SNPs in disease gene mapping, medicinal drug development and evolution

Identifying Novel Osteoarthritis-Associated Genes in Human Cartilage Using a Systematic Meta-Analysis and a Multi-Source Integrated Network

Osteoarthritis, the most common joint disorder, is characterised by deterioration of the articular cartilage. Many studies have identified potential therapeutic targets, yet no effective treatment has been determined. The aim of this study was to identify and rank osteoarthritis-associated genes and micro-RNAs to prioritise those most integral to the disease. A systematic meta-analysis of differentially expressed mRNA and micro-RNAs in human osteoarthritic cartilage was conducted. Ingenuity pathway analysis identified cellular senescence as an enriched pathway, confirmed by a significant overlap (p < 0.01) with cellular senescence drivers (CellAge Database). A co-expression network was built using genes from the meta-analysis as seed nodes and combined with micro-RNA targets and SNP datasets to construct a multi-source information network. This accumulated and connected 1689 genes which were ranked based on node and edge aggregated scores. These bioinformatic analyses were confirmed at the protein level by mass spectrometry of the different zones of human osteoarthritic cartilage (superficial, middle, and deep) compared to normal controls. This analysis, and subsequent experimental confirmation, revealed five novel osteoarthritis-associated proteins (PPIB, ASS1, LHDB, TPI1, and ARPC4-TTLL3). Focusing future studies on these novel targets may lead to new therapies for osteoarthritis.

Efficient targeted insertion of large DNA fragments without DNA donors

Targeted insertion of large DNA fragments holds great potential for treating genetic diseases. Prime editors can effectively insert short fragments (~44 bp) but not large ones. Here we developed GRAND editing to precisely insert large DNA fragments without DNA donors. In contrast to prime editors, which require reverse transcription templates hybridizing with the target sequence, GRAND editing employs a pair of prime editing guide RNAs, with reverse transcription templates nonhomologous to the target site but complementary to each other. This strategy exhibited an efficiency of up to 63.0% of a 150-bp insertion with minor by-products and 28.4% of a 250-bp insertion. It allowed insertions up to ~1 kb, although the efficiency remains low for fragments larger than 400 bp. We confirmed efficient insertion in multiple genomic loci of several cell lines and non-dividing cells, which expands the scope of genome editing to enable donor-free insertion of large DNA sequences.

Presentation of potential genes and deleterious variants associated with non-syndromic hearing loss: a computational approach

Non-syndromic hearing loss (NSHL) is a common hereditary disorder. Both clinical and genetic heterogeneity has created many obstacles to understanding the causes of NSHL. The present study has attempted to ravel the genetic aetiology in NSHL progression and to screen out potential target genes using computational approaches. The reported NSHL target genes (2009-2020) have been studied by analyzing different biochemical and signaling pathways, interpretation of their functional association network, and discovery of important regulatory interactions with three previously established miRNAs in the human inner ear as well as in NSHL such as miR-183, miR-182, and miR-96. This study has identified SMAD4 and SNAI2 as the most putative target genes of NSHL. But pathogenic and deleterious non-synonymous single nucleotide polymorphisms discovered within SMAD4 is anticipated to have an impact on NSHL progression. Additionally, the identified deleterious variants in the functional domains of SMAD4 added a supportive clue for further study. Thus, the identified deleterious variant i.e., rs377767367 (G491V) in SMAD4 needs further clinical validation. The present outcomes would provide insights into the genetics of NSHL progression.

Impact of a Single Nucleotide Polymorphism on the 3D Protein Structure and Ubiquitination Activity of E3 Ubiquitin Ligase Arkadia

Single nucleotide polymorphisms (SNPs) are genetic variations which can play a vital role in the study of human health. SNP studies are often used to identify point mutations that are associated with diseases. Arkadia (RNF111) is an E3 ubiquitin ligase that enhances transforming growth factor-beta (TGF-β) signaling by targeting negative regulators for degradation. Dysregulation of the TGF-β pathway is implicated in cancer because it exhibits tumor suppressive activity in normal cells while in tumor cells it promotes invasiveness and metastasis. Τhe SNP CGT > TGT generated an amino-acid (aa) substitution of Arginine 957 to Cysteine on the enzymatic RING domain of Arkadia. This was more prevalent in a tumor than in a normal tissue sample of a patient with colorectal cancer. This prompted us to investigate the effect of this mutation in the structure and activity of Arkadia RING. We used nuclear magnetic resonance (NMR) to analyze at an atomic-level the structural and dynamic properties of the R957C Arkadia RING domain, while ubiquitination and luciferase assays provided information about its enzymatic functionality. Our study showed that the R957C mutation changed the electrostatic properties of the RING domain however, without significant effects on the structure of its core region. However, the functional studies revealed that the R957C Arkadia exhibits significantly increased enzymatic activity supporting literature data that Arkadia within tumor cells promotes aggressive and metastatic behavior.

Patients with SERPINC1 rs2227589 polymorphism found to have multiple cerebral venous sinus thromboses despite a normal antithrombin level: A case report

BACKGROUND

The hereditary antithrombin (AT) deficiency caused by SERPINC1 gene mutation is an autosomal dominant thrombotic disorder. An increasing number of studies have shown that mutations in the SERPINC1 rs2227589 polymorphic site are correlated with a risk of venous thromboembolism (VTE) at common sites, such as lower extremity deep venous thrombosis and pulmonary thromboembolism. Currently, there are no reports of cerebral venous sinus thrombosis (CVST), a VTE site with a low incidence rate and rs2227589 polymorphism.

CASE SUMMARY

Here, we report a Chinese CVST case with a mutation of the SERPINC1 rs2227589 polymorphic site, which did not cause significant AT deficiency. In a 50-year-old male patient presenting with multiple cerebral venous sinus thromboses no predisposing factors were detected, although a relative had a history of lower extremity deep venous thrombosis. We performed sequencing of the SERPINC1 gene for the patient and his daughter, which revealed the same heterozygous mutation at the rs2227589 polymorphic site: c.41+141G>A.

CONCLUSION

The results showed that more studies should be conducted to assess the correlation between rs2227589 polymorphism and CVST.

APOBEC3, TRIM5α, and BST2 polymorphisms in healthy individuals of various populations with special references to its impact on HIV transmission

AIDS restriction genes (ARGs) like APOBEC3, TRIM5α, and BST2 can act as immunological detectors of the innate protective mechanism of the body. ARGs influence the course of viral pathogenesis and progression of the disease. The infection caused by different viruses including HIV activates the innate immune receptors leading to production of proinflammatory cytokines, interferons and signals that recruit and activate cells involved in the process of inflammation following induction of adaptive immunity. Differential expression of genes involved in viral infection decide the fate and subsequent susceptibility to infection and its clinical outcome. Nevertheless, comprehensive reports on the incidence of genetic polymorphism of APOBEC3s, TRIM5α, and BST-2 in the general population and its association with pathological conditions have not been described well. Therefore, the occurrence of APOBEC3, TRIM5α, and BST2 polymorphism in healthy individuals and its impact on HIV transmission was analyzed. We conducted an extensive search using the several databases including, EMBASE, PubMed (Medline), and Google Scholar. APOBEC3-D, -F, -G, and -H out of the seven human APOBEC3s, help in the control of viral infection. Amongst various restriction factors, TRIM5α and BST-2 also restrict the viral infection followed by the development of the disease. In the current review, a brief account of the polymorphism in the APOBEC3G, TRIM5α, and BST2 genes are explored among different populations along with the interaction of APOBEC3G with Vif protein. Furthermore, this review specifically focus on ARGs polymorphism (APOBEC3G, TRIM5α, and BST2) associated with HIV transmission.

