scholarly journals USE OF MOLECULAR GENETIC METHODS IN THE STUDY OF HEREDITARY PREDISPOSITION TO ATOPIC DISEASES INCHILDREN

2011 ◽  
Vol 8 (3) ◽  
pp. 48-55
Author(s):  
E S Tyumentseva ◽  
N V Petrova ◽  
I I Balabolkin ◽  
V G Pinelis ◽  
E S Tumentseva ◽  
...  
Keyword(s):  
Reduction Method ◽  
Molecular Genetic ◽  
Gene Interaction ◽  
Atopic Disease ◽  
Gene Interactions ◽  
Atopic Diseases ◽  
European Part Of Russia ◽  
Polymorphic Variants ◽  
Significant Model ◽  
Dimentionality Reduction

Background. Study of the аssociations of susceptibility genes to the development of atopic diseases in children. Materials and methods. All 325 examined children reside on the territory of the European part of Russia who by according to surveys, Russian by nationality. Analysis of polymorphism in genes of receptors ADRB2, GRL, ALOX5, genes of biotransformation - CYP1A1, CYP2C9, CYP2C19, GSTT1, GSTM1, NAT2 as well as the variants of the genes MTHFR and TNFA was performed in patients suffering from atopic disease and in healthy individuals. Using Multifactor Dimentionality Reduction method (MDR) it was defined the most significant model of genegene interaction for the development of atopic disease Results. Association of the development of atopic diseases with polymorphic variants of the genes: ALOX5 (VNTR) GRL (1220A > G) TNFA (-308G > A) CYP1A1 (6235T > C) and GSTM1 was identified in surveyed children. The highrisk alleles and genotypes of developing atopic diseases in pediatric patients were determined. Using Multifactor Dimentionality Reduction method (MDR) it was defined the most significant model of gene-gene interaction for the development of atopic disease, including ADRB2 (79 C >G), (46A > G), CYP2C19 (G681A) was defined. Conclusion. There were identified polymorphic variants of genes and important gene-gene interactions associated with development of atopic diseases in children.

scholarly journals Analysis of the mutational spectrum of the SLC26A4 gene and its contribution to the etiology of inherited hearing loss in the indigenous population of Southern Siberia

2020 ◽  
pp. 43-45
Author(s):  
В.Ю. Данильченко ◽  
М.В. Зыцарь ◽  
Е.А. Маслова ◽  
М.С. Бады-Хоо ◽  
И.В. Морозов ◽  
...  
Keyword(s):  
Hearing Loss ◽  
Molecular Genetic ◽  
Molecular Genetic Analysis ◽  
Unknown Etiology ◽  
Southern Siberia ◽  
Pathogenic Variants ◽  
Slc26a4 Gene ◽  
Wide Range ◽  
Polymorphic Variants ◽  
Tyva Republic

Мутации в гене SLC26A4 являются частой причиной потери слуха во многих регионах мира. В работе приводятся результаты молекулярно-генетического анализа (с использованием секвенирования по Сэнгеру) последовательности гена SLC26A4, впервые проведенного в выборке пациентов с потерей слуха неустановленной этиологии (n=232) из Республик Тыва и Алтай. Установлены контрастные различия патогенетического вклада мутаций в гене SLC26A4 в этиологию нарушения слуха у коренных жителей этих географически близких регионов: 28,2% - для тувинцев и 4,3% - для алтайцев. Выявлены как уже известные, так и новые патогенные варианты, а также широкий спектр полиморфных вариантов гена SLC26A4. Mutations in the SLC26A4 gene are a common cause of hearing loss in many regions of the world. This paper presents the results of molecular genetic analysis (by Sanger sequencing) of the SLC26A4 sequence, first performed in the sample of patients with hearing loss of unknown etiology (n=232) from the Tyva Republic and the Altai Republic. Contrast differences of the pathogenic contribution of SLC26A4 mutations to the etiology of hearing impairment were revealed in the indigenous peoples of these geographically close regions: 28.2% for Tuvinians and 4.3% for Altaians. Both known and novel pathogenic variants as well as a wide range of polymorphic variants were found in the SLC26A4 gene sequence.

scholarly journals Role of toll-like receptors in complications of cardiac surgery for congenital heart defects in children

