LDER-GE estimates phenotypic variance component of gene-environment interactions in human complex traits accurately with GE interaction summary statistics and full LD information.

Gene-environment (GE) interactions are essential in understanding human complex traits. Identifying these interactions is necessary for deciphering the biological basis of such traits. In this study, we review state-of-art methods for estimating the proportion of phenotypic variance explained by genome-wide GE interactions and introduce a novel statistical method Linkage-Disequilibrium Eigenvalue Regression for Gene-Environment interactions (LDER-GE). LDER-GE improves the accuracy of estimating the phenotypic variance component explained by genome-wide GE interactions using large-scale biobank association summary statistics. LDER-GE leverages the complete Linkage Disequilibrium (LD) matrix, as opposed to only the diagonal squared LD matrix utilized by LDSC (Linkage Disequilibrium Score)-based methods. Our extensive simulation studies demonstrate that LDER-GE performs better than LDSC-based approaches by enhancing statistical efficiency by ~23%. This improvement is equivalent to a sample size increase of around 51%. Additionally, LDER-GE effectively controls type-I error rate and produces unbiased results. We conducted an analysis using UK Biobank data, comprising 307 259 unrelated European-Ancestry subjects and 966 766 variants, across 217 environmental covariate-phenotype (E-Y) pairs. LDER-GE identified 34 significant E-Y pairs while LDSC-based method only identified 23 significant E-Y pairs with 22 overlapped with LDER-GE. Furthermore, we employed LDER-GE to estimate the aggregated variance component attributed to multiple GE interactions, leading to an increase in the explained phenotypic variance with GE interactions compared to considering main genetic effects only. Our results suggest the importance of impacts of GE interactions on human complex traits.

Rare variations within the serine/arginine-rich splicing factor PtoRSZ21 modulate stomatal size to determine drought tolerance in Populus.

Rare variants contribute significantly to the 'missing heritability' of quantitative traits. The genome-wide characteristics of rare variants and their roles in environmental adaptation of woody plants remain unexplored. Utilizing genome-wide rare variant association study (RVAS), expression quantitative trait loci (eQTL) mapping, genetic transformation, and molecular experiments, we explored the impact of rare variants on stomatal morphology and drought adaptation in Populus. Through comparative analysis of five world-wide Populus species, we observed the influence of mutational bias and adaptive selection on the distribution of rare variants. RVAS identified 75 candidate genes correlated with stomatal size (SS)/stomatal density (SD), and a rare haplotype in the promoter of serine/arginine-rich splicing factor PtoRSZ21 emerged as the foremost association signal governing SS. As a positive regulator of drought tolerance, PtoRSZ21 can recruit the core splicing factor PtoU1-70K to regulate alternative splicing (AS) of PtoATG2b (autophagy-related 2). The rare haplotype PtoRSZ21hap2 weakens binding affinity to PtoMYB61, consequently affecting PtoRSZ21 expression and SS, ultimately resulting in differential distribution of Populus accessions in arid and humid climates. This study enhances the understanding of regulatory mechanisms that underlie AS induced by rare variants and might provide targets for drought-tolerant varieties breeding in Populus.

A genome-wide spectrum of tandem repeat expansions in 338,963 humans.

The Genome Aggregation Database (gnomAD), widely recognized as the gold-standard reference map of human genetic variation, has largely overlooked tandem repeat (TR) expansions, despite the fact that TRs constitute ∼6% of our genome and are linked to over 50 human diseases. Here, we introduce the TR-gnomAD (https://wlcb.oit.uci.edu/TRgnomAD), a biobank-scale reference of 0.86 million TRs derived from 338,963 whole-genome sequencing (WGS) samples of diverse ancestries (39.5% non-European samples). TR-gnomAD offers critical insights into ancestry-specific disease prevalence using disparities in TR unit number frequencies among ancestries. Moreover, TR-gnomAD is able to differentiate between common, presumably benign TR expansions, which are prevalent in TR-gnomAD, from those potentially pathogenic TR expansions, which are found more frequently in disease groups than within TR-gnomAD. Together, TR-gnomAD is an invaluable resource for researchers and physicians to interpret TR expansions in individuals with genetic diseases.

