Population genetic models of GERP scores suggest pervasive turnover of constrained sites across mammalian evolution

Unifying approaches from statistical genetics and phylogenetics for mapping phenotypes in structured populations

In both statistical genetics and phylogenetics, a major goal is to identify correlations between genetic loci or other aspects of the phenotype or environment and a focal trait. In these 2 fields, there are sophisticated but disparate statistical traditions aimed at these tasks. The disconnect between their respective approaches is becoming untenable as questions in medicine, conservation biology, and evolutionary biology increasingly rely on integrating data from within and among species, and once-clear conceptual divisions are becoming increasingly blurred. To help bridge this divide, we lay out a general model describing the covariance between the genetic contributions to the quantitative phenotypes of different individuals. Taking this approach shows that standard models in both statistical genetics (e.g., genome-wide association studies; GWAS) and phylogenetic comparative biology (e.g., phylogenetic regression) can be interpreted as special cases of this more general quantitative-genetic model. The fact that these models share the same core architecture means that we can build a unified understanding of the strengths and limitations of different methods for controlling for genetic structure when testing for associations. We develop intuition for why and when spurious correlations may occur analytically and conduct population-genetic and phylogenetic simulations of quantitative traits. The structural similarity of problems in statistical genetics and phylogenetics enables us to take methodological advances from one field and apply them in the other. We demonstrate by showing how a standard GWAS technique-including both the genetic relatedness matrix (GRM) as well as its leading eigenvectors, corresponding to the principal components of the genotype matrix, in a regression model-can mitigate spurious correlations in phylogenetic analyses. As a case study, we re-examine an analysis testing for coevolution of expression levels between genes across a fungal phylogeny and show that including eigenvectors of the covariance matrix as covariates decreases the false positive rate while simultaneously increasing the true positive rate. More generally, this work provides a foundation for more integrative approaches for understanding the genetic architecture of phenotypes and how evolutionary processes shape it.

Whole-genome sequencing in 333,100 individuals reveals rare non-coding single variant and aggregate associations with height

The role of rare non-coding variation in complex human phenotypes is still largely unknown. To elucidate the impact of rare variants in regulatory elements, we performed a whole-genome sequencing association analysis for height using 333,100 individuals from three datasets: UK Biobank (N = 200,003), TOPMed (N = 87,652) and All of Us (N = 45,445). We performed rare ( < 0.1% minor-allele-frequency) single-variant and aggregate testing of non-coding variants in regulatory regions based on proximal-regulatory, intergenic-regulatory and deep-intronic annotation. We observed 29 independent variants associated with height at P <  6 × 10 - 10 after conditioning on previously reported variants, with effect sizes ranging from -7cm to +4.7 cm. We also identified and replicated non-coding aggregate-based associations proximal to HMGA1 containing variants associated with a 5 cm taller height and of highly-conserved variants in MIR497HG on chromosome 17. We have developed an approach for identifying non-coding rare variants in regulatory regions with large effects from whole-genome sequencing data associated with complex traits.

Genomic adaptation to small population size and saltwater consumption in the critically endangered Cat Ba langur

Many mammal species have declining populations, but the consequences of small population size on the genomic makeup of species remain largely unknown. We investigated the evolutionary history, genetic load and adaptive potential of the Cat Ba langur (Trachypithecus poliocephalus), a primate species endemic to Vietnam's famous Ha Long Bay and with less than 100 living individuals one of the most threatened primates in the world. Using high-coverage whole genome data of four wild individuals, we revealed the Cat Ba langur as sister species to its conspecifics of the northern limestone langur clade and found no evidence for extensive secondary gene flow after their initial separation. Compared to other primates and mammals, the Cat Ba langur showed low levels of genetic diversity, long runs of homozygosity, high levels of inbreeding and an excess of deleterious mutations in homozygous state. On the other hand, genetic diversity has been maintained in protein-coding genes and on the gene-rich human chromosome 19 ortholog, suggesting that the Cat Ba langur retained most of its adaptive potential. The Cat Ba langur also exhibits several unique non-synonymous variants that are related to calcium and sodium metabolism, which may have improved adaptation to high calcium intake and saltwater consumption.

Unveiling Genetic Potential for Equine Meat Production: A Bioinformatics Approach

In view of the predicted significant increase in global meat production, alternative sources such as horsemeat are becoming increasingly important due to their lower environmental impact and high nutritional value. This study aimed to identify SNP markers on the GeneSeek® Genomic Profiler™ Equine (Neogen, Lansing, MI, USA) that are important for horsemeat production traits. First, orthologous genes related to meat yield in cattle and common genes between horses and cattle within QTLs for body size and weight were identified. Markers for these genes were then evaluated based on predicted variant consequences, GERP scores, and positions within constrained elements and orthologous regulatory regions in pigs. A total of 268 markers in 57 genes related to meat production were analyzed. This resulted in 27 prioritized SNP markers in 22 genes, including notable markers in LCORL, LASP1, IGF1R, and MSTN. These results will benefit smallholder farmers by providing genetic insights for selective breeding that could improve meat yield. This study also supports future large-scale genetic analyses such as GWAS and Genomic Best Linear Unbiased Prediction (GBLUP). The results of this study may be helpful in improving the accuracy of genomic breeding values. However, limitations include reliance on bioinformatics without experimental validation. Future research can validate these markers and consider a wider range of traits to ensure accuracy in equine breeding.

Exploring the genetic and epigenetic underpinnings of early-onset cancers: Variant prioritization for long read whole genome sequencing from family cancer pedigrees

Despite significant advances in our understanding of genetic cancer susceptibility, known inherited cancer predisposition syndromes explain at most 20% of early-onset cancers. As early-onset cancer prevalence continues to increase, the need to assess previously inaccessible areas of the human genome, harnessing a trio or quad family-based architecture for variant filtration, may reveal further insights into cancer susceptibility. To assess a broader spectrum of variation than can be ascertained by multi-gene panel sequencing, or even whole genome sequencing with short reads, we employed long read whole genome sequencing using an Oxford Nanopore Technology (ONT) PromethION of 3 families containing an early-onset cancer proband using a trio or quad family architecture. Analysis included 2 early-onset colorectal cancer family trios and one quad consisting of two siblings with testicular cancer, all with unaffected parents. Structural variants (SVs), epigenetic profiles and single nucleotide variants (SNVs) were determined for each individual, and a filtering strategy was employed to refine and prioritize candidate variants based on the family architecture. The family architecture enabled us to focus on inapposite variants while filtering variants shared with the unaffected parents, significantly decreasing background variation that can hamper identification of potentially disease causing differences. Candidate d e novo and compound heterozygous variants were identified in this way. Gene expression, in matched neoplastic and pre-neoplastic lesions, was assessed for one trio. Our study demonstrates the feasibility of a streamlined analysis of genomic variants from long read ONT whole genome sequencing and a way to prioritize key variants for further evaluation of pathogenicity, while revealing what may be missing from panel based analyses.

Clinical manifestations and spermatogenesis outcomes in Chinese patients with congenital hypogonadotropic hypogonadism caused by inherited or de novo FGFR1 mutations

Fibroblast growth factor receptor 1 ( FGFR1 ) mutations are associated with congenital hypogonadotropic hypogonadism (CHH) through inheritance or spontaneous occurrence. We detected FGFR1 mutations in a Chinese cohort of 210 CHH patients at Peking Union Medical College Hospital (Beijing, China) using next-generation and Sanger sequencing. We assessed missense variant pathogenicity using six bioinformatics tools and compared clinical features and treatment outcomes between inherited and de novo mutation groups. Among 19 patients with FGFR1 mutations, three were recurrent, and 16 were novel variants. Sixteen of the novel mutations were likely pathogenic according to the American College of Medical Genetics and Genomics (ACMG) guidelines, with the prevalent P366L variant. The majority of FGFR1 mutations was inherited (57.9%), with frameshift mutations exclusive to the de novo mutation group. The inherited mutation group had a lower incidence of cryptorchidism, short stature, and skeletal deformities. In the inherited mutation group, luteinizing hormone (LH) levels were 0.5 IU l -1 , follicle-stimulating hormone (FSH) levels were 1.0 IU l -1 , and testosterone levels were 1.3 nmol l -1 . In contrast, the de novo group had LH levels of 0.2 IU l -1 , FSH levels of 0.5 IU l -1 , and testosterone levels of 0.9 nmol l -1 , indicating milder hypothalamus-pituitary-gonadal axis (HPGA) functional deficiency in the inherited group. The inherited mutation group showed a tendency toward higher spermatogenesis rates. In conclusion, this study underscores the predominance of inherited FGFR1 mutations and their association with milder HPGA dysfunction compared to de novo mutations, contributing to our understanding of the genetic and clinical aspects of FGFR1 mutations.

