Mapping complex disease loci in whole-genome association studies

Powerful QTL mapping and favorable allele mining in an all-in-one population: a case study of heading date

The multiparent advanced generation intercross (MAGIC) population is characterized with great potentials in power and resolution of quantitative trait locus (QTL) mapping, but single nucleotide polymorphism (SNP)-based GWAS does not fully reach its potential. In this study, a MAGIC population of 1021 lines was developed from four Xian and four Geng varieties from five subgroups of rice. A total of 44 000 genes showed functional polymorphisms among eight parents, including frameshift variations or premature stop codon variations, which provides the potential to map almost all genes of the MAGIC population. Principal component analysis results showed that the MAGIC population had a weak population structure. A high-density bin map of 24 414 bins was constructed. Segregation distortion occurred in the regions possessing the genes underlying genetic incompatibility and gamete development. SNP-based association analysis and bin-based linkage analysis identified 25 significant loci and 47 QTLs for heading date, including 14 known heading date genes. The mapping resolution of genes is dependent on genetic effects with offset distances of <55 kb for major effect genes and <123 kb for moderate effect genes. Four causal variants and noncoding structure variants were identified to be associated with heading date. Three to four types of alleles with strong, intermediate, weak, and no genetic effects were identified from eight parents, providing flexibility for the improvement of rice heading date. In most cases, japonica rice carries weak alleles, and indica rice carries strong alleles and nonfunctional alleles. These results confirm that the MAGIC population provides the exceptional opportunity to detect QTLs, and its use is encouraged for mapping genes and mining favorable alleles for breeding.

DeepRisk: A deep learning approach for genome-wide assessment of common disease risk

The potential for being able to identify individuals at high disease risk solely based on genotype data has garnered significant interest. Although widely applied, traditional polygenic risk scoring methods fall short, as they are built on additive models that fail to capture the intricate associations among single nucleotide polymorphisms (SNPs). This presents a limitation, as genetic diseases often arise from complex interactions between multiple SNPs. To address this challenge, we developed DeepRisk, a biological knowledge-driven deep learning method for modeling these complex, nonlinear associations among SNPs, to provide a more effective method for scoring the risk of common diseases with genome-wide genotype data. Evaluations demonstrated that DeepRisk outperforms existing PRS-based methods in identifying individuals at high risk for four common diseases: Alzheimer's disease, inflammatory bowel disease, type 2 diabetes, and breast cancer.

Disentangling the relationship between sensory processing, alexithymia and broad autism spectrum: A study in parents' of children with autism spectrum disorders and sensory processing disorders

BACKGROUND

Autistic features and sensory processing difficulties and their phenotypic co-expression with alexithymia share a transdiagnostic vulnerability. In this work, we explored whether the current concept of broad autism phenotype rather translates altered sensory processing (non-specific to autism), meaning that the characteristics of altered sensory processing should be overexpressed among individuals with heightened vulnerability to sensory processing atypicalities (parents of children with sensorial processing disorder, or SPD parents) and individuals with heightened vulnerability to autistic traits (parents of children with autism spectrum disorders, or ASD parents). In addition, the association between altered sensory processing and alexithymia was inspected.

METHOD

The Adolescent/Adult Sensory Profile, Autism Spectrum Quotient, and Toronto Alexithymia Scale were completed by 31 parents of children with ASD, 32 parents of children with SPD, and 52 parents of typically developed (TD) children.

RESULTS

Extreme sensory patterns were overexpressed both in parents of children with SPD and parents of children with ASD when compared to parents of TD children. In addition, extreme sensory patterns were significantly associated with alexithymia scores. Specifically, sensory avoidance, low registration, and sensory sensitivity were positively correlated with alexithymia. No significant differences were found regarding the proportion of autistic traits and alexithymia between ASD and SPD groups of parents.

CONCLUSIONS

These results challenge the specificity of broad autism phenotype and suggest a neurodevelopmental atypicity with roots in altered sensory and emotional processing.

Scavenger receptor class B type I genetic variants associated with disease severity in chronic hepatitis C virus infection

Analysis of host genetic polymorphisms is an increasingly important tool for understanding and predicting pathogenesis and treatment response of viral diseases. The gene locus of scavenger receptor class B type I (SR-BI), encoding a cell entry factor and receptor for hepatitis C virus (HCV), contains several genetic polymorphisms. We applied a probe extension assay to determine the frequency of six single nucleotide polymorphisms (SNPs) within the SR-BI gene locus in 374 individuals with history of HCV infection. In addition, SR-BI messenger RNA (mRNA) levels were analyzed in liver biopsy specimens of chronically infected HCV subjects. The rs5888 variant allele T was present at a higher frequency in subjects with advanced fibrosis (χ² , p = 0.016) and after adjusting for age, duration of infection and alcohol intake as confounding factors. Haplotype analysis of SNP frequencies showed that a haplotype consisting of rs61932577 variant allele C and rs5888 variant allele T was associated with an increased risk of advanced liver fibrosis (defined by an Ishak score 4-6) (adjusted odds ratio 2.81; 95% confidence interval 1.06-7.46. p = 0.038). Carriers of the rs5888 variant allele T displayed reduced SR-BI mRNA expression in liver biopsy specimens. In conclusion the rs5888 polymorphism variant is associated with decreased SR-BI expression and an increased risk of development of advanced fibrosis in chronic HCV infection. These findings provide further evidence for a role of SR-BI in HCV pathogenesis and provides a genetic marker for prediction of those infected individuals at greater risk of developing severe disease.

Genome-wide population structure inferences of human coxsackievirus-A; insights the genotypes diversity and evolution

Coxsackievirus-A (CV-A) is a causative agent of Hand Foot Mouth Disease (HFMD) worldwide. It belongs to the Human Enterovirus genus of the family Picornaviridae. The genomics data availability of CV-A samples, isolated from human host across different continental regions, provide an excellent opportunity to study its genetic composition, diversity, and evolutionary events. The complete genome sequences of 424 CV-A isolates were analyzed through a model-based population genetic approach implemented in the STRUCTURE program. Twelve genetically distinct sub-populations were identified for CV-A isolates with a marked Fst distinction of 0.76991 (P-value = 0.00000). Besides, genetically admixed strains were characterized in the G-Id, G-IIIb clusters constituted by the CV-A12 and CV-A6 enterovirus serotypes. The serotypes depicted inter/intra-genotype recombination and episodic positive selection signatures in the structural and non-structural protein-coding regions. The observed genetic composition of CV-A samples was also deduced by the phylogenetic tree analyses, where a uniform genetic structure was inferred for most of the CV-A genotypes. However, the CV-A6 serotype samples genetically stratified into three sub-populations that may lead to the emergence of new lineages in future. These informations may implicate in planning the effective strategies to combat the coxsackievirus-A-mediated infection.

Precise diagnosis of three top cancers using dbGaP data

The challenge of decoding information about complex diseases hidden in huge number of single nucleotide polymorphism (SNP) genotypes is undertaken based on five dbGaP studies. Current genome-wide association studies have successfully identified many high-risk SNPs associated with diseases, but precise diagnostic models for complex diseases by these or more other SNP genotypes are still unavailable in the literature. We report that lung cancer, breast cancer and prostate cancer as the first three top cancers worldwide can be predicted precisely via 240–370 SNPs with accuracy up to 99% according to leave-one-out and 10-fold cross-validation. Our findings (1) confirm an early guess of Dr. Mitchell H. Gail that about 300 SNPs are needed to improve risk forecasts for breast cancer, (2) reveal an incredible fact that SNP genotypes may contain almost all information that one wants to know, and (3) show a hopeful possibility that complex diseases can be precisely diagnosed by means of SNP genotypes without using phenotypical features. In short words, information hidden in SNP genotypes can be extracted in efficient ways to make precise diagnoses for complex diseases.

