G3: Genes|Genomes|Genetics最新文献

Phenotypic plasticity allows organisms to express different traits in response to different environmental or genetic conditions. Understanding the evolution of conditional phenotypes is challenging because they are not expressed by all members of a population, which allows for the accumulation of deleterious variation due to a reduced efficacy of purifying selection. Theory suggests pleiotropic effects help prevent the decay of conditional phenotypes by exposing the variation accrued in one context to the effects of purifying selection in an alternative context. However, existing frameworks for describing the evolutionary dynamics of conditional phenotypes are limited in their ability to flexibly model the complex pleiotropic architectures that often underlie conditional phenotypes. To help improve our understanding of the evolutionary stability of conditional phenotypes, here we describe a geometric model that allows for explicit modeling of different fitness optima for conditional and alternative phenotypes, as well as their underlying pleiotropic associations. Using stochastic simulations and mathematical analyses, we show that this model recapitulates and elaborates on existing predictions regarding the role of pleiotropy in maintaining conditional phenotypes. Specifically, we found that more pleiotropic conditional phenotypes experience decreased rates of decay in fitness over periods of inexpression, the effects of which are comparable for phenotypes that are spatially and temporally conditional. Furthermore, the functional form of the relationship between conditional phenotype expression pattern and decay rate is mediated by pleiotropic effect, which provides more explicit hypotheses of when pleiotropic constraint is expected to play a significant role in the evolutionary maintenance of conditional phenotypes. Finally, we found that when pleiotropic architectures evolve over periods of conditional phenotype inexpression, decoupling from other phenotypes readily evolves and facilitates decay in fitness.

Pork is the most widely consumed meat globally, and the industry has achieved substantial genetic advancements for several traits using genomic selection. However, traditional linear genomic prediction models may be inadequate for predicting complex traits, such as feed efficiency, as they primarily capture additive genetic effects and overlook nonadditive effects, including dominance and epistasis. Deep learning (DL) has the potential to address this limitation due to its ability to model nonlinear patterns inherent in genomic data. The objectives of this study were to compare the predictive ability of DL models to the linear models for predicting feed efficiency (FE) trait in 2 boar populations, estimate the nonadditive genetic variance captured by DL, and assess its effect on predictive ability. Our results showed that the DL models using the averaged-prediction method had the highest predictive ability in the sire line test population (0.381 for multilayer perceptron [MLP] and 0.377 for convolutional neural network [CNN]), compared to 0.366 for linear models. DL models also showed higher abilities in the dam line test population, with MLP achieving a predictive ability of 0.364. Additionally, we showed that DL models captured nonadditive variance; however, this did not significantly improve predictive ability. In conclusion, DL models, particularly MLP, demonstrated the highest predictive ability for FE, improving performance by approximately 4.1% for the sire line and 2.8% for the dam line compared to the traditional linear models. Therefore, DL models are recommended for predicting phenotypes and for estimating total genetic effects, including nonadditive components. However, this comes at a significant increase of computational cost.

The olive fruit fly, Bactrocera oleae (Rossi) (Diptera: Tephritidae), is a specialist of Olea fruits and is a major pest of commercial olives due to their adverse impacts to fruit quality. In support of genomic and physiological research of the olive fly, we sequenced, assembled, and annotated 2 independent genomes: one from a wild-collected male and one from a wild-collected female. The resulting genomes are highly contiguous, collinear, and complete, attesting to the accuracy and quality of both assemblies. In addition to the autosomes captured as single contigs, the X and Y chromosomes were also identified as evidenced by the X chromosome showing diploid coverage in the female assembly compared to haploid coverage in the male assembly and the Y chromosome being entirely absent from the female assembly. These assemblies represent the first full chromosome-level assembly for olive fly. In addition, a complete genome assembly of a known obligate symbiont, Candidatus Erwinia dacicola, was fully sequenced. The Ca. E. dacicola genome we report here is the most contiguous to date, represented by a gapless chromosome and 2 separate gapless plasmids. These genome assemblies, along with bacterial symbiont assembly, provide foundational resources for future genetic and genomic research in support of its management as an agricultural pest.