Mutations in yeast are deleterious on average regardless of the degree of adaptation to the testing environment

The role of spontaneous mutations in evolution depends on the distribution of their effects on fitness. Despite a general consensus that new mutations are deleterious on average, a handful of mutation accumulation experiments in diverse organisms instead suggest that beneficial and deleterious mutations can have comparable fitness impacts, i.e. the product of their respective rates and effects can be roughly equal. We currently lack a general framework for predicting when such a pattern will occur. One idea is that beneficial mutations will be more evident in genotypes that are not well adapted to the testing environment. We tested this prediction experimentally in the laboratory yeast Saccharomyces cerevisiae by allowing nine replicate populations to adapt to novel environments with complex sets of stressors. After >1000 asexual generations interspersed with 41 rounds of sexual reproduction, we assessed the mean effect of induced mutations on yeast growth in both the environment to which they had been adapting and the alternative novel environment. The mutations were deleterious on average, with the severity depending on the testing environment. However, we found no evidence that the adaptive match between genotype and environment is predictive of mutational fitness effects.

In Silico Characterization of Pathogenic Homeodomain Missense Mutations in the PITX2 Gene

Paired homologous domain transcription factor 2 (PITX2) is critically involved in ocular and cardiac development. Mutations in PITX2 are consistently reported in association with Axenfeld-Rieger syndrome, an autosomal dominant genetic disorder and atrial fibrillation, a common cardiac arrhythmia. In this study, we have mined missense mutations in PITX2 gene from NCBI-dbSNP and Ensembl databases, evaluated the pathogenicity of the missense variants in the homeodomain and C-terminal region using five in silico prediction tools SIFT, PolyPhen2, GERP, Mutation Assessor and CADD. Fifteen homeodomain mutations G42V, G42R, R45W, S49Y, R53W, E53D, E55V, R62H, P65S, R69H, G75R, R84G, R86K, R87W, R91P were found to be highly pathogenic by both SIFT, PolyPhen2 were further functionally characterized using I-Mutant 2.0, Consurf, MutPred and Project Hope. The findings of the study can be used for prioritizing mutations in the context of genetic studies.

Where do obesity and male infertility collide?

The parallel rise in obesity and male infertility in modern societies necessitates the identification of susceptibility genes underlying these interconnected health issues. In our study, we conducted a comprehensive search in the OMIM database to identify genes commonly associated with male infertility and obesity. Subsequently, we performed an insilico analysis using the REVEL algorithm to detect pathogenic single nucleotide polymorphisms (SNPs) in the coding region of these candidate genes. To validate our findings in vivo, we conducted a comprehensive analysis of SNPs and gene expression of candidate genes in 200 obese infertile subjects and 240 obese fertile individuals using ARMS-PCR. Additionally, we analyzed 20 fertile and 22 infertile obese individuals using Realtime-qPCR. By removing duplicated queries, we obtained 197 obesity-related genes and 102 male infertility-related genes from the OMIM database. Interestingly, the APOB gene was found in common between the two datasets. REVEL identified the rs13306194 variant as potentially pathogenic with a calculated score of 0.524. The study identified a significant association between the AA (P value = 0.001) genotype and A allele (P value = 0.003) of the APOB rs13306194 variant and infertility in obese men. APOB expression levels were significantly lower in obese infertile men compared to obese fertile controls (p < 0.01). Moreover, the AA genotype of rs13306194 APOB was associated with a significant decrease in APOB gene expression in obese infertile men (p = 0.05). There is a significant association between the Waist-to-Hip Ratio (WHR) and LH with infertility in the obese infertile group. These results are likely to contribute to a better understanding of the causes of male infertility and its association with obesity.

Whole genome sequencing of mouse lines divergently selected for fatness (FLI) and leanness (FHI) revealed several genetic variants as candidates for novel obesity genes

BACKGROUND

Analysing genomes of animal model organisms is widely used for understanding the genetic basis of complex traits and diseases, such as obesity, for which only a few mouse models exist, however, without their lean counterparts.

OBJECTIVE

To analyse genetic differences in the unique mouse models of polygenic obesity (Fat line) and leanness (Lean line) originating from the same base population and established by divergent selection over more than 60 generations.

METHODS

Genetic variability was analysed using WGS. Variants were identified with GATK and annotated with Ensembl VEP. g.Profiler, WebGestalt, and KEGG were used for GO and pathway enrichment analysis. miRNA seed regions were obtained with miRPathDB 2.0, LncRRIsearch was used to predict targets of identified lncRNAs, and genes influencing adipose tissue amount were searched using the IMPC database.

RESULTS

WGS analysis revealed 6.3 million SNPs, 1.3 million were new. Thousands of potentially impactful SNPs were identified, including within 24 genes related to adipose tissue amount. SNP density was highest in pseudogenes and regulatory RNAs. The Lean line carries SNP rs248726381 in the seed region of mmu-miR-3086-3p, which may affect fatty acid metabolism. KEGG analysis showed deleterious missense variants in immune response and diabetes genes, with food perception pathways being most enriched. Gene prioritisation considering SNP GERP scores, variant consequences, and allele comparison with other mouse lines identified seven novel obesity candidate genes: 4930441H08Rik, Aff3, Fam237b, Gm36633, Pced1a, Tecrl, and Zfp536.

CONCLUSION

WGS revealed many genetic differences between the lines that accumulated over the selection period, including variants with potential negative impacts on gene function. Given the increasing availability of mouse strains and genetic polymorphism catalogues, the study is a valuable resource for researchers to study obesity.

Genetic load and viability of a future restored northern white rhino population

As biodiversity loss outpaces recovery, conservationists are increasingly turning to novel tools for preventing extinction, including cloning and in vitro gametogenesis of biobanked cells. However, restoration of populations can be hindered by low genetic diversity and deleterious genetic load. The persistence of the northern white rhino (Ceratotherium simum cottoni) now depends on the cryopreserved cells of 12 individuals. These banked genomes have higher genetic diversity than southern white rhinos (C. s. simum), a sister subspecies that successfully recovered from a severe bottleneck, but the potential impact of genetic load is unknown. We estimated how demographic history has shaped genome-wide genetic load in nine northern and 13 southern white rhinos. The bottleneck left southern white rhinos with more fixed and homozygous deleterious alleles and longer runs of homozygosity, whereas northern white rhinos retained more deleterious alleles masked in heterozygosity. To gauge the impact of genetic load on the fitness of a northern white rhino population restored from biobanked cells, we simulated recovery using fitness of southern white rhinos as a benchmark for a viable population. Unlike traditional restoration, cell-derived founders can be reintroduced in subsequent generations to boost lost genetic diversity and relieve inbreeding. In simulations with repeated reintroduction of founders into a restored population, the fitness cost of genetic load remained lower than that borne by southern white rhinos. Without reintroductions, rapid growth of the restored population (>20-30% per generation) would be needed to maintain comparable fitness. Our results suggest that inbreeding depression from genetic load is not necessarily a barrier to recovery of the northern white rhino and demonstrate how restoration from biobanked cells relieves some constraints of conventional restoration from a limited founder pool. Established conservation methods that protect healthy populations will remain paramount, but emerging technologies hold promise to bolster these tools to combat the extinction crisis.

