply this strategy to link changes in sulfur, amino acid and lipid production under heat stress by relating ratios of compounds to potential precursors and regulators. This approach provides integration of multi-omics data to link previously described, discrete units of regulation into functional pathways and hypothesizes novel biology relevant to the heat stress response.

genomics↗