Genome-wide prediction of splice-modifying SNPs in human genes using a new analysis pipeline called AASsites

An elevated level of interleukin-17A in a Senegalese malaria cohort is associated with rs8193038 IL-17A genetic variant

Malaria infection is a multifactorial disease partly modulated by host immuno-genetic factors. Recent evidence has demonstrated the importance of Interleukin-17 family proinflammatory cytokines and their genetic variants in host immunity. However, limited knowledge exists about their role in parasitic infections such as malaria. We aimed to investigate IL-17A serum levels in patients with severe and uncomplicated malaria and gene polymorphism's influence on the IL-17A serum levels. In this research, 125 severe (SM) and uncomplicated (UM) malaria patients and 48 free malaria controls were enrolled. IL-17A serum levels were measured with ELISA. PCR and DNA sequencing were used to assess host genetic polymorphisms in IL-17A. We performed a multivariate regression to estimate the impact of human IL-17A variants on IL-17A serum levels and malaria outcomes. Elevated serum IL-17A levels accompanied by increased parasitemia were found in SM patients compared to UM and controls (P < 0.0001). Also, the IL-17A levels were lower in SM patients who were deceased than in those who survived. In addition, the minor allele frequencies (MAF) of two IL-17A polymorphisms (rs3819024 and rs3748067) were more prevalent in SM patients than UM patients, indicating an essential role in SM. Interestingly, the heterozygous rs8193038 AG genotype was significantly associated with higher levels of IL-17A than the homozygous wild type (AA). According to our results, it can be concluded that the IL-17A gene rs8193038 polymorphism significantly affects IL-17A gene expression. Our results fill a gap in the implication of IL-17A gene polymorphisms on the cytokine level in a malaria cohort. IL-17A gene polymorphisms also may influence cytokine production in response to Plasmodium infections and may contribute to the hyperinflammatory responses during severe malaria outcomes.

Predicting functional consequences of SNPs on mRNA translation via machine learning

The functional impact of single nucleotide polymorphisms (SNPs) on translation has yet to be considered when prioritizing disease-causing SNPs from genome-wide association studies (GWAS). Here we apply machine learning models to genome-wide ribosome profiling data to predict SNP function by forecasting ribosome collisions during mRNA translation. SNPs causing remarkable ribosome occupancy changes are named RibOc-SNPs (Ribosome-Occupancy-SNPs). We found that disease-related SNPs tend to cause notable changes in ribosome occupancy, suggesting translational regulation as an essential pathogenesis step. Nucleotide conversions, such as 'G → T', 'T → G' and 'C → A', are enriched in RibOc-SNPs, with the most significant impact on ribosome occupancy, while 'A → G' (or 'A→ I' RNA editing) and 'G → A' are less deterministic. Among amino acid conversions, 'Glu → stop (codon)' shows the most significant enrichment in RibOc-SNPs. Interestingly, there is selection pressure on stop codons with a lower collision likelihood. RibOc-SNPs are enriched at the 5'-coding sequence regions, implying hot spots of translation initiation regulation. Strikingly, ∼22.1% of the RibOc-SNPs lead to opposite changes in ribosome occupancy on alternative transcript isoforms, suggesting that SNPs can amplify the differences between splicing isoforms by oppositely regulating their translation efficiency.

Bioinformatic analysis of KIT juxtamembrane domain mutations in Syrian GIST patients: jigsaw puzzle completed

BACKGROUND

The huge number of detected somatic KIT mutations highlights the necessity of in silico analyses that are almost absent in the relevant medical literature. The aim of this study is to report the mutation spectrum analysis of exon 11 encoding the juxtamembrane (JM) domain of the KIT gene in a group of Syrian GIST patients.

METHODS

Forty-eight formalin-fixed paraffin-embedded GIST tissue samples, collected between 2006 and 2016, were retrieved from the pathological archives and analyzed for KIT exon 11 mutations by DNA sequencing. Structural/functional impact of detected variants was predicted using several bioinformatic tools.

RESULTS

Twenty-one different variants have been detected in intron 10, exon 11, and intron 11 of the KIT gene, eight of which were novel changes. Mutations in exon 11 of the KIT gene were detected in 28 of 48 (58.3%) GIST patients and predicted to be pathogenic and cancer promoting. Specifically, age above 60 was very significantly associated with the negative selection of deletion mutations (p = .007), a phenomenon that points to deletion severity.