Acoustic Biosensors and Microfluidic Devices in the Decennium: Principles and Applications

Lab-on-a-chip (LOC) technology has gained primary attention in the past decade, where label-free biosensors and microfluidic actuation platforms are integrated to realize such LOC devices. Among the multitude of technologies that enables the successful integration of these two features, the piezoelectric acoustic wave method is best suited for handling biological samples due to biocompatibility, label-free and non-invasive properties. In this review paper, we present a study on the use of acoustic waves generated by piezoelectric materials in the area of label-free biosensors and microfluidic actuation towards the realization of LOC and POC devices. The categorization of acoustic wave technology into the bulk acoustic wave and surface acoustic wave has been considered with the inclusion of biological sample sensing and manipulation applications. This paper presents an approach with a comprehensive study on the fundamental operating principles of acoustic waves in biosensing and microfluidic actuation, acoustic wave modes suitable for sensing and actuation, piezoelectric materials used for acoustic wave generation, fabrication methods, and challenges in the use of acoustic wave modes in biosensing. Recent developments in the past decade, in various sensing potentialities of acoustic waves in a myriad of applications, including sensing of proteins, disease biomarkers, DNA, pathogenic microorganisms, acoustofluidic manipulation, and the sorting of biological samples such as cells, have been given primary focus. An insight into the future perspectives of real-time, label-free, and portable LOC devices utilizing acoustic waves is also presented. The developments in the field of thin-film piezoelectric materials, with the possibility of integrating sensing and actuation on a single platform utilizing the reversible property of smart piezoelectric materials, provide a step forward in the realization of monolithic integrated LOC and POC devices. Finally, the present paper highlights the key benefits and challenges in terms of commercialization, in the field of acoustic wave-based biosensors and actuation platforms.

Genetic variations analysis for complex brain disease diagnosis using machine learning techniques: opportunities and hurdles

BACKGROUND AND OBJECTIVES

This paper presents an in-depth review of the state-of-the-art genetic variations analysis to discover complex genes associated with the brain's genetic disorders. We first introduce the genetic analysis of complex brain diseases, genetic variation, and DNA microarrays. Then, the review focuses on available machine learning methods used for complex brain disease classification. Therein, we discuss the various datasets, preprocessing, feature selection and extraction, and classification strategies. In particular, we concentrate on studying single nucleotide polymorphisms (SNP) that support the highest resolution for genomic fingerprinting for tracking disease genes. Subsequently, the study provides an overview of the applications for some specific diseases, including autism spectrum disorder, brain cancer, and Alzheimer's disease (AD). The study argues that despite the significant recent developments in the analysis and treatment of genetic disorders, there are considerable challenges to elucidate causative mutations, especially from the viewpoint of implementing genetic analysis in clinical practice. The review finally provides a critical discussion on the applicability of genetic variations analysis for complex brain disease identification highlighting the future challenges.

METHODS

We used a methodology for literature surveys to obtain data from academic databases. Criteria were defined for inclusion and exclusion. The selection of articles was followed by three stages. In addition, the principal methods for machine learning to classify the disease were presented in each stage in more detail.

RESULTS

It was revealed that machine learning based on SNP was widely utilized to solve problems of genetic variation for complex diseases related to genes.

CONCLUSIONS

Despite significant developments in genetic diseases in the past two decades of the diagnosis and treatment, there is still a large percentage in which the causative mutation cannot be determined, and a final genetic diagnosis remains elusive. So, we need to detect the variations of the genes related to brain disorders in the early disease stages.

From genome scissors to molecular scalpel: evolution of CRISPR systems

From bizarre palindromic repeats to a bacterial defense mechanism, to genome editing tool, and more, Clustered Regularly Interspaced Short Palindromic Repeats or CRISPR has significantly impacted the way we study genome modification in less than a decade. In this review, we would like to highlight some key players over 30 years of research and explain this biotechnological tool's basic mechanisms. We also refer to the evolution of the CRISPR variants and some of the applications derived from them. The understanding and upgrading of this system will be a valuable tool in the years to come to solve some of the challenges in diverse fields from pharmaceuticals to therapeutics, from basic plant genetics to crop improvement, from metabolic engineering to waste management and industrial processing.

Association of IFN-gamma and IL-10 gene variants with the risk of extrapulmonary tuberculosis

Tuberculosis (TB) caused by Mycobacterium tuberculosis (MTB) is a chronic infectious disease. Interferon-gamma (IFN-γ) is an important cytokine imparting resistance to mycobacterial diseases. It is believed that IFN-γ and Interleukin-10 (IL-10) play divergent roles in the host immune system against MTB infection. IL-10 is an important inhibitory cytokine and helps balancing the inflammatory and immune responses. IL-10 is involved in down regulation of Th1 cytokines, MHC class II antigen and co-stimulatory molecular expression on macrophages, while IFN-γ results in macrophage activation allowing them to exert the microbicidal role. The objectives were to find out the association of IL-10 (-1082 A/G) and IFN-γ (+874 A/T) single nucleotide polymorphisms (SNPs) with extrapulmonary tuberculosis in ethnic Kashmiri population. A total of 100 extrapulmonary tuberculosis cases and 102 healthy controls were analyzed for IL-10 (-1082 A/G) and IFN- γ (+874 A/T) SNPs using Allele-Specific PCR. We found a significant association of IFN-γ + 874 'TT' genotype with extrapulmonary tuberculosis (p = 0.006) and in case of IL-10 (-1082 A/G) we found a significant association with extrapulmonary tuberculosis under recessive model (GG vs GA + AA) (p = 0.03) in Kashmiri population. IL-10 (-1082 A/G) and IFN-γ (+874 A/T) have a significant association with extrapulmonary tuberculosis in ethnic Kashmiri population.

Classification of cannabis strains in the Canadian market with discriminant analysis of principal components using genome-wide single nucleotide polymorphisms

The cannabis community typically uses the terms “Sativa” and “Indica” to characterize drug strains with high tetrahydrocannabinol (THC) levels. Due to large scale, extensive, and unrecorded hybridization in the past 40 years, this vernacular naming convention has become unreliable and inadequate for identifying or selecting strains for clinical research and medicinal production. Additionally, cannabidiol (CBD) dominant strains and balanced strains (or intermediate strains, which have intermediate levels of THC and CBD), are not included in the current classification studies despite the increasing research interest in the therapeutic potential of CBD. This paper is the first in a series of studies proposing that a new classification system be established based on genome-wide variation and supplemented by data on secondary metabolites and morphological characteristics. This study performed a whole-genome sequencing of 23 cannabis strains marketed in Canada, aligned sequences to a reference genome, and, after filtering for minor allele frequency of 10%, identified 137,858 single nucleotide polymorphisms (SNPs). Discriminant analysis of principal components (DAPC) was applied to these SNPs and further identified 344 structural SNPs, which classified individual strains into five chemotype-aligned groups: one CBD dominant, one balanced, and three THC dominant clusters. These structural SNPs were all multiallelic and were predominantly tri-allelic (339/344). The largest portion of these SNPs (37%) occurred on the same chromosome containing genes for CBD acid synthases (CBDAS) and THC acid synthases (THCAS). The remainder (63%) were located on the other nine chromosomes. These results showed that the genetic differences between modern cannabis strains were at a whole-genome level and not limited to THC or CBD production. These SNPs contained enough genetic variation for classifying individual strains into corresponding chemotypes. In an effort to elucidate the confused genetic backgrounds of commercially available cannabis strains, this classification attempt investigated the utility of DAPC for classifying modern cannabis strains and for identifying structural SNPs.

