Genetics最新文献

Purifying selection is a critical factor in shaping genetic diversity. Current theoretical models mostly address scenarios of either very weak or strong selection, leaving a significant gap in our knowledge. The effects of purifying selection on patterns of genomic diversity remain poorly understood when selection against deleterious mutations is weak to moderate, particularly when recombination is limited or absent. In this study, we extend an existing approach, the fitness-class coalescent, to incorporate arbitrary levels of purifying selection in haploid populations. This model offers a comprehensive framework for exploring the influence of purifying selection in a wide range of demographic scenarios. Moreover, our research reveals potential sources of qualitative and quantitative biases in demographic inference, highlighting the significant risk of attributing genetic patterns to past demographic events rather than purifying selection. This work expands our understanding of the complex interplay between selection, drift, and population dynamics, and how purifying selection distorts demographic inference.

Long, identical haplotypes shared between pairs of individuals, known as identity-by-descent (IBD) segments, result from recently shared co-ancestry. Various methods have been developed to utilize IBD sharing for demographic inference in contemporary DNA data. Recent methodological advances have extended the screening for IBD segments to ancient DNA (aDNA) data, making demographic inference based on IBD also possible for aDNA. However, aDNA data typically have varying sampling times, but most demographic inference methods for modern data assume that sampling is contemporaneous. Here, we present Ttne (Time-Transect Ne), which models time-transect sampling to infer recent effective population size trajectories. Using simulations, we show that utilizing IBD sharing in time series increased resolution to infer recent fluctuations in effective population sizes compared with methods that only use contemporaneous samples. To account for IBD detection errors common in empirical analyses, we implemented an approach to estimate and model IBD detection errors. Finally, we applied Ttne to two aDNA time transects: individuals associated with the Copper Age Corded Ware Culture and Medieval England. In both cases, we found evidence of a growing population, a signal consistent with archaeological records.

The Drosophila TRIM-NHL RNA-binding protein (RBP), MEI-P26, has previously been shown to suppress tumor formation in the germline. Here we show that, in the Drosophila larval central brain, cell-type specific expression of MEI-P26 plays a vital role in regulating neural development. MEI-P26 and another TRIM-NHL RBP, Brain tumor (BRAT), have distinct expression patterns in Type I neuroblast (NB) lineages: While both proteins are expressed in NBs, BRAT is expressed in ganglion mother cells (GMCs) but not neurons whereas MEI-P26 is expressed in neurons but not GMCs. Knockdown of MEI-P26 leads to re-expression of the stem cell marker Deadpan (DPN) and over-production of neurons. In contrast, ectopically expressed MEI-P26 reduces NB lineage size by repressing division of GMCs, resulting in reduced neuron production. We show that MEI-P26 positively regulates expression of Prospero (PROS), a transcription factor that is known to repress cell cycle related genes. Ectopic expression of PROS phenocopies ectopic expression of MEI-P26. In both cases, Cyclin B (CYCB) expression is downregulated. Importantly, knockdown of PROS in the context of ectopic MEI-P26 rescues the neural lineage. Based on these results, we conclude that MEI-P26 functions to prevent over-production of neurons by promoting production of PROS which, in turn, downregulates cell division.

Genomic prediction applies to any agro- or ecologically relevant traits, with distinct ontologies and genetic architectures. Selecting the most appropriate model for the distribution of genetic effects and their associated allele frequencies in the training population is crucial. Linear regression models are often preferred for genomic prediction. However, linear models may not suit all genetic architectures and training populations. Machine Learning approaches have been proposed to improve genomic prediction owing to their capacity to capture complex biology including epistasis. However, the applicability of different genomic prediction models, including non-linear, non-parametric approaches, have not been rigorously assessed across a wide variety of plant traits in natural outbreeding populations. This study evaluates genomic prediction sensitivity to trait ontology and the impact of population structure on model selection and prediction accuracy. Examining 36 quantitative traits in 1000+ natural genotypes of the model plant Arabidopsis thaliana, we assessed the performance of penalised regression, random forest, and multilayer perceptron at producing genomic predictions. Regression models were generally the most accurate, except for biochemical traits where random forest performed best. We link this result to the genetic architecture of each trait - notably that biochemical traits have simpler genetic architecture than macroscopic traits. Moreover, complex macroscopic traits, particularly those related to flowering time and yield, were strongly correlated to population structure, while molecular traits were better predicted by fewer, independent markers. This study highlights the relevance of machine learning approaches for simple molecular traits and underscores the need to consider ancestral population history when designing training samples.