CONCLUSIONS

Six bioinformatic tools have proved efficient in predicting the impact of detected KIT variations in view of published structural, experimental, and clinical findings.

Entailing the Next-Generation Sequencing and Metabolome for Sustainable Agriculture by Improving Plant Tolerance

Crop production is a serious challenge to provide food for the 10 billion individuals forecasted to live across the globe in 2050. The scientists' emphasize establishing an equilibrium among diversity and quality of crops by enhancing yield to fulfill the increasing demand for food supply sustainably. The exploitation of genetic resources using genomics and metabolomics strategies can help generate resilient plants against stressors in the future. The innovation of the next-generation sequencing (NGS) strategies laid the foundation to unveil various plants' genetic potential and help us to understand the domestication process to unmask the genetic potential among wild-type plants to utilize for crop improvement. Nowadays, NGS is generating massive genomic resources using wild-type and domesticated plants grown under normal and harsh environments to explore the stress regulatory factors and determine the key metabolites. Improved food nutritional value is also the key to eradicating malnutrition problems around the globe, which could be attained by employing the knowledge gained through NGS and metabolomics to achieve suitability in crop yield. Advanced technologies can further enhance our understanding in defining the strategy to obtain a specific phenotype of a crop. Integration among bioinformatic tools and molecular techniques, such as marker-assisted, QTLs mapping, creation of reference genome, de novo genome assembly, pan- and/or super-pan-genomes, etc., will boost breeding programs. The current article provides sequential progress in NGS technologies, a broad application of NGS, enhancement of genetic manipulation resources, and understanding the crop response to stress by producing plant metabolites. The NGS and metabolomics utilization in generating stress-tolerant plants/crops without deteriorating a natural ecosystem is considered a sustainable way to improve agriculture production. This highlighted knowledge also provides useful research that explores the suitable resources for agriculture sustainability.

What's Wrong in a Jump? Prediction and Validation of Splice Site Variants

Alternative splicing (AS) is a crucial process to enhance gene expression driving organism development. Interestingly, more than 95% of human genes undergo AS, producing multiple protein isoforms from the same transcript. Any alteration (e.g., nucleotide substitutions, insertions, and deletions) involving consensus splicing regulatory sequences in a specific gene may result in the production of aberrant and not properly working proteins. In this review, we introduce the key steps of splicing mechanism and describe all different types of genomic variants affecting this process (splicing variants in acceptor/donor sites or branch point or polypyrimidine tract, exonic, and deep intronic changes). Then, we provide an updated approach to improve splice variants detection. First, we review the main computational tools, including the recent Machine Learning-based algorithms, for the prediction of splice site variants, in order to characterize how a genomic variant interferes with splicing process. Next, we report the experimental methods to validate the predictive analyses are defined, distinguishing between methods testing RNA (transcriptomics analysis) or proteins (proteomics experiments). For both prediction and validation steps, benefits and weaknesses of each tool/procedure are accurately reported, as well as suggestions on which approaches are more suitable in diagnostic rather than in clinical research.

Resequencing CYP2D6 gene in Indian population: CYP2D6*41 identified as the major reduced function allele

Aim: The CYP2D6 gene is highly polymorphic and harbors population specific alleles that define its predominant metabolizer phenotype. This study aimed to identify polymorphisms in Indian population owing to scarcity of CYP2D6 data in this population. Materials & methods: The CYP2D6 gene was resequenced in 105 south Indians using next generation sequencing technology and haplotypes were reconstructed. Results & conclusion: Four novel missense variants have been designated as CYP2D6*110, *111, *112 and *113. The most common alleles were CYP2D6*1 (42%), *2 (32%), and *41 (12.3%) and diplotypes were CYP2D6*1/*2 (26%), *1/*1 (11%), *2/*41 (10%) and *1/*41 (7%) accounting for high incidence of extensive metabolizers in Indians.