Genome Wide Prediction, Mapping and Development of Genomic Resources of Mastitis Associated Genes in Water Buffalo

Water buffalo (Bubalus bubalis) are an important animal resource that contributes milk, meat, leather, dairy products, and power for plowing and transport. However, mastitis, a bacterial disease affecting milk production and reproduction efficiency, is most prevalent in populations having intensive selection for higher milk yield, especially where the inbreeding level is also high. Climate change and poor hygiene management practices further complicate the issue. The management of this disease faces major challenges, like antibiotic resistance, maximum residue level, horizontal gene transfer, and limited success in resistance breeding. Bovine mastitis genome wide association studies have had limited success due to breed differences, sample sizes, and minor allele frequency, lowering the power to detect the diseases associated with SNPs. In this work, we focused on the application of targeted gene panels (TGPs) in screening for candidate gene association analysis, and how this approach overcomes the limitation of genome wide association studies. This work will facilitate the targeted sequencing of buffalo genomic regions with high depth coverage required to mine the extremely rare variants potentially associated with buffalo mastitis. Although the whole genome assembly of water buffalo is available, neither mastitis genes are predicted nor TGP in the form of web-genomic resources are available for future variant mining and association studies. Out of the 129 mastitis associated genes of cattle, 101 were completely mapped on the buffalo genome to make TGP. This further helped in identifying rare variants in water buffalo. Eighty-five genes were validated in the buffalo gene expression atlas, with the RNA-Seq data of 50 tissues. The functions of 97 genes were predicted, revealing 225 pathways. The mastitis proteins were used for protein-protein interaction network analysis to obtain additional cross-talking proteins. A total of 1,306 SNPs and 152 indels were identified from 101 genes. Water Buffalo-MSTdb was developed with 3-tier architecture to retrieve mastitis associated genes having genomic coordinates with chromosomal details for TGP sequencing for mining of minor alleles for further association studies. Lastly, a web-genomic resource was made available to mine variants of targeted gene panels in buffalo for mastitis resistance breeding in an endeavor to ensure improved productivity and the reproductive efficiency of water buffalo.

Implementation of Pharmacogenomics and Artificial Intelligence Tools for Chronic Disease Management in Primary Care Setting

Chronic disease management often requires use of multiple drug regimens that lead to polypharmacy challenges and suboptimal utilization of healthcare services. While the rising costs and healthcare utilization associated with polypharmacy and drug interactions have been well documented, effective tools to address these challenges remain elusive. Emerging evidence that proactive medication management, combined with pharmacogenomic testing, can lead to improved health outcomes and reduced cost burdens may help to address such gaps. In this report, we describe informatic and bioanalytic methodologies that integrate weak signals in symptoms and chief complaints with pharmacogenomic analysis of ~90 single nucleotide polymorphic variants, CYP2D6 copy number, and clinical pharmacokinetic profiles to monitor drug–gene pairs and drug–drug interactions for medications with significant pharmacogenomic profiles. The utility of the approach was validated in a virtual patient case showing detection of significant drug–gene and drug–drug interactions of clinical significance. This effort is being used to establish proof-of-concept for the creation of a regional database to track clinical outcomes in patients enrolled in a bioanalytically-informed medication management program. Our integrated informatic and bioanalytic platform can provide facile clinical decision support to inform and augment medication management in the primary care setting.

Leptin Receptor Compound Heterozygosity in Humans and Animal Models

Leptin and its receptor are essential for regulating food intake, energy expenditure, glucose homeostasis and fertility. Mutations within leptin or the leptin receptor cause early-onset obesity and hyperphagia, as described in human and animal models. The effect of both heterozygous and homozygous variants is much more investigated than compound heterozygous ones. Recently, we discovered a spontaneous compound heterozygous mutation within the leptin receptor, resulting in a considerably more obese phenotype than described for the homozygous leptin receptor deficient mice. Accordingly, we focus on compound heterozygous mutations of the leptin receptor and their effects on health, as well as possible therapy options in human and animal models in this review.

Structure analysis of deleterious nsSNPs in human PALB2 protein for functional inference

Partner and Localizer of BRCA2 or PALB2 is a typical tumor suppressor protein, that responds to DNA double stranded breaks through homologous recombination repair. Heterozygous mutations in PALB2 are known to contribute to the susceptibility of breast and ovarian cancer. However, there is no comprehensive study characterizing the structural and functional impacts of SNPs located in the PALB2 gene. Therefore, it is of interest to document a comprehensive analysis of coding and non-coding SNPs located at the PALB2 loci using in silico tools. The data for 1455 non-synonymous SNPs (nsSNPs) located in the PALB2 loci were retrieved from the dbSNP database. Comprehensive characterization of the SNPs using a combination of in silico tools such as SIFT, PROVEAN, PolyPhen, PANTHER, PhD-SNP, Pmut, MutPred 2.0 and SNAP-2, identified 28 functionally important SNPs. Among these, 16 nsSNPs were further selected for structural analysis using conservation profile and protein stability. The most deleterious nsSNPs were documented within the WD40 domain of PALB2. A general outline of the structural consequences of each variant was developed using the HOPE project data. These 16 mutant structures were further modelled using SWISS Model and three most damaging mutant models (rs78179744, rs180177123 and rs45525135) were identified. The non-coding SNPs in the 3' UTR region of the PALB2 gene were analyzed for altered miRNA target sites. The comprehensive characterization of the coding and non-coding SNPs in the PALB2 locus has provided a list of damaging SNPs with potential disease association. Further validation through genetic association study will reveal their clinical significance.

Functional Genetic Variants in ATG10 Are Associated with Acute Myeloid Leukemia

Simple Summary

Acute myeloid leukemia (AML) is a hematological neoplasm with a very poor survival rate. To date, diagnostic tools to monitor individuals at higher risk of developing AML are scarce. Single nucleotide polymorphisms (SNPs) have emerged as good candidates for disease prevention. AML is characterized by altered autophagy, a vital mechanism to remove and recycle unnecessary or dysfunctional cellular components. ATG10 is one of the autophagy core genes involved in the autophagosome formation. We hypothesize that SNPs located in regulatory regions of the ATG10 gene could predispose individuals to AML development. We therefore genotyped three SNPs within the ATG10 locus. We identified the ATG10_rs3734114 as a potential risk factor for developing AML, whereas the ATG10_rs1864182 was associated with decreased risk. These findings highlight ATG10 as a key regulator of susceptibility to AML. Furthermore, we believe that ATG10 SNPs could be exploited in the clinical setting as an AML prevention strategy.

