G3: Genes|Genomes|Genetics最新文献

A high degree of cell and circuit-specific regulation has presented challenges for efforts to precisely define molecular mechanisms controlling synapse formation and maturation. Here, we pursue an unbiased forward genetic approach to identify Caenorhabditis elegans genes involved in the formation and maturation of cholinergic synaptic connections with GABAergic motor neurons as indicated by the distribution of GFP-tagged postsynaptic acetylcholine receptors (AChR) on GABAergic dendrites. We identified mutations in 3 genes that identify key processes in synapse/circuit maturation. Mutation of the RUN domain (RPIP8, UNC-14, and NESCA) cargo adaptor gene unc-14 dramatically impacts overall GABAergic neuron morphology and dendritic spines. Mutation of the nicotinic acetylcholine alpha subunit gene unc-63 causes a failure in AChR assembly in GABAergic neurons but does not significantly alter dendritic spine structure or abundance. Finally, a mutation in the Liprin-α synaptic scaffold gene syd-2 severely disrupts both dendritic spines and AChR localization. The identification of these three genes from our screen highlights how mechanisms for cargo trafficking, receptor assembly, and synapse structural organization each make distinct contributions to synapse assembly and circuit connectivity.

Rice blast is a destructive rice disease caused by the fungus Magnaporthe oryzae (M. oryzae). Here, we identified a resistance gene from the rice cultivar Wanhui 66 which is resistant to the rice blast Guy11 isolate. Genetic mapping positioned a blast resistance locus to chromosome 6. Employing map-based cloning approach ultimately mapped the novel blast resistance locus to a genomic region of 113 kb that contains the Pid3 gene. Candidate gene prediction and cDNA sequencing indicate that the target resistance gene in the Wanhui 66 is allelic to Pid3, thus it was designated Pid3-1. Further analysis showed that the Pid3-1 has 3 nucleotide substitutions, resulting in 3 amino acid substitutions in the Pid3-1 protein, which significantly affect the structure of the Pid3-1 protein as indicated by the 3-D structure simulation. The CRISPR/Cas9 system was employed to generate a Pid3-1 knockout mutants that confirmed that the Wanhui 66 resistant phenotype is controlled by Pid3-1. A molecular marker, Indel-6-34, cosegregates with Pid3-1 was identified that could have a great impact on ice breeding against blast disease resistance.

With continuous progress of single-cell chromatin accessibility profiling techniques, scATAC-seq has become more commonly used in investigating regulatory genomic regions and their involvement in developmental, evolutionary, and disease-related processes. At the same time, accurate cell type annotation plays a crucial role in comprehending the cellular makeup of complex tissues and uncovering novel cell types. Unfortunately, the majority of existing methods primarily focus on label transfer within scRNA-seq datasets and only a limited number of approaches have been specifically developed for transferring labels from scRNA-seq to scATAC-seq data. Moreover, many methods have been published for the joint embedding of data from the two modalities, which can be used for label transfer by adding a classifier trained on the latent space. Given these available methods, this study presents a comprehensive benchmarking study evaluating 27 computational tools for scATAC-seq label annotations through tasks involving single-cell RNA and ATAC data from various human and mouse tissues. We found that when high quality paired data were available to transfer labels across unpaired data, Bridge and GLUE were the best performers; otherwise, bindSC and GLUE achieved the highest prediction accuracy overall. All these methods were able to use peak-level information instead of purely relying on the gene activities from scATAC-seq. Furthermore, we found that data imbalance, cross-omics dissimilarity on common cell types, data binarization, and the introduction of semi-supervised strategy usually had negative impacts on model performance. In terms of scalability, we found that the most time and memory efficient methods were Bridge and deep-learning-based algorithms like GLUE. Based on the results of this study, we provide several suggestions for future methodology development.