Genetic regulation of antibody responsiveness to immunization in substrains of BALB/c mice

Antibody‐mediated immunity is highly protective against disease. The majority of current vaccines confer protection through humoral immunity, but there is high variability in responsiveness across populations. Identifying immune mechanisms that mediate low antibody responsiveness may provide potential strategies to boost vaccine efficacy. Here, we report diverse antibody responsiveness to unadjuvanted as well as adjuvanted immunization in substrains of BALB/c mice, resulting in high and low antibody response phenotypes. Furthermore, these antibody phenotypes were not affected by changes in environmental factors such as the gut microbiota composition. Antigen‐specific B cells following immunization had a marked difference in capability to class switch, resulting in perturbed IgG isotype antibody production. In vitro, a B‐cell intrinsic defect in the regulation of class‐switch recombination was identified in mice with low IgG antibody production. Whole genome sequencing identified polymorphisms associated with the magnitude of antibody produced, and we propose candidate genes that may regulate isotype class‐switching capability. This study highlights that mice sourced from different vendors can have significantly altered humoral immune response profiles, and provides a resource to interrogate genetic regulators of antibody responsiveness. Together these results further our understanding of immune heterogeneity and suggest additional research on the genetic influences of adjuvanted vaccine strategies is warranted for enhancing vaccine efficacy.

Architecture of polymorphisms in the human genome reveals functionally important and positively selected variants in immune response and drug transporter genes

Background

Genetic polymorphisms can contribute to phenotypic differences amongst individuals, including disease risk and drug response. Characterization of genetic polymorphisms that modulate gene expression and/or protein function may facilitate the identification of the causal variants. Here, we present the architecture of genetic polymorphisms in the human genome focusing on those predicted to be potentially functional/under natural selection and the pathways that they reside.

Results

In the human genome, polymorphisms that directly affect protein sequences and potentially affect function are the most constrained variants with the lowest single-nucleotide variant (SNV) density, least population differentiation and most significant enrichment of rare alleles. SNVs which potentially alter various regulatory sites, e.g. splicing regulatory elements, are also generally under negative selection.

Interestingly, genes that regulate the expression of transcription/splicing factors and histones are conserved as a higher proportion of these genes is non-polymorphic, contain ultra-conserved elements (UCEs) and/or has no non-synonymous SNVs (nsSNVs)/coding INDELs. On the other hand, major histocompatibility complex (MHC) genes are the most polymorphic with SNVs potentially affecting the binding of transcription/splicing factors and microRNAs (miRNA) exhibiting recent positive selection (RPS). The drug transporter genes carry the most number of potentially deleterious nsSNVs and exhibit signatures of RPS and/or population differentiation. These observations suggest that genes that interact with the environment are highly polymorphic and targeted by RPS.

Conclusions

In conclusion, selective constraints are observed in coding regions, master regulator genes, and potentially functional SNVs. In contrast, genes that modulate response to the environment are highly polymorphic and under positive selection.

Electronic supplementary material

The online version of this article (10.1186/s40246-018-0175-1) contains supplementary material, which is available to authorized users.

Genomic and Bioinformatics Approaches for Analysis of Genes Associated With Cancer Risks Following Exposure to Tobacco Smoking

Cancer is a significant health problem in the Middle East and global population. It is well established that there is a direct link between tobacco smoking and cancer, which will continue to pose a significant threat to human health. The impact of long-term exposure to tobacco smoke on the risk of cancer encouraged the study of biomarkers for vulnerable individuals to tobacco smoking, especially children, who are more susceptible than adults to the action of environmental carcinogens. The carcinogens in tobacco smoke condensate induce DNA damage and play a significant role in determining the health and well-being of smokers, non-smoker, and primarily children. Cancer is a result of genomic and epigenomic malfunctions that lead to an initial premalignant condition. Although premalignancy genetic cascade is a much-delayed process, it will end with adverse health consequences. In addition to the DNA damage and mutations, tobacco smoke can cause changes in the DNA methylation and gene expression associated with cancer. The genetic events hint on the possible use of genomic–epigenomic changes in genes related to cancer, in predicting cancer risks associated with exposure to tobacco smoking. Bioinformatics provides indispensable tools to identify the cascade of expressed genes in active smokers and non-smokers and could assist the development of a framework to manage this cascade of events linked with the evolvement of disease including cancer. The aim of this mini review is to cognize the essential genomic processes and health risks associated with tobacco smoking and the implications of bioinformatics in cancer prediction, prevention, and intervention.

Identification of functional single nucleotide polymorphisms in the branchpoint site

Background

The human genome contains millions of single nucleotide polymorphisms (SNPs); many of these SNPs are intronic and have unknown functional significance. SNPs occurring within intron branchpoint sites, especially at the adenine (A), would presumably affect splicing; however, this has not been systematically studied. We employed a splicing prediction tool to identify human intron branchpoint sites and screened dbSNP for identifying SNPs located in the predicted sites to generate a genome-wide branchpoint site SNP database.

