Trending Papers in genetics

Pyruvate Kinase Deficiency (PKD) is an autosomal recessive disorder caused by mutations in the gene, which constitutes the main cause of chronic non-spherocytic hemolytic anemia. PKD incidence is estimated in 1 in 20,000 people worldwide. The gene encodes for the erythroid pyruvate kinase protein (RPK) implicated in the last step of the anaerobic glycolysis in red blood cells. The defective enzyme fails to maintain normal erythrocyte ATP levels, producing severe hemolytic anemia, and can be fatal in severe patients. The only curative treatment for PKD is allogeneic hematopoietic stem and progenitor cells (HSPC) transplantation, so far. However, HSPC transplant is associated with a significant morbidity and mortality, especially in PKD patients. Here, we address the correction of PKD through precise gene editing at the endogenous locus to keep the tight regulation of RPK enzyme during erythropoiesis. We combined CRISPR/Cas9 system and rAAVs for donor matrix delivery to build an efficient and safe system to knock-in a therapeutic donor at the translation start site of the RPK isoform in human hematopoietic progenitors. Edited human hematopoietic progenitors efficiently reconstituted human hematopoiesis in primary and secondary immunodeficient recipient mice. Moreover, erythroid cells derived from edited PKD-HSPCs restored normal levels of ATP, demonstrating the restoration of RPK function in PKD erythropoiesis after gene editing. Our gene editing strategy may represent a lifelong therapy to restore RPK functionality in RBCs of patients and correct PKD.

Arsenic is reportedly a biphasic inorganic compound for its toxicity and anticancer effects in humans [1, 2]. Recent studies have shown that certain arsenic compounds including arsenic hexoxide (AS O ; hereafter, AS6) induce programmed cell death and cell cycle arrest in human cancer cells and murine cancer models [3, 4]. However, the mechanisms by which AS6 suppresses cancer cells are incompletely understood. In this study, we report the mechanisms of AS6 through transcriptome analyses. In particular, the cytotoxicity and global gene expression regulation by AS6 were compared in human normal and cancer breast epithelial cells. Using RNA-sequencing and bioinformatics analyses, differentially expressed genes in significantly affected biological pathways in these cell types were validated by real-time quantitative polymerase chain reaction and immunoblotting assays. Our data show markedly differential effects of AS6 on cytotoxicity and gene expression in human mammary epithelial normal cells (HUMEC) and Michigan Cancer Foundation 7 (MCF7), a human mammary epithelial cancer cell line. AS6 selectively arrests cell growth and induces cell death in MCF7 cells without affecting the growth of HUMEC in a dose-dependent manner. AS6 alters the transcription of a large number of genes in MCF7 cells, but much fewer genes in HUMEC. Importantly, we found that the cell proliferation, cell cycle, and DNA repair pathways are significantly suppressed whereas cellular stress response and apoptotic pathways increase in AS6-treated MCF7 cells. Together, we provide the first evidence of differential effects of AS6 on normal and cancerous breast epithelial cells, suggesting that AS6 at moderate concentrations induces cell cycle arrest and apoptosis through modulating genome-wide gene expression, leading to compromised DNA repair and increased genome instability selectively in human breast cancer cells.

Child educational development is associated with major psychological, social, economic and health milestones throughout the life course. Understanding the early origins of educational inequalities and their reproduction across generations is therefore crucial. Recent genomic studies provide novel insights in this regard, uncovering “genetic nurture” effects, whereby parental genotypes influence offspring’s educational development via environmental pathways rather than genetic transmission. These findings have yet to be systematically appraised. We conducted the first systematic review and meta-analysis to quantify genetic nurture effects on educational outcomes and investigate key moderators. Twelve studies comprising 38,654 distinct parent(s)-offspring pairs or trios from eight cohorts were included, from which we derived 22 estimates of genetic nurture effects. Multilevel random effects models showed that the effect of genetic nurture on offspring’s educational outcomes ( = 0.08, 95% CI [0.07, 0.09]) was about half the size of direct genetic effects ( = 0.17, 95% CI [0.13, 0.20]). Maternal and paternal genetic nurture effects were similar in magnitude, suggesting comparable roles of mothers and fathers in determining their children’s educational outcomes. Genetic nurture effects were largely explained by parental educational level and family socioeconomic status, suggesting that genetically influenced environments play an important role in shaping child educational outcomes. Even after accounting for genetic transmission, we provide evidence that environmentally mediated parental genetic influences contribute to the intergenerational transmission of educational outcomes. Further exploring these downstream environmental pathways may inform educational policies aiming to break the intergenerational cycle of educational underachievement and foster social mobility.