High genetic load without purging in caribou, a diverse species at risk

High intra-specific genetic diversity is associated with adaptive potential, which is key for resilience to global change. However, high variation may also support deleterious alleles through genetic load, thereby increasing the risk of inbreeding depression if population sizes decrease. Purging of deleterious variation has been demonstrated in some threatened species. However, less is known about the costs of declines and inbreeding in species with large population sizes and high genetic diversity even though this encompasses many species globally that are expected to undergo population declines. Caribou is a species of ecological and cultural significance in North America with a wide distribution supporting extensive phenotypic variation but with some populations undergoing significant declines resulting in their at-risk status in Canada. We assessed intra-specific genetic variation, adaptive divergence, inbreeding, and genetic load across populations with different demographic histories using an annotated chromosome-scale reference genome and 66 whole-genome sequences. We found high genetic diversity and nine phylogenomic lineages across the continent with adaptive diversification of genes, but also high genetic load among lineages. We found highly divergent levels of inbreeding across individuals, including the loss of alleles by drift but not increased purging in inbred individuals, which had more homozygous deleterious alleles. We also found comparable frequencies of homozygous deleterious alleles between lineages regardless of nucleotide diversity. Thus, further inbreeding may need to be mitigated through conservation efforts. Our results highlight the "double-edged sword" of genetic diversity that may be representative of other species atrisk affected by anthropogenic activities.

Unifying approaches from statistical genetics and phylogenetics for mapping phenotypes in structured populations

In both statistical genetics and phylogenetics, a major goal is to identify correlations between genetic loci or other aspects of the phenotype or environment and a focal trait. In these two fields, there are sophisticated but disparate statistical traditions aimed at these tasks. The disconnect between their respective approaches is becoming untenable as questions in medicine, conservation biology, and evolutionary biology increasingly rely on integrating data from within and among species, and once-clear conceptual divisions are becoming increasingly blurred. To help bridge this divide, we derive a general model describing the covariance between the genetic contributions to the quantitative phenotypes of different individuals. Taking this approach shows that standard models in both statistical genetics (e.g., Genome-Wide Association Studies; GWAS) and phylogenetic comparative biology (e.g., phylogenetic regression) can be interpreted as special cases of this more general quantitative-genetic model. The fact that these models share the same core architecture means that we can build a unified understanding of the strengths and limitations of different methods for controlling for genetic structure when testing for associations. We develop intuition for why and when spurious correlations may occur using analytical theory and conduct population-genetic and phylogenetic simulations of quantitative traits. The structural similarity of problems in statistical genetics and phylogenetics enables us to take methodological advances from one field and apply them in the other. We demonstrate this by showing how a standard GWAS technique-including both the genetic relatedness matrix (GRM) as well as its leading eigenvectors, corresponding to the principal components of the genotype matrix, in a regression model-can mitigate spurious correlations in phylogenetic analyses. As a case study of this, we re-examine an analysis testing for co-evolution of expression levels between genes across a fungal phylogeny, and show that including covariance matrix eigenvectors as covariates decreases the false positive rate while simultaneously increasing the true positive rate. More generally, this work provides a foundation for more integrative approaches for understanding the genetic architecture of phenotypes and how evolutionary processes shape it.

Exploring TTN variants as genetic insights into cardiomyopathy pathogenesis and potential emerging clues to molecular mechanisms in cardiomyopathies

The giant protein titin (TTN) is a sarcomeric protein that forms the myofibrillar backbone for the components of the contractile machinery which plays a crucial role in muscle disorders and cardiomyopathies. Diagnosing TTN pathogenic variants has important implications for patient management and genetic counseling. Genetic testing for TTN variants can help identify individuals at risk for developing cardiomyopathies, allowing for early intervention and personalized treatment strategies. Furthermore, identifying TTN variants can inform prognosis and guide therapeutic decisions. Deciphering the intricate genotype-phenotype correlations between TTN variants and their pathologic traits in cardiomyopathies is imperative for gene-based diagnosis, risk assessment, and personalized clinical management. With the increasing use of next-generation sequencing (NGS), a high number of variants in the TTN gene have been detected in patients with cardiomyopathies. However, not all TTN variants detected in cardiomyopathy cohorts can be assumed to be disease-causing. The interpretation of TTN variants remains challenging due to high background population variation. This narrative review aimed to comprehensively summarize current evidence on TTN variants identified in published cardiomyopathy studies and determine which specific variants are likely pathogenic contributors to cardiomyopathy development.

Genetic polymorphisms in vitamin E transport genes as determinants for risk of equine neuroaxonal dystrophy

BACKGROUND

Equine neuroaxonal dystrophy/equine degenerative myeloencephalopathy (eNAD/EDM) is an inherited neurodegenerative disorder associated with vitamin E deficiency. In humans, polymorphisms in genes involved in vitamin E uptake and distribution determines individual vitamin E requirements.

HYPOTHESIS/OBJECTIVES

Genetic polymorphisms in genes involved in vitamin E metabolism would be associated with an increased risk of eNAD/EDM in Quarter Horses (QHs).

ANIMALS

Whole-genome sequencing: eNAD/EDM affected (n = 9, postmortem [PM]-confirmed) and control (n = 32) QHs.

VALIDATION

eNAD/EDM affected (n = 39, 23-PM confirmed) and control (n = 68, 7-PM confirmed) QHs. Allele frequency (AF): Publicly available data from 504 horses across 47 breeds.

METHODS

Retrospective, case control study. Whole-genome sequencing was performed and genetic variants identified within 28 vitamin E candidate genes. These variants were subsequently genotyped in the validation cohort.

RESULTS

Thirty-nine confirmed variants in 15 vitamin E candidate genes were significantly associated with eNAD/EDM (P < .01). In the validation cohort, 2 intronic CD36 variants (chr4:726485 and chr4:731082) were significantly associated with eNAD/EDM in clinical (P = 2.78 × 10-4 and P = 4 × 10-4 , respectively) and PM-confirmed cases (P = 6.32 × 10-6 and 1.04 × 10-5 , respectively). Despite the significant association, variant AFs were low in the postmortem-confirmed eNAD/EDM cases (0.22-0.26). In publicly available equine genomes, AFs ranged from 0.06 to 0.1.

CONCLUSIONS AND CLINICAL IMPORTANCE

Many PM-confirmed cases of eNAD/EDM were wild-type for the 2 intronic CD36 SNPs, suggesting either a false positive association or genetic heterogeneity of eNAD/EDM within the QH breed.

A Functional Single-Nucleotide Polymorphism Upstream of the Collagen Type III Gene Is Associated with Catastrophic Fracture Risk in Thoroughbred Horses

Fractures caused by bone overloading are a leading cause of euthanasia in Thoroughbred racehorses. The risk of fatal fracture has been shown to be influenced by both environmental and genetic factors but, to date, no specific genetic mechanisms underpinning fractures have been identified. In this study, we utilised a genome-wide polygenic risk score to establish an in vitro cell system to study bone gene regulation in horses at high and low genetic risk of fracture. Candidate gene expression analysis revealed differential expression of COL3A1 and STAT1 genes in osteoblasts derived from high- and low-risk horses. Whole-genome sequencing of two fracture cases and two control horses revealed a single-nucleotide polymorphism (SNP) upstream of COL3A1 that was confirmed in a larger cohort to be significantly associated with fractures. Bioinformatics tools predicted that this SNP may impact the binding of the transcription factor SOX11. Gene modulation demonstrated SOX11 is upstream of COL3A1, and the region binds to nuclear proteins. Furthermore, luciferase assays demonstrated that the region containing the SNP has promoter activity. However, the specific effect of the SNP depends on the broader genetic background of the cells and suggests other factors may also be involved in regulating COL3A1 expression. In conclusion, we have identified a novel SNP that is significantly associated with fracture risk and provide new insights into the regulation of the COL3A1 gene.

Selection on the promoter regions plays an important role in complex traits during duck domestication

BACKGROUND

Identifying the key factors that underlie complex traits during domestication is a great challenge for evolutionary and biological studies. In addition to the protein-coding region differences caused by variants, a large number of variants are located in the noncoding regions containing multiple types of regulatory elements. However, the roles of accumulated variants in gene regulatory elements during duck domestication and economic trait improvement are poorly understood.

RESULTS

We constructed a genomics, transcriptomics, and epigenomics map of the duck genome and assessed the evolutionary forces that have been in play across the whole genome during domestication. In total, 304 (42.94%) gene promoters have been specifically selected in Pekin duck among all selected genes. Joint multi-omics analysis reveals that 218 genes (72.01%) with selected promoters are located in open and active chromatin, and 267 genes (87.83%) with selected promoters were highly and differentially expressed in domestic trait-related tissues. One important candidate gene ELOVL3, with a strong signature of differentiation on the core promoter region, is known to regulate fatty acid elongation. Functional experiments showed that the nearly fixed variants in the top selected ELOVL3 promoter in Pekin duck decreased binding ability with HLF and increased gene expression, with the overexpression of ELOVL3 able to increase lipid deposition and unsaturated fatty acid enrichment.