Results

We identified 600 SNPs located within branchpoint sites; among which, 216 showed a change in A. After scoring the SNPs by counting the As in the ± 10 nucleotide region, only four SNPs were identified without additional As (rs13296170, rs12769205, rs75434223, and rs67785924). Using minigene constructs, we examined the effects of these SNPs on splicing. The three SNPs (rs13296170, rs12769205, and rs75434223) with nucleotide substitution at the A position resulted in abnormal splicing (exon skipping and/or intron inclusion). However, rs67785924, a 5-bp deletion that abolished the branchpoint A nucleotide, exhibited normal RNA splicing pattern, presumably using two of the downstream As as alternative branchpoints. The influence of additional As on splicing was further confirmed by studying rs2733532, which contains three additional As in the ± 10 nucleotide region.

Conclusions

We generated a high-confidence genome-wide branchpoint site SNP database, experimentally verified the importance of A in the branchpoint, and suggested that other nearby As can protect branchpoint A substitution from abnormal splicing.

Electronic supplementary material

The online version of this article (10.1186/s40246-017-0122-6) contains supplementary material, which is available to authorized users.

Alternative Splicing in Genetic Diseases: Improved Diagnosis and Novel Treatment Options

Alternative splicing is an important mechanism to regulate gene expression and to expand the repertoire of gene products in order to accommodate an increase in complexity of multicellular organisms. It needs to be precisely regulated, which is achieved via RNA structure, splicing factors, transcriptional regulation, and chromatin. Changes in any of these factors can lead to disease. These may include the core spliceosome, splicing enhancer/repressor sequences and their interacting proteins, the speed of transcription by RNA polymerase II, and histone modifications. While the basic principle of splicing is well understood, it is still very difficult to predict splicing outcome, due to the multiple levels of regulation. Current molecular diagnostics mainly uses Sanger sequencing of exons, or next-generation sequencing of gene panels or the whole exome. Functional analysis of potential splicing variants is scarce, and intronic variants are often not considered. This likely results in underestimation of the percentage of splicing variants. Understanding how sequence variants may affect splicing is not only crucial for confirmation of diagnosis and for genetic counseling, but also for the development of novel treatment options. These include small molecules, transsplicing, antisense oligonucleotides, and gene therapy. Here we review the current state of molecular mechanisms of splicing regulation and how deregulation can lead to human disease, diagnostics to detect splicing variants, and novel treatment options based on splicing correction.

ATM mutations and E-cadherin expression define sensitivity to EGFR-targeted therapy in colorectal cancer

EGFR-targeted therapy is a key treatment approach in patients with RAS wildtype metastatic colorectal cancers (CRC). Still, also RAS wildtype CRC may be resistant to EGFR-targeted therapy, with few predictive markers available for improved stratification of patients. Here, we investigated response of 7 CRC cell lines (Caco-2, DLD1, HCT116, HT29, LS174T, RKO, SW480) to Cetuximab and correlated this to NGS-based mutation profiles, EGFR promoter methylation and EGFR expression status as well as to E-cadherin expression. Moreover, tissue specimens of primary and/or recurrent tumors as well as liver and/or lung metastases of 25 CRC patients having received Cetuximab and/or Panitumumab were examined for the same molecular markers. In vitro and in situ analyses showed that EGFR promoter methylation and EGFR expression as well as the MSI and or CIMP-type status did not guide treatment responses. In fact, EGFR-targeted treatment responses were also observed in RAS exon 2 p.G13 mutated CRC cell lines or CRC cases and were further linked to PIK3CA exon 9 mutations. In contrast, non-response to EGFR-targeted treatment was associated with ATM mutations and low E-cadherin expression. Moreover, down-regulation of E-cadherin by siRNA in otherwise Cetuximab responding E-cadherin positive cells abrogated their response. Hence, we here identify ATM and E-cadherin expression as potential novel supportive predictive markers for EGFR-targeted therapy.