Abstract

Acute myeloid leukemia (AML) is the most common acute leukemia, characterized by a heterogeneous genetic landscape contributing, among others, to the occurrence of metabolic reprogramming. Autophagy, a key player on metabolism, plays an essential role in AML. Here, we examined the association of three potentially functional genetic polymorphisms in the ATG10 gene, central for the autophagosome formation. We screened a multicenter cohort involving 309 AML patients and 356 healthy subjects for three ATG10 SNPs: rs1864182T>G, rs1864183C>T and rs3734114T>C. The functional consequences of the ATG10 SNPs in its canonical function were investigated in vitro using peripheral blood mononuclear cells from a cohort of 46 healthy individuals. Logistic regression analysis adjusted for age and gender revealed that patients carrying the ATG10_rs1864182G allele showed a significantly decreased risk of developing AML (OR [odds ratio] = 0.58, p = 0.001), whereas patients carrying the homozygous ATG10_rs3734114C allele had a significantly increased risk of developing AML (OR = 2.70, p = 0.004). Functional analysis showed that individuals carrying the ATG10_rs1864182G allele had decreased autophagy when compared to homozygous major allele carriers. Our results uncover the potential of screening for ATG10 genetic variants in AML prevention strategies, in particular for subjects carrying other AML risk factors such as elderly individuals with clonal hematopoiesis of indeterminate potential.

The Effects of Single Nucleotide Polymorphisms in Cancer RNAi Therapies

Tremendous progress in RNAi delivery methods and design has allowed for the effective development of siRNA-based therapeutics that are currently under clinical investigation for various cancer treatments. This approach has the potential to revolutionize cancer therapy by providing the ability to specifically downregulate or upregulate the mRNA of any protein of interest. This exquisite specificity, unfortunately, also has a downside. Genetic variations in the human population are common because of the presence of single nucleotide polymorphisms (SNPs). SNPs lead to synonymous and non-synonymous changes and they occur once in every 300 base pairs in both coding and non-coding regions in the human genome. Much less common are the somatic mosaicism variations associated with genetically distinct populations of cells within an individual that is derived from postzygotic mutations. These heterogeneities in the population can affect the RNAi's efficacy or more problematically, which can lead to unpredictable and sometimes adverse side effects. From a more positive viewpoint, both SNPs and somatic mosaicisms have also been implicated in human diseases, including cancer, and these specific changes could offer the ability to effectively and, more importantly, selectively target the cancer cells. In this review, we discuss how SNPs in the human population can influence the development and success of novel anticancer RNAi therapies and the importance of why SNPs should be carefully considered.

SNPs in Sites for DNA Methylation, Transcription Factor Binding, and miRNA Targets Leading to Allele-Specific Gene Expression and Contributing to Complex Disease Risk: A Systematic Review

INTRODUCTION

The complex genetic diversity among human populations results from an assortment of factors acting at various sequential levels, including mutations, population migrations, genetic drift, and selection. Although there are a plethora of DNA sequence variations identified through genome-wide association studies (GWAS), the challenge remains to explain the mechanisms underlying interindividual phenotypic disparity accounting for disease susceptibility. Single nucleotide polymorphisms (SNPs) present in the sites for DNA methylation, transcription factor (TF) binding, or miRNA targets can alter the gene expression. The systematic review aimed to evaluate the complex crosstalk among SNPs, miRNAs, DNA methylation, and TFs for complex multifactorial disease risk.

METHODS

PubMed and Scopus databases were used from inception until May 15, 2019. Initially, screening of articles involved studies assessing the interaction of SNPs with TFs, DNA methylation, or miRNAs resulting in allele-specific gene expression in complex multifactorial diseases. We also included the studies which provided experimental validation of the interaction of SNPs with each of these factors. The results from various studies on multifactorial diseases were assessed.

RESULTS

A total of 11 articles for SNPs interacting with DNA methylation, 30 articles for SNPs interacting with TFs, and 11 articles for SNPs in miRNA binding sites were selected. The interactions of SNPs with epigenetic factors were found to be implicated in different types of cancers, autoimmune diseases, cardiovascular diseases, diabetes, and asthma.

CONCLUSION

The systematic review provides evidence for the interplay between genetic and epigenetic risk factors through allele-specific gene expression in various complex multifactorial diseases.

Genetic polymorphisms of superoxide dismutase 1 are associated with the serum lipid profiles of Han Chinese adults in a sexually dimorphic manner

Inspired by the mechanistic correlations between superoxide dismutase 1 (SOD1) and lipid metabolism, the associations of SOD1 single nucleotide polymorphisms (SNPs) with circulating lipid levels were explored. In 2621 Chinese Han adults, randomly recruited from a health examination center without organic diseases, cancers, and pregnancy, three tag SNPs, rs4998557, rs1041740, and rs17880487 selected by Haploview software were genotyped with a probe-based real-time quantitative PCR method. In both genders, most parameters of the dyslipidemia adults were inferior (P < 0.001) to those of the non-dyslipidemia adults, and genotype frequencies of rs4998557 and rs17880487 were significantly different (P < 0.05) between the normal and abnormal subgroups of total cholesterol (TC) or high-density lipoprotein cholesterol (HDLC). Adjusted for confounding factors, logistic regression analyses revealed that in males rs4998557A, rs1041740T, and rs17880487T reduced the risk of high TC and/or LDLC (P < 0.05), and rs4998557A and rs17880487T increased the risk of low HDLC (P < 0.05); but in females, none of the SNPs had associations with any of the lipid parameters (P > 0.05). Conclusively, characterized by a sexual dimorphism, the SOD1 polymorphisms were associated with the lipid disorders in the adult males but not females of the Chinese Han population.

CD44 Gene Polymorphisms as a Risk Factor for Susceptibility and Their Effect on the Clinicopathological Characteristics of Lung Adenocarcinoma in Male Patients

Lung adenocarcinoma is a subtype of lung cancer with high morbidity and mortality. CD44 is instrumental in many physiological and tumor pathological processes. The expression of unique single nucleotide polymorphisms (SNPs) contributes to protein dysfunction and influences cancer susceptibility. In the current study, we investigated the relationship between CD44 polymorphisms and the susceptibility to lung adenocarcinoma with or without epidermal growth factor receptor (EGFR) gene mutations. This study included 279 patients with lung adenocarcinoma. In total, six CD44 SNPs (rs1425802, rs11821102, rs10836347, rs13347, rs187115, and rs713330) were genotyped using a real-time polymerase chain reaction. We found no significant differences in genotype distribution of CD44 polymorphisms between EGFR wild-type and EGFR mutation type in patients with lung adenocarcinoma. We observed a strong association between CD44 rs11821102 G/A polymorphism and EGFR L858R mutation (odds ratio (OR) = 3.846, 95% confidence interval (CI) = 1.018–14.538; p = 0.037) compared with the EGFR wild-type group. In the subgroup of male patients with lung adenocarcinoma harboring the EGFR wild-type, both CD44 rs713330 T/C (OR = 4.317, 95% CI = 1.029–18.115; p = 0.035) and rs10836347 C/T polymorphisms (OR = 9.391, 95% CI = 1.061–83.136; p = 0.019) exhibited significant associations with tumor size and invasion. Data from the present study suggest that CD44 SNPs may help to predict cancer susceptibility and tumor growth in male patients with lung adenocarcinoma.