Next Generation Sequencing and Bioinformatics Analysis of Family Genetic Inheritance

Mendelian and complex genetic trait diseases continue to burden and affect society both socially and economically. The lack of effective tests has hampered diagnosis thus, the affected lack proper prognosis. Mendelian diseases are caused by genetic mutations in a singular gene while complex trait diseases are caused by the accumulation of mutations in either linked or unlinked genomic regions. Significant advances have been made in identifying novel diseases associated mutations especially with the introduction of next generation and third generation sequencing. Regardless, some diseases are still without diagnosis as most tests rely on SNP genotyping panels developed from population based genetic analyses. Analysis of family genetic inheritance using whole genomes, whole exomes or a panel of genes has been shown to be effective in identifying disease-causing mutations. In this review, we discuss next generation and third generation sequencing platforms, bioinformatic tools and genetic resources commonly used to analyze family based genomic data with a focus on identifying inherited or novel disease-causing mutations. Additionally, we also highlight the analytical, ethical and regulatory challenges associated with analyzing personal genomes which constitute the data used for family genetic inheritance.

Associating COVID-19 Severity with Urban Factors: A Case Study of Wuhan

Wuhan encountered a serious attack in the first round of the coronavirus disease 2019 (COVID-19) pandemic, which has resulted in a public health social impact, including public mental health. Based on the Weibo help data, we inferred the spatial distribution pattern of the epidemic situation and its impacts. Seven urban factors, i.e., urban growth, general hospital, commercial facilities, subway station, land-use mixture, aging ratio, and road density, were selected for validation with the ordinary linear model, in which the former six factors presented a globally significant association with epidemic severity. Then, the geographically weighted regression model (GWR) was adopted to identify their unevenly distributed effects in the urban space. Among the six factors, the distribution and density of major hospitals exerted significant effects on epidemic situation. Commercial facilities appear to be the most prevalently distributed significant factor on epidemic situation over the city. Urban growth, in particular the newly developed residential quarters with high-rise buildings around the waterfront area of Hanyang and Wuchang, face greater risk of the distribution. The influence of subway stations concentrates at the adjacency place where the three towns meet and some near-terminal locations. The aging ratio of the community dominantly affects the hinterland of Hankou to a broader extent than other areas in the city. Upon discovering the result, a series of managerial implications that coordinate various urban factors were proposed. This research may contribute toward developing specific planning and design responses for different areas in the city based on a better understanding of the occurrence, transmission, and diffusion of the COVID-19 epidemic in the metropolitan area.

Genetic variation in the chemokine receptor 5 gene and course of HIV infection; review on genetics and immunological aspect

Chemokines are small protein molecules associated with various physiological events precisely in immune modulation via chemokine receptors. The chemokine receptors are G-protein coupled receptors express mainly on the cell surface of immune cells. Retroviruses, including HIV in the early stage of infection, primarily target chemokines receptors and get internalized easily into immune cells; T cell and escape from immune surveillance. HIV glycoprotein selectively develops an affinity for the extracellular domain of chemokines receptors and allows the pathogen to internalize via CCR-5. Now, CCR-5 remains a crucial signaling pathway that can be translated into the therapeutic target by changing the receptor protein environment. Many populations have a mutation in coding and promoter regions of CCR-5, tuning a resistance for HIV infection. Natively, there are several mechanisms where the human genome remains in the dynamic state by changing its composition and acquiring variations. Single nucleotide polymorphism is spontaneous phenomenon responsible for precise and point mutation at the genome. Several studies have demonstrated that European and African American populations are enriched in significant CCR5 promoter SNP (CCR5Δ32) in the coding and promoter region as well. Now, such SNP can be an early-stage biomarker in studying HIV and other similar infections. Here, in this study, we have elucidated the role of SNP (both the promoter and coding region) and the fate of HIV infections. We also empathized with the genetics of such SNPs, mostly frequency and its immunological impact.

Role of DRD2 and ALDH2 genes in bipolar II disorder with and without comorbid anxiety disorder

The presence of comorbid anxiety disorders (AD) and bipolar II disorders (BP-II) compounds disability complicates treatment, worsens prognosis, and has been understudied. The genes involved in metabolizing dopamine and encoding dopamine receptors, such as aldehyde dehydrogenase 2 (ALDH2) and dopamine D2 receptor (DRD2) genes, may be important to the pathogenesis of BP-II comorbid with AD. We aimed to clarify ALDH2 and DRD2 genes for predisposition to BP-II comorbid with and without AD. The sample consisted of 335 subjects BP-II without AD, 127 subjects BP-II with AD and 348 healthy subjects as normal control. The genotypes of the ALDH2 and DRD2 Taq-IA polymorphisms were determined using polymerase chain reactions plus restriction fragment length polymorphism analysis. Logistic regression analysis showed a statistically significant association between DRD2 Taq-I A1/A2 genotype and BP-II with AD (OR = 2.231, P = 0.021). Moreover, a significant interaction of the DRD2 Taq-I A1/A1 and the ALDH2*1*1 genotypes in BP-II without AD was revealed (OR = 5.623, P = 0.001) compared with normal control. Our findings support the hypothesis that a unique genetic distinction between BP-II with and without AD, and suggest a novel association between DRD2 Taq-I A1/A2 genotype and BP-II with AD. Our study also provides further evidence that the ALDH2 and DRD2 genes interact in BP-II, particularly BP-II without AD.

PAST: The Pathway Association Studies Tool to Infer Biological Meaning from GWAS Datasets

In recent years, a bioinformatics method for interpreting genome-wide association study (GWAS) data using metabolic pathway analysis has been developed and successfully used to find significant pathways and mechanisms explaining phenotypic traits of interest in plants. However, the many scripts implementing this method were not straightforward to use, had to be customized for each project, required user supervision, and took more than 24 h to process data. PAST (Pathway Association Study Tool), a new implementation of this method, has been developed to address these concerns. PAST has been implemented as a package for the R language. Two user-interfaces are provided; PAST can be run by loading the package in R and calling its methods, or by using an R Shiny guided user interface. In testing, PAST completed analyses in approximately half an hour to one hour by processing data in parallel and produced the same results as the previously developed method. PAST has many user-specified options for maximum customization. Thus, to promote a powerful new pathway analysis methodology that interprets GWAS data to find biological mechanisms associated with traits of interest, we developed a more accessible, efficient, and user-friendly tool. These attributes make PAST accessible to researchers interested in associating metabolic pathways with GWAS datasets to better understand the genetic architecture and mechanisms affecting phenotypes.

Ancestry-Dependent Enrichment of Deleterious Homozygotes in Runs of Homozygosity

Runs of homozygosity (ROH) are important genomic features that manifest when an individual inherits two haplotypes that are identical by descent. Their length distributions are informative about population history, and their genomic locations are useful for mapping recessive loci contributing to both Mendelian and complex disease risk. We have previously shown that ROH, and especially long ROH that are likely the result of recent parental relatedness, are enriched for homozygous deleterious coding variation in a worldwide sample of outbred individuals. However, the distribution of ROH in admixed populations and their relationship to deleterious homozygous genotypes is understudied. Here we analyze whole-genome sequencing data from 1,441 unrelated individuals from self-identified African American, Puerto Rican, and Mexican American populations. These populations are three-way admixed between European, African, and Native American ancestries and provide an opportunity to study the distribution of deleterious alleles partitioned by local ancestry and ROH. We re-capitulate previous findings that long ROH are enriched for deleterious variation genome-wide. We then partition by local ancestry and show that deleterious homozygotes arise at a higher rate when ROH overlap African ancestry segments than when they overlap European or Native American ancestry segments of the genome. These results suggest that, while ROH on any haplotype background are associated with an inflation of deleterious homozygous variation, African haplotype backgrounds may play a particularly important role in the genetic architecture of complex diseases for admixed individuals, highlighting the need for further study of these populations.