Therapeutic drug monitoring, liquid biopsies or pharmacogenomics for prediction of human drug metabolism and response.

Pharmacokinetics plays a central role in understanding the significant interindividual differences that exist in drug metabolism and response. Effectively addressing these differences requires a multi-faceted approach that encompasses a variety of tools and methods. In this review, we examine three key strategies to achieve this goal, namely pharmacogenomics, therapeutic drug monitoring (TDM) and liquid biopsy-based monitoring of hepatic ADME gene expression and highlight their advantages and limitations. We note that larger cohort studies are needed to validate the utility of liquid biopsy-based assessment of hepatic ADME gene expression, which includes prediction of drug metabolism in the clinical setting. Modern mass spectrometers have improved traditional TDM methods, offering versatility and sensitivity. In addition, the identification of endogenous or dietary markers for CYP metabolic traits offers simpler and more cost-effective alternatives to determine the phenotype. We believe that future pharmacogenomic applications in clinical practice should prioritize the identification of missing heritable factors, using larger, well-characterized patient studies and controlling for confounding factors such as diet, concomitant medication and physical health. The intricate regulation of ADME gene expression implies that large-scale studies combining long-read next-generation sequencing (NGS) of complete genomes with phenotyping of patients taking different medications are essential to identify these missing heritabilities. The continuous integration of such data into AI-driven analytical systems could provide a comprehensive and useful framework. This could lead to the development of highly effective algorithms to improve genetics-based precision treatment by predicting drug metabolism and response, significantly improving clinical outcomes.

[Genome-wide association analysis of agronomic traits related to eggplant fruits: a review].

Eggplant is an important horticultural crop and one of the most widely grown vegetables in the Solanaceae family. Eggplant fruit-related agronomic traits are complex quantitative traits with low efficiency and long cycle time for traditional breeding selection. With the rapid development of high-throughput sequencing technology and bioinformatics tools, genome-wide association study (GWAS) has shown great application potential in analyzing the genetic rules of complex agronomic traits related to eggplant fruits. This paper first reviews the progress of genome-wide association analysis in eggplant fruit shape, fruit color and other fruit-related agronomic traits. Subsequently, aiming at the problem of missing heritability, which is common in the genetic studies of eggplant quantitative traits, this paper puts forward the development strategies of eggplant GWAS in the future based on the hot spots of application of four GWAS strategies in the research of agronomics traits related to eggplant fruits. Lastly, the application of GWAS strategy in the field of eggplant molecular breeding is expected to provide a theoretical basis and reference for the future use of GWAS to analyze the genetic basis of various eggplant fruit-related traits and to select fruit materials that meet consumer needs.

Missing Heritability in Albinism: Deep Characterization of a Hungarian Albinism Cohort Raises the Possibility of the Digenic Genetic Background of the Disease.

Albinism is characterized by a variable degree of hypopigmentation affecting the skin and the hair, and causing ophthalmologic abnormalities. Its oculocutaneous, ocular and syndromic forms follow an autosomal or X-linked recessive mode of inheritance, and 22 disease-causing genes are implicated in their development. Our aim was to clarify the genetic background of a Hungarian albinism cohort. Using a 22-gene albinism panel, the genetic background of 11 of the 17 Hungarian patients was elucidated. In patients with unidentified genetic backgrounds (n = 6), whole exome sequencing was performed. Our investigations revealed a novel, previously unreported rare variant (N687S) of the two-pore channel two gene (TPCN2). The N687S variant of the encoded TPC2 protein is carried by a 15-year-old Hungarian male albinism patient and his clinically unaffected mother. Our segregational analysis and in vitro functional experiments suggest that the detected novel rare TPCN2 variant alone is not a disease-causing variant in albinism. Deep genetic analyses of the family revealed that the patient also carries a phenotype-modifying R305W variant of the OCA2 protein, and he is the only family member harboring this genotype. Our results raise the possibility that this digenic combination might contribute to the observed differences between the patient and the mother, and found the genetic background of the disease in his case.

