G3: Genes|Genomes|Genetics最新文献

The mechanisms that maintain a non-cycling status in postmitotic tissues are not well understood. Many cell cycle genes have promoters and enhancers that remain accessible even when cells are terminally differentiated and in a non-cycling state, suggesting their repression must be maintained long term. In contrast, enhancer decommissioning has been observed for rate-limiting cell cycle genes in the Drosophila wing, a tissue where the cells die soon after eclosion, but it has been unclear if this also occurs in other contexts of terminal differentiation. In this study, we show that enhancer decommissioning also occurs at specific, rate-limiting cell cycle genes in the long-lived tissues of the Drosophila eye and brain, and we propose this loss of chromatin accessibility may help maintain a robust postmitotic state. We examined the decommissioned enhancers at specific rate-limiting cell cycle genes and showed that they encode for dynamic temporal and spatial expression patterns that include shared, as well as tissue-specific elements, resulting in broad gene expression with developmentally controlled temporal regulation. We extend our analysis to cell cycle gene expression and chromatin accessibility in the mammalian retina using a published dataset and find that the principles of cell cycle gene regulation identified in terminally differentiating Drosophila tissues are conserved in the differentiating mammalian retina. We propose a robust, non-cycling status is maintained in long-lived postmitotic tissues through a combination of stable repression at most cell cycle genes, alongside enhancer decommissioning at specific rate-limiting cell cycle genes.

Organisms use constitutive or induced defenses against pathogens and other external threats. Constitutive defenses are constantly on, whereas induced defenses are activated when needed. Each of these strategies has costs and benefits, which can affect the type of defense that evolves in response to pathogens. In addition, induced defenses are usually regulated by multiple negative feedback mechanisms that prevent overactivation of the immune response. However, it is unclear how negative feedback affects the costs, benefits, and evolution of induced responses. To address this gap, we developed a mechanistic model of the well-characterized Drosophila melanogaster immune signaling network that includes 3 separate mechanisms of negative feedback as a representative of the widespread phenomenon of multilevel regulation of induced responses. We show that, under stochastic fly-bacteria encounters, an induced defense is favored when bacterial encounters are rare or uncertain, but in ways that depend on the bacterial proliferation rate. Our model also predicts that the specific negative regulators that optimize the induced response depend on the bacterial proliferation rate, linking negative feedback mechanisms to the factors that favor induction.

We genotyped a population of 618 diploid potato clones derived from six independent potato-breeding programmes from NW-Europe. The diploids were phenotyped for 23 traits, using standardized protocols and common check varieties, enabling us to derive whole population estimators for most traits. We subsequently performed a genome-wide association study (GWAS) to identify quantitative trait loci (QTL) for all traits with SNPs and short-read haplotypes derived from read-backed phasing. In this study, we used a marker platform called PotatoMASH (Potato Multi-Allele Scanning Haplotags); a pooled multiplex amplicon sequencing based approach. Through this method, neighboring SNPs within an amplicon can be combined to generate multiallelic short-read haplotypes (haplotags) that capture recombination history between the constituent SNPs and reflect the allelic diversity of a given locus in a different way than single bi-allelic SNPs. We found a total of 37 unique QTL across both marker types. A core of 10 QTL was detected with SNPs as well as with haplotags. Haplotags allowed to detect an additional 14 QTL not found based on the SNP set. Conversely, the bi-allelic SNP set also found 13 QTL not detectable using the haplotag set. We conclude that both marker types should routinely be used in parallel to maximize the QTL detection power. We report 19 novel QTL for nine traits: Skin Smoothness, Sprout Dormancy, Total Tuber Number, Tuber Length, Yield, Chipping Color, After-cooking Blackening, Cooking Type, and Eye depth.

The Nepetoideae, a subfamily of Lamiaceae (mint family), is rich in aromatic plants, many of which are sought after for their use as flavors and fragrances or for their medicinal properties. Here, we present genome assemblies for two species in Nepetiodeae: Drepanocaruym sewerzowii and Marmoritis complanata. Both assemblies were generated using Oxford Nanopore Q20 + reads with contigs anchored to nine pseudomolecules that resulted in 335 Mb and 305 Mb assemblies, respectively, and BUSCO scores above 95% for both the assembly and annotation. We furthermore provide a species tree for the Lamiaceae using only genome-derived gene models, complementing existing transcriptome and marker-based phylogenies.

When adaptive phenotypic variation or quantitative trait loci map within an inverted segment of a chromosome, researchers often despair because the suppression of crossing over will prevent the discovery of selective target genes that established the rearrangement. If an inversion polymorphism is old enough, then the accumulation of gene conversion tracts offers the promise that quantitative trait loci or selected loci within inversions can be mapped. The inversion polymorphism of Drosophila pseudoobscura is a model system to show that gene conversion analysis is a useful tool for mapping selected loci within inversions. D. pseudoobscura has over 30 different chromosomal arrangements on the third chromosome (Muller C) in natural populations and their frequencies vary with changes in environmental habitats. Statistical tests of five D. pseudoobscura gene arrangements identified outlier genes within inverted regions that had potentially heritable variation, either fixed amino acid differences or differential expression patterns. We use genome sequences of the inverted third chromosome (Muller C) to infer 98,443 gene conversion tracts for a total coverage of 142 Mb or 7.2× coverage of the 19.7 Mb chromosome. We estimated gene conversion tract coverage in the 2,668 genes on Muller C and tested whether gene conversion coverage was similar among arrangements for outlier vs non-outlier loci. Outlier genes had lower gene conversion tract coverage among arrangements than the non-outlier genes suggesting that selection removes exchanged DNA in the outlier genes. These data support the hypothesis that the third chromosome in D. pseudoobscura captured locally adapted combinations of alleles prior to inversion mutation events.