Extensive In Silico Analysis of ATL1 Gene : Discovered Five Mutations That May Cause Hereditary Spastic Paraplegia Type 3A

BACKGROUND

Hereditary spastic paraplegia type 3A (SPG3A) is a neurodegenerative disease inherited type of Hereditary spastic paraplegia (HSP). It is the second most frequent type of HSP which is characterized by progressive bilateral and mostly symmetric spasticity and weakness of the legs. SPG3A gene mutations and the phenotype-genotype correlations have not yet been recognized. The aim of this work was to categorize the most damaging SNPs in ATL1 gene and to predict their impact on the functional and structural levels by several computational analysis tools.

METHODS

The raw data of ATL1 gene were retrieved from dbSNP database and then run into numerous computational analysis tools. Additionally; we submitted the common six deleterious outcomes from the previous functional analysis tools to I-mutant 3.0 and MUPro, respectively, to investigate their effect on the structural level. The 3D structure of ATL1 was predicted by RaptorX and modeled using UCSF Chimera to compare the differences between the native and the mutant amino acids.

RESULTS

Five nsSNPs out of 249 were classified as the most deleterious (rs746927118, rs979765709, rs119476049, rs864622269, and rs1242753115).

CONCLUSIONS

In this study, the impact of nsSNPs in the ATL1 gene was investigated by various in silico tools that revealed five nsSNPs (V67F, T120I, R217Q, R495W, and G504E) are deleterious SNPs, which have a functional impact on ATL1 protein and, therefore, can be used as genomic biomarkers specifically before 4 years of age; also, it may play a key role in pharmacogenomics by evaluating drug response for this disabling disease.

Comprehensive in silico screening and molecular dynamics studies of missense mutations in Sjogren-Larsson syndrome associated with the ALDH3A2 gene

Sjögren-Larsson syndrome (SLS) is an autoimmune disorder inherited in an autosomal recessive pattern. To date, 80 missense mutations have been identified in association with the Aldehyde Dehydrogenase 3 Family Member A2 (ALDH3A2) gene causing SLS. Disruption of the function of ALDH3A2 leads to excessive accumulation of fat in the cells, which interferes with the normal function of protective membranes or materials that are necessary for the body to function normally. We retrieved 54 missense mutations in the ALDH3A2 from the OMIM, UniProt, dbSNP, and HGMD databases that are known to cause SLS. These mutations were examined with various in silico stability tools, which predicted that the mutations p.S308N and p.R423H that are located at the protein-protein interaction domains are the most destabilizing. Furthermore, to determine the atomistic-level differences within the protein-protein interactions owing to mutations, we performed macromolecular simulation (MMS) using GROMACS to validate the motion patterns and dynamic behavior of the biological system. We found that both mutations (p.S380N and p.R423H) had significant effects on the protein-protein interaction and disrupted the dimeric interactions. The computational pipeline provided in this study helps to elucidate the potential structural and functional differences between the ALDH3A2 native and mutant homodimeric proteins, and will pave the way for drug discovery against specific targets in the SLS patients.

Sequence analysis and variant identification at the APOC3 gene locus indicates association of rs5218 with BMI in a sample of Kuwaiti's

Background

APOC3 is important in lipid transport and metabolism with limited studies reporting genetic sequence variations in specific ethnic groups. The present study aimed to analyze the full APOC3 sequence among Kuwaiti Arabs and test the association of selected variants with lipid levels and BMI.

Methods

Variants were identified by Sanger sequencing the entire APOC3 gene in 100 Kuwaiti Arabs. Variants and their genotypes were fully characterized and used to construct haplotype blocks. Four variants (rs5128, rs2854117, rs2070668, KUAPOC3N3 g.5196 A > G) were selected for testing association with serum lipid levels and BMI in a cohort (n = 733).

Results

APOC3 sequence (4.3 kb) of a Kuwaiti Arab was deposited in Genbank (accession number KJ437193). Forty-two variants including 3 novels were identified including an “A” insertion at genomic positions 116,700,599–116,700,600 (promoter region) and two substitutions in intron 1 at genomic positions 116,700,819 and 116,701,159. Only three variants, (rs5128, rs2854117, and rs2070668) were analyzed for association of which rs5128 showed a trend for association with increased BMI, TG and VLDL levels that was further investigated using multivariate analysis. A significant association of rs5128 with BMI (p <  0.05) was observed following a dominant genetic model with increased risk by an OR of 4.022 (CI: 1.13–14.30).

Conclusion

The present study is the first to report sequence analysis of APOC3 in an Arab ethnic group. This study supports the inclusion of rs5128 as a marker for assessing genetic risk to dyslipidemia and obesity and the inclusion of the novel variant g.5196 A > G for population stratification of Arabs.

Editorial focus: understanding off-target effects as the key to successful RNAi therapy

With the first RNA interference (RNAi) drug (ONPATTRO (patisiran)) on the market, we witness the RNAi therapy field reaching a critical turning point, when further improvements in drug candidate design and delivery pipelines should enable fast delivery of novel life changing treatments to patients. Nevertheless, ignoring parallel development of RNAi dedicated in vitro pharmacological profiling aiming to identify undesirable off-target activity may slow down or halt progress in the RNAi field. Since academic research is currently fueling the RNAi development pipeline with new therapeutic options, the objective of this article is to briefly summarize the basics of RNAi therapy, as well as to discuss how to translate basic research into better understanding of related drug candidate safety profiles early in the process.

In Silico Genetics Revealing 5 Mutations in CEBPA Gene Associated With Acute Myeloid Leukemia

Background:

Acute myeloid leukemia (AML) is an extremely heterogeneous malignant disorder; AML has been reported as one of the main causes of death in children. The objective of this work was to classify the most deleterious mutation in CCAAT/enhancer-binding protein-alpha (CEBPA) and to predict their influence on the functional, structural, and expression levels by various Bioinformatics analysis tools.

Methods:

The single nucleotide polymorphisms (SNPs) were claimed from the National Center for Biotechnology Information (NCBI) database and then submitted into various functional analysis tools, which were done to predict the influence of each SNP, followed by structural analysis of modeled protein followed by predicting the mutation effect on energy stability; the most damaging mutations were chosen for additional investigation by Mutation3D, Project hope, ConSurf, BioEdit, and UCSF Chimera tools.

Results:

A total of 5 mutations out of 248 were likely to be responsible for the structural and functional variations in CEBPA protein, whereas in the 3′-untranslated region (3′-UTR) the result showed that among 350 SNPs in the 3′-UTR of CEBPA gene, about 11 SNPs were predicted. Among these 11 SNPs, 65 alleles disrupted a conserved miRNA site and 22 derived alleles created a new site of miRNA.

Conclusions:

In this study, the impact of functional mutations in the CEBPA gene was investigated through different bioinformatics analysis techniques, which determined that R339W, R288P, N292S, N292T, and D63N are pathogenic mutations that have a possible functional and structural influence, therefore, could be used as genetic biomarkers and may assist in genetic studies with a special consideration of the large heterogeneity of AML.