Scarless genome editing is an important tool for the accurate recapitulation of genetic variation in human disease models. Various CRISPR/Cas9-based scarless editing methods have been reported. However, some of these methods have low editing efficiency (1-5%) and require manual selection of hundreds of clones to reach the desired number. Other protocols use large selection cassettes with laborious vector assembly and specialized reagents and equipment, or have poorly understood off-target effects. To address these limitations, we developed a simple, highly efficient scarless editing strategy to edit DNA sequences in induced pluripotent stem cells, which we call CRISPR Del/Rei. This novel editing strategy consists of a two-step deletion-reinsertion strategy that produces isogenic clones in ~8 weeks using accessible, user-friendly reagents. The editing efficiency ranges from ~15–100% for Step 1 and ~5–20% for Step 2 after selection, which greatly reduces the amount of required manual clone isolation. Screening the transfected bulk cells and the individual clones is rapid and simple, consisting of PCR and gel electrophoresis. Despite the two editing steps, off-target effects are rare. Additionally, the experiment is well-controlled because the same protocol generates isogenic clones carrying all variant alleles. In this way, CRISPR Del/Rei serves as a valuable addition to the evolving CRISPR/Cas9 gene-editing toolset.

Transcriptional regulation by Wnt signalling is primarily thought to be accomplished by a complex of β-catenin and TCF family transcription factors (TFs). Although numerous studies have suggested that additional TFs play roles in regulating Wnt target genes, their mechanisms of action have not been investigated in detail. We characterised a Wnt-responsive element (WRE) downstream of the Wnt target gene and found that TCFs and Caudal-related homeodomain (CDX) proteins were required for its activation. Using a new separation-of-function TCF mutant, we found that WRE activity requires the formation of a TCF/CDX complex. Our systematic mutagenesis of this enhancer identified other sequences essential for activation by Wnt signalling, including several copies of a novel CAG DNA motif. Computational and experimental evidence indicates that the TCF/CDX/CAG mode of regulation is prevalent in multiple WREs. Put together, our results demonstrate the complex nature of cis- and trans- interactions required for signal-dependent enhancer activity.

Complementary to the genome, the concept of exposome has been proposed to capture the totality of human environmental exposures. While there has been some recent progress on the construction of the exposome, few tools exist that can integrate the genome and exposome for complex trait analyses. Here we propose a linear mixed model approach to bridge this gap, which jointly models the random effects of the two omics layers on phenotypes of complex traits. We illustrate our approach using traits from the UK Biobank (e.g., BMI & height for N ∼ 35,000) with a small fraction of the exposome that comprises 28 lifestyle factors. The joint model of the genome and exposome explains substantially more phenotypic variance and significantly improves phenotypic prediction accuracy, compared to the model based on the genome alone. The additional phenotypic variance captured by the exposome includes its additive effects as well as non-additive effects such as genome-exposome (gxe) and exposome-exposome (exe) interactions. For example, 19% of variation in BMI is explained by additive effects of the genome, while additional 7.2% by additive effects of the exposome, 1.9% by exe interactions and 4.5% by gxe interactions. Correspondingly, the prediction accuracy for BMI, computed using Pearson’s correlation between the observed and predicted phenotypes, improves from 0.15 (based on the genome alone) to 0.35 (based on the genome & exposome). We also show, using established theories, integrating genomic and exposomic data is essential to attaining a clinically meaningful level of prediction accuracy for disease traits. In conclusion, the genomic and exposomic effects can contribute to phenotypic variation via their latent relationships, i.e. genome-exposome correlation, and gxe and exe interactions, and modelling these effects has a great potential to improve phenotypic prediction accuracy and thus holds a great promise for future clinical practice.

