Shifting paradigm of association studies: value of rare single-nucleotide polymorphisms

Association of Genetic Polymorphisms in Long Noncoding RNA HOTTIP with Risk of Idiopathic Recurrent Spontaneous Abortion

The clustered homeobox gene family known as the Hox family plays a fundamental role in the morphogenesis of the vertebrate's embryo. A long noncoding RNA (lncRNA), known as HOTTIP (HOXA transcript at the distal tip), has been functionally characterized and contributed to the pathogenesis of various conditions. The current case-control study was undertaken to examine the gene frequencies and shared alleles of the HOTTIP  gene in Iranian participants with or without idiopathic recurrent spontaneous abortion (RSA). Both ARMS-PCR reaction and RFLP-PCR techniques were employed to detect three HOTTIP polymorphisms (rs2023843C/T, rs78248039A/T, and rs1859168C/A) in a DNA sample of 161 women with RSA and 177 healthy women. We found that the TT genotype of the HOTTIP rs2023843 C/T polymorphism was associated with a lower risk for idiopathic RSA. In contrast, the TT genotype of the HOTTIP rs78248039 A/T polymorphism was correlated with an enhanced risk of RSA. The presence of the A-allele for HOTTIP rs1859168 C/A polymorphism was associated with an increased risk for idiopathic RSA. Haplotype analysis showed that the T/T/A, C/T/A, T/T/C, and T/A/A haplotypes of rs2023843/rs78248039/rs1859168 enhanced RSA susceptibility. Computational analysis predicted that this lncRNA might act as a potential sponge for some microRNAs; therefore, affecting the expression of genes being targeted by them. In addition, both rs2023843 and rs1859168 variants could alter the local secondary structure of HOTTIP. Our results showed that HOTTIP rs2023843C/T, rs78248039A/T, and rs1859168C/A polymorphisms may confer genetic susceptibility to idiopathic RSA in an Iranian population.

Rare variants analyses suggest novel cleft genes in the African population

Non-syndromic orofacial clefts (NSOFCs) are common birth defects with a complex etiology. While over 60 common risk loci have been identified, they explain only a small proportion of the heritability for NSOFCs. Rare variants have been implicated in the missing heritability. Thus, our study aimed to identify genes enriched with nonsynonymous rare coding variants associated with NSOFCs. Our sample included 814 non-syndromic cleft lip with or without palate (NSCL/P), 205 non-syndromic cleft palate only (NSCPO), and 2150 unrelated control children from Nigeria, Ghana, and Ethiopia. We conducted a gene-based analysis separately for each phenotype using three rare-variants collapsing models: (1) protein-altering (PA), (2) missense variants only (MO); and (3) loss of function variants only (LOFO). Subsequently, we utilized relevant transcriptomics data to evaluate associated gene expression and examined their mutation constraint using the gnomeAD database. In total, 13 genes showed suggestive associations (p = E-04). Among them, eight genes (ABCB1, ALKBH8, CENPF, CSAD, EXPH5, PDZD8, SLC16A9, and TTC28) were consistently expressed in relevant mouse and human craniofacial tissues during the formation of the face, and three genes (ABCB1, TTC28, and PDZD8) showed statistically significant mutation constraint. These findings underscore the role of rare variants in identifying candidate genes for NSOFCs.

Phenotypic and genetic characterization of unexplored, potential cattle population of Madhya Pradesh

Bawri or Garri, a non-descript cattle population managed under an extensive system in Madhya Pradesh state of India, was identified and characterized both genetically and phenotypically to check whether or not it can be recognised as a breed. The cattle have white and gray colour and are medium sized with 122.5 ± 7.5 cm and 109.45 ± 0.39 cm height at withers in male and female, respectively. Double-digest restriction site associated DNA (ddRAD) sequencing was employed to identify ascertainment bias free SNPs representing the entire genome cost effectively; resulting in calling 1,156,650 high quality SNPs. Observed homozygosity was 0.76, indicating Bawri as a quite unique population. However, the inbreeding coefficient was 0.025, indicating lack of selection. SNPs found here can be used in GWAS and genetic evaluation programs. Considering the uniqueness of Bawri cattle, it can be registered as a breed for its better genetic management.

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.

Rare Variants Analyses Suggest Novel Cleft Genes in the African Population

Non-syndromic orofacial clefts (NSOFCs) are common birth defects with a complex etiology. While over 60 common risk loci have been identified, they explain only a small proportion of the heritability for NSOFC. Rare variants have been implicated in the missing heritability. Thus, our study aimed to identify genes enriched with nonsynonymous rare coding variants associated with NSOFCs. Our sample included 814 non-syndromic cleft lip with or without palate (NSCL/P), 205 non-syndromic cleft palate only (NSCPO), and 2150 unrelated control children from Nigeria, Ghana, and Ethiopia. We conducted a gene-based analysis separately for each phenotype using three rare-variants collapsing models: (1) protein-altering (PA), (2) missense variants only (MO); and (3) loss of function variants only (LOFO). Subsequently, we utilized relevant transcriptomics data to evaluate associated gene expression and examined their mutation constraint using the gnomeAD database. In total, 13 genes showed suggestive associations (p = E-04). Among them, eight genes (ABCB1, ALKBH8, CENPF, CSAD, EXPH5, PDZD8, SLC16A9, and TTC28) were consistently expressed in relevant mouse and human craniofacial tissues during the formation of the face, and three genes (ABCB1, TTC28, and PDZD8) showed statistically significant mutation constraint. These findings underscore the role of rare variants in identifying candidate genes for NSOFCs.

Schizophrenia in the genetic era: a review from development history, clinical features and genomic research approaches to insights of susceptibility genes

Schizophrenia is a devastating neuropsychiatric disorder affecting 1% of the world population and ranks as one of the disorders providing the most severe burden for society. Schizophrenia etiology remains obscure involving multi-risk factors, such as genetic, environmental, nutritional, and developmental factors. Complex interactions of genetic and environmental factors have been implicated in the etiology of schizophrenia. This review provides an overview of the historical origins, pathophysiological mechanisms, diagnosis, clinical symptoms and corresponding treatment of schizophrenia. In addition, as schizophrenia is a polygenic, genetic disorder caused by the combined action of multiple micro-effective genes, we further detail several approaches, such as candidate gene association study (CGAS) and genome-wide association study (GWAS), which are commonly used in schizophrenia genomics studies. A number of GWASs about schizophrenia have been performed with the hope to identify novel, consistent and influential risk genetic factors. Finally, some schizophrenia susceptibility genes have been identified and reported in recent years and their biological functions are also listed. This review may serve as a summary of past research on schizophrenia genomics and susceptibility genes (NRG1, DISC1, RELN, BDNF, MSI2), which may point the way to future schizophrenia genetics research. In addition, depending on the above discovery of susceptibility genes and their exact function, the development and application of antipsychotic drugs will be promoted in the future.

Transmission ratio distortion regions in the context of genomic evaluation and their effects on reproductive traits in cattle

Transmission ratio distortion (TRD), which is a deviation from Mendelian expectations, has been associated with basic mechanisms of life such as sperm and ova fertility and viability at developmental stages of the reproductive cycle. In this study different models including TRD regions were tested for different reproductive traits [days from first service to conception (FSTC), number of services, first service nonreturn rate (NRR), and stillbirth (SB)]. Thus, in addition to a basic model with systematic and random effects, including genetic effects modeled through a genomic relationship matrix, we developed 2 additional models, including a second genomic relationship matrix based on TRD regions, and TRD regions as a random effect assuming heterogeneous variances. The analyses were performed with 10,623 cows and 1,520 bulls genotyped for 47,910 SNPs, 590 TRD regions, and several records ranging from 9,587 (FSTC) to 19,667 (SB). The results of this study showed the ability of TRD regions to capture some additional genetic variance for some traits; however, this did not translate into higher accuracy for genomic prediction. This could be explained by the nature of TRD itself, which may arise in different stages of the reproductive cycle. Nevertheless, important effects of TRD regions were found on SB (31 regions) and NRR (18 regions) when comparing at-risk versus control matings, especially for regions with allelic TRD pattern. Particularly for NRR, the probability of observing nonpregnant cow increases by up to 27% for specific TRD regions, and the probability of observing stillbirth increased by up to 254%. These results support the relevance of several TRD regions on some reproductive traits, especially those with allelic patterns that have not received as much attention as recessive TRD patterns.

