Trends in Genetics最新文献

As the field of spatial omics continues to expand, the spatially resolved profiling of microRNA (miRNA) expression in tissues, or 'spatial miRNomics,' remains in its infancy, with only a few initial pioneering studies to date. MiRNA expression exhibits distinct spatial, temporal, and cell type-specific patterns, and the dysregulation of these patterns is associated with numerous pathological conditions. This highlights the potential of miRNAs as targets for spatial transcriptomic studies in translational and clinical research. In this review, we examine the current landscape of spatial technologies for miRNA detection, from foundational methods to cutting-edge innovations, and we discuss conceptual and technical challenges. We also outline the biomedical implications of spatial miRNA profiling and set out future directions for exploring the spatial dimension of gene regulation.

Small nuclear ribonucleoproteins (snRNPs) U1/U2/U4/U6 are critical constituents of the spliceosome. Recent studies showed that each of them exhibits a role in the inhibition of global PCPA (premature cleavage and polyadenylation), thereby supporting the hypothesis that the splicing process inhibits PCPA. In this forum article we summarize evidence to reinforce this hypothesis and envision potential mechanisms.

Genomic landscapes of introgression provide valuable information on how different evolutionary processes interact and leave signatures in genomes. The recent expansion of genomic datasets across diverse taxa, together with advances in methodological development, have created new opportunities to investigate the impact of introgression along individual genomes in various clades, making the precise identification of introgressed loci a rapidly evolving area of research. In this review we summarize recent methodological progress within three major categories: summary statistics, probabilistic modeling, and supervised learning. We examine how these approaches have been applied to data beyond humans and discuss the challenges associated with their application. Finally, we outline future directions for each category, including accessible implementation, transparent analysis, and systematic benchmarking.

How do new species arise? This is among the most fundamental questions in evolutionary biology. The first genetic model for how reproductive barriers lead to the origin of new species was proposed nearly 90 years ago. However, empirical evidence for the genetic mechanisms that cause reproductive barriers took many decades to accumulate. In 2010, Presgraves presented a comprehensive review of the literature on known 'speciation genes' and the possible evolutionary mechanisms through which they arose. Fifteen years later, with an explosion of studies that include both non-model and model organisms, the number of known hybrid incompatibility genes has increased approximately sevenfold. Here, we synthesize previous and new empirical examples to investigate the genetic mechanisms through which intrinsic incompatibilities in hybrids arise and highlight current gaps in our understanding.

Public interpretations of genetic science in popular media shape its meaning, regulation, and sometimes even its trajectory. Drawing on examples from film and television, we argue that cultural narratives are not merely reflections of science but active forces in the production of genetic meaning.

The concurrent processes of DNA replication and RNA transcription pose a significant challenge to genome integrity. Nascent RNA, the newly synthesized transcript, is emerging as a critical determinant of transcription-replication conflict (TRC) outcomes, exerting influence through its modifications, its ability to form RNA:DNA hybrids (R-loops), its regulation of chromatin structure, and its interaction with protein complexes at the transcription-replication interface. Here, we synthesize recent advances on how nascent RNA modulates transcription dynamics, replication fork progression, and genome stability. We explore its paradoxical roles - both inducing replication stress and orchestrating protective responses - highlighting how RNA processing factors mitigate TRCs. Finally, we emphasize the need for innovative technologies to dissect the dynamic and context-dependent roles of nascent RNA and therapeutic potential for genomic instability-linked diseases.

Small nucleolar RNAs (snoRNAs), traditionally regarded as guides for RNA modification, have emerged as critical regulators of tumor progression and treatment resistance. This review comprehensively outlines the roles of snoRNAs and their host genes in mediating cancer treatment resistance, with an emphasis on mechanisms involving epigenetic regulation, metabolic reprogramming, and tumor microenvironment (TME) remodeling. It further explores their potential as predictive biomarkers for cancer diagnosis, prognosis, and treatment response. In addition, the review addresses current technical challenges related to detection standardization and clinical translation. Future research is expected to establish a solid theoretical foundation and practical strategies to overcome drug resistance and promote the development of personalized cancer therapy.

Genomics research has historically been biased toward individuals of European ancestry, which has the potential to exacerbate health inequities (Martin, A.R. et al.) To reduce these disparities, current efforts in human genetics emphasize the inclusion of diverse populations (All of Us Research Program Investigators). Here, we highlight recent preprints that focus on the intricacies of researching participants with multiple genetic ancestries.

Transcriptional cis-regulation has emerged as the predominant force underlying the evolution of phenotypic diversity, yet our understanding of it is still rudimentary. While empirical comparative genomic approaches have been quite informative, they also suffer from numerous confounders and limited scalability. Here we propose using machine-learning-based methods that predict cis-regulatory activity from DNA sequence to perform in silico 'genome transplants' to predict cis-regulatory features as if the genome from one species had been transplanted into the nuclei of another species. Inference of natural selection from the resulting genome-wide catalogs of cis-regulatory divergence could be far more powerful, efficient, and widely applicable than current empirical approaches, enabling unprecedented insights into the genetic basis of biodiversity across the tree of life.