A Pathway-Based Kernel Boosting Method for Sample Classification Using Genomic Data

The analysis of cancer genomic data has long suffered "the curse of dimensionality." Sample sizes for most cancer genomic studies are a few hundreds at most while there are tens of thousands of genomic features studied. Various methods have been proposed to leverage prior biological knowledge, such as pathways, to more effectively analyze cancer genomic data. Most of the methods focus on testing marginal significance of the associations between pathways and clinical phenotypes. They can identify informative pathways but do not involve predictive modeling. In this article, we propose a Pathway-based Kernel Boosting (PKB) method for integrating gene pathway information for sample classification, where we use kernel functions calculated from each pathway as base learners and learn the weights through iterative optimization of the classification loss function. We apply PKB and several competing methods to three cancer studies with pathological and clinical information, including tumor grade, stage, tumor sites and metastasis status. Our results show that PKB outperforms other methods and identifies pathways relevant to the outcome variables.

FunVar: A systematic pipeline to unravel the convergence patterns of genetic variants in ASD, a paradigmatic complex disease

In recent years, the technological advances for capturing genetic variation in large populations led to the identification of large numbers of putative or disease-causing variants. However, their mechanistic understanding is lagging far behind and has posed new challenges regarding their relevance for disease phenotypes, particularly for common complex disorders. In this study, we propose a systematic pipeline to infer biological meaning from genetic variants, namely rare Copy Number Variants (CNVs). The pipeline consists of three modules that seek to (1) improve genetic data quality by excluding low confidence CNVs, (2) identify disrupted biological processes, and (3) aggregate similar enriched biological processes terms using semantic similarity. The proposed pipeline was applied to CNVs from individuals diagnosed with Autism Spectrum Disorder (ASD). We found that rare CNVs disrupting brain expressed genes dysregulated a wide range of biological processes, such as nervous system development and protein polyubiquitination. The disrupted biological processes identified in ASD patients were in accordance with previous findings. This coherence with literature indicates the feasibility of the proposed pipeline in interpreting the biological role of genetic variants in complex disease development. The suggested pipeline is easily adjustable at each step and its independence from any specific dataset and software makes it an effective tool in analyzing existing genetic resources. The FunVar pipeline is available at https://github.com/lasigeBioTM/FunVar and includes pre and post processing steps to effectively interpret biological mechanisms of putative disease causing genetic variants.

Association of CTLA-4 tagging polymorphisms and haplotypes with hepatocellular carcinoma risk: A case-control study

It has been proposed that cytotoxic T-lymphocyte antigen 4 (CTLA-4) may attenuate the T-cell activation threshold, thereby decreasing the antitumor response and conferring susceptibility to hepatocellular carcinoma (HCC).In the present study, we selected CTLA-4 tagging single nucleotide polymorphisms (SNPs) and explored the relationship between these polymorphisms and susceptibility to HCC. A hospital-based case-control study, comprising 584 cases with HCC and 923 controls, was performed in an eastern Chinese Han population. CTLA-4 SNPs were genotyped using a custom-by-design 48-Plex SNPscan Kit.We found that the CTLA-4 rs3087243 G>A polymorphism might be associated with increased risk of HCC (GA vs GG: adjusted odds ratio [OR], 1.38; 95% confidence interval [CI], 1.04-1.85; P = .028 and AA/GA vs GG: adjusted OR, 1.43; 95% CI, 1.08-1.89; P = .012). After using Bonferroni correction, this association remained (P = .012 for the AA/GA vs GG genetic model). In addition, the power value was 0.904 in the AA/GA versus GG genetic model. Haplotype analysis showed that CTLA4 Crs16840252Ars231775Ars3087243Trs733618, Crs16840252Grs231775Ars3087243Trs733618, and other haplotypes might increase the risk of HCC risk (P = .018, <.001, and .017, respectively). However, we found that CTLA4 Trs16840252A rs231775Grs3087243Trs733618 decreased the risk of HCC (P = .020).Our results suggest that the CTLA-4 rs3087243 G>A polymorphism increases susceptibility to HCC in an eastern Chinese Han population. CTLA-4 haplotypes may influence the development of HCC. In the future, a population-based fine-mapping study with functional assessment should be performed to further determine these potential correlations.

Intronic polymorphisms in genes LRFN2 (rs2494938) and DNAH11 (rs2285947) are prognostic indicators of esophageal squamous cell carcinoma

Background

Genome wide association study (GWAS) has become the major means to screen for the genetic variants associated with risk and prognosis of different diseases. A recent GWAS has discovered three novel intronic single nucleotide polymorphisms in genes LRFN2 (rs2494938), DNAH11 (rs2285947) and PLCXD2 (rs2399395) that are associated with altered risk of esophageal squamous cell carcinoma (ESCC) among Han Chinese populations. However, the prognostic significance of these variations in ESCC remains unclear.

Methods

To investigate the association of three novel single nucleotide polymorphisms (rs2494938, rs2285947, rs2399395) with the prognosis of ESCC patients, we recruited 287 ESCC patients treated with surgical resection and evaluated the potential significance of the three polymorphisms through Kaplan-Meier survival analysis, log-rank test, and Cox proportional hazards regression models.

Results

The ESCC patients carrying genotype AA at rs2494938 had worse survival and genotype GG at 2285947 had better prognosis (Log-rank P = 0.003 and Log-rank P = 0.037, respectively). In addition, rs2494938 at 6p21.1 was independently associated with overall survival of ESCC patients in recessive model [AA vs. GG/GA, HR = 3.12, 95% CI = 1.43–6.83, P = 0.004], rs2285947 at 7p15.3 was independently associated with overall survival of ESCC patients in both dominant model [AA/GA vs. GG, HR = 1.59, 95% CI = 1.02–2.49, P = 0.042] and additive model [AA vs. GA vs. GG, HR = 1.45, 95% CI = 1.05–2.01, P = 0.025].

Conclusions

This study demonstrated that the polymorphisms rs2494938 at 6p21.1 and rs2285947 at 7p15.3 may serve as independent prognostic biomarkers for ESCC, implying the potential biological role of their related genes (LRFN2 and DNAH11) in the process of ESCC development.

Electronic supplementary material

The online version of this article (10.1186/s12881-019-0796-9) contains supplementary material, which is available to authorized users.

Linkage disequilibrium and within-breed genetic diversity in Iranian Zandi sheep

This research aimed to measure the extent of linkage disequilibrium (LD), effective population size (Ne), and runs of homozygosity (ROHs) in one of the major Iranian sheep breeds (Zandi) using 96 samples genotyped with Illumina Ovine SNP50 BeadChip. The amount of LD (r2) for single-nucleotide polymorphism (SNP) pairs in short distances (10–20 kb) was 0.21±0.25 but rapidly decreased to 0.10±0.16 by increasing the distance between SNP pairs (40–60 kb). The Ne of Zandi sheep in past (approximately 3500 generations ago) and recent (five generations ago) populations was estimated to be 6475 and 122, respectively. The ROH-based inbreeding was 0.023. We found 558 ROH regions, of which 37 % were relatively long (>10 Mb). Compared with the rate of LD reduction in other species (e.g., cattle and pigs), in Zandi, it was reduced more rapidly by increasing the distance between SNP pairs. According to the LD pattern and high genetic diversity of Zandi sheep, we need to use an SNP panel with a higher density than Illumina Ovine SNP50 BeadChip for genomic selection and genome-wide association studies in this breed.

A Low Resolution Epistasis Mapping Approach To Identify Chromosome Arm Interactions in Allohexaploid Wheat

Epistasis is an important contributor to genetic variance. In inbred populations, pairwise epistasis is present as additive by additive interactions. Testing for epistasis presents a multiple testing problem as the pairwise search space for modest numbers of markers is large. Single markers do not necessarily track functional units of interacting chromatin as well as haplotype based methods do. To harness the power of multiple markers while minimizing the number of tests conducted, we present a low resolution test for epistatic interactions across whole chromosome arms. Epistasis covariance matrices were constructed from the additive covariances of individual chromosome arms. These covariances were subsequently used to estimate an epistatic variance parameter while correcting for background additive and epistatic effects. We find significant epistasis for 2% of the interactions tested for four agronomic traits in a winter wheat breeding population. Interactions across homeologous chromosome arms were identified, but were less abundant than other chromosome arm pair interactions. The homeologous chromosome arm pair 4BL/4DL showed a strong negative relationship between additive and interaction effects that may be indicative of functional redundancy. Several chromosome arms appeared to act as hubs in an interaction network, suggesting that they may contain important regulatory factors. The differential patterns of epistasis across different traits demonstrate that detection of epistatic interactions is robust when correcting for background additive and epistatic effects in the population. The low resolution epistasis mapping method presented here identifies important epistatic interactions with a limited number of statistical tests at the cost of low precision.