Distortion of Mendelian segregation across the Angus cattle genome uncovering regions affecting reproduction

Nowadays, the availability of genotyped trios (sire-dam-offspring) in the livestock industry enables the implementation of the transmission ratio distortion (TRD) approach to discover deleterious alleles in the genome. Various biological mechanisms at different stages of the reproductive cycle such as gametogenesis, embryo development and postnatal viability can induce signals of TRD (i.e., deviation from Mendelian inheritance expectations). In this study, TRD was evaluated using both SNP-by-SNP and sliding windows of 2-, 4-, 7-, 10- and 20-SNP across 92,942 autosomal SNPs for 258,140 genotyped Angus cattle including 7,486 sires, 72,688 dams and 205,966 offspring. Transmission ratio distortion was characterized using allelic (specific- and unspecific-parent TRD) and genotypic parameterizations (additive- and dominance-TRD). Across the Angus autosomal chromosomes, 851 regions were clearly found with decisive evidence for TRD. Among these findings, 19 haplotypes with recessive patterns (potential lethality for homozygote individuals) and 52 regions with allelic patterns exhibiting complete or quasi-complete absence for homozygous individuals in addition to under-representation (potentially reduced viability) of the carrier (heterozygous) offspring were found. In addition, 64 (12) and 20 (4) regions showed significant influence on the trait heifer pregnancy at p-value < 0.05 (after chromosome-wise false discovery rate) and 0.01, respectively, reducing the pregnancy rate up to 15%, thus, supporting the biological importance of TRD phenomenon in reproduction.

Unravelling transmission ratio distortion across the bovine genome: identification of candidate regions for reproduction defects

BACKGROUND

Biological mechanisms affecting gametogenesis, embryo development and postnatal viability have the potential to alter Mendelian inheritance expectations resulting in observable transmission ratio distortion (TRD). Although the discovery of TRD cases have been around for a long time, the current widespread and growing use of DNA technologies in the livestock industry provides a valuable resource of large genomic data with parent-offspring genotyped trios, enabling the implementation of TRD approach. In this research, the objective is to investigate TRD using SNP-by-SNP and sliding windows approaches on 441,802 genotyped Holstein cattle and 132,991 (or 47,910 phased) autosomal SNPs.

RESULTS

The TRD was characterized using allelic and genotypic parameterizations. Across the whole genome a total of 604 chromosomal regions showed strong significant TRD. Most (85%) of the regions presented an allelic TRD pattern with an under-representation (reduced viability) of carrier (heterozygous) offspring or with the complete or quasi-complete absence (lethality) for homozygous individuals. On the other hand, the remaining regions with genotypic TRD patterns exhibited the classical recessive inheritance or either an excess or deficiency of heterozygote offspring. Among them, the number of most relevant novel regions with strong allelic and recessive TRD patterns were 10 and 5, respectively. In addition, functional analyses revealed candidate genes regulating key biological processes associated with embryonic development and survival, DNA repair and meiotic processes, among others, providing additional biological evidence of TRD findings.

CONCLUSIONS

Our results revealed the importance of implementing different TRD parameterizations to capture all types of distortions and to determine the corresponding inheritance pattern. Novel candidate genomic regions containing lethal alleles and genes with functional and biological consequences on fertility and pre- and post-natal viability were also identified, providing opportunities for improving breeding success in cattle.

The Role of Neural and Genetic Processes in Learning to Read and Specific Reading Disabilities: Implications for Instruction

To learn to read, the brain must repurpose neural systems for oral language and visual processing to mediate written language. We begin with a description of computational models for how alphabetic written language is processed. Next, we explain the roles of a dorsal sublexical system in the brain that relates print and speech, a ventral lexical system that develops the visual expertise for rapid orthographic processing at the word level, and the role of cognitive control networks that regulate attentional processes as children read. We then use studies of children, adult illiterates learning to read, and studies of poor readers involved in intervention, to demonstrate the plasticity of these neural networks in development and in relation to instruction. We provide a brief overview of the rapid increase in the field's understanding and technology for assessing genetic influence on reading. Family studies of twins have shown that reading skills are heritable, and molecular genetic studies have identified numerous regions of the genome that may harbor candidate genes for the heritability of reading. In selected families, reading impairment has been associated with major genetic effects, despite individual gene contributions across the broader population that appear to be small. Neural and genetic studies do not prescribe how children should be taught to read, but these studies have underscored the critical role of early intervention and ongoing support. These studies also have highlighted how structured instruction that facilitates access to the sublexical components of words is a critical part of training the brain to read.

High-throughput sequencing analysis of nuclear-encoded mitochondrial genes reveals a genetic signature of human longevity

Mitochondrial dysfunction is a well-known contributor to aging and age-related diseases. The precise mechanisms through which mitochondria impact human lifespan, however, remain unclear. We hypothesize that humans with exceptional longevity harbor rare variants in nuclear-encoded mitochondrial genes (mitonuclear genes) that confer resistance against age-related mitochondrial dysfunction. Here we report an integrated functional genomics study to identify rare functional variants in ~ 660 mitonuclear candidate genes discovered by target capture sequencing analysis of 496 centenarians and 572 controls of Ashkenazi Jewish descent. We identify and prioritize longevity-associated variants, genes, and mitochondrial pathways that are enriched with rare variants. We provide functional gene variants such as those in MTOR (Y2396Lfs*29), CPS1 (T1406N), and MFN2 (G548*) as well as LRPPRC (S1378G) that is predicted to affect mitochondrial translation. Taken together, our results suggest a functional role for specific mitonuclear genes and pathways in human longevity.

Genetic heterogeneity: Challenges, impacts, and methods through an associative lens

Genetic heterogeneity describes the occurrence of the same or similar phenotypes through different genetic mechanisms in different individuals. Robustly characterizing and accounting for genetic heterogeneity is crucial to pursuing the goals of precision medicine, for discovering novel disease biomarkers, and for identifying targets for treatments. Failure to account for genetic heterogeneity may lead to missed associations and incorrect inferences. Thus, it is critical to review the impact of genetic heterogeneity on the design and analysis of population level genetic studies, aspects that are often overlooked in the literature. In this review, we first contextualize our approach to genetic heterogeneity by proposing a high-level categorization of heterogeneity into "feature," "outcome," and "associative" heterogeneity, drawing on perspectives from epidemiology and machine learning to illustrate distinctions between them. We highlight the unique nature of genetic heterogeneity as a heterogeneous pattern of association that warrants specific methodological considerations. We then focus on the challenges that preclude effective detection and characterization of genetic heterogeneity across a variety of epidemiological contexts. Finally, we discuss systems heterogeneity as an integrated approach to using genetic and other high-dimensional multi-omic data in complex disease research.

PLK2 Single Nucleotide Variant in Gastric Cancer Patients Affects miR-23b-5p Binding

PURPOSE

Chromosomal instability is a hallmark of gastric cancer (GC). It can be driven by single nucleotide variants (SNVs) in cell cycle genes. We investigated the associations between SNVs in candidate genes, PLK2, PLK3, and ATM, and GC risk and clinicopathological features.

MATERIALS AND METHODS

The genotyping study included 542 patients with GC and healthy controls. Generalized linear models were used for the risk and clinicopathological association analyses. Survival analysis was performed using the Kaplan-Meier method. The binding of candidate miRs was analyzed using a luciferase reporter assay.