CONCLUSIONS

This study presents genome resequencing, RNA-Seq, Hi-C, and ATAC-Seq data of mallard and Pekin duck, showing that selection of the gene promoter region plays an important role in gene expression and phenotypic changes during domestication and highlights that the variants of the ELOVL3 promoter may have multiple effects on fat and long-chain fatty acid content in ducks.

Single-cell RNA-seq identified novel genes involved in primordial follicle formation

Introduction

The number of primordial follicles (PFs) in mammals determines the ovarian reserve, and impairment of primordial follicle formation (PFF) will cause premature ovarian insufficiency (POI).

Methods

By analyzing public single-cell RNA sequencing performed during PFF on mice and human ovaries, we identified novel functional genes and novel ligand-receptor interaction during PFF. Based on immunofluorescence and in vitro ovarian culture, we confirmed mechanisms of genes and ligand-receptor interaction in PFF. We also applied whole exome sequencing (WES) in 93 cases with POI and whole genome sequencing (WGS) in 465 controls. Variants in POI patients were further investigated by in silico analysis and functional verification.

Results

We revealed ANXA7 (annexin A7) and GTF2F1 (general transcription factor IIF subunit 1) in germ cells to be novel potentially genes in promoting PFF. Ligand Mdk (midkine) in germ cells and its receptor Sdc1 (syndecan 1) in granulosa cells are novel interaction crucial for PFF. Based on immunofluorescence, we confirmed significant up-regulation of ANXA7 in PFs compared with germline cysts, and uniform expression of GTF2F1, MDK and SDC1 during PFF, in 25 weeks human fetal ovary. In vitro investigation indicated that Anxa7 and Gtf2f1 are vital for mice PFF by regulating Jak/Stat3 and Jnk signaling pathways, respectively. Ligand-receptor (Mdk-Sdc1) are crucial for PFF by regulating Pi3k-akt signaling pathway. Two heterozygous variants in GTF2F1, and one heterozygous variants in SDC1 were identified in cases, but no variant were identified in controls. The protein level of GTF2F1 or SDC1 in POI cases are significantly lower than that of controls, indicating the pathogenic effects of the two genes on ovarian function were dosage dependent.

Discussion

Our study identified novel genes and novel ligand-receptor interaction during PFF, and further expanding the genetic architecture of POI.

Using Computational Simulations to Model Deleterious Variation and Genetic Load in Natural Populations

AbstractDeleterious genetic variation is abundant in wild populations, and understanding the ecological and conservation implications of such variation is an area of active research. Genomic methods are increasingly used to quantify the impacts of deleterious variation in natural populations; however, these approaches remain limited by an inability to accurately predict the selective and dominance effects of mutations. Computational simulations of deleterious variation offer a complementary tool that can help overcome these limitations, although such approaches have yet to be widely employed. In this perspective article, we aim to encourage ecological and conservation genomics researchers to adopt greater use of computational simulations to aid in deepening our understanding of deleterious variation in natural populations. We first provide an overview of the components of a simulation of deleterious variation, describing the key parameters involved in such models. Next, we discuss several approaches for validating simulation models. Finally, we compare and validate several recently proposed deleterious mutation models, demonstrating that models based on estimates of selection parameters from experimental systems are biased toward highly deleterious mutations. We describe a new model that is supported by multiple orthogonal lines of evidence and provide example scripts for implementing this model (https://github.com/ckyriazis/simulations_review).

Fitness consequences and ancestry loss in the Apennine brown bear after a simulated genetic rescue intervention

Reduction in population size, with its predicted effects on population fitness, is the most alarming anthropogenic impact on endangered species. By introducing compatible individuals, genetic rescue (GR) is a promising but debated approach for reducing the genetic load unmasked by inbreeding and for restoring the fitness of declining populations. Although GR can improve genetic diversity and fitness, it can also produce loss of ancestry, hampering local adaptation, or replace with introduced variants the unique genetic pools evolved in endemic groups. We used forward genetic simulations based on empirical genomic data to assess fitness benefits and loss of ancestry risks of GR in the Apennine brown bear (Ursus arctos marsicanus). There are approximately 50 individuals of this isolated subspecies, and they have lower genetic diversity and higher inbreeding than other European brown bears, and GR has been suggested to reduce extinction risks. We compared 10 GR scenarios in which the number and genetic characteristics of migrants varied with a non-GR scenario of simple demographic increase due to nongenetic factors. The introduction of 5 individuals of higher fitness or lower levels of deleterious mutations than the target Apennine brown bear from a larger European brown bear population produced a rapid 10-20% increase in fitness in the subspecies and up to 22.4% loss of ancestry over 30 generations. Without a contemporary demographic increase, fitness started to decline again after a few generations. Doubling the population size without GR gradually increased fitness to a comparable level, but without losing ancestry, thus resulting in the best strategy for the Apennine brown bear conservation. Our results highlight the importance for management of endangered species of realistic forward simulations grounded in empirical whole-genome data.

Genetic Screening of ZNF687 and PFN1 in a Paget's Disease of Bone Cohort Indicates an Important Role for the Nuclear Localization Signal of ZNF687

Paget's disease of bone (PDB) is a common, late-onset bone disorder, characterized by focal increases of bone turnover that can result in bone lesions. Heterozygous pathogenic variants in the Sequestosome 1 (SQSTM1) gene are found to be the main genetic cause of PDB. More recently, PFN1 and ZNF687 have been identified as causal genes in patients with a severe, early-onset, polyostotic form of PDB, and an increased likelihood to develop giant cell tumors. In our study, we screened the coding regions of PFN1 and ZNF687 in a Belgian PDB cohort (n = 188). In the PFN1 gene, no variants could be identified, supporting the observation that variants in this gene are extremely rare in PDB. However, we identified 3 non-synonymous coding variants in ZNF687. Interestingly, two of these rare variants (p.Pro937His and p.Arg939Cys) were clustering in the nuclear localization signal of the encoded ZNF687 protein, also harboring the p.Pro937Arg variant, a previously reported disease-causing variant. In conclusion, our findings support the involvement of genetic variation in ZNF687 in the pathogenesis of classical PDB, thereby expanding its mutational spectrum.

Species-wide genomics of kākāpō provides tools to accelerate recovery

The kākāpō is a critically endangered, intensively managed, long-lived nocturnal parrot endemic to Aotearoa New Zealand. We generated and analysed whole-genome sequence data for nearly all individuals living in early 2018 (169 individuals) to generate a high-quality species-wide genetic variant callset. We leverage extensive long-term metadata to quantify genome-wide diversity of the species over time and present new approaches using probabilistic programming, combined with a phenotype dataset spanning five decades, to disentangle phenotypic variance into environmental and genetic effects while quantifying uncertainty in small populations. We find associations for growth, disease susceptibility, clutch size and egg fertility within genic regions previously shown to influence these traits in other species. Finally, we generate breeding values to predict phenotype and illustrate that active management over the past 45 years has maintained both genome-wide diversity and diversity in breeding values and, hence, evolutionary potential. We provide new pathways for informing future conservation management decisions for kākāpō, including prioritizing individuals for translocation and monitoring individuals with poor growth or high disease risk. Overall, by explicitly addressing the challenge of the small sample size, we provide a template for the inclusion of genomic data that will be transformational for species recovery efforts around the globe.

Purging and accumulation of genetic load in conservation

Our ability to assess the threat posed by the genetic load to small and declining populations has been greatly improved by advances in genome sequencing and computational approaches. Yet, considerable confusion remains around the definitions of the genetic load and its dynamics, and how they impact individual fitness and population viability. We illustrate how both selective purging and drift affect the distribution of deleterious mutations during population size decline and recovery. We show how this impacts the composition of the genetic load, and how this affects the extinction risk and recovery potential of populations. We propose a framework to examine load dynamics and advocate for the introduction of load estimates in the management of endangered populations.

Genic constraint against nonsynonymous variation across the mouse genome

BACKGROUND

Selective constraint, the depletion of variation due to negative selection, provides insights into the functional impact of variants and disease mechanisms. However, its characterization in mice, the most commonly used mammalian model, remains limited. This study aims to quantify mouse gene constraint using a new metric called the nonsynonymous observed expected ratio (NOER) and investigate its relationship with gene function.