2021 ◽  
Vol 25 (3) ◽  
pp. 34
Author(s):  
A. V. Tsepokina ◽  
A. A. Anikeenko ◽  
S. A. Shmulevich ◽  
A. V. Ponasenko ◽  
A. V. Shabaldin
Keyword(s):  
Cardiac Surgery ◽  
Postoperative Complications ◽  
Congenital Heart Defects ◽  
Congenital Heart ◽  
Heart Defects ◽  
Gene Interaction ◽  
Infectious Complications ◽  
Toll Like Receptors ◽  
Cytokines And Chemokines ◽  
Polymorphic Variants

<p><strong>Background.</strong> Cardiac surgery in combination with hypothermia, ischaemia and reperfusion leads to an inflammatory response causing postoperative complications. Toll-like receptors are signalling molecules through which some functions of innate immunity can be activated, and polymorphic variants in the TLR-family genes can be predictors of complications after cardiac surgery.<br /><strong>Aim.</strong> To study the associations of TLR-family genes with infectious and non-infectious complications of cardiac surgery for congenital heart defects.<br /><strong>Methods.</strong> The study included 89 children (44 girls and 45 boys) with congenital heart defects who underwent cardiac surgery. Complications occurred in 47 children 47 days after cardiac surgery. There were no complications in 42 children. Genotyping was performed by real-time PCR using TaqMan probes.<br /><strong>Results.</strong> A two-locus model of gene-gene interaction between <em>TLR1</em> rs5743551 and <em>TLR2</em> rs3804099 was the best fit, accounting for 4.01% of phenotypic entropy. The <em>TLR2</em> gene polymorphic variant rs5743708 had the highest predictive potential (2.59%).<br /><strong>Conclusion.</strong> The development of postoperative complications of cardiac surgical treatment for congenital heart defects can be due to the synergistic effect of the polymorphic variants rs5743551 in the <em>TLR1</em> gene and rs3804099 in the <em>TLR2</em> gene. This effect occurs through the features of <em>TLR1</em> and <em>TLR2</em> transcription, the subsequent expression of receptors on cells and signalling which activates the synthesis of proinflammatory cytokines and chemokines.</p><p>Received 25 February 2021. Revised 11 May 2021. Accepted 12 May 2021.</p><p><strong>Funding:</strong> The work is supported by the complex program of fundamental research of the Siberian Branch of the Russian Academy of Sciences (No. 0554-2019-0002).</p><p><strong>Conflict of interest:</strong> The authors declare no conflicts of interests.</p><p><strong>Contribution of the authors</strong><br />Conception and study design: A.V. Shabaldin, A.V. Ponasenko, A.V. Tsepokina<br />Data collection and analysis: A.A. Anikeenko, A.V. Tsepokina, S.A. Shmulevich<br />Statistical analysis: A.V. Shabaldin, A.V. Tsepokina<br />Drafting the article: A.V. Shabaldin, A.V. Tsepokina, A.V. Ponasenko<br />Critical revision of the article: A.V. Tsepokina<br />Final approval of the version to be published: A.V. Tsepokina, A.A. Anikeenko, S.A. Shmulevich, A.V. Ponasenko, A.V. Shabaldin</p>

Genetic, morphometric, and molecular analyses of interspecies differences in head shape and hybrid developmental defects in the wasp genus Nasonia

2019 ◽  
Author(s):  
Lorna B Cohen ◽  
Rachel Edwards ◽  
Dyese Moody ◽  
Deanna Arsala ◽  
Jack H Werren ◽  
...  
Keyword(s):  
Parasitoid Wasp ◽  
Gene Interaction ◽  
Distinct Species ◽  
Diploid Male ◽  
Gene Interactions ◽  
Morphological Development ◽  
Head Shape ◽  
Developmental Defects ◽  
Primary Driver ◽  
Species Specific

