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While switch-like gene expression (“on” in some individuals and “off” in others) has been linked to biological variation and disease susceptibility, a systematic analysis across tissues is lacking. Here, we analyze genomes, transcriptomes, and methylomes from 943 individuals across 27 tissues, identifying 473 switch-like genes. The identified genes are enriched for associations with cancers and immune, metabolic, and skin diseases. Only 40 (8.5%) switch-like genes show genetically controlled switch-like expression in all tissues, i.e., universally switch-like expression. The rest show switch-like expression in specific tissues. Methylation analysis suggests that genetically driven epigenetic silencing explains the universally switch-like pattern, whereas hormone-driven epigenetic modification likely underlies the tissue-specific pattern. Notably, tissue-specific switch-like genes tend to be switched on or off in unison within individuals, driven by tissue-specific master regulators. In the vagina, we identified seven concordantly switched-off genes linked to vaginal atrophy in females. Experimental analysis of vaginal tissues shows that low estrogen levels lead to decreased epithelial thickness and ALOX12 expression. We propose that switched-off driver genes in basal and parabasal epithelia suppress cell proliferation, leading to epithelial thinning and vaginal atrophy. Our findings underscore the implications of switch-like genes for diagnostic and personalized therapeutic applications. 

With the recent availability of tissue-specific gene expression data, e.g., provided by the GTEx Consortium, there is interest in comparing gene co-expression patterns across tissues. One promising approach to this problem is to use a multilayer network analysis framework and perform multilayer community detection. Communities in gene co-expression networks reveal groups of genes similarly expressed across individuals, potentially involved in related biological processes responding to specific environmental stimuli or sharing common regulatory variations. We construct a multilayer network in which each of the four layers is an exocrine gland tissue-specific gene co-expression network. We develop methods for multilayer community detection with correlation matrix input and an appropriate null model. Our correlation matrix input method identifies five groups of genes that are similarly co-expressed in multiple tissues (a community that spans multiple layers, which we call a generalist community) and two groups of genes that are co-expressed in just one tissue (a community that lies primarily within just one layer, which we call a specialist community). We further found gene co-expression communities where the genes physically cluster across the genome significantly more than expected by chance (on chromosomes 1 and 11). This clustering hints at underlying regulatory elements determining similar expression patterns across individuals and cell types. We suggest thatKRTAP3-1,KRTAP3-3, andKRTAP3-5share regulatory elements in skin and pancreas. Furthermore, we find thatCELA3AandCELA3Bshare associated expression quantitative trait loci in the pancreas. The results indicate that our multilayer community detection method for correlation matrix input extracts biologically interesting communities of genes. 

Few students with disabilities transition from undergraduate to graduate programs. Graduate students often receive ineffective and insufficient accommodations, including lack of support specific to graduate students, because disability services policies are shaped by undergraduate experiences. To understand how disability services offices accommodate graduate students: we (1) critically analyzed disability services websites of 18 U.S. institutions, and (2) interviewed 17 disability services staff. Disability services websites publicly present institutional accommodation policies and guidelines, and staff are responsible for identifying, providing, and implementing reasonable accommodations. We found that policies may be interpreted differently depending on specific student circumstances. We discuss our findings in two main themes: (a) Policies and attitudes ascribed to disability, technology, and faculty, and (b) Impacts of policies and perspectives on accommodation decisions for graduate students. The contributions of this work include an empirical investigation of institutional support for disabled graduate students and suggestions for how to improve support from disability services offices to empower students.