Identification of a SiCL1 gene controlling leaf curling and capsule indehiscence in sesame via cross-population association mapping and genomic variants screening

BACKGROUND

Leaf shape can affect plantlet development and seed yield in sesame. The morphological, histological and genetic analyses of a sesame mutant cl1 (cl) with curly leaf and indehiscent capsule traits were performed in this study. In order to clone the cl1 gene for breeding selection, genome re-sequencing of the 130 individuals of cl1 × USA (0)-26 F₂ population and a bulked segregation analysis (BSA) pool was carried out. The genome re-sequencing data of the 822 germplasm with normal leaf shape were applied.

RESULTS

For cl1 mutant, the adaxial/abaxial character of the parenchyma cells in the leaf blades is reduced. Results proved that the leaf curling trait is controlled by a recessive gene (Sicl1). Cross- population association of the F₂ population of cl1 × USA (0)-26 indicated that the target cl locus was located on the interval C29 between C29_6522236 and C29_6918901 of SiChr. 1. Further regional genome variants screening determined the 6 candidate variants using genomic variants data of 822 natural germplasm and a BSA pool data. Of which, 5 markers C29_6717525, C29_6721553, C29_6721558, C29_6721563, and C29_6721565 existed in the same gene (C29.460). With the aid of the validation in the test F₂ population of cl1 × Yuzhi 11 and natural germplasm, the integrated marker SiCLInDel1 (C29: 6721553-6721572) was determined as the target marker, and C29.460 was the target gene SiCL1 in sesame. SiCL1 is a KAN1 homolog with the full length of 6835 bp. In cl1, the 20 nucleic acids (CAGGTAGCTATGTATATGCA) of SiCLInDel1 marker were mutagenized into 6 nucleic acids (TCTTTG). The deletion led to a frameshift mutation and resulted in the earlier translation termination of the CL gene. The Sicl1 allele was shortened to 1829 bp. SiCL1 gene was expressed mainly in the tissues of stem, leaf, bud, capsule and seed.

CONCLUSIONS

SiCL1 encodes a transcription repressor KAN1 protein and controls leaf curling and capsule indehiscence in sesame. The findings provided an example of high-efficient gene cloning in sesame. The SiCL1 gene and the cl1 mutant supply the opportunity to explore the development regulation of leaf and capsule, and would improve the new variety breeding with high harvest mechanization adaption in sesame.

Insistence on sameness and broader autism phenotype in simplex families with autism spectrum disorder

Insistence on sameness (IS) in individuals with autism spectrum disorder (ASD) and their families may have utility in identifying meaningful subgroups for studying the pathophysiological and genetic pathways affected in ASD. The primary objectives of the current study were to (1) characterize features of IS in parents of children with ASD and (2) examine their relationships with child IS symptoms. Participants were 2760 families who participated in the Simons Simplex Collection. Levels of parent IS were measured using the Broader Autism Phenotype Questionnaire (BAPQ). A factor analysis generated a BAPQ-IS scale, consisting of a subset of 11 items from the original BAPQ-Rigid scale. Correlations were run to examine the relationship between parent BAP and child IS variables. Correlations were found between parent IS and measures of child IS. Although relationships between parent and child IS features were statistically significant in this large sample, effect sizes were small. Results may be reflective of sample design that only included simplex families, where ASD severity may be predominantly driven by spontaneous mutations and less by common inherited risk from parents. In addition, child and parent measures used may have differentially captured features and severity of IS. Further research is needed on how IS can be accurately measured throughout development and across individuals with ASD and their unaffected family members to facilitate future studies on IS as a possible endophenotype for ASD. Autism Res 2018, 11: 1253-1263. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Previous research has suggested that insistence on sameness (IS) may be a heritable trait in autism spectrum disorder (ASD). The study examined whether children with high levels of IS had parents with IS tendencies. A small relationship was found between parent and child measures of IS. Future research is needed on measurement of insistence on sameness across individuals with and without ASD to further examine this relationship and improve understanding of the genetics of ASD.

The Genetics of Pemphigus Vulgaris

Pemphigus vulgaris (PV) is a severe autoimmune blistering disease caused by auto-antibodies (auto-Abs) directed against epithelial desmosomal components and leading to disruption of cell-cell adhesion. The exact mechanisms underlying the disease pathogenesis remain unknown and treatment is still based on immunosuppressive drugs, such as corticosteroids, which are associated with potentially significant side effects. Ethnic susceptibility, familial occurrence, and autoimmune comorbidity, suggest a genetic component to the pathogenesis of the disease, which, if discovered, could advance our understanding of PV pathogenesis and thereby point to novel therapeutic targets for this life-threatening disorder. In this article, we review the evidence for a genetic basis of PV, summarize the different approaches used to investigate susceptibility traits for the disease and describe past and recent discoveries regarding genes associated with PV, most of which belong to the human leukocyte antigen (HLA) locus with limited data regarding association of non-HLA genes with the disease.

CTLA4 tagging polymorphisms and risk of colorectal cancer: a case-control study involving 2,306 subjects

Background

CTLA4 is a candidate gene which has been implicated in the development of colorectal cancer (CRC).

Patients and Methods

To determine the important role of CTLA-4 polymorphisms on risk of CRC, we genotyped four CTLA-4 tagging polymorphisms and calculated crude/adjusted ORs with their 95% CIs. We recruited 1,003 sporadic CRC cases and 1,303 controls.

Results

The findings suggested that CTLA-4 rs231775 G>A polymorphism increased the risk of CRC (homozygote model: adjusted OR=1.40, 95% CI=1.05-1.87, P=0.022; dominant model: adjusted OR=1.19, 95% CI=1.00-1.41, P=0.047; and recessive model: adjusted OR=1.38, 95% CI=1.05-1.82, P=0.021). In a stratified analysis by site of tumor, this association was also found in colon cancer. We also found that CTLA-4 rs231775 GA/AA genotypes might be associated with an increased risk of CRC in Zhenjiang cohort. In addition, we found the CTLA-4 rs16840252 C>T polymorphism was associated with the risk of colon cancer. Haplotype comparison analysis showed that CTLA-4 G_rs3087243C_rs16840252C_rs733618 A_rs231775, G_rs3087243C_rs16840252T_rs733618A_rs231775, and other haplotypes increased the risk of CRC (P<0.001, <0.001, and 0.002, respectively).

Conclusion

This study evidences an association of CTLA-4 tagging polymorphisms and haplotypes with CRC risk. Additional well-designed studies with large sample sizes are required to confirm our findings.

Programmed death-1 polymorphisms is associated with risk of esophagogastric junction adenocarcinoma in the Chinese Han population: A case-control study involving 2,740 subjects

Single nucleotide polymorphisms (SNPs) in Programmed cell death 1 (PD-1) gene may contribute to the development of cancer. In this study, we selected PD-1 rs10204525 T>C, rs2227982 A>G, rs36084323 T>C and rs7421861 A>G polymorphisms and designed a hospital-based case-control study to determine the potential relationship between these functional SNPs in PD-1 gene and esophagogastric junction adenocarcinoma (EGJA) risk. A total of 1,063 EGJA patients and 1,677 controls were enrolled from Eastern Chinese Han population. SNPscan^TMgenotyping assay was used to analyze the genotyping of PD-1 polymorphisms. We found that PD-1 rs7421861 A>G polymorphism was associated with the development of EGJA. However, PD-1 rs2227982 A>G polymorphism was a protective factor for EGJA. In addition, PD-1 rs36084323 CC homozygote genotype might be associated with a borderline decreased risk of EGJA. In a subgroup analysis, a decreased risk of EGJA in never drinking and never smoking groups was identified. Haplotype comparison analysis suggested that PD-1 T_rs10204525G_rs2227982C_36084323A_rs7421861 haplotype significantly decreased the risk of EGJA. However, T_rs10204525G_rs2227982C_36084323G_rs7421861 haplotype in PD-1 gene may confer risk to EGJA. In conclusion, our study highlights rs2227982 A>G, rs36084323 T>C and rs7421861 A>G polymorphisms and haplotypes in PD-1 gene, especially within the intron region, are significantly associated with the risk of EGJA. Further case-control studies with larger sample size and detailed gene-environmental data to replicate these findings in different populations are needed to validate our conclusion.