AbstractMales in the parasitoid wasp genus Nasonia (N. vitripennis, N. giraulti, N. longicornis) have distinct, species specific, head shapes. Fertile hybrids among the species are readily produced in the lab allowing genetic analysis of the evolved differences. In addition, the obligate haploidy of males makes these wasps a uniquely powerful model for analyzing the role of complex gene interactions in development and evolution. Previous analyses have shown that complex gene interactions underpin different aspects of the shape differences, and developmental incompatibilities that are specific to the head in F2 haploid hybrid males are also governed by networks of gene interaction. Here we use the genetic tools available in Nasonia to extend our understanding of the gene interactions that affect development and morphogenesis in male heads. Using artificial diploid male hybrids, we show that alleles affecting head shape are codominant, leading to uniform, averaged hybrid F1 diploid male heads, while the alleles mediating developmental defects are recessive, and are not visible in the diploid hybrids. We also determine that divergence in time, rather than in morphological disparity is the primary driver of hybrid developmental defects. In addition, we show that doublesex is necessary for the male head shape differences, but is not the only important factor. Finally we demonstrate that we can dissect complex interspecies gene interaction networks using introgression in this system. These advances represent significant progress in the complex web of gene interactions that govern morphological development, and chart the connections between genomic and phenotypic variation.

scholarly journals CGINet: graph convolutional network-based model for identifying chemical-gene interaction in an integrated multi-relational graph

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Wei Wang ◽  
Xi Yang ◽  
Chengkun Wu ◽  
Canqun Yang
Keyword(s):  
Biological Network ◽  
Gene Interaction ◽  
Gene Interactions ◽  
Target Node ◽  
Convolutional Network ◽  
Initial Node ◽  
Interactive Relation ◽  
Drug Leads ◽  
Node Embeddings ◽  
Novel Therapeutic

Abstract Background Elucidation of interactive relation between chemicals and genes is of key relevance not only for discovering new drug leads in drug development but also for repositioning existing drugs to novel therapeutic targets. Recently, biological network-based approaches have been proven to be effective in predicting chemical-gene interactions. Results We present CGINet, a graph convolutional network-based method for identifying chemical-gene interactions in an integrated multi-relational graph containing three types of nodes: chemicals, genes, and pathways. We investigate two different perspectives on learning node embeddings. One is to view the graph as a whole, and the other is to adopt a subgraph view that initial node embeddings are learned from the binary association subgraphs and then transferred to the multi-interaction subgraph for more focused learning of higher-level target node representations. Besides, we reconstruct the topological structures of target nodes with the latent links captured by the designed substructures. CGINet adopts an end-to-end way that the encoder and the decoder are trained jointly with known chemical-gene interactions. We aim to predict unknown but potential associations between chemicals and genes as well as their interaction types. Conclusions We study three model implementations CGINet-1/2/3 with various components and compare them with baseline approaches. As the experimental results suggest, our models exhibit competitive performances on identifying chemical-gene interactions. Besides, the subgraph perspective and the latent link both play positive roles in learning much more informative node embeddings and can lead to improved prediction.

scholarly journals An Exploration of Gene-Gene Interactions and Their Effects on Hypertension

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Ying Meng ◽  
Susan Groth ◽  
Jill R. Quinn ◽  
John Bisognano ◽  
Tong Tong Wu
Keyword(s):  
Interaction Analysis ◽  
Association Studies ◽  
Independent Set ◽  
Gene Interaction ◽  
Single Locus ◽  
Gene Interactions ◽  
Genome Wide Association Studies ◽  
Original Cohort ◽  
Genome Wide ◽  
Heart Study

Hypertension tends to perpetuate in families and the heritability of hypertension is estimated to be around 20–60%. So far, the main proportion of this heritability has not been found by single-locus genome-wide association studies. Therefore, the current study explored gene-gene interactions that have the potential to partially fill in the missing heritability. A two-stage discovery-confirmatory analysis was carried out in the Framingham Heart Study cohorts. The first stage was an exhaustive pairwise search performed in 2320 early-onset hypertensive cases with matched normotensive controls from the offspring cohort. Then, identified gene-gene interactions were assessed in an independent set of 694 subjects from the original cohort. Four unique gene-gene interactions were found to be related to hypertension. Three detected genes were recognized by previous studies, and the other 5 loci/genes (MAN1A1, LMO3, NPAP1/SNRPN, DNAL4, and RNA5SP455/KRT8P5) were novel findings, which had no strong main effect on hypertension and could not be easily identified by single-locus genome-wide studies. Also, by including the identified gene-gene interactions, more variance was explained in hypertension. Overall, our study provides evidence that the genome-wide gene-gene interaction analysis has the possibility to identify new susceptibility genes, which can provide more insights into the genetic background of blood pressure regulation.

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