Angiopoietin receptor TEK mutations underlie primary congenital glaucoma with variable expressivity

Primary congenital glaucoma (PCG) is a devastating eye disease and an important cause of childhood blindness worldwide. In PCG, defects in the anterior chamber aqueous humor outflow structures of the eye result in elevated intraocular pressure (IOP); however, the genes and molecular mechanisms involved in the etiology of these defects have not been fully characterized. Previously, we observed PCG-like phenotypes in transgenic mice that lack functional angiopoietin-TEK signaling. Herein, we identified rare TEK variants in 10 of 189 unrelated PCG families and demonstrated that each mutation results in haploinsufficiency due to protein loss of function. Multiple cellular mechanisms were responsible for the loss of protein function resulting from individual TEK variants, including an absence of normal protein production, protein aggregate formation, enhanced proteasomal degradation, altered subcellular localization, and reduced responsiveness to ligand stimulation. Further, in mice, hemizygosity for Tek led to the formation of severely hypomorphic Schlemm's canal and trabecular meshwork, as well as elevated IOP, demonstrating that anterior chamber vascular development is sensitive to Tek gene dosage and the resulting decrease in angiopoietin-TEK signaling. Collectively, these results identify TEK mutations in patients with PCG that likely underlie disease and are transmitted in an autosomal dominant pattern with variable expressivity.

Experimental and Computational Considerations in the Study of RNA-Binding Protein-RNA Interactions

After an RNA is transcribed, it undergoes a variety of processing steps that can change the encoded protein sequence (through alternative splicing and RNA editing), regulate the stability of the RNA, and control subcellular localization, timing, and rate of translation. The recent explosion in genomics techniques has enabled transcriptome-wide profiling of RNA processing in an unbiased manner. However, it has also brought with it both experimental challenges in developing improved methods to probe distinct processing steps, as well as computational challenges in data storage, processing, and analysis tools to enable large-scale interpretation in the genomics era. In this chapter we review experimental techniques and challenges in profiling various aspects of RNA processing, as well as recent efforts to develop analyses integrating multiple data sources and techniques to infer RNA regulatory networks.

Multifaceted roles of 5'-regulatory region of the cancer associated gene B4GALT1 and its comparison with the gene family

β1,4-Galactosylransferases are a family of enzymes encoded by seven B4GALT genes and are involved in the development of anticancer drug resistance and metastasis. Among these genes, the B4GALT1 shows significant variations in the transcript origination sites in different cell types/tissues and encodes an interesting dually partitioning β-1, 4-galactosyltransferase protein. We identified at 5'-end of B4GALT1 a 1.454 kb sequence forming a transcription regulatory region, referred to by us as the TR1-PE1, had all characteristics of a bidirectional promoter directing the transcription of B4GALT1 in a divergent manner along with its long non-coding RNA (lncRNA) antisense counterpart B4GALT1-AS1. The TR1-PE1 showed unique dinucleotide base-stacking energy values specific to transcription factor binding sites (TFBSs), INR and BRE, and harbored CpG Island (CGI) that showed GC skew with potential for R-loop formation at the transcription starting sites (TSSs). The 5'-regulatory axis of B4GALT1 also included five more novel TFBSs for CTCF, GLI1, TCF7L2, GATA3 and SOX5, in addition to unique (TG)18 repeats in conjunction with 22 nucleotide TG-associated sequence (TGAS). The five lncRNA B4GALT1-AS1 transcripts showed significant complementarity with B4GALT1 mRNA. In contrast, the rest of B4GALT genes showed fewer lncRNAs, and all lacked the (TG)18 and TGAS. Our results are strongly supported by the FANTOM5 study which showed tissue-specific variations in transcript origination sites for this gene. We suggest that the unique expression patterns for the B4GALT1 in normal and malignant tissues are controlled by a differential usage of 5'-B4GALT1 regulatory units along with a post-transcriptional regulation by the antisense RNA, which in turn govern the cell-matrix interactions, neoplastic progression, anticancer drug sensitivity, and could be utilized in personalized therapy.

Alternative Splicing in Alzheimer's Disease

Neurodegenerative diseases have a variety of different genes contributing to their underlying pathology. Unfortunately, for many of these diseases it is not clear how changes in gene expression affect pathology. Transcriptome analysis of neurodegenerative diseases using ribonucleic acid sequencing (RNA Seq) and real time quantitative polymerase chain reaction (RT-qPCR) provides for a platform to allow investigators to determine the contribution of various genes to the disease phenotype. In Alzheimer's disease (AD) there are several candidate genes reported that may be associated with the underlying pathology and are, in addition, alternatively spliced. Thus, AD is an ideal disease to examine how alternative splicing may affect pathology. In this context, genes of particular interest to AD pathology include the amyloid precursor protein (APP), TAU, and apolipoprotein E (APOE). Here, we review the evidence of alternative splicing of these genes in normal and AD patients, and recent therapeutic approaches to control splicing.