Plant breeding is a complex endeavor that is almost always multi-objective in nature. In recent years, stochastic breeding simulations have been used by breeders to assess the merits of alternative breeding strategies and assist in decision-making. In addition to simulations, visualization of a Pareto frontier for multiple competing breeding objectives can assist breeders in decision-making. This paper introduces Python Breeding Optimizer and Simulator (PyBrOpS), a Python package capable of performing multi-objective optimization of breeding objectives and stochastic simulations of breeding pipelines. PyBrOpS is unique among other simulation platforms in that it can perform multi-objective optimizations and incorporate these results into breeding simulations. PyBrOpS is built to be highly modular and has a script-based philosophy, making it highly extensible and customizable. In this paper, we describe some of the main features of PyBrOpS and demonstrate its ability to map Pareto frontiers for breeding possibilities and perform multi-objective selection in a simulated breeding pipeline.

Entomopathogenic fungi belonging to the Order Hypocreales are renowned for their ability to infect and kill insect hosts, while their endophytic mode of life and the beneficial rhizosphere effects on plant hosts have only been recently recognized. Understanding the molecular mechanisms underlying their different lifestyles could optimize their potential as both biocontrol and biofertilizer agents, as well as the wider appreciation of niche plasticity in fungal ecology. This study describes the comprehensive whole genome sequencing and analysis of one of the most effective entomopathogenic and endophytic EPF strains, Metarhizium brunneum V275 (commercially known as Lalguard Met52), achieved through Nanopore and Illumina reads. Comparative genomics for exploring intraspecies variability and analyses of key gene sets were conducted with a second effective EPF strain, M. brunneum ARSEF 4556. The search for strain- or species-specific genes was extended to M. brunneum strain ARSEF 3297 and other species of genus Metarhizium, to identify molecular mechanisms and putative key genome adaptations associated with mode of life differences. Genome size differed significantly, with M. brunneum V275 having the largest genome amongst M. brunneum strains sequenced to date. Genome analyses revealed an abundance of plant-degrading enzymes, plant colonization-associated genes, and intriguing intraspecies variations regarding their predicted secondary metabolic compounds and the number and localization of Transposable Elements. The potential significance of the differences found between closely related endophytic and entomopathogenic fungi, regarding plant growth-promoting and entomopathogenic abilities, are discussed, enhancing our understanding of their diverse functionalities and putative applications in agriculture and ecology.

Striga hermonthica (Del.) Benth., a parasitic weed, causes substantial yield losses in maize production in sub-Saharan Africa. Breeding for Striga resistance in maize is constrained by limited genetic diversity for Striga resistance within the elite germplasm and phenotyping capacity under artificial Striga infestation. Genomics-enabled approaches have the potential to accelerate identification of Striga resistant lines for hybrid development. The objectives of this study were to evaluate the accuracy of genomic selection for traits associated with Striga resistance and grain yield (GY) and to predict genetic values of tested and untested doubled haploid maize lines. We genotyped 606 doubled haploid lines with 8,439 rAmpSeq markers. A training set of 116 doubled haploid lines crossed to 2 testers was phenotyped under artificial Striga infestation at 3 locations in Kenya. Heritability for Striga resistance parameters ranged from 0.38-0.65 while that for GY was 0.54. The prediction accuracies for Striga resistance-associated traits across locations, as determined by cross-validation (CV) were 0.24-0.53 for CV0 and from 0.20 to 0.37 for CV2. For GY, the prediction accuracies were 0.59 and 0.56 for CV0 and CV2, respectively. The results revealed 300 doubled haploid lines with desirable genomic estimated breeding values for reduced number of emerged Striga plants (STR) at 8, 10, and 12 weeks after planting. The genomic estimated breeding values of doubled haploid lines for Striga resistance-associated traits in the training and testing sets were similar in magnitude. These results highlight the potential application of genomic selection in breeding for Striga resistance in maize. The integration of genomic-assisted strategies and doubled haploid technology for line development coupled with forward breeding for major adaptive traits will enhance genetic gains in breeding for Striga resistance in maize.

The interaction of plant mitochondrial and nuclear genetic systems is exemplified by mitochondria-encoded cytoplasmic male sterility (CMS) under the control of nuclear restorer-of-fertility genes. The S type of CMS in maize is characterized by a pollen collapse phenotype and a unique paradigm for fertility restoration in which numerous nuclear restorer-of-fertility lethal mutations rescue pollen function but condition homozygous-lethal seed phenotypes. Two nonallelic restorer mutations recovered from Mutator transposon-active lines were investigated to determine the mechanisms of pollen fertility restoration and seed lethality. Mu Illumina sequencing of transposon-flanking regions identified insertion alleles of nuclear genes encoding mitochondrial ribosomal proteins RPL6 and RPL14 as candidate restorer-of-fertility lethal mutations. Both candidates were associated with lowered abundance of mitochondria-encoded proteins in developing maize pollen, and the rpl14 mutant candidate was confirmed by independent insertion alleles. While the restored pollen functioned despite reduced accumulation of mitochondrial respiratory proteins, normal-cytoplasm plants heterozygous for the mutant alleles showed a significant pollen transmission bias in favor of the nonmutant Rpl6 and Rpl14 alleles. CMS-S fertility restoration affords a unique forward genetic approach to investigate the mitochondrial requirements for, and contributions to, pollen and seed development.