Specter: linear deconvolution for targeted analysis of data-independent acquisition mass spectrometry proteomics

Mass spectrometry with data-independent acquisition (DIA) has emerged as a promising method to greatly improve the comprehensiveness and reproducibility of targeted and discovery proteomics, in theory systematically measuring all peptide precursors within a biological sample. Despite the technical maturity of DIA, the analytical challenges involved in discriminating between peptides with similar sequences in convoluted spectra have limited its applicability in important cases, such as the detection of single-nucleotide polymorphisms and alternative site localizations in phosphoproteomics data. We have developed Specter, an open-source software tool that uses linear algebra to deconvolute DIA mixture spectra directly in terms of a spectral library, circumventing the problems associated with typical fragment correlation-based approaches. We validate the sensitivity of Specter and its performance relative to other methods by means of several complex datasets, and show that Specter is able to successfully analyze cases involving highly similar peptides that are typically challenging for DIA analysis methods.

Comparative computational assessment of the pathogenicity of mutations in the Aspartoacylase enzyme

Aspartoacylase (ASPA) is a zinc-dependent abundant enzyme in the brain, which catalyzes the conversion of N-acetyl aspartate (NAA) into acetate and aspartate. Mutations in the ASPA gene are associated with the development of Canavan disease (CD), leading to the deficiency of ASPA activity. Patients with CD were characterized by degeneration of the white matter of the brain. We reported earlier on two patients with severe form of CD that both had two novel missense mutations in the ASPA: c.427 A > G; p. I143V and c.557 T > A; p. V186D (Zaki et al. 2017a), patient 1 harbored both mutations (p.I143V and p.V186D) in a heterozygous form together with four other mutations, and patient 2 had both mutations in homozygous form. Wijayasinghe et al. (2014) crystallized the 3D structures of four different ASPA mutants (p.K213E, p.Y231C, p.E285A, and p.F295S). In this study, we used in silico prediction methods and molecular dynamics simulation (MDS) to understand the structural impact of all these mutations. Moreover, we used molecular docking (MD) to investigate the binding patterns of the NAA substrate to the native and mutant proteins. Among the mutations, p.E285A (crystallized mutant) was predicted to be the most deleterious for the protein function and the least deleteriousness mutant was the p.I143V (novel mutant). Among the novel mutations, p.V186D was observed to be disruptive for both the zinc binding and NAA binding than the p.I143V. This study provides practical insights on the effect of these mutations on the ASPA function and might serve as a platform for drug design for CD treatment.

Nonsynonymous Polymorphisms in the Human AS3MT Arsenic Methylation Gene: Implications for Arsenic Toxicity

Arsenic methylation, the primary biotransformation in the human body, is catalyzed by the enzyme As(III) S-adenosylmethionine (SAM) methyltransferases (hAS3MT). This process is thought to be protective from acute high-level arsenic exposure. However, with long-term low-level exposure, hAS3MT produces intracellular methylarsenite (MAs(III)) and dimethylarsenite (DMAs(III)), which are considerably more toxic than inorganic As(III) and may contribute to arsenic-related diseases. Several single nucleotide polymorphisms (SNPs) in putative regulatory elements of the hAS3MT gene have been shown to be protective. In contrast, three previously identified exonic SNPs (R173W, M287T, and T306I) may be deleterious. The goal of this study was to examine the effect of single amino acid substitutions in hAS3MT on the activity of the enzyme that might explain their contributions to adverse health effects of environmental arsenic. We identified five additional intragenic variants in hAS3MT (H51R, C61W, I136T, W203C, and R251H). We purified the eight polymorphic hAS3MT proteins and characterized their enzymatic properties. Each enzyme had low methylation activity through decreased affinity for substrate, lower overall rates of catalysis, or lower stability. We propose that amino acid substitutions in hAS3MT with decreased catalytic activity lead to detrimental responses to environmental arsenic and may increase the risk of arsenic-related diseases.

Methods, Tools and Current Perspectives in Proteogenomics

With combined technological advancements in high-throughput next-generation sequencing and deep mass spectrometry-based proteomics, proteogenomics, i.e. the integrative analysis of proteomic and genomic data, has emerged as a new research field. Early efforts in the field were focused on improving protein identification using sample-specific genomic and transcriptomic sequencing data. More recently, integrative analysis of quantitative measurements from genomic and proteomic studies have identified novel insights into gene expression regulation, cell signaling, and disease. Many methods and tools have been developed or adapted to enable an array of integrative proteogenomic approaches and in this article, we systematically classify published methods and tools into four major categories, (1) Sequence-centric proteogenomics; (2) Analysis of proteogenomic relationships; (3) Integrative modeling of proteogenomic data; and (4) Data sharing and visualization. We provide a comprehensive review of methods and available tools in each category and highlight their typical applications.

SNPs in microRNA target sites and their potential role in human disease

In the post-genomic era, the goal of personalized medicine is to determine the correlation between genotype and phenotype. Developing high-throughput genotyping technologies such as genome-wide association studies (GWAS) and the 1000 Genomes Project (http://www.internationalgenome.org/about/#1000G_PROJECT) has dramatically enhanced our ability to map where changes in the genome occur on a population level by identifying millions of single nucleotide polymorphisms (SNPs). Polymorphisms, particularly those within the coding regions of proteins and at splice junctions, have received the most attention, but it is also now clear that polymorphisms in the non-coding regions are important. In these non-coding regions, the enhancer and promoter regions have received the most attention, whereas the 3'-UTR regions have until recently been overlooked. In this review, we examine how SNPs affect microRNA-binding sites in these regions, and how mRNA stability changes can lead to disease pathogenesis.

Development of T m -shift genotyping method for detection of cat-derived Giardia lamblia

To develop T _m -shift genotyping method for detection of cat-derived Giardia lamblia, two sets of primers with two GC-rich tails of unequal length attached to their 5'-end were designed according to two SNPs (BG434 and BG170) of β-giardin (bg) gene, and specific PCR products were identified by inspection of a melting curve on real-time PCR thermocycler. A series of experiments on the stability, sensitivity, and accuracy of T _m -shift method was tested, and clinical samples were also detected. The results showed that two sets of primers based on SNP could distinguish accurately between assemblages A and F. Coefficient of variation of T _m values of assemblage A and F was 0.14 and 0.07% in BG434 and 0.10 and 0.11% in BG170, respectively. The lowest detection concentration was 4.52 × 10^-5 and 4.88 × 10^-5 ng/μL samples of assemblage A and F standard plasmids. The T _m -shift genotyping results of ten DNA samples from the cat-derived G. lamblia were consistent with their known genotypes. The detection rate of clinical samples by T _m -shift was higher than that by microscopy, and their genotyping results were in complete accordance with sequencing results. It is concluded that the T _m -shift genotyping method is rapid, specific, and sensitive and may provide a new technological mean for molecular detection and epidemiological investigation of the cat-derived G. lamblia.

Genetic differences among ethnic groups

BACKGROUND

Many differences between different ethnic groups have been observed, such as skin color, eye color, height, susceptibility to some diseases, and response to certain drugs. However, the genetic bases of such differences have been under-investigated. Since the HapMap project, large-scale genotype data from Caucasian, African and Asian population samples have been available. The project found that these populations were located in different areas of the PCA (Principal Component Analysis) plot. However, as an unsupervised method, PCA does not measure the differences in each single nucleotide polymorphism (SNP) among populations.

RESULTS

We applied an advanced mutual information-based feature selection method to detect associations between SNP status and ethnic groups using the latest HapMap Phase 3 release version 3, which included more sub-populations. A total of 299 SNPs were identified, and they can accurately predicted the ethnicity of all HapMap populations. The 10-fold cross validation accuracy of the SMO (sequential minimal optimization) model on training dataset was 0.901, and the accuracy on independent test dataset was 0.895.

