Decreased left heart flow in fetal lambs causes left heart hypoplasia and pro-fibrotic tissue remodeling.

Low blood flow through the fetal left heart is often conjectured as an etiology for hypoplastic left heart syndrome (HLHS). To investigate if a decrease in left heart flow results in growth failure, we generate left ventricular inflow obstruction (LVIO) in mid-gestation fetal lambs by implanting coils in their left atrium using an ultrasound-guided percutaneous technique. Significant LVIO recapitulates important clinical features of HLHS: decreased antegrade aortic valve flow, compensatory retrograde perfusion of the brain and ascending aorta (AAo) from the arterial duct, severe left heart hypoplasia, a non-apex forming LV, and a thickened endocardial layer. The hypoplastic AAo have miRNA-gene pairs annotating to cell proliferation that are inversely differentially expressed by bulk RNA-seq. Single-nucleus RNA-seq of the hypoplastic LV myocardium shows an increase in fibroblasts with a reciprocal decrease in cardiomyocyte nuclei proportions. Fibroblasts, cardiomyocytes and endothelial cells from hypoplastic myocardium have increased expression of extracellular matrix component or fibrosis genes with dysregulated fibroblast growth factor signaling. Hence, a severe sustained ( ~ 1/3 gestation) reduction in fetal left heart flow is sufficient to cause left heart hypoplasia. This is accompanied by changes in cellular composition and gene expression consistent with a pro-fibrotic environment and aberrant induction of mesenchymal programs.

Transcriptomic effects of the foraging gene shed light on pathways of pleiotropy and plasticity.

Genes are often pleiotropic and plastic in their expression, features which increase and diversify the functionality of the genome. The foraging (for) gene in Drosophila melanogaster is highly pleiotropic and a long-standing model for studying individual differences in behavior and plasticity from ethological, evolutionary, and genetic perspectives. Its pleiotropy is known to be linked to its complex molecular structure; however, the downstream pathways and interactors remain mostly elusive. To uncover these pathways and interactors and gain a better understanding of how pleiotropy and plasticity are achieved at the molecular level, we explore the effects of different for alleles on gene expression at baseline and in response to 4 h of food deprivation, using RNA sequencing analysis in different Drosophila larval tissues. The results show tissue-specific transcriptomic dynamics influenced by for allelic variation and food deprivation, as well as genotype by treatment interactions. Differentially expressed genes yielded pathways linked to previously described for phenotypes and several potentially novel phenotypes. Together, these findings provide putative genes and pathways through which for might regulate its varied phenotypes in a pleiotropic, plastic, and gene-structure-dependent manner.

Differential Expression Enrichment Tool (DEET): an interactive atlas of human differential gene expression.

Differential gene expression analysis using RNA sequencing (RNA-seq) data is a standard approach for making biological discoveries. Ongoing large-scale efforts to process and normalize publicly available gene expression data enable rapid and systematic reanalysis. While several powerful tools systematically process RNA-seq data, enabling their reanalysis, few resources systematically recompute differentially expressed genes (DEGs) generated from individual studies. We developed a robust differential expression analysis pipeline to recompute 3162 human DEG lists from The Cancer Genome Atlas, Genotype-Tissue Expression Consortium, and 142 studies within the Sequence Read Archive. After measuring the accuracy of the recomputed DEG lists, we built the Differential Expression Enrichment Tool (DEET), which enables users to interact with the recomputed DEG lists. DEET, available through CRAN and RShiny, systematically queries which of the recomputed DEG lists share similar genes, pathways, and TF targets to their own gene lists. DEET identifies relevant studies based on shared results with the user's gene lists, aiding in hypothesis generation and data-driven literature review.

Women in science: a son's perspective.

I am often asked how our mother inspired my sister Moriah and me to want to become scientists. She never directly suggested we should go down that path. Instead, she shared the aspects of the natural world, that she loved, with us while keeping the non-science aspects of her job separate from our lives at home. Now, I have learned that her perspective provides insights that spark innovative discoveries, some of which challenged the status quo. Her passion for research has allowed her to pursue what she believes to be worth studying. Her personality and collaborative nature allow her to be teased at home, facilitate a room of diverse opinions, and command a hall of hundreds of people. Her respect for those around her is inspiring. My mom's trust in her trainees and collaborators allows her to answer questions that could fundamentally not be answered had she pigeonholed herself to a single field. She managed to accomplish everything while being nothing other than my mom to me, and I am so glad that I am growing into a person who can truly appreciate the woman she is to everyone else.

Single-cell mapper (scMappR): using scRNA-seq to infer the cell-type specificities of differentially expressed genes.

RNA sequencing (RNA-seq) is widely used to identify differentially expressed genes (DEGs) and reveal biological mechanisms underlying complex biological processes. RNA-seq is often performed on heterogeneous samples and the resulting DEGs do not necessarily indicate the cell-types where the differential expression occurred. While single-cell RNA-seq (scRNA-seq) methods solve this problem, technical and cost constraints currently limit its widespread use. Here we present single cell Mapper (scMappR), a method that assigns cell-type specificity scores to DEGs obtained from bulk RNA-seq by leveraging cell-type expression data generated by scRNA-seq and existing deconvolution methods. After evaluating scMappR with simulated RNA-seq data and benchmarking scMappR using RNA-seq data obtained from sorted blood cells, we asked if scMappR could reveal known cell-type specific changes that occur during kidney regeneration. scMappR appropriately assigned DEGs to cell-types involved in kidney regeneration, including a relatively small population of immune cells. While scMappR can work with user-supplied scRNA-seq data, we curated scRNA-seq expression matrices for ∼100 human and mouse tissues to facilitate its stand-alone use with bulk RNA-seq data from these species. Overall, scMappR is a user-friendly R package that complements traditional differential gene expression analysis of bulk RNA-seq data.

The Drosophila foraging gene human orthologue PRKG1 predicts individual differences in the effects of early adversity on maternal sensitivity.

There is variation in the extent to which childhood adverse experience affects adult individual differences in maternal behavior. Genetic variation in the animal foraging gene, which encodes a cGMP-dependent protein kinase, contributes to variation in the responses of adult fruit flies, Drosophila melanogaster, to early life adversity and is also known to play a role in maternal behavior in social insects. Here we investigate genetic variation in the human foraging gene (PRKG1) as a predictor of individual differences in the effects of early adversity on maternal behavior in two cohorts. We show that the PRKG1 genetic polymorphism rs2043556 associates with maternal sensitivity towards their infants. We also show that rs2043556 moderates the association between self-reported childhood adversity of the mother and her later maternal sensitivity. Mothers with the TT allele of rs2043556 appeared buffered from the effects of early adversity, whereas mothers with the presence of a C allele were not. Our study used the Toronto Longitudinal Cohort (N=288 mother-16 month old infant pairs) and the Maternal Adversity and Vulnerability and Neurodevelopment Cohort (N=281 mother-18 month old infant pairs). Our findings expand the literature on the contributions of both genetics and gene-environment interactions to maternal sensitivity, a salient feature of the early environment relevant for child neurodevelopment.