Trends in Genetics最新文献

Euglenids have long been studied due to their unique physiology and versatile metabolism, providing underpinnings for much of our understanding of photosynthesis and biochemistry, and a growing opportunity in biotechnology. Until recently there has been a lack of genetic studies due to their large and complex genomes, but recently new technologies have begun to unveil their genetic capabilities. Whilst much research has focused on the model organism Euglena gracilis, other members of the euglenids have now started to receive due attention. Currently only poor nuclear genome assemblies of E. gracilis and Rhabdomonas costata are available, but there are many more plastid genome sequences and an increasing number of transcriptomes. As more assemblies become available, there are great opportunities to understand the fundamental biology of these organisms and to exploit them for biotechnology.

Allele-specific expression (ASE) is a powerful signal that can be used to investigate multiple molecular mechanisms, such as cis-regulatory effects and imprinting. Single-cell RNA-sequencing (scRNA-seq) enables ASE characterization at the resolution of individual cells. In this review, we highlight the computational methods for processing and analyzing single-cell ASE data. We first describe a bioinformatics pipeline to obtain ASE counts from raw reads synthesized from previous literature. We then discuss statistical methods for detecting allelic imbalance and its variability across conditions using scRNA-seq data. In addition, we describe other methods that use single-cell ASE to address specific biological questions. Finally, we discuss future directions and emphasize the need for an integrated, optimized bioinformatics pipeline, and further development of statistical methods for different technologies.

Harnessing cutting-edge technologies to enhance crop productivity is a pivotal goal in modern plant breeding. Artificial intelligence (AI) is renowned for its prowess in big data analysis and pattern recognition, and is revolutionizing numerous scientific domains including plant breeding. We explore the wider potential of AI tools in various facets of breeding, including data collection, unlocking genetic diversity within genebanks, and bridging the genotype-phenotype gap to facilitate crop breeding. This will enable the development of crop cultivars tailored to the projected future environments. Moreover, AI tools also hold promise for refining crop traits by improving the precision of gene-editing systems and predicting the potential effects of gene variants on plant phenotypes. Leveraging AI-enabled precision breeding can augment the efficiency of breeding programs and holds promise for optimizing cropping systems at the grassroots level. This entails identifying optimal inter-cropping and crop-rotation models to enhance agricultural sustainability and productivity in the field.

Genome-wide association studies (GWASs) have identified numerous genetic loci associated with human traits and diseases. However, pinpointing the causal genes remains a challenge, which impedes the translation of GWAS findings into biological insights and medical applications. In this review, we provide an in-depth overview of the methods and technologies used for prioritizing genes from GWAS loci, including gene-based association tests, integrative analysis of GWAS and molecular quantitative trait loci (xQTL) data, linking GWAS variants to target genes through enhancer-gene connection maps, and network-based prioritization. We also outline strategies for generating context-dependent xQTL data and their applications in gene prioritization. We further highlight the potential of gene prioritization in drug repurposing. Lastly, we discuss future challenges and opportunities in this field.

Speciation is familiar in radiations, but personality is not. In a recent article, Sommer-Trembo et al. linked exploratory behavior in African cichlids to a SNP in the promoter of a gene, the homolog of which is associated with human personality disorders, offering clues about the first fish of this radiation, with implications for vertebrate evolution.

A new study by Schmitt et al. revealed that somatic mutations in tropical trees are passed on to their offspring. Furthermore, the study noted that the majority of inherited mutations were present at low allelic frequencies within the tree.

Positive-strand RNA [(+)RNA] viruses include pandemic SARS-CoV-2, tumor-inducing hepatitis C virus, debilitating chikungunya virus (CHIKV), lethal encephalitis viruses, and many other major pathogens. (+)RNA viruses replicate their RNA genomes in virus-induced replication organelles (ROs) that also evolve new viral species and variants by recombination and mutation and are crucial virus control targets. Recent cryo-electron microscopy (cryo-EM) reveals that viral RNA replication proteins form striking ringed 'crowns' at RO vesicle junctions with the cytosol. These crowns direct RO vesicle formation, viral (-)RNA and (+)RNA synthesis and capping, innate immune escape, and transfer of progeny (+)RNA genomes into translation and encapsidation. Ongoing studies are illuminating crown assembly, sequential functions, host factor interactions, etc., with significant implications for control and beneficial uses of viruses.

Intimate links between epigenome modifications and metabolites allude to a crucial role of cellular metabolism in transcriptional regulation. Retina, being a highly metabolic tissue, adapts by integrating inputs from genetic, epigenetic, and extracellular signals. Precise global epigenomic signatures guide development and homeostasis of the intricate retinal structure and function. Epigenomic and metabolic realignment are hallmarks of aging and highlight a link of the epigenome-metabolism nexus with aging-associated multifactorial traits affecting the retina, including age-related macular degeneration and glaucoma. Here, we focus on emerging principles of epigenomic and metabolic control of retinal gene regulation, with emphasis on their contribution to human disease. In addition, we discuss potential mitigation strategies involving lifestyle changes that target the epigenome-metabolome relationship for maintaining retinal function.