Pharmacogenomics Beyond Single Common Genetic Variants: The Way Forward.

Interindividual variability in genes encoding drug-metabolizing enzymes, transporters, receptors, and human leukocyte antigens has a major impact on a patient's response to drugs with regard to efficacy and safety. Enabled by both technological and conceptual advances, the field of pharmacogenomics is developing rapidly. Major progress in omics profiling methods has enabled novel genotypic and phenotypic characterization of patients and biobanks. These developments are paralleled by advances in machine learning, which have allowed us to parse the immense wealth of data and establish novel genetic markers and polygenic models for drug selection and dosing. Pharmacogenomics has recently become more widespread in clinical practice to personalize treatment and to develop new drugs tailored to specific patient populations. In this review, we provide an overview of the latest developments in the field and discuss the way forward, including how to address the missing heritability, develop novel polygenic models, and further improve the clinical implementation of pharmacogenomics.

Targeted sequencing and in vitro splice assays shed light on ABCA4-associated retinopathies missing heritability.

The ABCA4 gene is the most frequently mutated Mendelian retinopathy-associated gene. Biallelic variants lead to a variety of phenotypes, however, for thousands of cases the underlying variants remain unknown. Here, we aim to shed further light on the missing heritability of ABCA4-associated retinopathy by analyzing a large cohort of macular dystrophy probands. A total of 858 probands were collected from 26 centers, of whom 722 carried no or one pathogenic ABCA4 variant, while 136 cases carried two ABCA4 alleles, one of which was a frequent mild variant, suggesting that deep-intronic variants (DIVs) or other cis-modifiers might have been missed. After single molecule molecular inversion probes (smMIPs)-based sequencing of the complete 128-kb ABCA4 locus, the effect of putative splice variants was assessed in vitro by midigene splice assays in HEK293T cells. The breakpoints of copy number variants (CNVs) were determined by junction PCR and Sanger sequencing. ABCA4 sequence analysis solved 207 of 520 (39.8%) naive or unsolved cases and 70 of 202 (34.7%) monoallelic cases, while additional causal variants were identified in 54 of 136 (39.7%) probands carrying two variants. Seven novel DIVs and six novel non-canonical splice site variants were detected in a total of 35 alleles and characterized, including the c.6283-321C>G variant leading to a complex splicing defect. Additionally, four novel CNVs were identified and characterized in five alleles. These results confirm that smMIPs-based sequencing of the complete ABCA4 gene provides a cost-effective method to genetically solve retinopathy cases and that several rare structural and splice altering defects remain undiscovered in Stargardt disease cases.

Advanced searching for hypertrophic cardiomyopathy heritability in real practice tomorrow.

Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiac disease associated with morbidity and mortality at any age. As studies in recent decades have shown, the genetic architecture of HCM is quite complex both in the entire population and in each patient. In the rapidly advancing era of gene therapy, we have to provide a detailed molecular diagnosis to our patients to give them the chance for better and more personalized treatment. In addition to emphasizing the importance of genetic testing in routine practice, this review aims to discuss the possibility to go a step further and create an expanded genetic panel that contains not only variants in core genes but also new candidate genes, including those located in deep intron regions, as well as structural variations. It also highlights the benefits of calculating polygenic risk scores based on a combination of rare and common genetic variants for each patient and of using non-genetic HCM markers, such as microRNAs that can enhance stratification of risk for HCM in unselected populations alongside rare genetic variants and clinical factors. While this review is focusing on HCM, the discussed issues are relevant to other cardiomyopathies.

Whole-Exome Sequencing Identified Two Novel Pathogenic Mutations in the PTCH1 Gene in BCNS.

