Search for: All records

Abstract Living in nutrient-poor environments, the carnivorous Venus flytrapDionaea muscipulacaptures animal prey to compensate for this deficiency. Stimulation of trigger hairs located on the inner trap surface elicits an action potential (AP). While two consecutive APs result in fast trap closure in wildtype (WT) plants, sustained AP generation by the insect struggling to escape the trap leads to jasmonic acid (JA) biosynthesis, formation of the digestive “stomach”, and release of enzymes needed to decompose the victim. TheDionaea muscipulaDYSCALCULIA (DYSC) mutant is able to fire touch-induced APs, but unlike WT plants, it does not snap-close its traps after two consecutive APs. Moreover, DYSC plants fail to properly initiate the JA pathway in response to mechanostimulation and even wounding, a well-known JA-dependent process conserved among plants. As demonstrated in previous studies, this DYSC mutant defect is associated with impaired decoding of mechanostimulation (i.e. touch) -induced Ca²⁺signals. External JA application to the trap, however, restores slow trap closure and digestive gland function in DYSC, while rapid trap closure is JA-independent and cannot be rescued by exogenous JA application. Higher frequency mechanostimulation and thus more APs, however, revealed that DYSC is still able to close its traps, albeit much slower than WT plants. To reveal the molecular underpinnings of DYSC’s delayed trap movement, we generated a chromosome-scaleDionaeagenome assembly and profiled gene expression. The refined transcriptomic analysis uncovered widespread misregulation of cell wall-related genes in DYSC, implicating altered cell wall plasticity in the sluggish mutant. Cell indentation studies by atomic force microscopy revealed a strictly localized and strikingly enhanced stiffening of the cell wall for DYSC that may hinder rapid trap closure and snap buckling. Together, these genomic, transcriptomic, and biophysical data identify cell wall elasticity as a key constraint on voltage and Ca²⁺dependent trap kinetics. This finding documents the interrelationship between mechanosensing and Ca²⁺signaling in the ultrafast capture organ of the Venus flytrap. 

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. 

Abstract Structural variants have a considerable impact on human genomic diversity. However, their evolutionary history remains mostly unexplored. Here, we developed a new method to identify potentially adaptive structural variants based on a similarity-based analysis that incorporates genotype frequency data from 26 populations simultaneously. Using this method, we analyzed 57,629 structural variants and identified 576 structural variants that show unusual population differentiation. Of these putatively adaptive structural variants, we further showed that 24 variants are multiallelic and overlap with coding sequences, and 20 variants are significantly associated with GWAS traits. Closer inspection of the haplotypic variation associated with these putatively adaptive and functional structural variants reveals deviations from neutral expectations due to: 1) population differentiation of rapidly evolving multiallelic variants, 2) incomplete sweeps, and 3) recent population-specific negative selection. Overall, our study provides new methodological insights, documents hundreds of putatively adaptive variants, and introduces evolutionary models that may better explain the complex evolution of structural variants. 

Abstract Chemosensation (olfaction, taste) is essential for detecting and assessing foods, such that dietary shifts elicit evolutionary changes in vertebrate chemosensory genes. The transition from hunting and gathering to agriculture dramatically altered how humans acquire food. Recent genetic and linguistic studies suggest agriculture may have precipitated olfactory degeneration. Here, we explore the effects of subsistence behaviors on olfactory (OR) and taste (TASR) receptor genes among rainforest foragers and neighboring agriculturalists in Africa and Southeast Asia. We analyze 378 functionalORand 26 functionalTASRgenes in 133 individuals across populations in Uganda (Twa, Sua, BaKiga) and the Philippines (Agta, Mamanwa, Manobo) with differing subsistence histories. We find no evidence of relaxed selection on chemosensory genes in agricultural populations. However, we identify subsistence-related signatures of local adaptation on chemosensory genes within each geographic region. Our results highlight the importance of culture, subsistence economy, and drift in human chemosensory perception. 

Abstract Lipids are emerging as key regulators of apoptosis. Specific lipid species are associated with apoptosis with important functional roles, but the understanding of the regulation of these lipid species is still limited. It has been previously shown by our laboratory that polyunsaturated triacylglycerols accumulate and get stored within lipid droplets during apoptosis via activated glycerolipid biosynthesis. In this work, the biochemical mechanisms that result in the activation of glycerolipid biosynthesis and, consequently, triacylglycerol and lipid droplet accumulation during apoptosis are investigated. The transcriptomes of control and apoptotic HCT‐116 cells are compared and gene enrichment analysis revealed the upregulation of p38 mitogen‐activated protein kinase (MAPK). It is shown that p38 MAPK regulates triacylglycerol biosynthesis through diacylglycerol acyltransferase1 during apoptosis. Perilipin 2 and cytosolic phospholipase A2delta are also shown to be involved in lipid droplet and polyunsaturated triacylglycerol accumulation in this process. Overall, the results provide new insights into the upregulation of glycerolipid synthesis during apoptosis. 

In October 2021, 59 scientists from 14 countries and 13 U.S. states collaborated virtually in the Third Annual Baylor College of Medicine & DNANexus Structural Variation hackathon. The goal of the hackathon was to advance research on structural variants (SVs) by prototyping and iterating on open-source software. This led to nine hackathon projects focused on diverse genomics research interests, including various SV discovery and genotyping methods, SV sequence reconstruction, and clinically relevant structural variation, including SARS-CoV-2 variants. Repositories for the projects that participated in the hackathon are available at https://github.com/collaborativebioinformatics.