RESULTS

NOER was calculated using whole-genome sequencing data from wild mouse populations (Mus musculus sp and Mus spretus). Positive correlations were observed between mouse gene constraint and the number of associated knockout phenotypes, indicating stronger constraint on pleiotropic genes. Furthermore, mouse gene constraint showed a positive correlation with the number of pathogenic variant sites in their human orthologues, supporting the relevance of mouse models in studying human disease variants.

CONCLUSIONS

NOER provides a resource for assessing the fitness consequences of genetic variants in mouse genes and understanding the relationship between gene constraint and function. The study's findings highlight the importance of pleiotropy in selective constraint and support the utility of mouse models in investigating human disease variants. Further research with larger sample sizes can refine constraint estimates in mice and enable more comprehensive comparisons of constraint between mouse and human orthologues.

Unraveling Prevalence and Effects of Deleterious Mutations in Maize Elite Lines across Decades of Modern Breeding

Future breeding is likely to involve the detection and removal of deleterious alleles, which are mutations that negatively affect crop fitness. However, little is known about the prevalence of such mutations and their effects on phenotypic traits in the context of modern crop breeding. To address this, we examined the number and frequency of deleterious mutations in 350 elite maize inbred lines developed over the past few decades in China and the United States. Our findings reveal an accumulation of weakly deleterious mutations and a decrease in strongly deleterious mutations, indicating the dominant effects of genetic drift and purifying selection for the two types of mutations, respectively. We also discovered that slightly deleterious mutations, when at lower frequencies, were more likely to be heterozygous in the developed hybrids. This is consistent with complementation as a potential explanation for heterosis. Subsequently, we found that deleterious mutations accounted for more of the variation in phenotypic traits than nondeleterious mutations with matched minor allele frequencies, especially for traits related to leaf angle and flowering time. Moreover, we detected fewer deleterious mutations in the promoter and gene body regions of differentially expressed genes across breeding eras than in nondifferentially expressed genes. Overall, our results provide a comprehensive assessment of the prevalence and impact of deleterious mutations in modern maize breeding and establish a useful baseline for future maize improvement efforts.

GBA1 in Parkinson's disease: variant detection and pathogenicity scoring matters

BACKGROUND

GBA1 variants are the strongest genetic risk factor for Parkinson's disease (PD). However, the pathogenicity of GBA1 variants concerning PD is still not fully understood. Additionally, the frequency of GBA1 variants varies widely across populations.

OBJECTIVES

To evaluate Oxford Nanopore sequencing as a strategy, to determine the frequency of GBA1 variants in Norwegian PD patients and controls, and to review the current literature on newly identified variants that add to pathogenicity determination.

METHODS

We included 462 Norwegian PD patients and 367 healthy controls. We sequenced the full-length GBA1 gene on the Oxford Nanopore GridION as an 8.9 kb amplicon. Six analysis pipelines were compared using two aligners (NGMLR, Minimap2) and three variant callers (BCFtools, Clair3, Pepper-Margin-Deepvariant). Confirmation of GBA1 variants was performed by Sanger sequencing and the pathogenicity of variants was evaluated.

RESULTS

We found 95.8% (115/120) true-positive GBA1 variant calls, while 4.2% (5/120) variant calls were false-positive, with the NGMLR/Minimap2-BCFtools pipeline performing best. In total, 13 rare GBA1 variants were detected: two were predicted to be (likely) pathogenic and eleven were of uncertain significance. The odds of carrying one of the two common GBA1 variants, p.L483P or p.N409S, in PD patients were estimated to be 4.11 times the odds of carrying one of these variants in controls (OR = 4.11 [1.39, 12.12]).

CONCLUSIONS

In conclusion, we have demonstrated that Oxford long-read Nanopore sequencing, along with the NGMLR/Minimap2-BCFtools pipeline is an effective tool to investigate GBA1 variants. Further studies on the pathogenicity of GBA1 variants are needed to assess their effect on PD.

The contribution of historical processes to contemporary extinction risk in placental mammals

Species persistence can be influenced by the amount, type, and distribution of diversity across the genome, suggesting a potential relationship between historical demography and resilience. In this study, we surveyed genetic variation across single genomes of 240 mammals that compose the Zoonomia alignment to evaluate how historical effective population size (Ne) affects heterozygosity and deleterious genetic load and how these factors may contribute to extinction risk. We find that species with smaller historical Ne carry a proportionally larger burden of deleterious alleles owing to long-term accumulation and fixation of genetic load and have a higher risk of extinction. This suggests that historical demography can inform contemporary resilience. Models that included genomic data were predictive of species' conservation status, suggesting that, in the absence of adequate census or ecological data, genomic information may provide an initial risk assessment.

A Novel Variant in VPS13B Underlying Cohen Syndrome

Pathogenic variants in vacuolar protein sorting 13 homolog B (VPS13B) cause Cohen syndrome (CS), a clinically diverse neurodevelopmental disorder. We used whole exome and Sanger sequencing to identify disease-causing variants in a Pakistani family with intellectual disability, microcephaly, facial dysmorphism, neutropenia, truncal obesity, speech delay, motor delay, and insomnia. We identified a novel homozygous nonsense variant c.8841G > A: p.(W2947∗) in VPS13B (NM_017890.5) which segregated with the disease. Sleep disturbances are commonly seen in neurodevelopmental disorders and can exacerbate medical issues if left untreated. We demonstrate that individuals with Cohen syndrome may also be affected by sleep disturbances. In conclusion, we expand the genetic and phenotypic features of Cohen syndrome in the Pakistani population.

In silico exploration and molecular dynamics of deleterious SNPs on the human TERF1 protein triggering male infertility

By limiting chromosome erosion and end-to-end fusions, telomere integrity is critical for chromosome stability and cell survival. During mitotic cycles or due to environmental stresses, telomeres become progressively shorter and dysfunctional, thus triggering cellular senescence, genomic instability and cell death. To avoid such consequences, the telomerase action, as well as the Shelterin and CST complexes, assure the telomere's protection. Telomeric repeat binding factor 1 (TERF1), which is one of the primary components of the Shelterin complex, binds directly to the telomere and controls its length and function by regulating the telomerase activity. Several reports about TERF1 gene variations have been associated with different diseases, and some of them have linked these variations to male infertility. Hence, this paper can be advantageous to investigate the association between the missense variants of the TERF1 gene and the susceptibility to male infertility. The stepwise prediction of SNPs pathogenicity followed in this study was based on stability and conservation analysis, post-translational modification, secondary structure, functional interaction prediction, binding energy evaluation and finally molecular dynamic simulation. Prediction matching among the tools revealed that out of 18 SNPs, only four (rs1486407144, rs1259659354, rs1257022048 and rs1320180267) were predicted as the most damaging and highly deleterious SNPs affecting the TERF1 protein and its molecular dynamics when interacting with the TERB1 protein by influencing the function, structural stability, flexibility and compaction of the overall complex. Interestingly, these polymorphisms should be considered during genetic screening so they can be used effectively as genetic biomarkers for male infertility diagnosis.Communicated by Ramaswamy H. Sarma.

Regulatory and coding sequences of TRNP1 co-evolve with brain size and cortical folding in mammals

Brain size and cortical folding have increased and decreased recurrently during mammalian evolution. Identifying genetic elements whose sequence or functional properties co-evolve with these traits can provide unique information on evolutionary and developmental mechanisms. A good candidate for such a comparative approach is TRNP1, as it controls proliferation of neural progenitors in mice and ferrets. Here, we investigate the contribution of both regulatory and coding sequences of TRNP1 to brain size and cortical folding in over 30 mammals. We find that the rate of TRNP1 protein evolution (ω) significantly correlates with brain size, slightly less with cortical folding and much less with body size. This brain correlation is stronger than for >95% of random control proteins. This co-evolution is likely affecting TRNP1 activity, as we find that TRNP1 from species with larger brains and more cortical folding induce higher proliferation rates in neural stem cells. Furthermore, we compare the activity of putative cis-regulatory elements (CREs) of TRNP1 in a massively parallel reporter assay and identify one CRE that likely co-evolves with cortical folding in Old World monkeys and apes. Our analyses indicate that coding and regulatory changes that increased TRNP1 activity were positively selected either as a cause or a consequence of increases in brain size and cortical folding. They also provide an example how phylogenetic approaches can inform biological mechanisms, especially when combined with molecular phenotypes across several species.