RESULTS

The PLK2 Crs15009-Crs963615 haplotype was under-represented in the GC group compared to that in the control group (Pcorr=0.050). Male patients with the PLK2 rs963615 CT genotype had a lower risk of GC, whereas female patients had a higher risk (P=0.023; P=0.026). The PLK2 rs963615 CT genotype was associated with the absence of vascular invasion (P=0.012). The PLK3 rs12404160 AA genotype was associated with a higher risk of GC in the male population (P=0.015). The ATM Trs228589-Ars189037-Grs4585 haplotype was associated with a higher risk of GC (P<0.001). The ATM rs228589, rs189037, and rs4585 genotypes TA+AA, AG+GG, and TG+GG were associated with the absence of perineural invasion (P=0.034). In vitro analysis showed that the cancer-associated miR-23b-5p mimic specifically bound to the PLK2 rs15009 G allele (P=0.0097). Moreover, low miR-23b expression predicted longer 10-year survival (P=0.0066) in patients with GC.

CONCLUSIONS

PLK2, PLK3, and ATM SNVs could potentially be helpful for the prediction of GC risk and clinicopathological features. PLK2 rs15009 affects the binding of miR-23b-5p. MiR-23b-5p expression status could serve as a prognostic marker for survival in patients with GC.

A suggested shared aetiology of dementia - a colocalization study

Identification of shared causal genes between dementia and its related clinical outcomes can help understand shared aetiology and multimorbidity surrounding dementia. We performed the HyPrColoc colocalization analysis to detect possible shared causal genes between dementia or Alzheimer's disease (AD) and 5 selected traits: stroke, diabetes, atherosclerosis, cholesterol level, and alcohol consumption within 601 dementia or AD associated genetic regions using summary results of the UK Biobank genome-wide association studies. Functional analysis was performed on the candidate causal genes to explore potential biological pathways. Rs150562240 in the LPIN3 gene was identified as a candidate shared causal variant across dementia, AD and atherosclerosis. Evidence for pairwise colocalization between dementia and stroke, dementia (or AD) and atherosclerosis, and dementia (or AD) and diabetes was found in 2, 6 and 2 genetic regions respectively. Colocalization signals between diabetes and the other 3 non-dementia/AD traits were detected in 5 regions. The colocalization evidence shown in our study suggested shared aetiology between dementia and related diseases such as stroke, atherosclerosis, and diabetes.

Interaction Effects of DRD2 Genetic Polymorphism and Interpersonal Stress on Problematic Gaming in College Students

Problematic gaming has become a public concern, influenced both by genetic factors and stressful environments. Studies have reported the effects of dopamine-related genes and interpersonal stressors on problematic gaming, but gene and environment interaction (G × E) studies have not been conducted. In this study, we investigated the interaction effects of dopamine receptor D2 (DRD2) polymorphisms and interpersonal stress on problematic gaming and the mediating effect of avoidant coping to reveal the mechanism of the G × E process. We recruited 168 college students (mean age = 22; male 63.1%) and genotyped their DRD2 C957T (rs6277) and Taq1 (rs1800497) polymorphisms. The results of the mediated moderation analysis showed that, when experiencing interpersonal stressors, individuals with both the C957T T allele and the Taq1 A1 allele showed more elevated problematic gaming scores than non-carriers. Moreover, the interaction effect of the combined DRD2 polymorphisms and interpersonal stress was significantly mediated by avoidant coping. These findings suggest that the influence of interpersonal stress on problematic gaming can be changed as a function of DRD2 genotypes, which may be because of the avoidant coping styles of C957T T allele and Taq1 A1 allele carriers in response to stress.

Contribution of Rare and Low-Frequency Variants to Multiple Sclerosis Susceptibility in the Italian Continental Population

Genome-wide association studies identified over 200 risk loci for multiple sclerosis (MS) focusing on common variants, which account for about 50% of disease heritability. The goal of this study was to investigate whether low-frequency and rare functional variants, located in MS-established associated loci, may contribute to disease risk in a relatively homogeneous population, testing their cumulative effect (burden) with gene-wise tests. We sequenced 98 genes in 588 Italian patients with MS and 408 matched healthy controls (HCs). Variants were selected using different filtering criteria based on allelic frequency and in silico functional impacts. Genes showing a significant burden (n = 17) were sequenced in an independent cohort of 504 MS and 504 HC. The highest signal in both cohorts was observed for the disruptive variants (stop-gain, stop-loss, or splicing variants) located in EFCAB13, a gene coding for a protein of an unknown function (p < 10^-4). Among these variants, the minor allele of a stop-gain variant showed a significantly higher frequency in MS versus HC in both sequenced cohorts (p = 0.0093 and p = 0.025), confirmed by a meta-analysis on a third independent cohort of 1298 MS and 1430 HC (p = 0.001) assayed with an SNP array. Real-time PCR on 14 heterozygous individuals for this variant did not evidence the presence of the stop-gain allele, suggesting a transcript degradation by non-sense mediated decay, supported by the evidence that the carriers of the stop-gain variant had a lower expression of this gene (p = 0.0184). In conclusion, we identified a novel low-frequency functional variant associated with MS susceptibility, suggesting the possible role of rare/low-frequency variants in MS as reported for other complex diseases.

Genetic Variation in ABCC4 and CFTR and Acute Pancreatitis during Treatment of Pediatric Acute Lymphoblastic Leukemia

Background: Acute pancreatitis (AP) is a serious, mechanistically not entirely resolved side effect of L-asparaginase-containing treatment for acute lymphoblastic leukemia (ALL). To find new candidate variations for AP, we conducted a genome-wide association study (GWAS). Methods: In all, 1,004,623 single-nucleotide variants (SNVs) were analyzed in 51 pediatric ALL patients with AP (cases) and 1388 patients without AP (controls). Replication used independent patients. Results: The top-ranked SNV (rs4148513) was located within the ABCC4 gene (odds ratio (OR) 84.1; p = 1.04 × 10⁻¹⁴). Independent replication of our 20 top SNVs was not supportive of initial results, partly because rare variants were neither present in cases nor present in controls. However, results of combined analysis (GWAS and replication cohorts) remained significant (e.g., rs4148513; OR = 47.2; p = 7.31 × 10⁻⁹). Subsequently, we sequenced the entire ABCC4 gene and its close relative, the cystic fibrosis associated CFTR gene, a strong AP candidate gene, in 48 cases and 47 controls. Six AP-associated variants in ABCC4 and one variant in CFTR were detected. Replication confirmed the six ABCC4 variants but not the CFTR variant. Conclusions: Genetic variation within the ABCC4 gene was associated with AP during the treatment of ALL. No association of AP with CFTR was observed. Larger international studies are necessary to more conclusively assess the risk of rare clinical phenotypes.

The Shared Genetic Architectures Between Lung Cancer and Multiple Polygenic Phenotypes in Genome-Wide Association Studies

BACKGROUND

Prior genome-wide association studies have identified numerous lung cancer risk loci and reveal substantial etiologic heterogeneity across histologic subtypes. Analyzing the shared genetic architecture underlying variation in complex traits can elucidate common genetic etiologies across phenotypes. Exploring pairwise genetic correlations between lung cancer and other polygenic traits can reveal the common genetic etiology of correlated phenotypes.

METHODS

Using cross-trait linkage disequilibrium score regression, we estimated the pairwise genetic correlation and heritability between lung cancer and multiple traits using publicly available summary statistics. Identified genetic relationships were also examined after excluding genomic regions known to be associated with smoking behaviors, a major risk factor for lung cancer.

RESULTS

We observed several traits showing moderate single nucleotide polymorphism-based heritability and significant genetic correlations with lung cancer. We observed highly significant correlations between the genetic architectures of lung cancer and emphysema/chronic bronchitis across all histologic subtypes, as well as among lung cancer occurring among smokers. Our analyses revealed highly significant positive correlations between lung cancer and paternal history of lung cancer. We also observed a strong negative correlation with parental longevity. We observed consistent directions in genetic patterns after excluding genomic regions associated with smoking behaviors.