Linkage disequilibrium levels and allele frequency distribution in Blanco Orejinegro and Romosinuano Creole cattle using medium density SNP chip data

The linkage disequilibrium (LD) between molecular markers affects the accuracy of genome-wide association studies and genomic selection application. High-density genotyping platforms allow identifying the genotype of thousands of single nucleotide polymorphisms (SNPs) distributed throughout the animal genomes, which increases the resolution of LD evaluations. This study evaluated the distribution of minor allele frequencies (MAF) and the level of LD in the Colombian Creole cattle breeds Blanco Orejinegro (BON) and Romosinuano (ROMO) using a medium density SNP panel (BovineSNP50K_v2). The LD decay in these breeds was lower than those reported for other taurine breeds, achieving optimal LD values (r² ≥ 0.3) up to a distance of 70 kb in BON and 100 kb in ROMO, which is possibly associated with the conservation status of these cattle populations and their effective population size. The average MAF for both breeds was 0.27 ± 0.14 with a higher SNP proportion having high MAF values (≥ 0.3). The LD levels and distribution of allele frequencies found in this study suggest that it is possible to have adequate coverage throughout the genome of these breeds using the BovineSNP50K_v2, capturing the effect of most QTL related with productive traits, and ensuring an adequate prediction capacity in genomic analysis.

Relationship between Deleterious Variation, Genomic Autozygosity, and Disease Risk: Insights from The 1000 Genomes Project

Genomic regions of autozygosity (ROAs) represent segments of individual genomes that are homozygous for haplotypes inherited identical-by-descent (IBD) from a common ancestor. ROAs are nonuniformly distributed across the genome, and increased ROA levels are a reported risk factor for numerous complex diseases. Previously, we hypothesized that long ROAs are enriched for deleterious homozygotes as a result of young haplotypes with recent deleterious mutations-relatively untouched by purifying selection-being paired IBD as a consequence of recent parental relatedness, a pattern supported by ROA and whole-exome sequence data on 27 individuals. Here, we significantly bolster support for our hypothesis and expand upon our original analyses using ROA and whole-genome sequence data on 2,436 individuals from The 1000 Genomes Project. Considering CADD deleteriousness scores, we reaffirm our previous observation that long ROAs are enriched for damaging homozygotes worldwide. We show that strongly damaging homozygotes experience greater enrichment than weaker damaging homozygotes, while overall enrichment varies appreciably among populations. Mendelian disease genes and those encoding FDA-approved drug targets have significantly increased rates of gain in damaging homozygotes with increasing ROA coverage relative to all other genes. In genes implicated in eight complex phenotypes for which ROA levels have been identified as a risk factor, rates of gain in damaging homozygotes vary across phenotypes and populations but frequently differ significantly from non-disease genes. These findings highlight the potential confounding effects of population background in the assessment of associations between ROA levels and complex disease risk, which might underlie reported inconsistencies in ROA-phenotype associations.

Trait Mapping Approaches Through Association Analysis in Plants

Previously, association mapping (AM) methodology was used to unravel genetic complications in animal science by measuring the complex traits for candidate and non-candidate genes. Nowadays, this statistical approach is widely used to clarify the complexity in plant breeding program-based genome-wide breeding strategies, marker development, and diversity analysis. This chapter is particularly focused on methodologies with limitations and provides an overview of AM models and software used up to now. Association or linkage disequilibrium mapping has become a very popular method for discovering candidate and non-candidate genes and confirmation of quantitative trait loci (QTL) on various parts of the genome and in marker-assisted selection for breeding. Previously, various QTL investigations were carried out for different plants exclusively by linkage mapping. To help to understand the basics of modern molecular genetic techniques, in this chapter we summarize previous studies done on different crops. AM offers high-resolution power when there is large genotypic diversity and low linkage disequilibrium (LD) for the germplasm being investigated. The benefits of AM, compared with traditional QTL mapping, include a relatively detailed mapping resolution and a far less time-consuming approach since no mapping populations need to be generated. The advancements in genotyping and computational techniques have encouraged the use of AM. AM provides a fascinating approach for genetic investigation of QTLs, due to its resolution and the possibility to study the various genomic areas at the same time without construction of mapping populations. In this chapter we also discuss the advantages and disadvantages of AM, especially in the dicotyledonous crops Fabaceae and Solanaceae, with various genome-size reproductive strategies (clonal vs. sexual), and statistical models. The main objective of this chapter is to highlight the uses of association genetics in major and minor crop species that have trouble being analyzed for dissection of complex traits by identification of the factor responsible for controlling the effect of trait. Graphical Abstract.

High-throughput screening of T7 phage display and protein microarrays as a methodological approach for the identification of IgE-reactive components

Olive pollen and yellow mustard seeds are major allergenic sources with high clinical relevance. To aid with the identification of IgE-reactive components, the development of sensitive methodological approaches is required. Here, we have combined T7 phage display and protein microarrays for the identification of allergenic peptides and mimotopes from olive pollen and mustard seeds. The identification of these allergenic sequences involved the construction and biopanning of T7 phage display libraries of mustard seeds and olive pollen using sera from allergic patients to both biological sources together with the construction of phage microarrays printed with 1536 monoclonal phages from the third/four rounds of biopanning. The screening of the phage microarrays with individual sera from allergic patients enabled the identification of 10 and 9 IgE-reactive unique amino acid sequences from olive pollen and mustard seeds, respectively. Five immunoreactive amino acid sequences displayed on phages were selected for their expression as His6-GST tag fusion proteins and validation. After immunological characterization, we assessed the IgE-reactivity of the constructs. Our results show that protein microarrays printed with T7 phages displaying peptides from allergenic sources might be used to identify allergenic components -peptides, proteins or mimotopes- through their screening with specific IgE antibodies from allergic patients.

Weighted likelihood inference of genomic autozygosity patterns in dense genotype data

Background

Genomic regions of autozygosity (ROA) arise when an individual is homozygous for haplotypes inherited identical-by-descent from ancestors shared by both parents. Over the past decade, they have gained importance for understanding evolutionary history and the genetic basis of complex diseases and traits. However, methods to infer ROA in dense genotype data have not evolved in step with advances in genome technology that now enable us to rapidly create large high-resolution genotype datasets, limiting our ability to investigate their constituent ROA patterns.

Methods

We report a weighted likelihood approach for inferring ROA in dense genotype data that accounts for autocorrelation among genotyped positions and the possibilities of unobserved mutation and recombination events, and variability in the confidence of individual genotype calls in whole genome sequence (WGS) data.

Results

Forward-time genetic simulations under two demographic scenarios that reflect situations where inbreeding and its effect on fitness are of interest suggest this approach is better powered than existing state-of-the-art methods to infer ROA at marker densities consistent with WGS and popular microarray genotyping platforms used in human and non-human studies. Moreover, we present evidence that suggests this approach is able to distinguish ROA arising via consanguinity from ROA arising via endogamy. Using subsets of The 1000 Genomes Project Phase 3 data we show that, relative to WGS, intermediate and long ROA are captured robustly with popular microarray platforms, while detection of short ROA is more variable and improves with marker density. Worldwide ROA patterns inferred from WGS data are found to accord well with those previously reported on the basis of microarray genotype data. Finally, we highlight the potential of this approach to detect genomic regions enriched for autozygosity signals in one group relative to another based upon comparisons of per-individual autozygosity likelihoods instead of inferred ROA frequencies.