Deleterious Variation in Natural Populations and Implications for Conservation Genetics

Deleterious mutations decrease reproductive fitness and are ubiquitous in genomes. Given that many organisms face ongoing threats of extinction, there is interest in elucidating the impact of deleterious variation on extinction risk and optimizing management strategies accounting for such mutations. Quantifying deleterious variation and understanding the effects of population history on deleterious variation are complex endeavors because we do not know the strength of selection acting on each mutation. Further, the effect of demographic history on deleterious mutations depends on the strength of selection against the mutation and the degree of dominance. Here we clarify how deleterious variation can be quantified and studied in natural populations. We then discuss how different demographic factors, such as small population size, nonequilibrium population size changes, inbreeding, and gene flow, affect deleterious variation. Lastly, we provide guidance on studying deleterious variation in nonmodel populations of conservation concern.

The Effect of BSCL2 Gene on Fat Deposition Traits in Pigs

BSCL2 encodes seipin, a transmembrane endoplasmic reticulum protein associated with lipodystrophy and severe metabolic complications, including diabetes and hepatic steatosis. In pigs, BSCL2 expression increases during adipocyte differentiation. In the present study, we identified significant gene variants associated with fat deposition (FD)-related processes based on subcutaneous fat tissue RNA-seq data. In the association study, to prove our hypothesis, three Polish pig breeds were included: Złotnicka White (ZW, n = 72), Polish Landrace (PL, n = 201), and Polish Large White (PLW, n = 169). Based on variant calling analysis and χ² tests, BSCL2 mutations showing significantly different genotype/allele distribution between high- and low-fat pigs were selected for a comprehensive association study. Four interesting BSCL2 variants (rs346079334, rs341493267, rs330154033, and rs81333153) belonging to downstream and missense mutations were investigated. Our study showed a significant decrease in minor allele frequency for two BSCL2 variants (rs346079334 and rs341493267) in PL pigs in 2020-2021. In ZW, BSCL2 mutations significantly affected loin and ham fats, meat redness, and growth performance traits, such as feed conversion and daily feed intake. Similar observations were noted for PLW and PL, where BSCL2 mutations influenced fat depositions and meat traits, such as loin eye area, loin mass and fat, carcass yield, and growth performance traits. Based on the observation in pigs, our study supports the theory that BSCL2 expressed in subcutaneous fat is involved in the FD process.

Genomic Underpinnings of Population Persistence in Isle Royale Moose

Island ecosystems provide natural laboratories to assess the impacts of isolation on population persistence. However, most studies of persistence have focused on a single species, without comparisons to other organisms they interact with in the ecosystem. The case study of moose and gray wolves on Isle Royale allows for a direct contrast of genetic variation in isolated populations that have experienced dramatically differing population trajectories over the past decade. Whereas the Isle Royale wolf population recently declined nearly to extinction due to severe inbreeding depression, the moose population has thrived and continues to persist, despite having low genetic diversity and being isolated for ∼120 years. Here, we examine the patterns of genomic variation underlying the continued persistence of the Isle Royale moose population. We document high levels of inbreeding in the population, roughly as high as the wolf population at the time of its decline. However, inbreeding in the moose population manifests in the form of intermediate-length runs of homozygosity suggestive of historical inbreeding and purging, contrasting with the long runs of homozygosity observed in the smaller wolf population. Using simulations, we confirm that substantial purging has likely occurred in the moose population. However, we also document notable increases in genetic load, which could eventually threaten population viability over the long term. Overall, our results demonstrate a complex relationship between inbreeding, genetic diversity, and population viability that highlights the use of genomic datasets and computational simulation tools for understanding the factors enabling persistence in isolated populations.

Loci for insulin processing and secretion provide insight into type 2 diabetes risk

Insulin secretion is critical for glucose homeostasis, and increased levels of the precursor proinsulin relative to insulin indicate pancreatic islet beta-cell stress and insufficient insulin secretory capacity in the setting of insulin resistance. We conducted meta-analyses of genome-wide association results for fasting proinsulin from 16 European-ancestry studies in 45,861 individuals. We found 36 independent signals at 30 loci (p value < 5 × 10-8), which validated 12 previously reported loci for proinsulin and ten additional loci previously identified for another glycemic trait. Half of the alleles associated with higher proinsulin showed higher rather than lower effects on glucose levels, corresponding to different mechanisms. Proinsulin loci included genes that affect prohormone convertases, beta-cell dysfunction, vesicle trafficking, beta-cell transcriptional regulation, and lysosomes/autophagy processes. We colocalized 11 proinsulin signals with islet expression quantitative trait locus (eQTL) data, suggesting candidate genes, including ARSG, WIPI1, SLC7A14, and SIX3. The NKX6-3/ANK1 proinsulin signal colocalized with a T2D signal and an adipose ANK1 eQTL signal but not the islet NKX6-3 eQTL. Signals were enriched for islet enhancers, and we showed a plausible islet regulatory mechanism for the lead signal in the MADD locus. These results show how detailed genetic studies of an intermediate phenotype can elucidate mechanisms that may predispose one to disease.

Genomic health is dependent on long-term population demographic history

Current genetic methods of population assessment in conservation biology have been challenged by genome-scale analyses due to their quantitatively novel insights. These analyses include assessments of runs-of-homozygosity (ROH), genomic evolutionary rate profiling (GERP), and mutational load. Here, we aim to elucidate the relationships between these measures using three divergent ungulates: white-tailed deer, caribou, and mountain goat. The white-tailed deer is currently expanding, while caribou are in the midst of a significant decline. Mountain goats remain stable, having suffered a large historical bottleneck. We assessed genome-wide signatures of inbreeding using the inbreeding coefficient F and %ROH (F_ROH ) and identified evolutionarily constrained regions with GERP. Mutational load was estimated by identifying mutations in highly constrained elements (CEs) and sorting intolerant from tolerant (SIFT) mutations. Our results showed that F and F_ROH are higher in mountain goats than in caribou and white-tailed deer. Given the extended bottleneck and low N_e of the mountain goat, this supports the idea that the genome-wide effects of demographic change take time to accrue. Similarly, we found that mountain goats possess more highly constrained CEs and the lowest dN/dS values, both of which are indicative of greater purifying selection; this is also reflected by fewer mutations in CEs and deleterious mutations identified by SIFT. In contrast, white-tailed deer presented the highest mutational load with both metrics, in addition to dN/dS, while caribou were intermediate. Our results demonstrate that extended bottlenecks may lead to reduced diversity and increased F_ROH in ungulates, but not necessarily an increase in mutational load, probably due to the purging of deleterious alleles in small populations.

From high masked to high realized genetic load in inbred Scandinavian wolves

When new mutations arise at functional sites they are more likely to impair than improve fitness. If not removed by purifying selection, such deleterious mutations will generate a genetic load that can have negative fitness effects in small populations and increase the risk of extinction. This is relevant for the highly inbred Scandinavian wolf (Canis lupus) population, founded by only three wolves in the 1980s and suffering from inbreeding depression. We used functional annotation and evolutionary conservation scores to study deleterious variation in a total of 209 genomes from both the Scandinavian and neighbouring wolf populations in northern Europe. The masked load (deleterious mutations in heterozygote state) was highest in Russia and Finland with deleterious alleles segregating at lower frequency than neutral variation. Genetic drift in the Scandinavian population led to the loss of ancestral alleles, fixation of deleterious variants and a significant increase in the per-individual realized load (deleterious mutations in homozygote state; an increase by 45% in protein-coding genes) over five generations of inbreeding. Arrival of immigrants gave a temporary genetic rescue effect with ancestral alleles re-entering the population and thereby shifting deleterious alleles from homozygous into heterozygote genotypes. However, in the absence of permanent connectivity to Finnish and Russian populations, inbreeding has then again led to the exposure of deleterious mutations. These observations provide genome-wide insight into the magnitude of genetic load and genetic rescue at the molecular level, and in relation to population history. They emphasize the importance of securing gene flow in the management of endangered populations.