Aspergillosis caused by Aspergillus fumigatus is a clinical issue of such severity that the World Health Organization has designated this organism as 1 of the 4 most critical fungi to study. Progress in A. fumigatus has been limited by the availability of genetic tools with which to study this filamentous fungus. Currently available means of altering the dosage of genes and gene products include construction of disruption mutants as well as regulated promoters. These are powerful techniques but somewhat limited for the analysis of essential genes. Here we describe a new method that permits regulated proteolysis of any A. fumigatus protein that can be made as a fusion protein to the well-described green fluorescent protein (GFP) of Aequorea victoria. A GFP fusion protein of interest can be targeted for degradation using a single-chain antibody called a nanobody that recognizes GFP (GFPNb). This GFPNb is in turn fused to an E3 ligase protein called Rnf4 from rat that efficiently ubiquitinates target proteins. A fusion gene was constructed under control of a doxycycline-inducible promoter that produced a GFPNb-Rnf4 fusion protein in A. fumigatus. Here, we show that production of this GFPNb-Rnf4 protein led to the rapid proteolysis of a variety of GFP fusion proteins. Additionally, we found that some GFP fusion proteins triggered a corresponding genomic response when their degradation was induced, while others were simply degraded. These studies provide a new means to directly regulate protein levels in A. fumigatus and generate new alleles of genes, exposing the underlying regulatory circuitry.

Biological control is a sustainable strategy to combat agricultural pests. Yet, legislation increasingly restricts importing nonnative biocontrol agents. Thus, selective breeding of biocontrol traits is suggested to enhance performance of existing biocontrol agents. Genomic prediction, where genomic data are used to estimate the genetic merit of an individual for specific traits, is an alternative to exploit genetic variation for the improvement of native biocontrol agents. This study aims to establish a proof of principle for genomic prediction in insect biocontrol agents, using wing morphology traits in the model parasitoid Nasonia vitripennis Walker (Pteromalidae). We performed genomic prediction using a genomic best linear unbiased prediction (GBLUP) model, using 1,230 individuals with 8,639 SNPs generated by genotyping-by-sequencing (GBS). We used individuals from 2 generations from the outbred HVRx population, 717 individuals from generation 169 (G169) and 513 individuals from generation 172 (G172). To assess genomic prediction accuracy, we used across generation validation (forward validation for G172 from G169 and backward validation for G169 from G172) and also 5-fold cross-validation. For size-related traits, including tibia length, wing length, wing width, and second moment area, the accuracy of genomic prediction was close to 0 in both across generation validations but much higher in 5-fold cross-validation (ranging from 0.54 to 0.68). For the shape-related trait wing aspect ratio, a high accuracy was found for all 3 validation strategies, with 0.47 for across generation forward validation (AGFV), 0.65 for across generation backward validation (AGBV), and 0.54 for 5-fold cross-validation. Overall, genomic selection in insect biocontrol agents with a relative small effective population size seems promising. However, factors such as the biology of insects, phenotyping techniques, and large-scale genotyping costs still challenge the application of genomic selection to biocontrol agents.

Drought stress is a strong selective pressure for all plant species. Plants respond to water shortage through various strategies that confer drought tolerance. These strategies may be plastic responses that occur with the onset of stress or may comprise continuously expressed (constitutive) traits regardless of water availability. Here, we used RNA-seq to characterize transcriptional responses to dehydration in seedlings of a drought-tolerant oak, Quercus douglasii, from a local population in the Sierra Nevada Foothills in California. In the greenhouse, we subjected 24 seedlings from 6 maternal families to dry-down or well-watered treatments and prepared RNA libraries from tissue collected before and after each treatment (48 libraries). Our goals were to characterize the pattern of up- and downregulated genes in response to dehydration and to assess the extent to which this drought-tolerant species shows differential versus constitutive expression as a drought response strategy. We identified few differentially expressed genes in response to dehydration. Upregulated genes were related to known drought response functions, while downregulated genes were enriched for gene ontology terms related to growth and carbohydrate metabolism. We discovered high constitutive expression of many putatively drought-responsive genes that had been found to exhibit gene expression plasticity in a different oak species, which is drought-sensitive. This novel finding demonstrates the potential for constitutive expression of genes involved in drought stress to provide an additional mechanism of drought tolerance for some tree species, such as Q. douglasii.

