PLoS Genetics最新文献

Polyploidy, the result of whole genome duplication (WGD), is widespread across the tree of life and is often associated with speciation and adaptability. It is thought that adaptation in autopolyploids (within-species polyploids) may be facilitated by increased access to genetic variation. This variation may be sourced from gene flow with sister diploids and new access to other tetraploid lineages, as well as from increased mutational targets provided by doubled DNA content. Here, we deconstruct in detail the origins of haplotypes displaying the strongest selection signals in established, successful autopolyploids, Arabidopsis lyrata and Arabidopsis arenosa. We see strong signatures of selection in 17 genes implied in meiosis, cell cycle, and transcription across all four autotetraploid lineages present in our expanded sampling of 983 sequenced genomes. Most prominent in our results is the finding that the tetraploid-characteristic haplotypes with the most robust signals of selection were completely absent in all diploid sisters. In contrast, the fine-scaled variant 'mosaics' in the tetraploids originated from highly diverse evolutionary sources. These include widespread novel reassortments of trans-specific polymorphism from diploids, new mutations, and tetraploid-specific inter-species hybridization-a pattern that is in line with the broad-scale acquisition and reshuffling of potentially adaptive variation in tetraploids.

The translation of nucleotide sequences into amino acid sequences, governed by the genetic code, is one of the most conserved features of molecular biology. The standard genetic code, which uses 61 sense codons to encode one of the 20 standard amino acids and 3 stop codons (UAA, UAG, and UGA) to terminate translation, is used by most extant organisms. The protistan phylum Ciliophora (the 'ciliates') are the most prominent exception to this norm, exhibiting the grfeatest diversity of nuclear genetic code variants and evidence of repeated changes in the code. In this study, we report the discovery of multiple independent genetic code changes within the Phyllopharyngea class of ciliates. By mining publicly available ciliate genome datasets, we discovered that three ciliate species from the TARA Oceans eukaryotic metagenome dataset use the UAG codon to putatively encode leucine. We identified novel suppressor tRNA genes in two of these genomes which are predicted to decode the reassigned UAG codon to leucine. Phylogenomics analysis revealed that these three uncultivated taxa form a monophyletic lineage within the Phyllopharyngea class. Expanding our analysis by reassembling published phyllopharyngean genome datasets led to the discovery that the UAG codon had also been reassigned to putatively code for glutamine in Hartmannula sinica and Trochilia petrani. Phylogenomics analysis suggests that this occurred via two independent genetic code change events. These data demonstrate that the reassigned UAG codons have widespread usage as sense codons within the phyllopharyngean ciliates. Furthermore, we show that the function of UAA is firmly fixed as the preferred stop codon. These findings shed light on the evolvability of the genetic code in understudied microbial eukaryotes.

Taybi-Linder syndrome (TALS) is a rare autosomal recessive disorder characterized by severe microcephaly with abnormal gyral pattern, severe growth retardation and bone abnormalities. It is caused by pathogenic variants in the RNU4ATAC gene. Its transcript, the small nuclear RNA U4atac, is involved in the excision of ~850 minor introns. Here, we report a patient presenting with TALS features but no pathogenic variants were found in RNU4ATAC, instead the homozygous RTTN c.2953A>G variant was detected by whole-exome sequencing. After deciphering the impact of the variant on the RTTN protein function at centrosome in engineered RTTN-depleted RPE1 cells and patient fibroblasts, we analysed neural stem cells (NSC) derived from CRISPR/Cas9-edited induced pluripotent stem cells and revealed major cell cycle and mitotic abnormalities, leading to aneuploidy, cell cycle arrest and cell death. In cortical organoids, we discovered an additional function of RTTN in the self-organisation of NSC into neural rosettes, by observing delayed apico-basal polarization of NSC. Altogether, these defects contributed to a marked delay of rosette formation in RTTN-mutated organoids, thus impeding their overall growth and shedding light on mechanisms leading to microcephaly.

As the adaptor protein that determines substrate specificity of the Cul3-SPOP-Rbx1 E3 ligase complex, SPOP is involved in numerous biological processes. However, its physiological connections with adipogenesis and thermogenesis remain poorly understood. In the current study, we report that the conditional knockout of Spop in mice results in substantial changes in protein expression, including the upregulation of a critical factor associated with thermogenesis, UCP1. Loss of SPOP also led to defects in body weight gain. In addition, conditional knockout mice exhibited resistance to high-fat-diet-induced obesity. Proteomics analysis found that proteins upregulated in the knockout mice are primarily enriched for functions in glycolysis/gluconeogenesis, oxidative phosphorylation, and thermogenesis. Furthermore, Spop knockout mice were more resilient during cold tolerance assay compared with the wild-type controls. Finally, the knockout of SPOP efficiently impaired adipogenesis in primary preadipocytes and the expression of associated genes. Collectively, these findings demonstrate the critical roles of SPOP in regulating adipogenesis and thermogenic capacity in mice.