To dissect the genetic basis of quantitative traits, generation of numerous haploid segregants with diverse genotypes and phenotypes from heterozygous parental strains is a powerful approach. To identify quantitative trait loci (QTLs) associated with NaCl salt tolerance, we employed an iterative crossing strategy using parental strains with contrasting phenotypes. Whole-genome sequencing of selected individual offspring with the most extreme trait value from each generation as well as of the pools of segregants under extreme salt conditions enabled QTL mapping and identification of candidate causative variants. Their effects on phenotypic variation were quantified through a genome-wide screen of generation-dependent reduction of the causative loci and by allele swapping procedure of the putative quantitative trait genes in isogenic strain backgrounds. A combination of these complementary approaches enabled assessment of the causal loci with the strongest effect. We thus confirmed the causative role of the ENA locus, and proposed an additional contribution of the ASG1 gene in NaCl salt tolerance. Asg1 (Activator of Stress Genes 1) has been proposed as a transcriptional regulator of genes involved in lipid metabolism and various stress responses. Previous large-scale studies have indicated that Asg1 could have a negative effect on NaCl tolerance in S. cerevisiae. The results of our study confirm that prediction and further elucidate its previously uncharacterized negative role in NaCl stress adaptation. Our species-wide association analysis supports a universal contribution of ASG1 gene to NaCl tolerance, which had been masked by the dominant influence of the ENA locus in S. cerevisiae.

The wild blueberry relative Vaccinium stamineum offers a rich source of diversity for expanding the genetic pool of cultivated blueberries, and it has also potential for breeding as a crop on its own. Understanding the genetic architecture of fruit quality traits in this wild species can facilitate and speed up future breeding efforts for introgression and de novo domestication. Therefore, in this study, we developed a biparental population of 147 progenies from V. stamineum, which were phenotyped and genotyped for quantitative trait loci (QTL) mapping. Phenotypic data for acidity [total titratable acidity {TTA} and pH] and sweetness (soluble solids content) were collected over 3 yr. Genotypic data were obtained through targeted sequencing using 6,000 probes developed for blueberry. A linkage map was crafted containing a total of 3,797 markers spanning a cumulative distance of 1,801 cM across 12 linkage groups. Composite interval mapping revealed a total of 20 significant QTL considering the 3 traits and years of evaluation. Two consistent overlapping QTL intervals across 2 yr were found for TTA and soluble solids in linkage groups 8 and 9, respectively. We also found a QTL for TTA that has been previously reported for cultivated blueberry. Low to moderate heritability was observed, indicating the complex genetic architecture of these traits. Overall, the newly developed high-density genetic map provides a valuable resource for trait mapping efforts in this species, and the QTL identified for fruit quality can guide future molecular breeding strategies.

The fungal pathogen Rhizoctonia solani infects a diverse range of host plants and remains an intractable and economically significant disease for many crops. R. solani is classified into reproductively incompatible anastomosis groups (AGs). In the vegetative stage, most plant-pathogenic R. solani isolates are multinuclear and heterokaryotic, but little was previously known about the diversity between haplotypes due to highly fragmented, collapsed short-read assemblies. We present fully-phased, chromosome-scale genome assemblies of the broad host-range R. solani isolates AG8-1 and AG8-3. We demonstrate that both AG8 isolates have 2 distinct haplotypes, each of which is ∼50 Mbp spread across 16 chromosomes and use PacBio Iso-Seq data to achieve a high-quality gene annotation. We show that the 2 nuclear haplotypes display high heterozygosity and differences in haplotype abundance in vegetative cultures. Using transcriptome sequencing during infection of different host plants for AG8-1 and wheat for AG8-3, we show that the less abundant haplotype in both AG8-1 and AG8-3 might harbor more genes upregulated during infection. Taken together, these findings address some of the observed phylogenetic heterogeneity of AG-8 isolates and provide a platform to further dissect the mechanisms enabling this globally significant agricultural pathogen to inflict losses to a range of crop hosts.