Conclusions

This weighted likelihood ROA inference approach can assist population- and disease-geneticists working with a wide variety of data types and species to explore ROA patterns and to identify genomic regions with differential ROA signals among groups, thereby advancing our understanding of evolutionary history and the role of recessive variation in phenotypic variation and disease.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-4312-3) contains supplementary material, which is available to authorized users.

Methylenetetrahydrofolate reductase tagging polymorphisms are associated with risk of esophagogastric junction adenocarcinoma: a case-control study involving 2,740 Chinese Han subjects

In this study, we aimed to determine the potential association of MTHFR tagging single nucleotide polymorphisms (SNPs) with risk of developing esophagogastric junction adenocarcinoma (EGJA). MTHFR rs1801133 G>A, rs3753584 T>C, rs4845882 G>A, rs4846048 A>G and rs9651118 T>C polymorphisms were genotyped in 1,677 healthy individuals and 1,063 patients with EGJA. We found that MTHFR rs1801133 G>A polymorphism was significantly associated with the risk of developing EGJA (AA vs. GG: adjusted P = 0.001; GA/AA vs. GG: adjusted P = 0.007 and AA vs. GA/GG: adjusted P = 0.001). However, for MTHFR rs4845882 G>A polymorphism, the decreased risk of EGJA was found in two genetic models (AA vs. GG: adjusted P = 0.002 and AA vs. GA/GG: adjusted P = 0.005). In addition, for MTHFR rs3753584 T>C and rs9651118 T>C polymorphisms, a tendency to decreased risk of EGJA was noted. In a subgroup analysis, a significantly decreased risk of EGJA in <64 years subgroup was identified. We found that MTHFR G_rs1801133T_rs3753584G_rs4845882A_rs4846048C_rs9651118, G_rs1801133C_rs3753584A_rs4845882A_rs4846048T_rs9651118 and G_rs1801133T_rs3753584A_rs4845882G_rs4846048T_rs9651118 haplotypes significantly decreased the risk of EGJA (P = 0.002, P < 0.001 and P = 0.038, respectively). In conclusion, our study demonstrates that MTHFR rs1801133 G>A may be associated with the increased risk of EGJA. Meanwhile, MTHFR rs3753584 T>C, rs4845882 G>A and rs9651118 T>C polymorphisms and haplotypes may decrease the risk of EGJA in Eastern Chinese Han population. Further studies with large sample size and detailed gene-environmental data are needed to validate our conclusion.

Investigation of Cytotoxic T-lymphocyte antigen-4 polymorphisms in non-small cell lung cancer: a case-control study

The objective of this case-control study was to extensively explore the relationship of Cytotoxic T-lymphocyte antigen-4 (CTLA-4) tagging polymorphisms with susceptibility to non-small-cell lung cancer (NSCLC). We recruited 521 sporadic NSCLC cases and 1,030 non-cancer controls. The genotypes of CTLA-4 rs16840252 C>T, rs231775 G>A, rs3087243 G>A and rs733618 T>C polymorphisms were evaluated using a custom-by-design 48-Plex SNPscan Kit. Our findings revealed there was no statistically significant difference in CTLA-4 genotypes distribution among NSCLC patients and non-cancer controls. Similar findings were observed in the logistic regression analyses. However, the stratified analyses suggested CTLA-4 rs733618 vatiants were correlated with the development of NSCLC in ≥ 60 years subgroup (TC vs. TT: adjusted OR = 1.45, 95% CI = 1.04–2.02, P = 0.030) and even drinking subgroup (TC vs. TT: adjusted OR = 2.27, 95% CI = 1.11–4.60, P = 0.024 and TC/CC vs. TT: adjusted OR = 2.26, 95% CI = 1.15–4.43, P = 0.018). In conclusion, the present case-control study highlights that the CTLA-4 rs733618 T>C polymorphism was associated with the development of NSCLC in ≥ 60 years and even drinking subgroups. A fine-mapping study with functional assessment is necessary to confirm or refute our findings.

Investigation of methylenetetrahydrofolate reductase tagging polymorphisms with colorectal cancer in Chinese Han population

The aim of this case-control study was to assess the relationship between the tagging polymorphisms in methylenetetrahydrofolate reductase (MTHFR) gene and the susceptibility to colorectal cancer (CRC) in a Chinese Han population. A custom-by-design 48-Plex SNPscan Kit was used to determine the genotypes of MTHFR rs3753584 T>C, rs9651118 T>C, rs1801133 G>A, rs4846048 A>G and rs4845882 G>A polymorphisms in 387 CRC patients and 1,536 non-cancer controls. The results revealed that MTHFR rs1801133 G>A polymorphism was associated with a decreased risk of overall CRC. While MTHFR rs4845882 G>A polymorphism conferred an increased risk to overall CRC. In a stratified analysis by CRC region, we found MTHFR rs3753584 T>C and rs9651118 T>C polymorphisms were associated with the increased risk of colon cancer. In addition, a significantly increased risk of rectum cancer associated with MTHFR rs3753584 T>C polymorphism was overt. However, MTHFR rs1801133 G>A polymorphism conferred a decreased risk to colon cancer. In conclusion, findings of the present study reveal that the tagging polymorphisms in MTHFR gene (rs3753584 T>C, rs9651118 T>C and rs4845882 G>A) are associated with the increased risk of CRC. However, MTHFR rs1801133 G>A polymorphism confers a decreased risk to CRC. Additional studies with larger sample size are needed to confirm these findings.

Cost analysis of whole genome sequencing in German clinical practice

OBJECTIVES

Whole genome sequencing (WGS) is an emerging tool in clinical diagnostics. However, little has been said about its procedure costs, owing to a dearth of related cost studies. This study helps fill this research gap by analyzing the execution costs of WGS within the setting of German clinical practice.

METHODOLOGY

First, to estimate costs, a sequencing process related to clinical practice was undertaken. Once relevant resources were identified, a quantification and monetary evaluation was conducted using data and information from expert interviews with clinical geneticists, and personnel at private enterprises and hospitals. This study focuses on identifying the costs associated with the standard sequencing process, and the procedure costs for a single WGS were analyzed on the basis of two sequencing platforms-namely, HiSeq 2500 and HiSeq Xten, both by Illumina, Inc. In addition, sensitivity analyses were performed to assess the influence of various uses of sequencing platforms and various coverage values on a fixed-cost degression.

RESULTS

In the base case scenario-which features 80 % utilization and 30-times coverage-the cost of a single WGS analysis with the HiSeq 2500 was estimated at €3858.06. The cost of sequencing materials was estimated at €2848.08; related personnel costs of €396.94 and acquisition/maintenance costs (€607.39) were also found. In comparison, the cost of sequencing that uses the latest technology (i.e., HiSeq Xten) was approximately 63 % cheaper, at €1411.20.

CONCLUSIONS

The estimated costs of WGS currently exceed the prediction of a 'US$1000 per genome', by more than a factor of 3.8. In particular, the material costs in themselves exceed this predicted cost.

Association between PSCA gene polymorphisms and the risk of cancer: an updated meta-analysis and trial sequential analysis

Previous studies have investigated the relationships between PSCA rs2294008 C>T and rs2976392 G>A polymorphisms and cancer susceptibility. However, the available findings remained inconsistent and even controversial. Thus, the aim of this meta-analysis was performed to clarify such associations. The online databases PubMed, EMBASE and Web of Science searched for relevant studies, covering all the papers published until September 1st, 2016. Data were pooled by odds ratios (ORs) with 95% confidence intervals (CIs) to evaluate the strength of such associations. Then, trial sequential analysis was performed to estimate whether the evidence of the results was firm. Overall, a significant increased risk of cancer was associated with PSCA rs2294008 C>T and rs2976392 G>A polymorphisms. For the PSCA rs2294008 polymorphism, when stratified by type of cancer, the results were significant especially in gastric cancer and bladder cancer. Moreover, in the subgroup analysis by ethnicity, significant results were detected in both Asian and Caucasian populations. Similarly, for the PSCA rs2976392 polymorphism, the stratification analyses by type of cancer showed that the results were significant only in gastric cancer. In addition, the stratification analyses by ethnicity detected that this polymorphism increased cancer risk only in Asian populations. Then, trial sequential analyses demonstrated that the results of the meta-analysis were based on sufficient evidence. Therefore, this meta-analysis suggested that the PSCA rs2294008 C>T and rs2976392 G>A polymorphisms might be associated with cancer susceptibility, which might act as a potential predicted biomarker for genetic susceptibility to cancer, especially in gastric cancer and bladd er cancer.