The bumble bee wax moth, Aphomia sociella, is an important lepidopteran pest impacting bee colonies essential for pollination and apiculture. Like other moths, this species has been reported to ingest plastics. Although specific enzymes have been proposed to facilitate plastic catabolism in some moths, with controversial results, this remains entirely unexplored in A. sociella. Despite the biological and ecological relevance of A. sociella, sequence efforts aimed at understanding the genetic makeup of this species have not yet been undertaken. In this work, we successfully achieved a high-quality de novo genome assembly of A. sociella and comprehensive gene annotations generated from long-read DNA and RNA sequencing with Oxford Nanopore Technology. The haploid assembly includes 347 contigs, with an N50 of 4.96 Mb, and contains 12,618 protein-coding genes. Benchmarking Universal Single-Copy Orthologs (BUSCO) analyses indicates that the assembly has a high level of completeness (98.8%) and low level of fragmentation (4.1%) and duplication (0.2%). Phylogenomic analyses with other members of the Lepidoptera order placed A. sociella in the same clade as Aphomia cephalonica and indicates close evolutionary relationships with the other two species in the subfamily Galleriinae, namely Achroia grisella and Galleria mellonella. This new high-quality genome assembly, and associated annotations, represents a valuable resource for investigating the genomic basis of ecological specialization of A. sociella, including wax and possibly plastic utilization, while offering critical support for research aimed at developing sustainable and effective pest management strategies.

We have completed a systematic survey of Drosophila melanogaster enzymes, improving the coverage and accuracy of their functional Gene Ontology annotations in FlyBase and collaborating databases. We made >5,000 changes to manual Gene Ontology annotations by reviewing information from the literature and consulting expert databases, resulting in the final verification of 3,708 Drosophila enzyme-encoding genes. Herein, we present an overview of the enzyme landscape in Drosophila, including insights on enzyme paralogs, pseudoenzymes, and enzymatic complexes, and compare these with corresponding datasets for yeast and humans. We also show how the presentation of enzyme data on FlyBase gene reports has been enhanced, including the addition of Enzyme Commission (EC) information and RHEA reaction graphics. For each class of enzyme, we have created a "Gene Group" page in FlyBase to tabulate the group members and facilitate access to related information and tools. Together, this work provides a comprehensive enzyme resource to serve the Drosophila research community and beyond. As a practical example of its utility, we used our improved dataset to update the FlyCyc model of Drosophila metabolism.

Aminoacyl-tRNA synthetases (aaRSs) are essential for translation, as they charge tRNA molecules with their corresponding amino acids. Alterations in aaRSs can significantly disrupt both cytosolic and mitochondrial translation. Through a forward genetic screen for mitochondrial unfolded protein response (UPRmt) activators in Caenorhabditis elegans, we identified a missense mutation (P447V) in the previously uncharacterized gene Y105E8A.20, which encodes for a methionine tRNA synthetase (MetRS). Here, we characterize the UPRmt induction by Y105E8A.20, which we call mars-2, and demonstrate that the P447V allele is a loss-of-function mutation. Furthermore, we show that impaired mars-2 activity leads to reduced mitochondrial-encoded protein abundance, depletion of mitochondrial membrane potential, fragmented mitochondrial morphology, and mild developmental delay, although the animals remain viable. Hence, this hypomorphic mars-2(P447V) strain provides a valuable tool for studying mitochondrial translation and understanding how aaRSs are involved in mitochondrial homeostasis.

The highly conserved insulin signaling pathway regulates growth and development time in response to nutrition across metazoans. The fruit fly, Drosophila melanogaster, has 7 insulin-like peptides, which bind to a single insulin receptor and are differentially expressed across development time, organs, and with nutritional conditions. However, whether individual insulin-like peptides play specific roles in controlling growth remains unknown. Recent studies have revealed that, in addition to the caloric content of the diet, the ratio of protein to carbohydrates in the diet plays a key role in regulating life history traits. Furthermore, individual insulin-like peptides vary in their expression profiles according to nutrient conditions. Whether these differences in expression have any functional significance to animal life history traits remains unclear. Here, we report that reducing the protein content of the larval diet through macronutrient restriction-where the calories lost from protein dilution are offset by increased carbohydrate content-results in a more pronounced developmental delay compared to caloric restriction-where both protein and carbohydrate concentrations are reduced. We further reveal that these two diet types result in notable differences in the expression levels of Drosophila insulin-like peptides 2, 3, and 5, and observe distinct phenotypic responses of individual insulin-like peptide mutants raised on each diet type. Taken together, our findings highlight the distinct roles of individual insulin-like peptides in regulating growth and development time in response to changes in dietary macronutrients, and provide key insights into the molecular mechanisms controlling nutritional plasticity in Drosophila.