Principal component analysis (PCA) is widely used to control for population structure in genome-wide association studies (GWAS). Top principal components (PCs) typically reflect population structure, but challenges arise in deciding how many PCs are needed and ensuring that PCs do not capture other artifacts such as regions with atypical linkage disequilibrium (LD). In response to the latter, many groups suggest performing LD pruning or excluding known high LD regions prior to PCA. However, these suggestions are not universally implemented and the implications for GWAS are not fully understood, especially in the context of admixed populations. In this paper, we investigate the impact of pre-processing and the number of PCs included in GWAS models in African American samples from the Women's Health Initiative SNP Health Association Resource and two Trans-Omics for Precision Medicine Whole Genome Sequencing Project contributing studies (Jackson Heart Study and Genetic Epidemiology of Chronic Obstructive Pulmonary Disease Study). In all three samples, we find the first PC is highly correlated with genome-wide ancestry whereas later PCs often capture local genomic features. The pattern of which, and how many, genetic variants are highly correlated with individual PCs differs from what has been observed in prior studies focused on European populations and leads to distinct downstream consequences: adjusting for such PCs yields biased effect size estimates and elevated rates of spurious associations due to the phenomenon of collider bias. Excluding high LD regions identified in previous studies does not resolve these issues. LD pruning proves more effective, but the optimal choice of thresholds varies across datasets. Altogether, our work highlights unique issues that arise when using PCA to control for ancestral heterogeneity in admixed populations and demonstrates the importance of careful pre-processing and diagnostics to ensure that PCs capturing multiple local genomic features are not included in GWAS models.

Background: Mendelian randomization (MR) is a statistical approach using genetic variants as instrumental variables to estimate causal effects of a single exposure on an outcome. Multivariable MR (MVMR) extends this to estimate the direct effect of multiple exposures simulatiously. MR and MVMR can be biased by the presence of pleiotropic genetic variants in the set used as instrumental variables, violating one of the core IV assumptions. Genetic variants that give outlying estimates are often considered to be potentially pleiotropic variants. Radial plots can be used in MR to help identify these variants. Analogous plots for MVMR have so far been unavailable due to the multidimensional nature of the analysis.

Methods: We propose a radial formulation of MVMR, and an adapted Galbraith radial plot, which allows for the estimated effect of each exposure within an MVMR analysis to be visualised. Radial MVMR additionally includes an option for removal of outlying SNPs which may violate one or more assumptions of MVMR. A RMVMR R package is presented as accompanying software for implementing the methods described.

Results: We demonstrate the effectiveness of the radial MVMR approach through simulations and applied analyses. We highlight how outliers with respect to all exposures can be visualised and removed through Radial MVMR. We present simulations that illustrate how outlier removal decreases the bias in estimated effects under various forms of pleiotropy. We apply Radial MVMR to estimate the effect of lipid fractions on coronary heart disease (CHD). In combination with simulated examples, we highlight how important features of MVMR analyses can be explored using a range of tools incorporated within the RMVMR R package.

Conclusions: Radial MVMR effectively visualises causal effect estimates, and provides valuable diagnostic information with respect to the underlying assumptions of MVMR.

Enhancers play a critical role in regulating precise gene expression patterns essential for development and cellular identity; however, how gene-enhancer specificity is encoded within the genome is not clearly defined. To investigate how this specificity arises within topologically associated domains (TAD), we performed allele-specific genome editing of sequences surrounding the Lefty1 and Lefty2 paralogs in mouse embryonic stem cells. The Lefty genes arose from a tandem duplication event and these genes interact with each other in chromosome conformation capture assays which place these genes within the same TAD. Despite their physical proximity, we demonstrate that these genes are primarily regulated by separate enhancer elements. Through CRISPR-Cas9 mediated deletions to remove the intervening chromatin between the Lefty genes, we reveal a distance-dependent dosage effect of the Lefty2 enhancer on Lefty1 expression. These findings indicate a role for chromatin distance in insulating gene expression domains in the Lefty locus in the absence of architectural insulation.