Basal cell nevus syndrome (BCNS, OMIM 109400) is a familial cancer syndrome characterized by the development of numerous basal cell cancers and various other developmental abnormalities, including epidermal cysts of the skin, calcified dural folds, keratocysts of the jaw, palmar and plantar pits, ovarian fibromas, medulloblastomas, lymphomesenteric cysts, and fetal rhabdomyomas. BCNS shows autosomal dominant inheritance and is caused by mutations in the patched 1 (PTCH1) gene and the suppressor of the fused homolog (SUFU) gene. In a few cases, variants of patched 2 (PTCH2) have been found in patients who met the criteria for BCNS. In an investigation of 11 Hungarian families who fulfilled the diagnostic criteria for BCNS, whole-exome sequencing (WES) and multiplex ligation-dependent probe amplification (MLPA) identified two novel pathogenic variants (c.2994C>A; p.Cys998Ter and c.814_818del; p.Asn272SerfsTer11), one recently identified variant (c.1737_1745del p.Val580_Val582del), and three recurrent disease-causing variants of the PTCH1 gene with a diagnosis rate of 63.6%. Disease-causing variants were not found for the SUFU and PTCH2 genes. These applied methods could not fully elucidate the genetic background of all the BCNS cases that we investigated. To uncover the missing heritability of BCNS, whole-genome sequencing or an epigenetic approach might be considered in the future.

Imaging genomics: data fusion in uncovering disease heritability.

Sequencing of the human genome in the early 2000s enabled probing of the genetic basis of disease on a scale previously unimaginable. Now, two decades later, after interrogating millions of markers in thousands of individuals, a significant portion of disease heritability still remains hidden. Recent efforts to unravel this 'missing heritability' have focused on garnering new insight from merging different data types, including medical imaging. Imaging offers promising intermediate phenotypes to bridge the gap between genetic variation and disease pathology. In this review we outline this fusion and provide examples of imaging genomics in a range of diseases, from oncology to cardiovascular and neurodegenerative disease. Finally, we discuss how ongoing revolutions in data science and sharing are primed to advance the field.

Whole genome sequencing and inheritance-based variant filtering as a tool for unraveling missing heritability in pediatric cancer.

Survival rates for pediatric cancer have significantly increased the past decades, now exceeding 70-80% for most cancer types. The cause of cancer in children and adolescents remains largely unknown and a genetic susceptibility is considered in up to 10% of the cases, but most likely this is an underestimation. Families with multiple pediatric cancer patients are rare and strongly suggestive for an underlying predisposition to cancer. The absence of identifiable mutations in known cancer predisposing genes in such families could indicate undiscovered heritability. To discover candidate susceptibility variants, whole genome sequencing was performed on germline DNA of a family with two children affected by Burkitt lymphoma. Using an inheritance-based filtering approach, 18 correctly segregating coding variants were prioritized without a biased focus on specific genes or variants. Two variants in FAT4 and DCHS2 were highlighted, both involved in the Hippo signaling pathway, which controls tissue growth and stem cell activity. Similarly, a set of nine non-coding variants was prioritized, which might contribute, in differing degrees, to the increased cancer risk within this family. In conclusion, inheritance-based whole genome sequencing in selected families or cases is a valuable approach to prioritize variants and, thus, to further unravel genetic predisposition in childhood cancer.

Structural variants identified using non-Mendelian inheritance patterns advance the mechanistic understanding of autism spectrum disorder.

The heritability of autism spectrum disorder (ASD), based on 680,000 families and five countries, is estimated to be nearly 80%, yet heritability reported from SNP-based studies are consistently lower, and few significant loci have been identified with genome-wide association studies. This gap in genomic information may reside in rare variants, interaction among variants (epistasis), or cryptic structural variation (SV) and may provide mechanisms that underlie ASD. Here we use a method to identify potential SVs based on non-Mendelian inheritance patterns in pedigrees using parent-child genotypes from ASD families and demonstrate that they are enriched in ASD-risk genes. Most are in non-coding genic space and are over-represented in expression quantitative trait loci, suggesting that they affect gene regulation, which we confirm with their overlap of differentially expressed genes in postmortem brain tissue of ASD individuals. We then identify an SV in the GRIK2 gene that alters RNA splicing and a regulatory region of the ACMSD gene in the kynurenine pathway as significantly associated with a non-verbal ASD phenotype, supporting our hypothesis that these currently excluded loci can provide a clearer mechanistic understanding of ASD. Finally, we use an explainable artificial intelligence approach to define subgroups demonstrating their use in the context of precision medicine.