The rapid increase in the number of reference-quality genome assemblies presents significant new opportunities for genomic research. However, the absence of standardized naming conventions for genome assemblies and annotations across datasets creates substantial challenges. Inconsistent naming hinders the identification of correct assemblies, complicates the integration of bioinformatics pipelines, and makes it difficult to link assemblies across multiple resources. To address this, we developed a specification for standardizing the naming of reference genome assemblies, to improve consistency across datasets and facilitate interoperability. This specification was created with FAIR (Findable, Accessible, Interoperable, and Reusable) practices in mind, ensuring that reference assemblies are easier to locate, access, and reuse across research communities. Additionally, it has been designed to comply with primary genomic data repositories, including members of the International Nucleotide Sequence Database Collaboration (INSDC) consortium, ensuring compatibility with widely used databases. While initially tailored to the agricultural genomics community, the specification is adaptable for use across different taxa. Widespread adoption of this standardized nomenclature would streamline assembly management, better enable cross-species analyses, and improve the reproducibility of research. It would also enhance natural language processing applications that depend on consistent reference assembly names in genomic literature, promoting greater integration and automated analysis of genomic data. This is a good time to consider more consistent genomic data nomenclature as many research communities and data resources are now finding themselves juggling multiple datasets from multiple data providers.

Multiple methods of demography inference are based on the ancestral recombination graph. This powerful approach uses observed mutations to model local genealogies changing along chromosomes by historical recombination events. However, inference of underlying genealogies is difficult in regions with high recombination rate relative to mutation rate due to the lack of mutations representing genealogies. Despite the prevalence of high-recombining genomic regions in some organisms, such as birds, its impact on demography inference based on ancestral recombination graphs has not been well studied. Here, we use population genomic simulations to investigate the impact of high-recombining regions on demography inference based on ancestral recombination graphs. We demonstrate that inference of effective population size and the time of population split events is systematically affected when high-recombining regions cover wide breadths of the chromosomes. Excluding high-recombining genomic regions can practically mitigate this impact, and population genomic inference of recombination maps is informative in defining such regions, yet the estimated values of local recombination rate may not be utilized for this decision. Finally, we confirm the relevance of our findings in empirical analysis by contrasting demography inferences applied for a bird species, the Eurasian blackcap (Sylvia atricapilla), using different parts of the genome with high and low recombination rates. Our results suggest that demography inference methods based on ancestral recombination graphs should be carried out with caution when applied in species whose genomes contain long stretches of high-recombining regions.

Mismatch repair (MMR) is a highly conserved DNA repair pathway that recognizes mispairs that occur spontaneously during DNA replication and coordinates their repair. In Saccharomyces cerevisiae, Msh2-Msh3 and Msh2-Msh6 initiate MMR by recognizing and binding insertion deletion loops (in/dels) up to ∼ 17 nucleotides (nt.) and base-base mispairs, respectively; the two complexes have overlapping specificity for small (1-2 nt.) in/dels. The DNA-binding specificity for the two complexes resides in their respective mispair binding domains (MBDs) and have distinct DNA-binding modes. Msh2-Msh3 also plays a role in promoting CAG/CTG trinucleotide repeat (TNR) expansions, which underlie many neurodegenerative diseases such as Huntington's Disease and Myotonic Dystrophy Type 1. Models for Msh2-Msh3's role in promoting TNR tracts expansion have invoked its specific DNA-binding activity and predict that the TNR structure alters its DNA binding and downstream activities to block repair. Using a chimeric Msh complex that replaces the MBD of Msh6 with the Msh3 MBD, we demonstrate that Msh2-Msh3 DNA-binding activity is not sufficient to promote TNR expansions. We propose a model for Msh2-Msh3-mediated TNR expansions that requires a fully functional Msh2-Msh3 including DNA binding, coordinated ATP binding and hydrolysis activities and interactions with Mlh complexes that are analogous to those required for MMR.