The Heterogeneity in the Landscape of Gene Dominance in Maize is Accompanied by Unique Chromatin Environments

Subgenome dominance after whole-genome duplication (WGD) has been observed in many plant species. However, the degree to which the chromatin environment affects this bias has not been explored. Here, we compared the dominant subgenome (maize1) and the recessive subgenome (maize2) with respect to patterns of sequence substitutions, genes expression, transposable element accumulation, small interfering RNAs, DNA methylation, histone modifications, and accessible chromatin regions (ACRs). Our data show that the degree of bias between subgenomes for all the measured variables does not vary significantly when both of the WGD genes are located in pericentromeric regions. Our data further indicate that the location of maize1 genes in chromosomal arms is pivotal for maize1 to maintain its dominance, but location has a less effect on maize2 homoeologs. In addition to homoeologous genes, we compared ACRs, which often harbor cis-regulatory elements, between the two subgenomes and demonstrate that maize1 ACRs have a higher level of chromatin accessibility, a lower level of sequence substitution, and are enriched in chromosomal arms. Furthermore, we find that a loss of maize1 ACRs near their nearby genes is associated with a reduction in purifying selection and expression of maize1 genes relative to their maize2 homoeologs. Taken together, our data suggest that chromatin environment and cis-regulatory elements are important determinants shaping the divergence and evolution of duplicated genes.

A novel loss-of-function mutation of the voltage-gated potassium channel Kv10.2 involved in epilepsy and autism

Background

Novel developmental mutations associated with disease are a continuous challenge in medicine. Clinical consequences caused by these mutations include neuron and cognitive alterations that can lead to epilepsy or autism spectrum disorders. Often, it is difficult to identify the physiological defects and the appropriate treatments.

Results

We have isolated and cultured primary cells from the skin of a patient with combined epilepsy and autism syndrome. A mutation in the potassium channel protein Kv10.2 was identified. We have characterised the alteration of the mutant channel and found that it causes loss of function (LOF). Primary cells from the skin displayed a very striking growth defect and increased differentiation. In vitro treatment with various carbonic anhydrase inhibitors with various degrees of specificity for potassium channels, (Brinzolamide, Acetazolamide, Retigabine) restored the activation capacity of the mutated channel. Interestingly, the drugs also recovered in vitro the expansion capacity of the mutated skin cells. Furthermore, treatment with Acetazolamide clearly improved the patient regarding epilepsy and cognitive skills. When the treatment was temporarily halted the syndrome worsened again.

Conclusions

By in vitro studying primary cells from the patient and the activation capacity of the mutated protein, we could first, find a readout for the cellular defects and second, test pharmaceutical treatments that proved to be beneficial. The results show the involvement of a novel LOF mutation of a Potassium channel in autism syndrome with epilepsy and the great potential of in vitro cultures of primary cells in personalised medicine of rare diseases.

Prediction of evolutionary constraint by genomic annotations improves functional prioritization of genomic variants in maize

Background

Crop improvement through cross-population genomic prediction and genome editing requires identification of causal variants at high resolution, within fewer than hundreds of base pairs. Most genetic mapping studies have generally lacked such resolution. In contrast, evolutionary approaches can detect genetic effects at high resolution, but they are limited by shifting selection, missing data, and low depth of multiple-sequence alignments. Here we use genomic annotations to accurately predict nucleotide conservation across angiosperms, as a proxy for fitness effect of mutations.

Results

Using only sequence analysis, we annotate nonsynonymous mutations in 25,824 maize gene models, with information from bioinformatics and deep learning. Our predictions are validated by experimental information: within-species conservation, chromatin accessibility, and gene expression. According to gene ontology and pathway enrichment analyses, predicted nucleotide conservation points to genes in central carbon metabolism. Importantly, it improves genomic prediction for fitness-related traits such as grain yield, in elite maize panels, by stringent prioritization of fewer than 1% of single-site variants.

Conclusions

Our results suggest that predicting nucleotide conservation across angiosperms may effectively prioritize sites most likely to impact fitness-related traits in crops, without being limited by shifting selection, missing data, and low depth of multiple-sequence alignments. Our approach—Prediction of mutation Impact by Calibrated Nucleotide Conservation (PICNC)—could be useful to select polymorphisms for accurate genomic prediction, and candidate mutations for efficient base editing. The trained PICNC models and predicted nucleotide conservation at protein-coding SNPs in maize are publicly available in CyVerse (10.25739/hybz-2957).

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-022-02747-2.

Compound Homozygous Rare Mutations in PLCE1 and HPS1 Genes Associated with Autosomal Recessive Retinitis Pigmentosa in Pakistani Families

Background

Retinitis pigmentosa (RP) belongs to pigmentary retinopathies, a generic name for all retinal dystrophies with a major phenotypical and genotypical variation, characterized by progressive reduction of photo-receptor functionality of the rod and cone. Global prevalence of RP is ~ 1/4000 and it can be inherited as autosomal dominant (adRP), autosomal recessive (arRP) or X- linked (xlRP). We designed this study to identify causative mutations in Pakistani families affected with arRP.

Methods

In 2019, we recruited two unrelated Pakistani consanguineous families affected with progressive vision loss and night blindness from Punjab region. Clinical diagnosis confirmed the; bone spicule pigmentation of the retina, and an altered electroretinogram (EGR) response. Proband and healthy individual from each family were subjected for whole-exome sequencing (WES). Various computational tools were used to analyze the Next Generation Sequencing (NGS) data and to predict the pathogenicity of the identified mutations.

Results

WES data analysis highlighted two missense homozygous variants at position c.T1405A (p.S469T) in PLCE1 and c.T11C (p.V4A) in HPS1 genes in proband of both families. Healthy individuals of two families were tested negative for p.S469T and p.V4A mutations. The variant analysis study including molecular dynamic simulations predicted mutations as disease causing.

Conclusion

Compound effect of mutations in rarely linked PLCE1 and HPS1 genes could also cause RP. This study highlights the potential application of WES for a rapid and precise molecular diagnosis for heterogeneous genetic diseases such as RP.

The sequences of 150,119 genomes in the UK Biobank

Detailed knowledge of how diversity in the sequence of the human genome affects phenotypic diversity depends on a comprehensive and reliable characterization of both sequences and phenotypic variation. Over the past decade, insights into this relationship have been obtained from whole-exome sequencing or whole-genome sequencing of large cohorts with rich phenotypic data^1,2. Here we describe the analysis of whole-genome sequencing of 150,119 individuals from the UK Biobank³. This constitutes a set of high-quality variants, including 585,040,410 single-nucleotide polymorphisms, representing 7.0% of all possible human single-nucleotide polymorphisms, and 58,707,036 indels. This large set of variants allows us to characterize selection based on sequence variation within a population through a depletion rank score of windows along the genome. Depletion rank analysis shows that coding exons represent a small fraction of regions in the genome subject to strong sequence conservation. We define three cohorts within the UK Biobank: a large British Irish cohort, a smaller African cohort and a South Asian cohort. A haplotype reference panel is provided that allows reliable imputation of most variants carried by three or more sequenced individuals. We identified 895,055 structural variants and 2,536,688 microsatellites, groups of variants typically excluded from large-scale whole-genome sequencing studies. Using this formidable new resource, we provide several examples of trait associations for rare variants with large effects not found previously through studies based on whole-exome sequencing and/or imputation.

Ancestry adjustment improves genome-wide estimates of regional intolerance

Genomic regions subject to purifying selection are more likely to carry disease-causing mutations than regions not under selection. Cross species conservation is often used to identify such regions but with limited resolution to detect selection on short evolutionary timescales such as that occurring in only one species. In contrast, genetic intolerance looks for depletion of variation relative to expectation within a species, allowing species-specific features to be identified. When estimating the intolerance of noncoding sequence, methods strongly leverage variant frequency distributions. As the expected distributions depend on ancestry, if not properly controlled for, ancestral population source may obfuscate signals of selection. We demonstrate that properly incorporating ancestry in intolerance estimation greatly improved variant classification. We provide a genome-wide intolerance map that is conditional on ancestry and likely to be particularly valuable for variant prioritization.

Genetic load: genomic estimates and applications in non-model animals

Genetic variation, which is generated by mutation, recombination and gene flow, can reduce the mean fitness of a population, both now and in the future. This 'genetic load' has been estimated in a wide range of animal taxa using various approaches. Advances in genome sequencing and computational techniques now enable us to estimate the genetic load in populations and individuals without direct fitness estimates. Here, we review the classic and contemporary literature of genetic load. We describe approaches to quantify the genetic load in whole-genome sequence data based on evolutionary conservation and annotations. We show that splitting the load into its two components - the realized load (or expressed load) and the masked load (or inbreeding load) - can improve our understanding of the population genetics of deleterious mutations.