Segregation analysis of 17,425 population-based breast cancer families: Evidence for genetic susceptibility and risk prediction.

Rare pathogenic variants in known breast cancer-susceptibility genes and known common susceptibility variants do not fully explain the familial aggregation of breast cancer. To investigate plausible genetic models for the residual familial aggregation, we studied 17,425 families ascertained through population-based probands, 86% of whom were screened for pathogenic variants in BRCA1, BRCA2, PALB2, CHEK2, ATM, and TP53 via gene-panel sequencing. We conducted complex segregation analyses and fitted genetic models in which breast cancer incidence depended on the effects of known susceptibility genes and other unidentified major genes and a normally distributed polygenic component. The proportion of familial variance explained by the six genes was 46% at age 20-29 years and decreased steadily with age thereafter. After allowing for these genes, the best fitting model for the residual familial variance included a recessive risk component with a combined genotype frequency of 1.7% (95% CI: 0.3%-5.4%) and a penetrance to age 80 years of 69% (95% CI: 38%-95%) for homozygotes, which may reflect the combined effects of multiple variants acting in a recessive manner, and a polygenic variance of 1.27 (95% CI: 0.94%-1.65), which did not vary with age. The proportion of the residual familial variance explained by the recessive risk component was 40% at age 20-29 years and decreased with age thereafter. The model predicted age-specific familial relative risks consistent with those observed by large epidemiological studies. The findings have implications for strategies to identify new breast cancer-susceptibility genes and improve disease-risk prediction, especially at a young age.

Haplotype-specific chromatin looping reveals genetic interactions of regulatory regions modulating gene expression in 8p23.1.

A major goal of genetics research is to elucidate mechanisms explaining how genetic variation contributes to phenotypic variation. The genetic variants identified in genome-wide association studies (GWASs) generally explain only a small proportion of heritability of phenotypic traits, the so-called missing heritability problem. Recent evidence suggests that additional common variants beyond lead GWAS variants contribute to phenotypic variation; however, their mechanistic underpinnings generally remain unexplored. Herein, we undertake a study of haplotype-specific mechanisms of gene regulation at 8p23.1 in the human genome, a region associated with a number of complex diseases. The FAM167A-BLK locus in this region has been consistently found in the genome-wide association studies (GWASs) of systemic lupus erythematosus (SLE) in all major ancestries. Our haplotype-specific chromatin interaction (Hi-C) experiments, allele-specific enhancer activity measurements, genetic analyses, and epigenome editing experiments revealed that: 1) haplotype-specific long-range chromatin interactions are prevalent in 8p23.1; 2) BLK promoter and cis-regulatory elements cooperatively interact with haplotype-specificity; 3) genetic variants at distal regulatory elements are allele-specific modifiers of the promoter variants at FAM167A-BLK; 4) the BLK promoter interacts with and, as an enhancer-like promoter, regulates FAM167A expression and 5) local allele-specific enhancer activities are influenced by global haplotype structure due to chromatin looping. Although systemic lupus erythematosus causal variants at the FAM167A-BLK locus are thought to reside in the BLK promoter region, our results reveal that genetic variants at distal regulatory elements modulate promoter activity, changing BLK and FAM167A gene expression and disease risk. Our results suggest that global haplotype-specific 3-dimensional chromatin looping architecture has a strong influence on local allelic BLK and FAM167A gene expression, providing mechanistic details for how regional variants controlling the BLK promoter may influence disease risk.

Phenotypic but no genetic adaptation in zooplankton 24 years after an abrupt +10°C climate change.