CONCLUSIONS

This study identifies numerous phenotypic traits that share genomic architecture with lung carcinogenesis and are not fully accounted for by known smoking-associated genomic loci.

IMPACT

These findings provide new insights into the etiology of lung cancer by identifying traits that are genetically correlated with increased risk of lung cancer.

QTL mapping in Fusarium graminearum identified an allele of FgVe1 involved in reduced aggressiveness

Fusarium graminearum is one of the most frequent causal agents of the Fusarium Head Blight, a cereal disease spread throughout the world, reducing grain production and quality. F. graminearum isolates are genetically and phenotypically highly diverse. Notably, remarkable variations of aggressiveness between isolates have been observed, which could reflect an adaptive potential of this pathogen. In this study, we aimed to characterize the genetic basis of aggressiveness variation observed in an F1 population (n = 94), for which genome sequences of both parental strains are available. Aggressiveness was assessed by a panel of in planta and in vitro proxies during two phenotyping trials including, among others, disease severity and mycotoxin accumulation in wheat spike. One major and single QTL was mapped for all the traits measured, on chromosome I, that explained up to 90% of the variance for disease severity. The confidence interval at the QTL spanned 1.2 Mb and contained 428 genes on the reference genome. Of these, four candidates were selected based on the postulate that a non-synonymous mutation affecting protein function may be responsible for phenotypic differences. Finally, a new mutation was identified and functionally validated in the gene FgVe1, coding for a velvet protein known to be involved in pathogenicity and secondary metabolism production in several fungi.

Regarding the F-word: The effects of data filtering on inferred genotype-environment associations

Genotype-environment association (GEA) methods have become part of the standard landscape genomics toolkit, yet, we know little about how to best filter genotype-by-sequencing data to provide robust inferences for environmental adaptation. In many cases, default filtering thresholds for minor allele frequency and missing data are applied regardless of sample size, having unknown impacts on the results, negatively affecting management strategies. Here, we investigate the effects of filtering on GEA results and the potential implications for assessment of adaptation to environment. We use empirical and simulated data sets derived from two widespread tree species to assess the effects of filtering on GEA outputs. Critically, we find that the level of filtering of missing data and minor allele frequency affect the identification of true positives. Even slight adjustments to these thresholds can change the rate of true positive detection. Using conservative thresholds for missing data and minor allele frequency substantially reduces the size of the data set, lessening the power to detect adaptive variants (i.e., simulated true positives) with strong and weak strengths of selection. Regardless, strength of selection was a good predictor for GEA detection, but even some SNPs under strong selection went undetected. False positive rates varied depending on the species and GEA method, and filtering significantly impacted the predictions of adaptive capacity in downstream analyses. We make several recommendations regarding filtering for GEA methods. Ultimately, there is no filtering panacea, but some choices are better than others, depending on the study system, availability of genomic resources, and desired objectives.

Rare deleterious germline variants and risk of lung cancer

Recent studies suggest that rare variants exhibit stronger effect sizes and might play a crucial role in the etiology of lung cancers (LC). Whole exome plus targeted sequencing of germline DNA was performed on 1045 LC cases and 885 controls in the discovery set. To unveil the inherited causal variants, we focused on rare and predicted deleterious variants and small indels enriched in cases or controls. Promising candidates were further validated in a series of 26,803 LCs and 555,107 controls. During discovery, we identified 25 rare deleterious variants associated with LC susceptibility, including 13 reported in ClinVar. Of the five validated candidates, we discovered two pathogenic variants in known LC susceptibility loci, ATM p.V2716A (Odds Ratio [OR] 19.55, 95%CI 5.04-75.6) and MPZL2 p.I24M frameshift deletion (OR 3.88, 95%CI 1.71-8.8); and three in novel LC susceptibility genes, POMC c.*28delT at 3' UTR (OR 4.33, 95%CI 2.03-9.24), STAU2 p.N364M frameshift deletion (OR 4.48, 95%CI 1.73-11.55), and MLNR p.Q334V frameshift deletion (OR 2.69, 95%CI 1.33-5.43). The potential cancer-promoting role of selected candidate genes and variants was further supported by endogenous DNA damage assays. Our analyses led to the identification of new rare deleterious variants with LC susceptibility. However, in-depth mechanistic studies are still needed to evaluate the pathogenic effects of these specific alleles.

Assessing the effects of rare alleles and linkage disequilibrium on estimates of genetic diversity in the chicken populations

Phenotypic diversity in poultry has been mainly driven by artificial selection and genetic drift. These led to the adaptation to the environment and the development of specific phenotypic traits of chickens in response to their economic use. This study evaluated genetic diversity within and between Russian breeds and populations using Illumina Chicken 60K SNP iSelect BeadChip by analysing genetic differences between populations with Hudson's fixation index (F_ST statistic) and heterozygosity. We estimated the effect of rare alleles and linkage disequilibrium (LD) on these measurements. To assess the effect of LD on the genetic diversity population, we carried out the LD-based pruning (LD<0.5 and LD<0.1) for seven chicken populations combined (I) or separately (II). LD pruning was specific for different dataset groups. Because of the noticeably large sample size in the Russian White RG population, pruning was substantial for Dataset I, and F_ST values were only positive when LD<0.1 pruning was applied. For Dataset II, the LD pruning results were confirmed by examining heterozygosity and alleles' frequency distribution. LD between single nucleotide polymorphisms was consistent across the seven chicken populations, except the Russian White RG population with the smallest r² values and the largest effective population size. Our findings suggest to study variability in each population LD pruning has to be carried separately not after merging to avoid bias in estimates.

Single-nucleotide polymorphism rs10036727 in the SLIT3 gene is associated with osteoporosis at the femoral neck in older Mexican postmenopausal women

AIMS

Osteoporosis (OP) remains a major public health problem worldwide. The most serious complications of this disease are fragility fractures, which increase morbidity and mortality. Management of OP represents an economic burden for health systems. Therefore, it is necessary to develop new screening strategies to identify the population at risk and implement preventive measures. We previously identified the SNPs rs3801387 in WNT16, rs7108738 in SOX6, rs10036727 in SLIT3 and rs7584262 in PKDCC as associated with bone mineral density in postmenopausal women through a genome-wide association study. The aim of this study was to validate those SNPs in two independent cohorts of non-related postmenopausal women.

MATERIALS AND METHODS

We included 1160 women classifying them as normal, osteopenic or osteoporotic and a group with hip fragility fracture. Genotyping was performed using predesigned TaqMan assays.

RESULTS

The variants rs10036727 and rs7108738 showed a significant association with BMD at the femoral neck. SLIT3 has been previously proposed as a potential biomarker and therapeutic resource.

CONCLUSIONS

Our results provide new evidence regarding a possible involvement of SLIT3 in bone metabolisms and encourage the development of more studies in different populations to support these observations.

Discovering lethal alleles across the turkey genome using a transmission ratio distortion approach

Deviation from Mendelian inheritance expectations (transmission ratio distortion, TRD) has been observed in several species, including the mouse and humans. In this study, TRD was characterized in the turkey genome using both allelic (specific- and unspecific-parent TRD) and genotypic (additive- and dominance-TRD) parameterizations within a Bayesian framework. In this study, we evaluated TRD for 23 243 genotyped Turkeys across 56 393 autosomal SNPs. The analyses included 500 sires, 2013 dams and 11 047 offspring (trios). Three different haplotype sliding windows of 4, 10 and 20 SNPs were used across the autosomal chromosomes. Based on the genotypic parameterizations, 14 haplotypes showed additive and dominance TRD effects highlighting regions with a recessive TRD pattern. In contrast, the allelic model uncovered 12 haplotype alleles with the allelic TRD pattern which showed an underrepresentation of heterozygous offspring in addition to the absence of homozygous animals. For regions with the allelic pattern, only one particular region showed a parent-specific TRD where the penetrance was high via the dam, but low via the sire. The gene set analysis uncovered several gene ontology functional terms, Reactome pathways and several Medical Subject Headings that showed significant enrichment of genes associated with TRD. Many of these gene ontology functional terms (e.g. mitotic spindle assembly checkpoint, DRM complex and Aneuploidy), Reactome pathways (e.g. Mismatch repair) and Medical Subject Headings (e.g. Adenosine monophosphate) are known to be related to fertility, embryo development and lethality. The results of this study revealed potential novel candidate lethal haplotypes, functional terms and pathways that may enhance breeding programs in Turkeys through reducing mortality and improving reproduction rate.