Genome-wide association studies (GWAS) traditionally analyze single traits, e.g., disease diagnoses or biomarkers. Nowadays, large-scale cohorts such as UK Biobank (UKB) collect imaging data with sample sizes large enough to perform genetic association testing. Typical approaches to GWAS on high-dimensional modalities extract predefined features from the data, e.g., volumes of regions of interest. This limits the scope of such studies to predefined traits and can ignore novel patterns present in the data. TransferGWAS employs deep neural networks (DNNs) to extract low-dimensional representations of imaging data for GWAS, eliminating the need for predefined biomarkers. Here, we apply transferGWAS on brain MRI data from UKB. We encoded 36, 311 T1-weighted brain magnetic resonance imaging (MRI) scans using DNN models trained on MRI scans from the Alzheimer's Disease Neuroimaging Initiative, and on natural images from the ImageNet dataset, and performed a multivariate GWAS on the resulting features. We identified 289 independent loci, associated among others with bone density, brain, or cardiovascular traits, and 11 regions having no previously reported associations. We fitted polygenic scores (PGS) of the deep features, which improved predictions of bone mineral density and several other traits in a multi-PGS setting, and computed genetic correlations with selected phenotypes, which pointed to novel links between diffusion MRI traits and type 2 diabetes. Overall, our findings provided evidence that features learned with DNN models can uncover additional heritable variability in the human brain beyond the predefined measures, and link them to a range of non-brain phenotypes.

Integrin signaling plays important roles in development and disease. An adhesion signaling network called the integrin adhesome has been principally defined using bioinformatics and cell-based proteomics. To date, the adhesome has not been studied using integrated proteomic and genetic approaches. Here, proteomic studies in C. elegans identified physical associations between the RPM-1 ubiquitin ligase signaling hub and numerous adhesome components including Talin (TLN-1), Kindlin (UNC-112) and β-integrin (PAT-3). C. elegans RPM-1 is orthologous to human MYCBP2, a prominent player in nervous system development recently associated with a neurodevelopmental disorder. After curating and updating the conserved C. elegans adhesome, we identified an adhesome subnetwork physically associated with RPM-1 that has extensive links to human neurobehavioral abnormalities. Using neuron-specific, CRISPR loss-of-function strategies, we demonstrate that a PAT-3/UNC-112/TLN-1 adhesome axis regulates axon termination in mechanosensory neurons by inhibiting RPM-1. Developmental time-course studies and pharmacological results suggest TLN-1 inhibition of RPM-1 affects growth cone collapse and microtubule dynamics during axon outgrowth. These results indicate the PAT-3/UNC-112/TLN-1 adhesome axis restricts RPM-1 signaling to ensure axon outgrowth is terminated in a spatially and temporally accurate manner. Thus, our findings orthogonally validate the adhesome using an organismal setting, identify an adhesome axis that inhibits RPM-1 (MYCBP2), and highlight important new links between the adhesome and brain disorders.

Polycystic kidney disease (PKD) is an important cause of kidney failure, but treatment options are limited. While later stages of the disease have been extensively studied, mechanisms driving the initial conversion of kidney tubules into cysts are not understood. To identify genes with the potential to promote cyst initiation, we deleted polycystin-2 (Pkd2) in mice and surveyed transcriptional changes before and immediately after cysts developed. We identified 74 genes which we term cyst initiation candidates (CICs). To identify conserved changes with relevance to human disease we compared these murine CICs to single cell transcriptomic data derived from patients with PKD and from healthy controls. Tumor-associated calcium signal transducer 2 (Tacstd2) stood out as an epithelial-expressed gene with elevated levels early in cystic transformation that further increased with disease progression. Human tissue biopsies and organoids show that TACSTD2 protein is low in normal kidney cells but is elevated in cyst lining cells, making it an excellent candidate for mechanistic exploration of its role in cyst initiation. While TACSTD2 has not been studied in PKD, it has been studied in cancer where it is highly expressed in solid tumors while showing minimal expression in normal tissue. This property is being exploited by antibody drug conjugates that target TACSTD2 for the delivery of cytotoxic drugs. Our finding that Tacstd2/TACSTD2 is prevalent in cysts, but not normal tissue, suggests that it should be explored as a candidate for drug development in PKD. More immediately, our work suggests that PKD patients undergoing TACSTD2-directed treatment for breast and urothelial cancer should be monitored for kidney effects.