Rust diseases on plants are caused by fungi in the order Pucciniales. Typically, rust fungi have narrow host specificity however the pandemic biotype of Austropuccinia psidii has an unusually broad host range causing disease on over 480 myrtaceous species globally. We assembled and analyzed a fully phased chromosome-level genome for the pandemic A. psidii and addressed key outstanding questions of its infection biology. Our research revealed a conserved rust fungal karyotype of 18 haploid chromosomes, in line with fungi for distantly related cereal rusts. We observed chromosomal re-assortment between the 2 nuclei, with one nucleus carrying 19 and the other 17 chromosomes. The synteny of universal single-copy orthologs is mostly maintained with the distantly related rust fungus Puccinia graminis f. sp. tritici. In contrast, nucleotide composition and methylation profiles of A. psidii are distinct compared to rust fungi with smaller genome sizes that have not undergone massive transposable element expansions. Our analysis of MAT loci supports a tetrapolar mating system for A. psidii with a novel finding of expanded numbers of pheromone peptide precursors. We show that infection dynamics of A. psidii are consistent on 4 different susceptible host species separated by 65 mya of evolution and that transcriptional regulation during infection reveals 2 distinct waves of gene expression in early and late infection, including allele-specific expression of candidate effectors. Together, these findings enhance the understanding of the genome biology and pathology of A. psidii, while also providing a valuable resource for future research on this serious rust pathogen.

Combined Annotation Dependent Depletion (CADD) is a machine learning approach used to predict the deleteriousness of genetic variants across a genome. By integrating diverse genomic features, CADD assigns a PHRED-like rank score to each potential variant. Unlike other methods, CADD does not rely on limited datasets of known pathogenic or benign variants but uses larger and less biased training sets. The rapid increase in high-quality genomes and functional annotations across species highlights the need for an automated, non-species-specific pipeline to generate CADD scores. Here, we introduce such a pipeline, facilitating the generation of CADD scores for various species using only a high-quality genome with gene annotation and a multi-species alignment. Additionally, we present updated chickenCADD scores and newly generated turkeyCADD scores, both generated with the pipeline.

ORB2 is the Drosophila ortholog of the human CPEB2-4 family of RNA-binding proteins, which include a conserved C-terminal Zinc-binding ('ZZ') domain. We have recently shown that this domain interacts with several translational co-repressors in the early embryo, and that deletion of this domain from the endogenous orb2 gene results in derepression of its target mRNAs. Here we assess the effect of deletion of the ZZ domain on spermatogenesis. We find that deletion of the ZZ domain does not affect spatial localization of the ORB2 protein; orb2ΔZZ flies are sterile and lack mature sperm; meiosis is mostly normal in orb2ΔZZ testes; individualization complexes are defective and spermatid individualization fails; proteins known to play a role in spermatid individualization-ORB, IMP, SOTI-are mislocalized; and the SOTI-dependent Cleaved Caspase-3 gradient no longer forms in orb2ΔZZ mutant testes.

Disease resistance is one of the main targets of animal breeding programs. In recent years, incorporating genomic information to accelerate genetic progress has become one of the priorities of the industry. Here, we combined population-scale whole-genome sequencing with differential gene expression and functional annotation analyses to study resistance to tilapia lake virus (TiLV) in a breeding Nile tilapia (Oreochromis niloticus) GIFT population. Fish with survival data from a natural TiLV outbreak were sampled and genotyped for 6.7 M SNPs using whole-genome resequencing and imputation. Our results confirmed a QTL located in the proximal end of Oni22, identifying 74 out of the top 99 markers associated with binary survival within a 10 Mb window. The marker explaining the highest genetic variance of TiLV resistance is located at 1.7 Mb and presents a substitution effect of 0.15. Additionally, other SNPs in several other chromosomes explained a high percentage of the genetic variance, with an important number located in 2 separate regions of Oni09. These results suggest an oligogenic architecture underlying resistance to TiLV, with several QTLs with moderate effect and many with small effect. Host transcriptomic analyses identified genes differentially expressed between resistant and susceptible genotypes according to the QTL in Oni22, highlighting proteosome subunit beta type-9a, and ha1f as potential causal genes. This is the first study combining whole-genome sequencing at a population scale with genomic approaches to assess the underlying genomic basis for TiLV resistance. Our results confirm and narrow down a QTL underlying this key trait in a major aquaculture species worldwide, and found novel QTLs in other chromosomes. The identified markers and genes have the potential to improve resistance to TiLV in Nile tilapia, significantly improving animal health and welfare.