The rs78378222 prevalence and the copy loss of the protective allele A in the tumor tissue of diffuse large B-cell lymphoma

Background

Rare single nucleotide polymorphisms (SNPs) are likely to be a crucial genetic factor for human diseases, including cancer. rs78378222 is rare SNP in 3′-untranslated region (UTR) of TP53 gene leading to disturbance of 3′-end mRNA processing. The frequency of rs78378222 varies in several studied populations. The meta-analysis of 34 genome-wide association studies indicated that rs78378222 was significantly associated with an increased risk of cancer overall. Bioinformatic analysis indicates that somatic loss of the protective A allele of rs78378222 occurs in the tumor tissue of some malignant. The goal of the current study is to document the rs78378222 prevalence and evaluate the copy loss status of the protective allele A in the tumor tissue of patients with diffuse large B-cell lymphoma (DLBCL).

Methods

Total DNA was isolated from FFPE-samples and peripheral blood of patients with DLBCL and comparable in age and sex controls. rs78378222 genotyping was performed by the PCR-RFLP method using restriction endonuclease HindIII. Direct Sanger’s sequencing was used to confirm the presence of C allele of the rs78378222. The search for TP53 gene mutations was carried out by Sanger’s direct sequencing method, according to the IARC protocol.

Results

The result of genotyping of 136 DNA samples from DLBCL tumor tissue suggested that frequency of the rs78378222 was 11/136 (8.1%). Rare allele C frequency was 11/272 (4.2%). A total of 5/11 DLBCL rs78378222 heterozygous samples had the heterozygosity loss in the TP53 gene. Only one of these cases was combined with TP53 gene mutations which have proven oncogenic potential—p.Arg196Gln, other four cases have not mutations in the coding regions of gene.

Conclusions

At the stages of DLBCL initiation or progression a loss of the protective allele A of rs78378222 occurs. Further efforts are needed to study possible molecular mechanisms underlying somatic alterations in DLBCL in this region of the TP53 3′-UTR as well as functional studies to illustrate how the presents of rs78378222 may affect tumor progression of lymphoma.

Genetics of extreme human longevity to guide drug discovery for healthy ageing

Ageing is the greatest risk factor for most common chronic human diseases, and it therefore is a logical target for developing interventions to prevent, mitigate or reverse multiple age-related morbidities. Over the past two decades, genetic and pharmacologic interventions targeting conserved pathways of growth and metabolism have consistently led to substantial extension of the lifespan and healthspan in model organisms as diverse as nematodes, flies and mice. Recent genetic analysis of long-lived individuals is revealing common and rare variants enriched in these same conserved pathways that significantly correlate with longevity. In this Perspective, we summarize recent insights into the genetics of extreme human longevity and propose the use of this rare phenotype to identify genetic variants as molecular targets for gaining insight into the physiology of healthy ageing and the development of new therapies to extend the human healthspan.

Variation Screening of Zygote Arrest 1(ZAR1) in Women with Recurrent Zygote Arrest During IVF/ICSI Programs

Human zygote arrest during in vitro culture is rare and the etiology is unclear. The oocyte-specific gene Zar1 plays an essential role in oocyte-embryo transition, and most embryos from Zar1 knockout female mice arrest at the one-cell stage. This study investigates whether maternal ZAR1 gene variations play a role in human zygote arrest. Sequence analysis of ZAR1 was conducted for 47 women with recurrent uncleaved zygotes in in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) cycles (≥ 70% zygotes uncleaved in at least 2 cycles), 93 women from IVF/ICSI cycles with normal uncleaved rate and live birth (control subset I) and 188 women with spontaneous pregnancy and live birth (control subset II). One novel synonymous variation (c.516C>T) and one novel intron variation (c.964-55A>T) of ZAR1 were identified in the zygote arrest group but not in any of the 188 controls. However, the bioinformatics analysis revealed that neither of the mutations in ZAR1 has effect on ZAR1 protein function. Compared with control subset I, the allele frequencies of rare SNPs rs117545505 and rs17609740 were significantly different in patients with zygote arrest (P = 0.047, OR = 3.66). Allele frequencies of these two SNPs were also significantly different between the case group and control subset II (P = 0.024, OR = 3.28). In conclusion, two SNPs in ZAR1 are associated with human zygote arrest, although additional proof is needed for validation.

Gene-based analyses of the maternal genome implicate maternal effect genes as risk factors for conotruncal heart defects

Congenital heart defects (CHDs) affect approximately 1% of newborns. Epidemiological studies have identified several genetically-mediated maternal phenotypes (e.g., pregestational diabetes, chronic hypertension) that are associated with the risk of CHDs in offspring. However, the role of the maternal genome in determining CHD risk has not been defined. We present findings from gene-level, genome-wide studies that link CHDs to maternal effect genes as well as to maternal genes related to hypertension and proteostasis. Maternal effect genes, which provide the mRNAs and proteins in the oocyte that guide early embryonic development before zygotic gene activation, have not previously been implicated in CHD risk. Our findings support a role for and suggest new pathways by which the maternal genome may contribute to the development of CHDs in offspring.

Role of Rare and Low-Frequency Variants in Gene-Alcohol Interactions on Plasma Lipid Levels

BACKGROUND

Alcohol intake influences plasma lipid levels, and such effects may be moderated by genetic variants. We aimed to characterize the role of aggregated rare and low-frequency protein-coding variants in gene by alcohol consumption interactions associated with fasting plasma lipid levels.

METHODS

In the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, fasting plasma triglycerides and high- and low-density lipoprotein cholesterol were measured in 34 153 individuals with European ancestry from 5 discovery studies and 32 277 individuals from 6 replication studies. Rare and low-frequency functional protein-coding variants (minor allele frequency, ≤5%) measured by an exome array were aggregated by genes and evaluated by a gene-environment interaction test and a joint test of genetic main and gene-environment interaction effects. Two dichotomous self-reported alcohol consumption variables, current drinker, defined as any recurrent drinking behavior, and regular drinker, defined as the subset of current drinkers who consume at least 2 drinks per week, were considered.

RESULTS

We discovered and replicated 21 gene-lipid associations at 13 known lipid loci through the joint test. Eight loci (PCSK9, LPA, LPL, LIPG, ANGPTL4, APOB, APOC3, and CD300LG) remained significant after conditioning on the common index single-nucleotide polymorphism identified by previous genome-wide association studies, suggesting an independent role for rare and low-frequency variants at these loci. One significant gene-alcohol interaction on triglycerides in a novel locus was significantly discovered (P=6.65×10^-6 for the interaction test) and replicated at nominal significance level (P=0.013) in SMC5.

CONCLUSIONS

In conclusion, this study applied new gene-based statistical approaches and suggested that rare and low-frequency genetic variants interacted with alcohol consumption on lipid levels.

Assessing the power of principal components and wright's fixation index analyzes applied to reveal the genome-wide genetic differences between herds of Holstein cows

Background

Due to the advent of SNP array technology, a genome-wide analysis of genetic differences between populations and breeds has become possible at a previously unattainable level. The Wright’s fixation index (F_st) and the principal component analysis (PCA) are widely used methods in animal genetics studies. In paper we compared the power of these methods, their complementing each other and which of them is the most powerful.