TILLING mutants of durum wheat result in a high amylose phenotype and provide information on alternative splicing mechanisms

The amylose/amylopectin ratio has a major influence over the properties of starch and determines its optimal end use. Here, high amylose durum wheat has been bred by combining knock down alleles at the two homoelogous genes encoding starch branching enzyme IIa (SBEIIa-A and SBEIIa-B). The complete silencing of these genes had a number of pleiotropic effects on starch synthesis: it affected the transcriptional activity of SBEIIb, ISA1 (starch debranching enzyme) and all of the genes encoding starch synthases (SSI, SSIIa, SSIII and GBSSI). The starch produced by grain of the double SBEIIa mutants was high in amylose (up to ∼1.95 fold that of the wild type) and contained up to about eight fold more resistant starch. A single nucleotide polymorphism adjacent to the splice site at the end of exon 10 of the G364E mutant copies of both SBEIIa-A and SBEIIa-B resulted in the loss of a conserved exonic splicing silencer element. Its starch was similar to that of the SBEIIa double mutant. G364E SBEIIa pre-mRNA was incorrectly processed, resulting in the formation of alternative, but non-functional splicing products.

SNPlice: variants that modulate Intron retention from RNA-sequencing data

RATIONALE

The growing recognition of the importance of splicing, together with rapidly accumulating RNA-sequencing data, demand robust high-throughput approaches, which efficiently analyze experimentally derived whole-transcriptome splice profiles.

RESULTS

We have developed a computational approach, called SNPlice, for identifying cis-acting, splice-modulating variants from RNA-seq datasets. SNPlice mines RNA-seq datasets to find reads that span single-nucleotide variant (SNV) loci and nearby splice junctions, assessing the co-occurrence of variants and molecules that remain unspliced at nearby exon-intron boundaries. Hence, SNPlice highlights variants preferentially occurring on intron-containing molecules, possibly resulting from altered splicing. To illustrate co-occurrence of variant nucleotide and exon-intron boundary, allele-specific sequencing was used. SNPlice results are generally consistent with splice-prediction tools, but also indicate splice-modulating elements missed by other algorithms. SNPlice can be applied to identify variants that correlate with unexpected splicing events, and to measure the splice-modulating potential of canonical splice-site SNVs.

AVAILABILITY AND IMPLEMENTATION

SNPlice is freely available for download from https://code.google.com/p/snplice/ as a self-contained binary package for 64-bit Linux computers and as python source-code.

CONTACT

pmudvari@gwu.edu or horvatha@gwu.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

In silico tools for splicing defect prediction: a survey from the viewpoint of end users

RNA splicing is the process during which introns are excised and exons are spliced. The precise recognition of splicing signals is critical to this process and mutations affecting splicing comprise a considerable proportion of genetic disease etiology. Analysis of RNA samples from the patient is the most straightforward and reliable method to detect splicing defects. However, currently the technical limitation prohibits its use in routine clinical practice. In silico tools that predict potential consequences of splicing mutations may be useful in daily diagnostic activities. In this review, we provide medical geneticists with some basic insights into some of the most popular in silico tools for splicing defect prediction, from the viewpoint of end-users. Bioinformaticians in relevant areas who are working on huge datasets may also benefit from this review. Specifically, we focus on those tools whose primary goal is to predict the impact of mutations within the 5′ and 3′ splicing consensus regions: the algorithms used by different tools as well as their major advantages and disadvantages are briefly introduced; the formats of their input and output are summarized; and the interpretation, evaluation, and prospection are also discussed.

A genetic association study of NLRP2 and NLRP7 genes in idiopathic recurrent miscarriage

STUDY QUESTION

Do gene polymorphisms of two members of the human innate immune sensor nucleotide-binding oligomerization domain, leucine-rich repeat and pyrin domain-containing proteins (NLRP) family, NLRP2 and NLRP7, confer susceptibility to idiopathic recurrent miscarriage (RM)?

SUMMARY ANSWER

We found a significant association of a tag single-nucleotide polymorphism (SNP) of NLRP7 (rs26949) with idiopathic RM, while a tag SNP of NLRP2 (rs127868) showed a marginally significant association.