CONCLUSIONS

In-depth functional analysis of these SNPs and their nearby genes revealed the genetic bases of skin and eye color differences among populations.

A genetic study of steroid-resistant nephrotic syndrome: relationship between polymorphism -173 G to C in the MIF gene and serum level MIF in children

There is no satisfactory explanation as to why some nephrotic syndrome (NS) patients respond to glucocorticoids and others do not. The aim of this study was to investigate an association between single nucleotide polymorphism of the MIF gene -rs755622 and serum MIF concentrations in NS patients. During a period between November 2011 and September 2012, 120 consecutive children divided into three groups [healthy children, steroid-resistant nephrotic syndrome (SRNS) and steroid-sensitive nephrotic syndrome (SSNS)] were examined. Children were defined as healthy when they had a normal estimated glomerular filtration rate and spot urinary albumin creatinine ratio <150 μg/mg creatinine. SRNS was diagnosed in children who did not respond to the usual doses of steroids within 4 weeks of initiating treatment. SSNS patients were defined as those who had remission after usual doses of steroids. The genotype of -173 G to C polymorphism of the MIF gene was determined using polymerase chain reaction restriction fragment length polymorphism methods. Serum MIF concentration was measured using sandwich enzyme-linked immunosorbent assay. The allele frequency of the C allele was higher in SRNS compared with that of SSNS patients (P=0.025). There was a trend toward an association between genotypes and serum MIF disturbances. In conclusion, this study noted elevated circulating serum MIF levels and higher frequency of the C allele of the MIF gene in SRNS patients. The presence of the C allele implies an increased risk for steroid resistance.

Novel molecular approach demonstrates that turbid river plumes reduce predation mortality on larval fish

Turbidity associated with river plumes is known to affect the search ability of visual predators and thus can drive 'top-down' impacts on prey populations in complex ecosystems; however, traditional quantification of predator-prey relationships (i.e. stomach content analysis) often fails with larval fish due to rapid digestion rates. Herein, we use novel molecular genetic methods to quantify larval yellow perch (YP) in predator stomachs in western Lake Erie to test the hypothesis that turbidity drives variation in larval predation. We characterize predator stomach content DNA to first identify YP DNA (single nucleotide polymorphism) and then quantify larval YP predation (microsatellite allele counting) in two river plumes differing in turbidity. Our results showed elevated larval YP predation in the less turbid river plume, consistent with a top-down impact of turbidity on larval survival. Our analyses highlight novel ecological hypothesis testing using the power of innovative molecular genetic approaches.

Genotyping technologies: application to biotransformation enzyme genetic polymorphism screening

Pharmacogenomics encompasses several major areas: the study of polymorphic variations to drug response and disease susceptibility, identification of the effects of drugs/xenobiotics at the genomic level, and genotype/phenotype associations. The most common type of human genetic variations is single-nucleotide polymorphisms (SNPs). Several novel approaches to detection of SNPs are currently available. The range of new methods includes modifications of several conventional techniques such as PCR, mass spectrometry, and sequencing as well as more innovative technologies such as fluorescence resonance energy transfer and microarrays. The application of each of these techniques is largely dependent on the number of SNPs to be screened and sample size. The current chapter presents an overview of the general concepts of a variety of genotyping technologies with an emphasis on the recently developed methodologies, including a comparison of the advantages, applicability, cost efficiency, and limitations of these methods.

A novel catechol-O-methyltransferase variant associated with human disc degeneration

BACKGROUND

Disc degeneration and its associated low back pain are a major health care concern causing disability with a prominent role in this country's medical, social and economic structure. Low back pain is devastating and influences the quality of life for millions. Low back pain lifetime prevalence approximates 80% with an estimated direct cost burden of $86 billion per year. Back pain patients incur higher costs, greater health care utilization, and greater work loss than patients without back pain.

METHODS

Research was performed following approval of our Institutional Review Board. DNA was isolated, processed and amplified using routine techniques. Amplified DNA was hybridized to Affymetrix Genome-Wide Human SNP Arrays. Quality control and genotyping analysis were performed using Affymetrix Genotyping Console. The Birdseed v2 algorithm was used for genotyping analysis. 2589 SNPs were selected a priori to enter statistical analysis using lotistic regression in SAS.

RESULTS

Our objective was to search for novel single nucleotide polymorphisms (SNPs) associated with disc degeneration. Four SNPs were found to have a significant relationship to disc degeneration; three are novel. Rs165656, a new SNP found to be associated with disc degeneration, was in catechol-O-methyltransferase (COMT), a gene with well-recognized pain involvement, especially in female subjects (p=0.01). Analysis confirmed the previously association between COMT SNP rs4633 and disc degeneration. We also report two novel disc degeneration-related SNPs (rs2095019 and rs470859) located in intergenic regions upstream to thrombospondin 2.

CONCLUSIONS

Findings contribute to the challenging field of disc degeneration and pain, and are important in light of the high clinical relevance of low back pain and the need for improved understanding of its fundamental basis.

A TNF variant that associates with susceptibility to musculoskeletal disease modulates thyroid hormone receptor binding to control promoter activation

Tumor necrosis factor (TNF) is a powerful pro-inflammatory cytokine and immuno-regulatory molecule, and modulates susceptibility to musculoskeletal diseases. Several meta-analyses and replicated association studies have implicated the minor 'A' variant within the TNF promoter single nucleotide polymorphism (SNP) rs361525 (-238A/G) as a risk allele in joint related disorders, including psoriatic and juvenile idiopathic arthritis, and osteolysis after joint arthroplasty. Here we characterized the effect of this variant on TNF promoter function. A transcriptional reporter, encoding the -238A variant of the TNF promoter, resulted in 2.2 to 2.8 times greater transcriptional activation versus the 'G' variant in murine macrophages when stimulated with pro-inflammatory stimuli. Bioinformatic analysis predicted a putative binding site for thyroid hormone receptor (TR) for the -238A but not the -238G allele. Overexpression of TR-α induced promoter expression 1.8-fold in the presence of the 'A' allele only. TR-α expression both potentiated and sensitized the -238A response to LPS or a titanium particulate stimulus, whilst siRNA knockdown of either THRA or THRB impaired transcriptional activation for the -238A variant only. This effect was independent of receptor-ligand binding of triiodothyronine. Immunohistochemical analysis of osteolysis interface membranes from patients undergoing revision surgery confirmed expression of TR-α within osteoclast nuclei at the resorption surface. The 'A' allele at rs361525 confers increased transcriptional activation of the TNF promoter and influences susceptibility to several arthritic conditions. This effect is modulated, at least in part, by binding of TR, which both sensitizes and potentiates transcriptional activation of the 'A' variant independent of its endogenous ligand.