Results

Comparative analysis of the power Principal Components Analysis (PCA) and F_st were carried out to reveal genetic differences between herds of Holsteinized cows. Totally, 803 BovineSNP50 genotypes of cows from 13 herds were used in current study. Obtained F_st values were in the range of 0.002–0.012 (mean 0.0049) while for rare SNPs with MAF 0.0001–0.005 they were even smaller in the range of 0.001–0.01 (mean 0.0027). Genetic relatedness of the cows in the herds was the cause of such small F_st values. The contribution of rare alleles with MAF 0.0001–0.01 to the F_st values was much less than common alleles and this effect depends on linkage disequilibrium (LD). Despite of substantial change in the MAF spectrum and the number of SNPs we observed small effect size of LD - based pruning on F_st data. PCA analysis confirmed the mutual admixture and small genetic difference between herds. Moreover, PCA analysis of the herds based on the visualization the results of a single eigenvector cannot be used to significantly differentiate herds. Only summed eigenvectors should be used to realize full power of PCA to differentiate small between herds genetic difference. Finally, we presented evidences that the significance of F_st data far exceeds the significance of PCA data when these methods are used to reveal genetic differences between herds.

Conclusions

LD - based pruning had a small effect on findings of F_st and PCA analyzes. Therefore, for weakly structured populations the LD - based pruning is not effective. In addition, our results show that the significance of genetic differences between herds obtained by F_st analysis exceeds the values of PCA. Proposed, to differentiate herds or low structured populations we recommend primarily using the F_st approach and only then PCA.

Evidence for craniofacial enhancer variation underlying nonsyndromic cleft lip and palate

Nonsyndromic cleft lip with or without cleft palate (NSCLP) is a common birth defect for which only ~ 20% of the underlying genetic variation has been identified. Variants in noncoding regions have been increasingly suggested to contribute to the missing heritability. In this study, we investigated whether variation in craniofacial enhancers contributes to NSCLP. Candidate enhancers were identified using VISTA Enhancer Browser and previous publications. Prioritization was based on patterning defects in knockout mice, deletion/duplication of craniofacial genes in animal models and results of whole exome/whole genome sequencing studies. This resulted in 20 craniofacial enhancers to be investigated. Custom amplicon-based sequencing probes were designed and used for sequencing 380 NSCLP probands (from multiplex and simplex families of non-Hispanic white (NHW) and Hispanic ethnicities) using Illumina MiSeq. The frequencies of identified variants were compared to ethnically matched European (CEU) and Los Angeles Mexican (MXL) control genomes and used for association analyses. Variants in mm427/MSX1 and hs1582/SPRY1 showed genome-wide significant association with NSCLP (p ≤ 6.4 × 10^-11). In silico analysis showed that these enhancer variants may disrupt important transcription factor binding sites. Haplotypes involving these enhancers and also mm435/ABCA4 were significantly associated with NSCLP, especially in NHW (p ≤ 6.3 × 10^-7). Importantly, groupwise burden analysis showed several enhancer combinations significantly over-represented in NSCLP individuals, revealing novel NSCLP pathways and supporting a polygenic inheritance model. Our findings support the role of craniofacial enhancer sequence variation in the etiology of NSCLP.

Contribution of Rare Variants of the SLC22A12 Gene to the Missing Heritability of Serum Urate Levels

Gout is a common arthritis caused by monosodium urate crystals. The heritability of serum urate levels is estimated to be 30-70%; however, common genetic variants account for only 7.9% of the variance in serum urate levels. This discrepancy is an example of "missing heritability." The "missing heritability" suggests that variants associated with uric acid levels are yet to be found. By using genomic sequences of the ToMMo cohort, we identified rare variants of the SLC22A12 gene that affect the urate transport activity of URAT1. URAT1 is a transporter protein encoded by the SLC22A12 gene. We grouped the participants with variants affecting urate uptake by URAT1 and analyzed the variance of serum urate levels. The results showed that the heritability explained by the SLC22A12 variants of men and women exceeds 10%, suggesting that rare variants underlie a substantial portion of the "missing heritability" of serum urate levels.

Evolutionary perspectives on polygenic selection, missing heritability, and GWAS

Genome-wide association studies (GWAS) have successfully identified many trait-associated variants, but there is still much we do not know about the genetic basis of complex traits. Here, we review recent theoretical and empirical literature regarding selection on complex traits to argue that "missing heritability" is as much an evolutionary problem as it is a statistical problem. We discuss empirical findings that suggest a role for selection in shaping the effect sizes and allele frequencies of causal variation underlying complex traits, and the limitations of these studies. We then use simulations of selection, realistic genome structure, and complex human demography to illustrate the results of recent theoretical work on polygenic selection, and show that statistical inference of causal loci is sharply affected by evolutionary processes. In particular, when selection acts on causal alleles, it hampers the ability to detect causal loci and constrains the transferability of GWAS results across populations. Last, we discuss the implications of these findings for future association studies, and suggest that future statistical methods to infer causal loci for genetic traits will benefit from explicit modeling of the joint distribution of effect sizes and allele frequencies under plausible evolutionary models.

The Pathogenesis of Endometriosis: Molecular and Cell Biology Insights

The etiopathogenesis of endometriosis is a multifactorial process resulting in a heterogeneous disease. Considering that endometriosis etiology and pathogenesis are still far from being fully elucidated, the current review aims to offer a comprehensive summary of the available evidence. We performed a narrative review synthesizing the findings of the English literature retrieved from computerized databases from inception to June 2019, using the Medical Subject Headings (MeSH) unique ID term "Endometriosis" (ID:D004715) with "Etiology" (ID:Q000209), "Immunology" (ID:Q000276), "Genetics" (ID:D005823) and "Epigenesis, Genetic" (ID:D044127). Endometriosis may origin from Müllerian or non-Müllerian stem cells including those from the endometrial basal layer, Müllerian remnants, bone marrow, or the peritoneum. The innate ability of endometrial stem cells to regenerate cyclically seems to play a key role, as well as the dysregulated hormonal pathways. The presence of such cells in the peritoneal cavity and what leads to the development of endometriosis is a complex process with a large number of interconnected factors, potentially both inherited and acquired. Genetic predisposition is complex and related to the combined action of several genes with limited influence. The epigenetic mechanisms control many of the processes involved in the immunologic, immunohistochemical, histological, and biological aberrations that characterize the eutopic and ectopic endometrium in affected patients. However, what triggers such alterations is not clear and may be both genetically and epigenetically inherited, or it may be acquired by the particular combination of several elements such as the persistent peritoneal menstrual reflux as well as exogenous factors. The heterogeneity of endometriosis and the different contexts in which it develops suggest that a single etiopathogenetic model is not sufficient to explain its complex pathobiology.

Extensive disruption of protein interactions by genetic variants across the allele frequency spectrum in human populations

Each human genome carries tens of thousands of coding variants. The extent to which this variation is functional and the mechanisms by which they exert their influence remains largely unexplored. To address this gap, we leverage the ExAC database of 60,706 human exomes to investigate experimentally the impact of 2009 missense single nucleotide variants (SNVs) across 2185 protein-protein interactions, generating interaction profiles for 4797 SNV-interaction pairs, of which 421 SNVs segregate at > 1% allele frequency in human populations. We find that interaction-disruptive SNVs are prevalent at both rare and common allele frequencies. Furthermore, these results suggest that 10.5% of missense variants carried per individual are disruptive, a higher proportion than previously reported; this indicates that each individual's genetic makeup may be significantly more complex than expected. Finally, we demonstrate that candidate disease-associated mutations can be identified through shared interaction perturbations between variants of interest and known disease mutations.