Bloom Syndrome helicase (Blm) is a RecQ family helicase involved in DNA repair, cell-cycle progression, and development. Pathogenic variants in human BLM cause the autosomal recessive disorder Bloom Syndrome, characterized by predisposition to numerous types of cancer. Prior studies of Drosophila Blm mutants lacking helicase activity or protein have shown sensitivity to DNA damaging agents, defects in repairing DNA double-strand breaks (DSBs), female sterility, and improper segregation of chromosomes in meiosis. Blm orthologs have a well conserved and highly structured RecQ helicase domain, but more than half of the protein, particularly in the N-terminus, is predicted to be intrinsically disordered. Because this region is poorly conserved across metazoa, we compared closely related species to identify regions of conservation that might be associated with important functions. We deleted two Drosophila-conserved regions in D. melanogaster using CRISPR/Cas9 gene editing and assessed the effects on several Blm functions. Each deletion had distinct effects. Deletion of either conserved region 1 (CR1) or conserved region 2 (CR2) compromised DSB repair through synthesis-dependent strand annealing and resulted in increased mitotic crossovers. In contrast, CR2 is critical for embryonic development but CR1 is less important. Loss of CR1 leads to defects in meiotic crossover designation and patterning but does not impact meiotic chromosome segregation, whereas deletion of CR2 does not result in significant meiotic defects. Thus, while the two regions have overlapping functions, there are distinct roles facilitated by each. These results provide novel insights into functions of the N-terminal region of Blm helicase.

To understand the function of cells such as neurons within an organism, it can be instrumental to inhibit cellular function, or to remove the cell (type) from the organism, and thus to observe the consequences on organismic and/or circuit function and animal behavior. A range of approaches and tools were developed and used over the past few decades that act either constitutively or acutely and reversibly, in systemic or local fashion. These approaches make use of either drugs or genetically encoded tools. Also, there are acutely acting inhibitory tools that require an exogenous trigger like light. Here, we give an overview of such methods developed and used in the nematode Caenorhabditis elegans.

Metabolic mechanisms conferring pyrethroid resistance in malaria vectors are jeopardizing the effectiveness of insecticide-based interventions, and identification of their markers is a key requirement for robust resistance management. Here, using a field-lab-field approach, we demonstrated that a single mutation G454A in the P450 CYP9K1 is driving pyrethroid resistance in the major malaria vector Anopheles funestus in East and Central Africa. Drastic reduction in CYP9K1 diversity was observed in Ugandan samples collected in 2014, with the selection of a predominant haplotype (G454A mutation at 90%), which was completely absent in the other African regions. However, 6 years later (2020) the Ugandan 454A-CYP9K1 haplotype was found predominant in Cameroon (84.6%), but absent in Malawi (Southern Africa) and Ghana (West Africa). Comparative in vitro heterologous expression and metabolism assays revealed that the mutant 454A-CYP9K1 (R) allele significantly metabolizes more type II pyrethroid (deltamethrin) compared with the wild G454-CYP9K1 (S) allele. Transgenic Drosophila melanogaster flies expressing 454A-CYP9K1 (R) allele exhibited significantly higher type I and II pyrethroids resistance compared to flies expressing the wild G454-CYP9K1 (S) allele. Furthermore, laboratory testing and field experimental hut trials in Cameroon demonstrated that mosquitoes harboring the resistant 454A-CYP9K1 allele significantly survived pyrethroids exposure (odds ratio = 567, P < 0.0001). This study highlights the rapid spread of pyrethroid-resistant CYP9K1 allele, under directional selection in East and Central Africa, contributing to reduced bed net efficacy. The newly designed DNA-based assay here will add to the toolbox of resistance monitoring and improving its management strategies.