Gene-gene Interaction Analyses for Atrial Fibrillation

Atrial fibrillation (AF) is a heritable disease that affects more than thirty million individuals worldwide. Extensive efforts have been devoted to the study of genetic determinants of AF. The objective of our study is to examine the effect of gene-gene interaction on AF susceptibility. We performed a large-scale association analysis of gene-gene interactions with AF in 8,173 AF cases, and 65,237 AF-free referents collected from 15 studies for discovery. We examined putative interactions between genome-wide SNPs and 17 known AF-related SNPs. The top interactions were then tested for association in an independent cohort for replication, which included more than 2,363 AF cases and 114,746 AF-free referents. One interaction, between rs7164883 at the HCN4 locus and rs4980345 at the SLC28A1 locus, was found to be significantly associated with AF in the discovery cohorts (interaction OR = 1.44, 95% CI: 1.27–1.65, P = 4.3 × 10^–8). Eight additional gene-gene interactions were also marginally significant (P < 5 × 10^–7). However, none of the top interactions were replicated. In summary, we did not find significant interactions that were associated with AF susceptibility. Future increases in sample size and denser genotyping might facilitate the identification of gene-gene interactions associated with AF.

Investigation of Cytotoxic T-lymphocyte antigen 4 Polymorphisms in Gastric Cardia Adenocarcinoma

To assess the potential effects of Cytotoxic T-lymphocyte antigen 4 (CTLA4) gene polymorphisms on susceptibility to gastric cardia adenocarcinoma (GCA), we genotyped four polymorphisms (rs733618 A>G, rs16840252 C>T, rs231775 G>A and rs3087243 G>A) in CTLA4 and calculated odds ratios (ORs) with the corresponding 95% confidence intervals (95% CIs) for the genotype and allele distributions between GCA cases and controls. The CTLA4 genotypes were determined by the polymerase chain reaction-ligase detection reaction (PCR-LDR) analysis in 330 GCA patients and 608 unrelated cancer-free controls. In this case-control study, there was no significant difference in the genotype and allele distributions of four CTLA4 polymorphisms between GCA patients and controls. However, haplotype association analysis indicated that compared with CTLA4 Grs733618 Crs16840252 Grs231775 Crs3087243 , CTLA4 Grs733618 Crs16840252 Ars231775 Grs3087243 and Ars733618 Crs16840252 Grs231775 Ars3087243 haplotypes conferred increased risks of GCA (OR = 6.46, 95% CI = 1.33-31.28; P = 0.012; both); however, CTLA4 Ars733618 Crs16840252 Ars231775 Grs3087243 and Ars733618 Trs16840252 Grs231775 Grs3087243 haplotypes conferred decreased risks of GCA (P = 0.001 and P = 0.011, respectively). These results highlight that the rare CTLA4 haplotypes may affect the development of GCA in the Chinese population.

Learning Abilities and Disabilities: Generalist Genes, Specialist Environments

Twin studies comparing identical and fraternal twins consistently show substantial genetic influence on individual differences in learning abilities such as reading and mathematics, as well as in other cognitive abilities such as spatial ability and memory. Multivariate genetic research has shown that the same set of genes is largely responsible for genetic influence on these diverse cognitive areas. We call these "generalist genes." What differentiates these abilities is largely the environment, especially nonshared environments that make children growing up in the same family different from one another. These multivariate genetic findings of generalist genes and specialist environments have far-reaching implications for diagnosis and treatment of learning disabilities and for understanding the brain mechanisms that mediate these effects.

The Relevance of Genomic Signatures at Adhesion GPCR Loci in Humans

Adhesion G protein-coupled receptors (aGPCRs) have a long evolutionary history dating back to very basal unicellular eukaryotes. Almost every vertebrate is equipped with a set of different aGPCRs. Genomic sequence data of several hundred extinct and extant species allows for reconstruction of aGPCR phylogeny in vertebrates and non-vertebrates in general but also provides a detailed view into the recent evolutionary history of human aGPCRs. Mining these sequence sources with bioinformatic tools can unveil many facets of formerly unappreciated aGPCR functions. In this review, we extracted such information from the literature and open public sources and provide insights into the history of aGPCR in humans. This includes comprehensive analyses of signatures of selection, variability of human aGPCR genes, and quantitative traits at human aGPCR loci. As indicated by a large number of genome-wide genotype-phenotype association studies, variations in aGPCR contribute to specific human phenotypes. Our survey demonstrates that aGPCRs are significantly involved in adaptation processes, phenotype variations, and diseases in humans.

A forest-based feature screening approach for large-scale genome data with complex structures

Background

Genome-wide association studies (GWAS) interrogate large-scale whole genome to characterize the complex genetic architecture for biomedical traits. When the number of SNPs dramatically increases to half million but the sample size is still limited to thousands, the traditional p-value based statistical approaches suffer from unprecedented limitations. Feature screening has proved to be an effective and powerful approach to handle ultrahigh dimensional data statistically, yet it has not received much attention in GWAS. Feature screening reduces the feature space from millions to hundreds by removing non-informative noise. However, the univariate measures used to rank features are mainly based on individual effect without considering the mutual interactions with other features. In this article, we explore the performance of a random forest (RF) based feature screening procedure to emphasize the SNPs that have complex effects for a continuous phenotype.

Results

Both simulation and real data analysis are conducted to examine the power of the forest-based feature screening. We compare it with five other popular feature screening approaches via simulation and conclude that RF can serve as a decent feature screening tool to accommodate complex genetic effects such as nonlinear, interactive, correlative, and joint effects. Unlike the traditional p-value based Manhattan plot, we use the Permutation Variable Importance Measure (PVIM) to display the relative significance and believe that it will provide as much useful information as the traditional plot.

Conclusion

Most complex traits are found to be regulated by epistatic and polygenic variants. The forest-based feature screening is proven to be an efficient, easily implemented, and accurate approach to cope whole genome data with complex structures. Our explorations should add to a growing body of enlargement of feature screening better serving the demands of contemporary genome data.

Transcriptional Enhancers: Bridging the Genome and Phenome

Enhancers play a major role in animal development by modulating spatiotemporal expression of genes. They interact with sequence-specific transcriptional regulators in response to internal and external cues to bring about transcriptional changes, thus serving as the critical link between an organism's genome and its phenotypic traits. Deciphering the biology of enhancers is a key to understanding the genetic basis of common human diseases. Although a large number of candidate enhancers have been annotated through genome-wide analyses of chromatin accessibility, transcription factor binding, and histone modification in diverse cell types, efforts to characterize their biological roles in human diseases have only begun. Recent experiments have suggested a role for the three-dimensional chromatin architecture in regulation of gene expression by enhancers.

Using genome-wide associations to identify metabolic pathways involved in maize aflatoxin accumulation resistance

BACKGROUND

Aflatoxin is a potent carcinogen that can contaminate grain infected with the fungus Aspergillus flavus. However, resistance to aflatoxin accumulation in maize is a complex trait with low heritability. Here, two complementary analyses were performed to better understand the mechanisms involved. The first coupled results of a genome-wide association study (GWAS) that accounted for linkage disequilibrium among single nucleotide polymorphisms (SNPs) with gene-set enrichment for a pathway-based approach. The rationale was that the cumulative effects of genes in a pathway would give insight into genetic differences that distinguish resistant from susceptible lines of maize. The second involved finding non-pathway genes close to the most significant SNP-trait associations with the greatest effect on reducing aflatoxin in multiple environments. Unlike conventional GWAS, the latter analysis emphasized multiple aspects of SNP-trait associations rather than just significance and was performed because of the high genotype x environment variability exhibited by this trait.