Gene-based genome-wide association studies and meta-analyses of conotruncal heart defects

Conotruncal heart defects (CTDs) are among the most common and severe groups of congenital heart defects. Despite evidence of an inherited genetic contribution to CTDs, little is known about the specific genes that contribute to the development of CTDs. We performed gene-based genome-wide analyses using microarray-genotyped and imputed common and rare variants data from two large studies of CTDs in the United States. We performed two case-parent trio analyses (N = 640 and 317 trios), using an extension of the family-based multi-marker association test, and two case-control analyses (N = 482 and 406 patients and comparable numbers of controls), using a sequence kernel association test. We also undertook two meta-analyses to combine the results from the analyses that used the same approach (i.e. family-based or case-control). To our knowledge, these analyses are the first reported gene-based, genome-wide association studies of CTDs. Based on our findings, we propose eight CTD candidate genes (ARF5, EIF4E, KPNA1, MAP4K3, MBNL1, NCAPG, NDFUS1 and PSMG3). Four of these genes (ARF5, KPNA1, NDUFS1 and PSMG3) have not been previously associated with normal or abnormal heart development. In addition, our analyses provide additional evidence that genes involved in chromatin-modification and in ribonucleic acid splicing are associated with congenital heart defects.

Functional characterization of a SNP (F51S) found in human alpha 1-antitrypsin

BACKGROUND

Alpha 1-antitrypsin (A1AT) deficiency is related to lung and liver diseases, including pulmonary emphysema and liver cirrhosis in humans. Genetic variations including single nucleotide polymorphisms (SNPs) of SERPINA1 are responsible for A1AT deficiency, but the characteristics of the SNPs are not well-understood. Here, we investigated the features of a rare SNP (F51S) of A1AT, which introduces an additional N-glycosylation site in the N-terminal region of A1AT.

METHODS

We evaluated the F51S variant compared with the wild-type (WT) A1AT with regard to expression in CHO-K1 cells, trypsin inhibitory activity, polymerization, and thermal stability.

RESULTS

The recombinant F51S protein expressed in CHO-K1 cells was mostly retained inside cells. The F51S variant had trypsin inhibitory activity, but reduced thermal stability compared with the WT A1AT. The native acrylamide gel data showed that F51S tended to prevent polymerization of A1AT.

CONCLUSION

The results of this study indicate that Phe51 and the surrounding hydrophobic residue cluster plays an important role in the conformation and secretion of A1AT and suggest the harmful effects of a rare F51S SNP in human health.

Identifying Rare Variant Associations in Admixed Populations

An admixed population and its ancestral populations bear different burdens of a complex disease. The ancestral populations may have different haplotypes of deleterious alleles and thus ancestry-gene interaction can influence disease risk in the admixed population. Among admixed individuals, deleterious haplotypes and their ancestries are dependent and can provide non-redundant association information. Herein we propose a local ancestry boosted sum test (LABST) for identifying chromosomal blocks that harbor rare variants but have no ancestry switches. For such a stable ancestral block, our LABST exploits ancestry-gene interaction and the number of rare alleles therein. Under the null of no genetic association, the test statistic asymptotically follows a chi-square distribution with one degree of freedom (1-df). Our LABST properly controlled type I error rates under extensive simulations, suggesting that the asymptotic approximation was accurate for the null distribution of the test statistic. In terms of power for identifying rare variant associations, our LABST uniformly outperformed several famed methods under four important modes of disease genetics over a large range of relative risks. In conclusion, exploiting ancestry-gene interaction can boost statistical power for rare variant association mapping in admixed populations.

Phenotypic and genome-wide association with the local environment of Arabidopsis

The environment imposes critical selective forces on all living organisms, and the sessile nature of plants makes them particularly useful for investigating the relationship between genetic variation and environmental adaptation. In the model plant Arabidopsis thaliana, extensive information on phenotypic and genotypic variation is available, but comparable information on environmental variation within the native range of the species is lacking. Here, we compile 204 geoclimatic variables to describe the local environments of Arabidopsis accessions with known collection sites encompassing a wide geo-environmental range, and fully sequenced genomes from the 1001 Genomes Project. We identify candidate adaptive genetic variation associated with these environmental variables, and validate this approach through comparison with previous experimental studies, and by targeted confirmation of a role of the heterotrimeric G-protein γ subunit, AGG3, in cold tolerance, as newly predicted from our environmental genome wide association study (GWAS). To facilitate identification of adaptive variation, we created Arabidopsis CLIMtools : interactive web-based databases of the environment × genome associations and correlations between the local environments and 131 phenotypes compiled from previous experimental GWASs. Our study presents an extensive analysis of the local environments, landscape genomics and phenotypic variation of Arabidopsis, and illustrates how 'in silico GWAS' approaches can inform and complement experimental phenomics studies.

Rare Variants in Known Susceptibility Loci and Their Contribution to Risk of Lung Cancer

BACKGROUND

Genome-wide association studies are widely used to map genomic regions contributing to lung cancer (LC) susceptibility, but they typically do not identify the precise disease-causing genes/variants. To unveil the inherited genetic variants that cause LC, we performed focused exome-sequencing analyses on genes located in 121 genome-wide association study-identified loci previously implicated in the risk of LC, chronic obstructive pulmonary disease, pulmonary function level, and smoking behavior.

METHODS

Germline DNA from 260 case patients with LC and 318 controls were sequenced by utilizing VCRome 2.1 exome capture. Filtering was based on enrichment of rare and potential deleterious variants in cases (risk alleles) or controls (protective alleles). Allelic association analyses of single-variant and gene-based burden tests of multiple variants were performed. Promising candidates were tested in two independent validation studies with a total of 1773 case patients and 1123 controls.

RESULTS

We identified 48 rare variants with deleterious effects in the discovery analysis and validated 12 of the 43 candidates that were covered in the validation platforms. The top validated candidates included one well-established truncating variant, namely, BRCA2, DNA repair associated gene (BRCA2) K3326X (OR = 2.36, 95% confidence interval [CI]: 1.38-3.99), and three newly identified variations, namely, lymphotoxin beta gene (LTB) p.Leu87Phe (OR = 7.52, 95% CI: 1.01-16.56), prolyl 3-hydroxylase 2 gene (P3H2) p.Gln185His (OR = 5.39, 95% CI: 0.75-15.43), and dishevelled associated activator of morphogenesis 2 gene (DAAM2) p.Asp762Gly (OR = 0.25, 95% CI: 0.10-0.79). Burden tests revealed strong associations between zinc finger protein 93 gene (ZNF93), DAAM2, bromodomain containing 9 gene (BRD9), and the gene LTB and LC susceptibility.

CONCLUSION

Our results extend the catalogue of regions associated with LC and highlight the importance of germline rare coding variants in LC susceptibility.

S. P, M. S. R, R. T, Naik VG. Association mapping of quantitative resistance to charcoal root rot in mulberry germplasm

Outbreaks of root rot disease in the productive South Indian sericulture belt have threatened the sustainability of the industry. Macrophomina phaseolina (Tassi) Goid. causing charcoal rot is the predominant pathogen to which all productive mulberry cultivars are susceptible. The present study was undertaken to identify molecular markers associated with charcoal rot resistance in mulberry. A mapping panel comprising 214 diverse entries from the Indian germplasm collection was assessed for charcoal rot resistance by artificial inoculation. Resistance to the pathogen was observed in 20 entries, and 51 were found to be moderately resistant. A total of 773 alleles generated across 105 SSR loci and 20,384 AFLP markers generated using 32 EcoRI-NN and MseI-CNN primer combinations were used in genetic analysis. The panel was weakly structured with two subpopulations. However, most entries were found to be admixtures. Survival of cuttings and number of roots per sapling were associated with root rot resistance. Association mapping was performed using different linear mixed models. Five AFLP markers explaining 9.6-12.7% of the total phenotypic variance were found to be significantly (p < 0.05) associated with root rot resistance. Significant associations were also detected in four AFLP markers for survival of cuttings, and these markers explained 10.7-14.2% of the total phenotypic variance. These markers should be validated using mapping populations derived from contrasting biparental combinations by linkage analysis for use in marker-assisted gene pyramiding for durable resistance. The resistant genotypes identified in this study will substantially contribute to genetic improvement of mulberry for charcoal rot resistance and can be integrated into conventional breeding programmes.