The climate is currently warming fast, threatening biodiversity all over the globe. Populations often adapt rapidly to environmental change, but for climate warming very little evidence is available. Here, we investigate the pattern of adaptation to an extreme +10°C climate change in the wild, following the introduction of brine shrimp Artemia franciscana from San Francisco Bay, USA, to Vinh Chau saltern in Vietnam. We use a resurrection ecology approach, hatching diapause eggs from the ancestral population and the introduced population after 13 and 24 years (∼54 and ∼100 generations, respectively). In a series of coordinated experiments, we determined whether the introduced Artemia show increased tolerance to higher temperatures, and the extent to which genetic adaptation, developmental plasticity, transgenerational effects, and local microbiome differences contributed to this tolerance. We find that introduced brine shrimp do show increased phenotypic tolerance to warming. Yet strikingly, these changes do not have a detectable additive genetic component, are not caused by mitochondrial genetic variation, and do not seem to be caused by epigenetic marks set by adult parents exposed to warming. Further, we do not find any developmental plasticity that would help cope with warming, nor any protective effect of heat-tolerant local microbiota. The evolved thermal tolerance might therefore be entirely due to transgenerational (great)grandparental effects, possibly epigenetic marks set by parents who were exposed to high temperatures as juveniles. This study is a striking example of "missing heritability," where a large adaptive phenotypic change is not accompanied by additive genetic effects.

Nature versus nurture-on the origins of a specious argument.

The concept of heritability parses out genetic and environmental causes of diseases and does not fit the underlying biology of complex diseases that arise from interactions among genetics and environment. Exposomics places environment on a similar scale as genomics and allows for more modern research approaches that estimate time-varying genome by exposome interactions. By addressing the biological underpinnings of disease comprehensively, we will find the "missing heritability" which is not solely based on genetic variation but is instead driven by time, life stage, and geographic variability in our exposome as it interacts with our genome.

Cytochrome P450 polymorphism: From evolution to clinical use.

The cytochromes P450s can be divided in two groups, those of high importance for endogenous functions being evolutionary quite stable and those participating in detoxification of drugs and other xenobiotics having less important endogenous functions. In the latter group extensive genetic diversity has been allowed and in addition this is of high importance for survival in different environments. The genetic polymorphisms in these genes have evolved to some extent based on dietary restrictions and environmental factors and have not been subject of conservation due to less importance for survival. In cases of high dietary selection events, gene multiplication and amplification events have been seen. The different variants in genes encoding drug metabolizing enzymes can be used as genetic biomarkers (pharmacogenomic labels) for adjustment of drug treatment leading to less adverse drug reactions and better response. Indeed, this has improved the use of personalized medicine, although the missing heredity seen based on twin studies indicates that there are indeed many more genetic variants to be discovered before one can achieve a satisfactory relationship between genotype and phenotype with respect to drug metabolism and toxicity.

Why We Need to Take a Closer Look at Genetic Contributions to CYP3A Activity.

Cytochrome P450 3A (CYP3A) subfamily enzymes are involved in the metabolism of 40% of drugs in clinical use. Twin studies have indicated that 66% of the variability in CYP3A4 activity is hereditary. Yet, the complexity of the CYP3A locus and the lack of distinct drug metabolizer phenotypes has limited the identification and clinical application of CYP3A genetic variants compared to other Cytochrome P450 enzymes. In recent years evidence has emerged indicating that a substantial part of the missing heritability is caused by low frequency genetic variation. In this review, we outline the current pharmacogenomics knowledge of CYP3A activity and discuss potential future directions to improve our genetic knowledge and ability to explain CYP3A variability.

Open problems in human trait genetics.

Genetic studies of human traits have revolutionized our understanding of the variation between individuals, and yet, the genetics of most traits is still poorly understood. In this review, we highlight the major open problems that need to be solved, and by discussing these challenges provide a primer to the field. We cover general issues such as population structure, epistasis and gene-environment interactions, data-related issues such as ancestry diversity and rare genetic variants, and specific challenges related to heritability estimates, genetic association studies, and polygenic risk scores. We emphasize the interconnectedness of these problems and suggest promising avenues to address them.