RESULTS

The most significant metabolic pathway identified was jasmonic acid (JA) biosynthesis. Specifically, there was at least one allelic variant for each step in the JA biosynthesis pathway that conferred an incremental decrease to the level of aflatoxin observed among the inbred lines in the GWAS panel. Several non-pathway genes were also consistently associated with lowered aflatoxin levels. Those with predicted functions related to defense were: leucine-rich repeat protein kinase, expansin B3, reversion-to-ethylene sensitivity1, adaptor protein complex2, and a multidrug and toxic compound extrusion protein.

CONCLUSIONS

Our genetic analysis provided strong evidence for several genes that were associated with aflatoxin resistance. Inbred lines that exhibited lower levels of aflatoxin accumulation tended to share similar haplotypes for genes specifically in the pathway of JA biosynthesis, along with several non-pathway genes with putative defense-related functions. Knowledge gained from these two complementary analyses has improved our understanding of population differences in aflatoxin resistance.

Association and gene-gene interactions study of reelin signaling pathway related genes with autism in the Han Chinese population

Autism is a neurodevelopmental disorder with unclear etiology. Reelin had been proposed to participate in the etiology of autism due to its important role in brain development. The goal of this study was to explore the association and gene-gene interactions of reelin signaling pathway related genes (RELN, VLDLR, LRP8, DAB1, FYN, and CDK5) with autism in Han Chinese population. Genotyping data of the six genes were obtained from a recent genome-wide association study performed in 430 autistic children who fulfilled the DSM-IV-TR criteria for autistic disorder, and 1,074 healthy controls. Single marker case-control association analysis and haplotype case-control association analysis were conducted after the data was screened. Multifactor dimensionality reduction (MDR) was applied to further test gene-gene interactions. Neither the single marker nor the haplotype association tests found any significant difference between the autistic group and the control group after permutation test of 1,000 rounds. The 4-locus MDR model (comprising rs6143734, rs1858782, rs634500, and rs1924267 which belong to RELN and DAB1) was determined to be the model with the highest cross-validation consistency (CVC) and testing balanced accuracy. The results indicate that an interaction between RELN and DAB1 may increase the risk of autism in the Han Chinese population. Furthermore, it can also be inferred that the involvement of RELN in the etiology of autism would occur through interaction with DAB1.

New insights from monogenic diabetes for "common" type 2 diabetes

Boundaries between monogenic and complex genetic diseases are becoming increasingly blurred, as a result of better understanding of phenotypes and their genetic determinants. This had a large impact on the way complex disease genetics is now being investigated. Starting with conventional approaches like familial linkage, positional cloning and candidate genes strategies, the scope of complex disease genetics has grown exponentially with scientific and technological advances in recent times. Despite identification of multiple loci harboring common and rare variants associated with complex diseases, interpreting and evaluating their functional role has proven to be difficult. Information from monogenic diseases, especially related to the intermediate traits associated with complex diseases comes handy. The significant overlap between traits and phenotypes of monogenic diseases with related complex diseases provides a platform to understand the disease biology better. In this review, we would discuss about one such complex disease, type 2 diabetes, which shares marked similarity of intermediate traits with different forms of monogenic diabetes.

Targeted Recombinant Progeny: a design for ultra-high resolution mapping of Quantitative Trait Loci in crosses between inbred or pure lines

BACKGROUND

High-resolution mapping of the loci (QTN) responsible for genetic variation in quantitative traits is essential for positional cloning of candidate genes, and for effective marker assisted selection. The confidence interval (QTL) flanking the point estimate of QTN-location is proportional to the number of individuals in the mapping population carrying chromosomes recombinant in the given interval. Consequently, many designs for high resolution QTN mapping are based on increasing the proportion of recombinants in the mapping population. The "Targeted Recombinant Progeny" (TRP) design is a new design for high resolution mapping of a target QTN in crosses between pure, or inbred lines. It is a three-generation procedure generating a large number of recombinant individuals within a QTL previously shown to contain a QTN. This is achieved by having individuals that carry chromosomes recombinant across the target QTL interval as parents of a large mapping population; most of whom will therefore carry recombinant chromosomes targeted to the given QTL. The TRP design is particularly useful for high resolution mapping of QTN that differentiate inbred or pure lines, and hence are not amenable to high resolution mapping by genome-wide association tests.

RESULTS

In the absence of residual polygenic variation, population sizes required for achieving given mapping resolution by the TRP-F2 design relative to a standard F2 design ranged from 0.289 for a QTN with standardized allele substitution effect = 0.2, mapped to an initial QTL of 0.2 Morgan to 0.041 for equivalent QTN mapped to an initial QTL of 0.02 M. In the presence of residual polygenic variation, the relative effectiveness of the TRP design ranges from 1.068 to 0.151 for the same initial QTL intervals and QTN effect. Thus even in the presence of polygenic variation, the TRP can still provide major savings. Simulation showed that mapping by TRP should be based on 30-50 markers spanning the initial interval; and on at least 50 or more G2 families representing this number of recombination points,.

CONCLUSIONS

The TRP design can be an effective procedure for achieving high and ultra-high mapping resolution of a target QTN previously mapped to a known confidence interval (QTL).

PSCA s2294008 C>T and rs2976392 G>A polymorphisms contribute to cancer susceptibility: evidence from published studies

PSCA gene plays an important role in cell adhesion, proliferation and survival. Increasing studies have focused on the association of PSCA gene rs2294008 C>T and rs2976392 G>A with cancer risk. However, the conclusions were inconsistent. Therefore, we performed a meta-analysis to elucidate whether there is a true association, or artifact. We systematically searched eligible studies from MEDLINE, EMBASE and CBM database. Odds ratios and 95% confidence intervals were used to evaluate the strength of the association. The final analysis included 32 studies consisting of 30028 cases and 38765 controls for the rs2294008 C>T polymorphism, and 14 studies with 8190 cases and 7176 controls for the rs2976392 G>A polymorphism. Consequently, the PSCA rs2294008 C>T polymorphism was significantly associated with increased overall cancer risk. Further stratifications indicated the increased risk was more pronounced for gastric (diffused type and non-gastric cardia adenocarcinoma) and bladder cancer. A similar association was observed for the rs2976392 G>A polymorphism. This meta-analysis demonstrated that both of the PSCA rs2294008 C>T and rs2976392 G>A polymorphisms are associated with increased cancer risk, especially for gastric cancer and bladder cancer. Further large-scale studies with different ethnicities and subtypes of gastric cancer are required to confirm the results from this meta-analysis.

Identifying signatures of sexual selection using genomewide selection components analysis

Sexual selection must affect the genome for it to have an evolutionary impact, yet signatures of selection remain elusive. Here we use an individual-based model to investigate the utility of genome-wide selection components analysis, which compares allele frequencies of individuals at different life history stages within a single population to detect selection without requiring a priori knowledge of traits under selection. We modeled a diploid, sexually reproducing population and introduced strong mate choice on a quantitative trait to simulate sexual selection. Genome-wide allele frequencies in adults and offspring were compared using weighted F_ST values. The average number of outlier peaks (i.e., those with significantly large F_ST values) with a quantitative trait locus in close proximity (“real” peaks) represented correct diagnoses of loci under selection, whereas peaks above the F_ST significance threshold without a quantitative trait locus reflected spurious peaks. We found that, even with moderate sample sizes, signatures of strong sexual selection were detectable, but larger sample sizes improved detection rates. The model was better able to detect selection with more neutral markers, and when quantitative trait loci and neutral markers were distributed across multiple chromosomes. Although environmental variation decreased detection rates, the identification of real peaks nevertheless remained feasible. We also found that detection rates can be improved by sampling multiple populations experiencing similar selection regimes. In short, genome-wide selection components analysis is a challenging but feasible approach for the identification of regions of the genome under selection.