The search for loci under selection: trends, biases and progress

Detecting genetic variants under selection using F_ST outlier analysis (OA) and environmental association analyses (EAAs) are popular approaches that provide insight into the genetic basis of local adaptation. Despite the frequent use of OA and EAA approaches and their increasing attractiveness for detecting signatures of selection, their application to field-based empirical data have not been synthesized. Here, we review 66 empirical studies that use Single Nucleotide Polymorphisms (SNPs) in OA and EAA. We report trends and biases across biological systems, sequencing methods, approaches, parameters, environmental variables and their influence on detecting signatures of selection. We found striking variability in both the use and reporting of environmental data and statistical parameters. For example, linkage disequilibrium among SNPs and numbers of unique SNP associations identified with EAA were rarely reported. The proportion of putatively adaptive SNPs detected varied widely among studies, and decreased with the number of SNPs analysed. We found that genomic sampling effort had a greater impact than biological sampling effort on the proportion of identified SNPs under selection. OA identified a higher proportion of outliers when more individuals were sampled, but this was not the case for EAA. To facilitate repeatability, interpretation and synthesis of studies detecting selection, we recommend that future studies consistently report geographical coordinates, environmental data, model parameters, linkage disequilibrium, and measures of genetic structure. Identifying standards for how OA and EAA studies are designed and reported will aid future transparency and comparability of SNP-based selection studies and help to progress landscape and evolutionary genomics.

GCAT|Genomes for life: a prospective cohort study of the genomes of Catalonia

PURPOSE

The prevalence of chronic non-communicable diseases (NCDs) is increasing worldwide. NCDs are the leading cause of both morbidity and mortality, and it is estimated that by 2030, they will be responsible for 80% of deaths across the world. The Genomes for Life (GCAT) project is a long-term prospective cohort study that was designed to integrate and assess the role of epidemiological, genomic and epigenomic factors in the development of major chronic diseases in Catalonia, a north-east region of Spain.

PARTICIPANTS

At the end of 2017, the GCAT Study will have recruited 20 000 participants aged 40-65 years. Participants who agreed to take part in the study completed a self-administered computer-driven questionnaire, and underwent blood pressure, cardiac frequency and anthropometry measurements. For each participant, blood plasma, blood serum and white blood cells are collected at baseline. The GCAT Study has access to the electronic health records of the Catalan Public Healthcare System. Participants will be followed biannually at least 20 years after recruitment.

FINDINGS TO DATE

Among all GCAT participants, 59.2% are women and 83.3% of the cohort identified themselves as Caucasian/white. More than half of the participants have higher education levels, 72.2% are current workers and 42.1% are classified as overweight (body mass index ≥25 and <30 kg/m²). We have genotyped 5459 participants, of which 5000 have metabolome data. Further, the whole genome of 808 participants will be sequenced by the end of 2017.

FUTURE PLANS

The first follow-up study started in December 2017 and will end by March 2018. Residences of all subjects will be geocoded during the following year. Several genomic analyses are ongoing, and metabolomic and genomic integrations will be performed to identify underlying genetic variants, as well as environmental factors that influence metabolites.

Statistical properties of simple random-effects models for genetic heritability

Random-effects models are a popular tool for analysing total narrow-sense heritability for quantitative phenotypes, on the basis of large-scale SNP data. Recently, there have been disputes over the validity of conclusions that may be drawn from such analysis. We derive some of the fundamental statistical properties of heritability estimates arising from these models, showing that the bias will generally be small. We show that that the score function may be manipulated into a form that facilitates intelligible interpretations of the results. We go on to use this score function to explore the behavior of the model when certain key assumptions of the model are not satisfied - shared environment, measurement error, and genetic effects that are confined to a small subset of sites. The variance and bias depend crucially on the variance of certain functionals of the singular values of the genotype matrix. A useful baseline is the singular value distribution associated with genotypes that are completely independent - that is, with no linkage and no relatedness - for a given number of individuals and sites. We calculate the corresponding variance and bias for this setting.

Efficiency of different strategies to mitigate ascertainment bias when using SNP panels in diversity studies

Background

Single nucleotide polymorphism (SNP) panels have been widely used to study genomic variations within and between populations. Methods of SNP discovery have been a matter of debate for their potential of introducing ascertainment bias, and genetic diversity results obtained from the SNP genotype data can be misleading. We used a total of 42 chicken populations where both individual genotyped array data and pool whole genome resequencing (WGS) data were available. We compared allele frequency distributions and genetic diversity measures (expected heterozygosity (H_e), fixation index (F_ST) values, genetic distances and principal components analysis (PCA)) between the two data types. With the array data, we applied different filtering options (SNPs polymorphic in samples of two Gallus gallus wild populations, linkage disequilibrium (LD) based pruning and minor allele frequency (MAF) filtering, and combinations thereof) to assess their potential to mitigate the ascertainment bias.

Results

Rare SNPs were underrepresented in the array data. Array data consistently overestimated H_e compared to WGS data, however, with a similar ranking of the breeds, as demonstrated by Spearman’s rank correlations ranging between 0.956 and 0.985. LD based pruning resulted in a reduced overestimation of H_e compared to the other filters and slightly improved the relationship with the WGS results. The raw array data and those with polymorphic SNPs in the wild samples underestimated pairwise F_ST values between breeds which had low F_ST (<0.15) in the WGS, and overestimated this parameter for high WGS F_ST (>0.15). LD based pruned data underestimated F_ST in a consistent manner. The genetic distance matrix from LD pruned data was more closely related to that of WGS than the other array versions. PCA was rather robust in all array versions, since the population structure on the PCA plot was generally well captured in comparison to the WGS data.

Conclusions

Among the tested filtering strategies, LD based pruning was found to account for the effects of ascertainment bias in the relatively best way, producing results which are most comparable to those obtained from WGS data and therefore is recommended for practical use.

Electronic supplementary material

The online version of this article (doi: 10.1186/s12864-017-4416-9) contains supplementary material, which is available to authorized users.

Association of polymorphisms in the intron of TCF4 gene to late-onset Fuchs endothelial corneal dystrophy: An Indian cohort study

Purpose:

Fuchs endothelial corneal dystrophy (FECD) is a progressive degenerative disease of the corneal endothelium. It is genetically heterogeneous and follows either an autosomal dominant or sporadic pattern of inheritance. Here, we have explored the association of four previously reported intronic single nucleotide polymorphisms and intronic CTG repeat expansions in TCF4 gene to FECD in an Indian cohort.

Methods:

The cohort consisting of 52 sporadic late-onset cases, 5 early-onset cases, and 148 controls was taken for the study. rs2286812 and rs613872 were genotyped by allele specific polymerase chain reaction (ASPCR) and PCR-based restriction digestion, respectively; rs17595731 and rs9954153 were genotyped by Taqman assay using real-time PCR. The quantitative assessment of the CTG repeat region was performed by PCR/Sanger DNA sequencing. The repeats were assessed qualitatively by short tandem repeat and triplet repeat primed PCR assays. The statistical analysis was performed using two-tailed Fisher's exact probability test.

Results:

SNPsrs613872 (G/T) for the ‘G’ allele (P value: 4.57 × 10⁻⁵) and rs17595731 (C/T) for the ‘C’ allele (P value: 1.87 × 10⁻⁵), respectively, showed a significant association to sporadic late-onset FECD. CTG repeat expansions were found to be associated with FECD with a P value = 2.4 × 10⁻³.

Conclusion:

rs613872, rs17595731, and CTG repeat expansions in intronic region of TCF4 are associated with increased risk of sporadic late-onset FECD in the Indian cohort studied.