Ethiopia, the probable center of origin and diversity for sorghum ( L. [Moench]) and with unique eco-geographic features, possesses a large number of sorghum landraces that have not been well studied. Increased knowledge of this diverse germplasm through large-scale genomic characterization may contribute for understanding of evolutionary biology, and adequate use of these valuable resources from the center of origin. In this study, we characterized genetic diversity, population structure and selection signature in 304 sorghum accessions collected from diverse sorghum growing regions of Ethiopia using genotyping-by-sequencing (GBS). We identified a total of 108,107 high-quality single nucleotide polymorphism (SNPs) markers that were evenly distributed across the sorghum genome. The average gene diversity among accessions was high(H = 0.29). We detected a relatively low frequency of rare alleles (26%), highlighting the potential of this germplasm for subsequent allele mining studies through genome wide association studies (GWAS). While we found no evidence of genetic differentiation among administrative regions (F = 0.02, = 0.12), population structure and cluster analyses showed clear differentiation among six Ethiopian sorghum populations (F = 0.28, = 0.01) adapting to different environments. Analysis of SNP differentiation between the identified genetic groups revealed a total of 40 genomic regions carrying signatures of selection. These regions harbored candidate genes potentially involved in a variety of biological processes, including abiotic stress tolerance, pathogen defense and reproduction. Overall, a high level of untapped diversity for sorghum improvement remains available in Ethiopia, with patterns of diversity consistent with divergent selection on a range of adaptive characteristics.

Because no feasible theoretical model can depict the complexity of phenotype development from a genotype, the joint significance of linkage disequilibrium (LD), epistasis, and inbreeding on the genetic variances remains unclear. The objective of this investigation was to assess the impact of LD and epistasis on the genetic variances and covariances between relatives in non-inbred and inbred populations using simulated data. We provided the theoretical background and simulated grain yield assuming 400 genes in 10 chromosomes of 200 and 50 cM. We generated five populations with low to high LD levels, assuming 10 generations of random cross and selfing. The analysis of the parametric LD in the populations shows that the LD level depends mainly on the gene density. The significance of the LD level is impressive on the magnitude of the genotypic and additive variances, which is the most important component of the genotypic variance, regardless of the LD level and the degree of inbreeding. Regardless of the type of epistasis, the ratio epistatic variance/genotypic variance is proportional to the percentage of the epistatic genes. For the epistatic variances, except for duplicate epistasis and dominant and recessive epistasis, with 100% of epistatic genes, their magnitudes are much lower than the magnitude of the additive variance. The additive x additive variance is the most important epistatic variance. Our results explain why LD for genes and relationship information are key factors affecting the genomic prediction accuracy of complex traits and the efficacy of association studies.

Hundreds of the proteins encoded in human genomes contain domains that vary in size or copy number due to variable numbers of tandem repeats (VNTRs) in protein-coding exons. VNTRs have eluded analysis by the molecular methods-SNP arrays and high-throughput sequencing-used in large-scale human genetic studies to date; thus, the relationships of VNTRs to most human phenotypes are unknown. We developed ways to estimate VNTR lengths from whole-exome sequencing data, identify the SNP haplotypes on which VNTR alleles reside, and use imputation to project these haplotypes into abundant SNP data. We analyzed 118 protein-altering VNTRs in 415,280 UK Biobank participants for association with 791 phenotypes. Analysis revealed some of the strongest associations of common variants with human phenotypes including height, hair morphology, and biomarkers of human health; for example, a VNTR encoding 13-44 copies of a 19-amino-acid repeat in the chondroitin sulfate domain of aggrecan (ACAN) associated with height variation of 3.4 centimeters (s.e. 0.3 cm). Incorporating large-effect VNTRs into analysis also made it possible to map many additional effects at the same loci: for the blood biomarker lipoprotein(a), for example, analysis of the kringle IV-2 VNTR within the LPA gene revealed that 18 coding SNPs and the VNTR in LPA explained 90% of lipoprotein(a) heritability in Europeans, enabling insights about population differences and epidemiological significance of this clinical biomarker. These results point to strong, cryptic effects of highly polymorphic common structural variants that have largely eluded molecular analyses to date.