Abstract Regulated gene expression in bacteria accommodates demands imposed by different environments. In addition to ensuring the production of required metabolic and structural components, gene regulation protects bacteria against the adverse effects of misexpression. Upon encountering a novel environment, such as sustained exposure to antibiotics, transcriptional recalibration ensues to improve fitness. For antibiotics, this involves enhancing the expression of an existing repertoire of resistance mechanisms and is often mediated by mutations in regulators of gene expression. Here, we review how diverse gene regulatory mutations confer antibiotic resistance to bacterial pathogens. We view these strategies through the lens of the Gene Expression Demand Theory, originally proposed for inducible operons involved in sugar metabolism, and describe the molecular basis and evolutionary consequences for a few well-studied examples. Broad underlying preferences of when and which kind of regulatory mutations bacteria employ emerge from these examples. A key pattern appears to be a preference for derepression rather than activating mutations, and we highlight potential underlying genetic and evolutionary explanations. Finally, even as our knowledge of molecular mechanisms of antibiotic adaptation continues to expand, we propose that adaptation by regulatory mutations provides a framework for assessing the risk of resistance evolution in the case of novel antibiotics and alternative targets for diagnostic and therapeutic interventions.
Abstract Deciphering the genetic basis of complex traits increasingly leverages intermediate molecular layers (“in-between-omes,” eg the transcriptome) in association studies such as transcriptome-wide association studies. Despite many emerging statistical and machine-learning approaches, there is no flexible standard for simulating phenotypes from genotypes while explicitly modeling the role of an in-between-ome, especially under nonlinear architectures (eg co-expression networks). This gap hampers fair power estimation and rigorous benchmarking. We present OmeSim, a configurable simulator that jointly generates genotype, an in-between-ome, and phenotype, capturing complex (including nonlinear) relationships. OmeSim outputs the full generative/causal graph together with data matrices and the induced correlation and association structures, providing gold-standard datasets for developing and evaluating methods that integrate an in-between-ome into genotype–phenotype studies. We validate OmeSim by comparing simulated human transcriptomes to real human transcriptomes and by benchmarking alternative association-mapping tools, demonstrating its utility for reproducible power analyses and method comparison in multi-omics integration. Source code and documentation: https://github.com/zhoulongcoding/OmeSim.
Abstract Pathogenic variants in SNRPB, a common core spliceosomal factor, cause Cerebrocostomandibular Syndrome (CCMS). Most CCMS-associated variants result in increased inclusion of a PTC-containing alternative exon 2 (AE2). Using CRISPR/Cas9 we generated two mutant mice that carried a 46bp or a 61bp deletion upstream of Snrpb AE2. Mice and embryos carrying the 46bp deletion are normal. Whereas heterozygous and homozygous mutant embryos carrying the 61bp deletion (Δ61) exhibited smaller heads, micrognathia, malformations in the bones of the craniofacial region and ribs, and reduced survival, at low penetrance. Embryos homozygous for Δ61 showed a tendency towards increased inclusion of AE2 and reduced levels of Snrpb. In addition, this deletion increased the penetrance and severity of defects in Snrpbncc and Snrpbmes mutant embryos. Our findings indicate that this intronic region is important for SNRPB regulation in mice and should be investigated in CCMS patients that do not carry mutations in SNRPB coding exons.
Abstract Germline-restricted chromosomes (GRCs) constitute a unique class of chromosomes confined to germ cells. Arising in multiple evolutionarily distant lineages, GRCs have been identified in three insect families (non-biting midges, gall midges, and fungus gnats), each within the order Diptera. Genomic characterisation in fungus gnats has revealed GRCs to be large, gene-rich chromosomes, which, together with their persistence over millennia, implies they play important biological roles within this clade. However, transcription from these chromosomes has yet to be demonstrated, leaving key questions about their function and activity unresolved. Here, we present the first direct analysis of GRC transcription in Diptera, combining immunofluorescence staining with bulk RNA-seq data in the fungus gnat Bradysia coprophila (Sciaridae). We find that transcription from GRCs is highly limited during key developmental stages. In larval and adult gonads, elongating polymerase II appears to be active at all chromosomes except the GRCs in most cells. Furthermore, using stringent filtering criteria, we identify only 10 confidently expressed GRC-linked genes, mostly of unknown function. In addition, we report the surprising presence of a ∼290 kb region of bacterial-derived sequence on GRC2, likely acquired through horizontal transfer from germline-associated endosymbionts. Overall, these findings identify GRCs in fungus gnats as unique chromosomes, largely transcriptionally quiescent during key stages of B. coprophila development, yet capable of maintaining both endogenous and potentially horizontally acquired genes over evolutionary timescales. This raises fundamental questions about the mechanisms that maintain gene content in these chromosomes and their contribution, if any, to germline biology.