Derived SNP alleles are used more frequently than ancestral alleles as risk-associated variants in common human diseases

Evolutionary aspects of the genetic architecture of common human diseases remain enigmatic. The results of more than 200 genome-wide association studies published to date were compiled in a catalog (). We used cataloged data to determine whether derived (mutant) alleles are associated with higher risk of human disease more frequently than ancestral alleles. We placed all allelic variants into ten categories of population frequency (0%-100%) in 10% increments. We then analyzed the relationship between allelic frequency, evolutionary status of the polymorphic site (ancestral versus derived), and disease risk status (risk versus protection). Given the same population frequency, derived alleles are more likely to be risk associated than ancestral alleles, as are rarer alleles. The common interpretation of this association is that negative selection prevents fixation of the risk variants. However, disease stratification as early or late onset suggests that weak selection against risk-associated alleles is unlikely a major factor shaping genetic architecture of common diseases. Our results clearly suggest that the duration of existence of an allele in a population is more important. Alleles existing longer tend to show weaker linkage disequilibrium with neighboring alleles, including the causal alleles, and are less likely to tag a SNP-disease association.

Long span DNA paired-end-tag (DNA-PET) sequencing strategy for the interrogation of genomic structural mutations and fusion-point-guided reconstruction of amplicons

Structural variations (SVs) contribute significantly to the variability of the human genome and extensive genomic rearrangements are a hallmark of cancer. While genomic DNA paired-end-tag (DNA-PET) sequencing is an attractive approach to identify genomic SVs, the current application of PET sequencing with short insert size DNA can be insufficient for the comprehensive mapping of SVs in low complexity and repeat-rich genomic regions. We employed a recently developed procedure to generate PET sequencing data using large DNA inserts of 10–20 kb and compared their characteristics with short insert (1 kb) libraries for their ability to identify SVs. Our results suggest that although short insert libraries bear an advantage in identifying small deletions, they do not provide significantly better breakpoint resolution. In contrast, large inserts are superior to short inserts in providing higher physical genome coverage for the same sequencing cost and achieve greater sensitivity, in practice, for the identification of several classes of SVs, such as copy number neutral and complex events. Furthermore, our results confirm that large insert libraries allow for the identification of SVs within repetitive sequences, which cannot be spanned by short inserts. This provides a key advantage in studying rearrangements in cancer, and we show how it can be used in a fusion-point-guided-concatenation algorithm to study focally amplified regions in cancer.

Single nucleotide polymorphism barcoding to evaluate oral cancer risk using odds ratio-based genetic algorithms

Cancers often involve the synergistic effects of gene-gene interactions, but identifying these interactions remains challenging. Here, we present an odds ratio-based genetic algorithm (OR-GA) that is able to solve the problems associated with the simultaneous analysis of multiple independent single nucleotide polymorphisms (SNPs) that are associated with oral cancer. The SNP interactions between four SNPs-namely rs1799782, rs2040639, rs861539, rs2075685, and belonging to four genes (XRCC1, XRCC2, XRCC3, and XRCC4)-were tested in this study, respectively. The GA decomposes the SNPs sets into different SNP combinations with their corresponding genotypes (called SNP barcodes). The GA can effectively identify a specific SNP barcode that has an optimized fitness value and uses this to calculate the difference between the case and control groups. The SNP barcodes with a low fitness value are naturally removed from the population. Using two to four SNPs, the best SNP barcodes with maximum differences in occurrence between the case and control groups were generated by GA algorithm. Subsequently, the OR provides a quantitative measure of the multiple SNP synergies between the oral cancer and control groups by calculating the risk related to the best SNP barcodes and others. When these were compared to their corresponding non-SNP barcodes, the estimated ORs for oral cancer were found to be great than 1 [approx. 1.72-2.23; confidence intervals (CIs): 0.94-5.30, p < 0.03-0.07] for various specific SNP barcodes with two to four SNPs. In conclusion, the proposed OR-GA method successfully generates SNP barcodes, which allow oral cancer risk to be evaluated and in the process the OR-GA method identifies possible SNP-SNP interactions.

Direct-to-Consumer Genetic Testing

Genetics has fascinated societies since ancient times, and references to traits or behaviors that appear to be shared or different among related individuals have permeated legends, literature, and popular culture. Biomedical advances from the past century, and particularly the discovery of the DNA double helix, the increasing numbers of links that were established between mutations and medical conditions or phenotypes, and technological advances that facilitated the sequencing of the human genome, catalyzed the development of genetic testing. Genetic tests were initially performed in health care facilities, interpreted by health care providers, and included the availability of counseling. Recent years have seen an increased availability of genetic tests that are offered by companies directly to consumers, a phenomenon that became known as direct-to-consumer genetic testing. Tests offered in this setting range from the ones that are also provided in health care establishments to tests known as ‘recreational genomics,’ and consumers directly receive the test results. In addition, testing in this context often does not involve the availability of counseling and, when this is provided, it frequently occurs on-line or over the phone. As a field situated at the interface between biotechnology, biomedical research, and social sciences, direct-to-consumer genetic testing opens multiple challenges that can be appropriately addressed only by developing a complex, inter-disciplinary framework.

ComB: SNP calling and mapping analysis for color and nucleotide space platforms

The determination of single nucleotide polymorphisms (SNPs) has become faster and more cost effective since the advent of short read data from next generation sequencing platforms such as Roche's 454 Sequencer, Illumina's Solexa platform, and Applied Biosystems SOLiD sequencer. The SOLiD sequencing platform, which is capable of producing more than 6 GB of sequence data in a single run, uses a unique encoding scheme where color reads represent transitions between adjacent nucleotides. The determination of SNPs from color reads usually involves the translation of color alignments to likely nucleotide strings to facilitate the use of tools designed for nucleotide reads. This technique results in the loss of significant information in the color read, producing many incorrect SNP calls, especially if regions exist with dense or adjacent polymorphism. Additionally, color reads align ambiguously and incorrectly more often than nucleotide reads making integrated SNP calling a difficult challenge. We have developed ComB, a SNP calling tool which operates directly in color space, using a Bayesian model to incorporate unique and ambiguous reads to iteratively determine SNP identity. ComB is capable of accurately calling short consecutive nucleotide polymorphisms and densely clustered SNPs; both of which other SNP calling tools fail to identify. ComB, which is capable of using billions of short reads to accurately and efficiently perform whole human genome SNP calling in parallel, is also capable of using sequence data or even integrating sequence and color space data sets. We use real and simulated data to demonstrate that ComB's iterative strategy and recalibration of quality scores allow it to discover more true SNPs while calling fewer false positives than tools which use only color alignments as well as tools which translate color reads to nucleotide strings.

Haplotypes covering the TNFSF10 gene are associated with bronchial asthma

Tumour necrosis factor-related apoptosis-inducing ligand (TRAIL) is elevated in the airways of subjects with asthma and has been linked to the development of allergic airway disease by promoting STAT6-dependent T helper 2 cell (T(H) 2) effector functions. To determine whether single nucleotide polymorphisms (SNPs) in the TNFSF10 gene are associated with bronchial asthma we genotyped 498 Caucasian subjects living in Southern Germany for eight SNPs in the TNFSF10 by restriction fragment length polymorphism analysis. In contrast to single SNPs, haplotypes constructed from eight SNPs were robustly associated with asthma (p=0.00012). A small haplotype approach returned four alleles consisting of two (rs3136586/ rs3136598), three (rs12488654/rs3136586/rs3136598 and rs3136586/rs3136598/rs3136604), and four SNPs (rs12488654/ rs3136586/ rs3136598/ rs3136604) that were highly associated with asthma (p=0.00005, p=0.00008, p=0.00017 and p=0.00038). Combinations of SNPs in the TNFSF10 allele were strongly associated with asthma supporting the concept that TRAIL is important in the development of hallmark features of this disease.