WHAT IS KNOWN ALREADY

Human NLRP2 and NLRP7 have been suggested to be maternal effect genes, regulating early embryonic development and establishment of maternal imprints. Anecdotal evidence showed women who had experienced at least three consecutive miscarriages without hydatidiform mole carried non-synonymous NLRP7 variants. Whether these two genes are associated with idiopathic RM remains obscure.

STUDY DESIGN, SIZE AND DURATION

In this case-controlled study, 143 women who had experienced at least two consecutive spontaneous miscarriages (n = 91 women with two miscarriages, n = 52 with three or more) and 149 controls were included between 2004 and 2010.

MATERIALS, SETTING, METHODS

A total of five tag SNPs of NLRP2 and eight tag SNPs of NLRP7 were genotyped using the primer extension analysis. The deviation from the Hardy-Weinberg equilibrium was checked using χ(2) analysis. The logistic odds ratios (ORs) of RM were estimated with a 95% confidence interval (CI) in multivariate analysis after maternal age adjustment. The false discovery rate (FDR) was used to adjust for multiple testing. Tests for haplotype association with RM were performed. Gene-gene interactions among loci of the two genes were evaluated by using the multifactor dimensionality reduction (MDR) method.

MAIN RESULTS AND THE ROLE OF CHANCE

One tag SNP rs269949 of NLRP7 showed significant difference between patients and controls in a recessive model (FDR P = 0.0456, age-adjusted OR (AOR) = 16.49, 95% CI = 2.00-136.11 for the GG genotype). The difference was significant in patients with two consecutive miscarriages and also in those with three or more consecutive miscarriages. Meanwhile, one tag SNP of NLRP2 (rs12768) showed marginal significance between patients and controls in a co-dominant model (FDR P = 0.0505, AOR = 2.15, 95% CI = 1.29-3.58 for the AC genotype). In the haplotype analysis, NLRP2 and NLRP7 did not show any significant difference between the patients and controls. MDR test revealed that there is no significant gene-gene interaction among loci of NLRP2 and NLRP7.

LIMITATIONS, REASONS FOR CAUTION

The results may be biased by heterogeneous ethnicities of the Taiwanese Han and a small sample size. The genetic loci responsible for the disease as well as their functional significance also await further investigation.

WIDER IMPLICATIONS OF THE FINDINGS

Our study suggests the role of the NLRP family proteins in RM.

STUDY FUNDING/COMPETING INTEREST(S)

This study was supported by grants from the National Science Council of the Republic of China (NSC-100-2314-B-006-011-MY3). None of the authors have any conflicts of interest.

The Association between Polymorphismsin Insulin and Obesity Related Genesand Risk of Colorectal Cancer

Colon cancer is the cancer of the large intestine (colon), which is located in the lower part of digestive system. Colon cancer is the third most common cancer in men and the second in women worldwide.Genetic background is thought to play a role in modulating individual risks of this cancer.Many studies support an association between insulin pathway gene polymorphisms and regulation of tumor cell biology in colorectal cancer. This review examines the role of polymorphisms of insulin and obesity pathway genes (IGFs, INS, INSR, ADIPOQ, ADIPOQR, LEP and LEPR) in development of colorectal cancer.

SNP Discovery through Next-Generation Sequencing and Its Applications

The decreasing cost along with rapid progress in next-generation sequencing and related bioinformatics computing resources has facilitated large-scale discovery of SNPs in various model and nonmodel plant species. Large numbers and genome-wide availability of SNPs make them the marker of choice in partially or completely sequenced genomes. Although excellent reviews have been published on next-generation sequencing, its associated bioinformatics challenges, and the applications of SNPs in genetic studies, a comprehensive review connecting these three intertwined research areas is needed. This paper touches upon various aspects of SNP discovery, highlighting key points in availability and selection of appropriate sequencing platforms, bioinformatics pipelines, SNP filtering criteria, and applications of SNPs in genetic analyses. The use of next-generation sequencing methodologies in many non-model crops leading to discovery and implementation of SNPs in various genetic studies is discussed. Development and improvement of bioinformatics software that are open source and freely available have accelerated the SNP discovery while reducing the associated cost. Key considerations for SNP filtering and associated pipelines are discussed in specific topics. A list of commonly used software and their sources is compiled for easy access and reference.