Comparative Population Genetics in the Human Gut Microbiome

Genetic variation in the human gut microbiome is responsible for conferring a number of crucial phenotypes like the ability to digest food and metabolize drugs. Yet, our understanding of how this variation arises and is maintained remains relatively poor. Thus, the microbiome remains a largely untapped resource, as the large number of coexisting species in the microbiome presents a unique opportunity to compare and contrast evolutionary processes across species to identify universal trends and deviations. Here we outline features of the human gut microbiome that, while not unique in isolation, as an assemblage make it a system with unparalleled potential for comparative population genomics studies. We consciously take a broad view of comparative population genetics, emphasizing how sampling a large number of species allows researchers to identify universal evolutionary dynamics in addition to new genes, which can then be leveraged to identify exceptional species that deviate from general patterns. To highlight the potential power of comparative population genetics in the microbiome, we reanalyze patterns of purifying selection across ∼40 prevalent species in the human gut microbiome to identify intriguing trends which highlight functional categories in the microbiome that may be under more or less constraint.

Fitness Effects of Mutations: An Assessment of PROVEAN Predictions Using Mutation Accumulation Data

Predicting fitness in natural populations is a major challenge in biology. It may be possible to leverage fast-accumulating genomic data sets to infer the fitness effects of mutant alleles, allowing evolutionary questions to be addressed in any organism. In this paper, we investigate the utility of one such tool, called PROVEAN. This program compares a query sequence with existing data to provide an alignment-based score for any protein variant, with scores categorized as neutral or deleterious based on a pre-set threshold. PROVEAN has been used widely in evolutionary studies, for example, to estimate mutation load in natural populations, but has not been formally tested as a predictor of aggregate mutational effects on fitness. Using three large published data sets on the genome sequences of laboratory mutation accumulation lines, we assessed how well PROVEAN predicted the actual fitness patterns observed, relative to other metrics. In most cases, we find that a simple count of the total number of mutant proteins is a better predictor of fitness than the number of proteins with variants scored as deleterious by PROVEAN. We also find that the sum of all mutant protein scores explains variation in fitness better than the number of mutant proteins in one of the data sets. We discuss the implications of these results for studies of populations in the wild.

Utilizing evolutionary conservation to detect deleterious mutations and improve genomic prediction in cassava

Introduction

Cassava (Manihot esculenta) is an annual root crop which provides the major source of calories for over half a billion people around the world. Since its domestication ~10,000 years ago, cassava has been largely clonally propagated through stem cuttings. Minimal sexual recombination has led to an accumulation of deleterious mutations made evident by heavy inbreeding depression.

Methods

To locate and characterize these deleterious mutations, and to measure selection pressure across the cassava genome, we aligned 52 related Euphorbiaceae and other related species representing millions of years of evolution. With single base-pair resolution of genetic conservation, we used protein structure models, amino acid impact, and evolutionary conservation across the Euphorbiaceae to estimate evolutionary constraint. With known deleterious mutations, we aimed to improve genomic evaluations of plant performance through genomic prediction. We first tested this hypothesis through simulation utilizing multi-kernel GBLUP to predict simulated phenotypes across separate populations of cassava.

Results

Simulations showed a sizable increase of prediction accuracy when incorporating functional variants in the model when the trait was determined by<100 quantitative trait loci (QTL). Utilizing deleterious mutations and functional weights informed through evolutionary conservation, we saw improvements in genomic prediction accuracy that were dependent on trait and prediction.

Conclusion

We showed the potential for using evolutionary information to track functional variation across the genome, in order to improve whole genome trait prediction. We anticipate that continued work to improve genotype accuracy and deleterious mutation assessment will lead to improved genomic assessments of cassava clones.

First Two Case Reports of Becker's Type Myotonia Congenita in Colombia: Clinical and Genetic Features

Background

Becker's type myotonia congenita is an autosomal recessive nondystrophic skeletal muscle disorder characterized by muscle stiffness and the inability of muscle relaxation after voluntary contraction. It is caused by mutations in the CLCN1 gene, which encodes for a chloride channel mainly expressed in the striated muscle. Most cases have been reported in the European population, and only mexiletine has demonstrated a randomized placebo-controlled, double-blinded effectiveness.

Case Presentation

We present two male siblings from Colombia with Latino ancestry, without parental consanguinity, with myotonia during voluntary movements, muscle hypertrophy of lower extremities, transient weakness, and severe muscle fatigue after exercise from three years of age. A genetic panel for dystrophic muscle disorders and a muscle biopsy were both negative. Genetic testing was performed in their second decade of life. Both patients' exomic sequencing test reported the mutation c.1129C >T (p.Arg377*) affecting exon 10 of the CLCN1, generating a premature stop codon. This mutation was described as pathogenic and observed in only one other patient in the United Kingdom.

Conclusion

To our knowledge, these are the first cases of Becker's type myotonia congenita reported in Colombia. Increasing awareness of healthcare providers for this type of disease in the region could lead to the identification of undiagnosed patients. Limited availability of medical geneticists as well as genetic testing may be the cause of the lack of previous description of cases, in addition to the delay in the diagnosis of the patients. Further epidemiological studies can reveal underdiagnosed myotonias in the country and in the Latin-American region.

In silico analysis of GATA4 variants demonstrates main contribution to congenital heart disease

Introduction: Congenital heart disease (CHD) is the most common congenital abnormality and the main cause of infant mortality worldwide. Some of the mutations that occur in the GATA4 gene region may result in different types of CHD. Here, we report our in silico analysis of gene variants to determine the effects of the GATA4 gene on the development of CHD.

Methods: Online 1000 Genomes Project, ExAC, gnomAD, GO-ESP, TOPMed, Iranome, GME, ClinVar, and HGMD databases were drawn upon to collect information on all the reported GATA4 variations.The functional importance of the genetic variants was assessed by using SIFT, MutationTaster, CADD,PolyPhen-2, PROVEAN, and GERP prediction tools. Thereafter, network analysis of the GATA4protein via STRING, normal/mutant protein structure prediction via HOPE and I-TASSER, and phylogenetic assessment of the GATA4 sequence alignment via ClustalW were performed.

Results: The most frequent variant was c.874T>C (45.58%), which was reported in Germany.Ventricular septal defect was the most frequent type of CHD. Out of all the reported variants of GATA4,38 variants were pathogenic. A high level of pathogenicity was shown for p.Gly221Arg (CADD score=31), which was further analyzed.

Conclusion: The GATA4 gene plays a significant role in CHD; we, therefore, suggest that it be accorded priority in CHD genetic screening.

Deleterious protein-coding variants in diverse cattle breeds of the world

The domestication of wild animals has resulted in a reduction in effective population sizes, which can affect the deleterious mutation load of domesticated breeds. In addition, artificial selection contributes to the accumulation of deleterious mutations because of an increased rate of inbreeding among domesticated animals. Since founder population sizes and artificial selection differ between cattle breeds, their deleterious mutation load can vary. We investigated this question by using whole-genome data from 432 animals belonging to 54 worldwide cattle breeds. Our analysis revealed a negative correlation between genomic heterozygosity and nonsynonymous-to-silent diversity ratio, which suggests a higher proportion of single nucleotide variants (SNVs) affecting proteins in low-diversity breeds. Our results also showed that low-diversity breeds had a larger number of high-frequency (derived allele frequency (DAF) > 0.51) deleterious SNVs than high-diversity breeds. An opposite trend was observed for the low-frequency (DAF ≤ 0.51) deleterious SNVs. Overall, the number of high-frequency deleterious SNVs was larger in the genomes of taurine cattle breeds than of indicine breeds, whereas the number of low-frequency deleterious SNVs was larger in the genomes of indicine cattle than in those of taurine cattle. Furthermore, we observed significant variation in the counts of deleterious SNVs within taurine breeds. The variations in deleterious mutation load between taurine and indicine breeds could be attributed to the population sizes of the wild progenitors before domestication, whereas the variations observed within taurine breeds could be due to differences in inbreeding level, strength of artificial selection, and/or founding population size. Our findings imply that the incidence of genetic diseases can vary between cattle breeds.