Search results for: genomic imprinting gene

Authors: Abu Salim Mustafa

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The comparisons of mycobacterial genomes have identified several Mycobacterium tuberculosis-specific genomic regions that are absent in other mycobacteria and are known as regions of differences. Due to M. tuberculosis-specificity, the peptides encoded by these regions could be useful in the specific diagnosis of tuberculosis. To explore this possibility, overlapping synthetic peptides corresponding to 39 proteins predicted to be encoded by genes present in regions of differences were tested for antibody-reactivity with sera from tuberculosis patients and healthy subjects. The results identified four immunodominant peptides corresponding to four different proteins, with three of the peptides showing significantly stronger antibody reactivity and rate of positivity with sera from tuberculosis patients than healthy subjects. The fourth peptide was recognized equally well by the sera of tuberculosis patients as well as healthy subjects. Predication of antibody epitopes by bioinformatics analyses using ABCpred server predicted multiple linear epitopes in each peptide. Furthermore, peptide sequence analysis for sequence identity using BLAST suggested M. tuberculosis-specificity for the three peptides that had preferential reactivity with sera from tuberculosis patients, but the peptide with equal reactivity with sera of TB patients and healthy subjects showed significant identity with sequences present in nob-tuberculous mycobacteria. The three identified M. tuberculosis-specific immunodominant peptides may be useful in the serological diagnosis of tuberculosis.

Keywords: genomic regions of differences, Mycobacterium tuberculossis, peptides, serodiagnosis

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Authors: Scott A. Ochsner, Christopher M. Watkins, Apollo McOwiti, David L. Steffen Lauren B. Becnel, Neil J. McKenna

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Understanding signaling by nuclear receptors (NRs) requires an appreciation of their cognate ligand- and tissue-specific transcriptomes. While target gene regulation data are abundant in this field, they reside in hundreds of discrete publications in formats refractory to routine query and analysis and, accordingly, their full value to the NR signaling community has not been realized. One of the mandates of the Nuclear Receptor Signaling Atlas (NURSA) is to facilitate access of the community to existing public datasets. Pursuant to this mandate we are developing a freely-accessible community web resource, Transcriptomine, to bring together the sum total of available expression array and RNA-Seq data points generated by the field in a single location. Transcriptomine currently contains over 25,000,000 gene fold change datapoints from over 1200 contrasts relevant to over 100 NRs, ligands and coregulators in over 200 tissues and cell lines. Transcriptomine is designed to accommodate a spectrum of end users ranging from the bench researcher to those with advanced bioinformatic training. Visualization tools allow users to build custom charts to compare and contrast patterns of gene regulation across different tissues and in response to different ligands. Our resource affords an entirely new paradigm for leveraging gene expression data in the NR signaling field, empowering users to query gene fold changes across diverse regulatory molecules, tissues and cell lines, target genes, biological functions and disease associations, and that would otherwise be prohibitive in terms of time and effort. Transcriptomine will be regularly updated with gene lists from future genome-wide expression array and expression-sequencing datasets in the NR signaling field.

Keywords: target gene database, informatics, gene expression, transcriptomics

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Authors: Leo Nnamdi Ozurumba-Dwight

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Single-cell genomic analytical systems have proved to be a platform to isolate bulk cells into selected single cells for genomic, proteomic, and related metabolomic studies. This is enabling systematic investigations of the level of heterogeneity in a diverse and wide pool of cell populations. Single cell technologies, embracing techniques such as high parameter flow cytometry, single-cell sequencing, and high-resolution images are playing vital roles in these investigations on messenger ribonucleic acid (mRNA) molecules and related gene expressions in tracking the nature and course of disease conditions. This entails targeted molecular investigations on unit cells that help us understand cell behavoiur and expressions, which can be examined for their health implications on the health state of patients. One of the vital good sides of single-cell RNA sequencing (scRNA seq) is its probing capacity to detect deranged or abnormal cell populations present within homogenously perceived pooled cells, which would have evaded cursory screening on the pooled cell populations of biological samples obtained as part of diagnostic procedures. Despite conduction of just single-cell transcriptome analysis, scRNAseq now permits comparison of the transcriptome of the individual cells, which can be evaluated for gene expressional patterns that depict areas of heterogeneity with pharmaceutical drug discovery and clinical treatment applications. It is vital to strictly work through the tools of investigations from wet lab to bioinformatics and computational tooled analyses. In the precise steps for scRNAseq, it is critical to do thorough and effective isolation of viable single cells from the tissues of interest using dependable techniques (such as FACS) before proceeding to lysis, as this enhances the appropriate picking of quality mRNA molecules for subsequent sequencing (such as by the use of Polymerase Chain Reaction machine). Interestingly, scRNAseq can be deployed to analyze various types of biological samples such as embryos, nervous systems, tumour cells, stem cells, lymphocytes, and haematopoietic cells. In haematopoietic cells, it can be used to stratify acute myeloid leukemia patterns in patients, sorting them out into cohorts that enable re-modeling of treatment regimens based on stratified presentations. In immunotherapy, it can furnish specialist clinician-immunologist with tools to re-model treatment for each patient, an attribute of precision medicine. Finally, the good predictive attribute of scRNAseq can help reduce the cost of treatment for patients, thus attracting more patients who would have otherwise been discouraged from seeking quality clinical consultation help due to perceived high cost. This is a positive paradigm shift for patients’ attitudes primed towards seeking treatment.

Keywords: immunotherapy, transcriptome, re-modeling, mRNA, scRNA-seq

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Authors: James Jr. Mashiyane, Risuna Nkolele, Stephanie J. Müller, Gciniwe S. Dlamini, Rebone L. Meraba, Darlington S. Mapiye

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When performing language tasks in natural language processing (NLP), the dimensionality of word embeddings is chosen either ad-hoc or is calculated by optimizing the Pairwise Inner Product (PIP) loss. The PIP loss is a metric that measures the dissimilarity between word embeddings, and it is obtained through matrix perturbation theory by utilizing the unitary invariance of word embeddings. Unlike in natural language, in genomics, especially in genome sequence processing, unlike in natural language processing, there is no notion of a “word,” but rather, there are sequence substrings of length k called k-mers. K-mers sizes matter, and they vary depending on the goal of the task at hand. The dimensionality of word embeddings in NLP has been studied using the matrix perturbation theory and the PIP loss. In this paper, the sufficiency and reliability of applying word-embedding algorithms to various genomic sequence datasets are investigated to understand the relationship between the k-mer size and their embedding dimension. This is completed by studying the scaling capability of three embedding algorithms, namely Latent Semantic analysis (LSA), Word2Vec, and Global Vectors (GloVe), with respect to the k-mer size. Utilising the PIP loss as a metric to train embeddings on different datasets, we also show that Word2Vec outperforms LSA and GloVe in accurate computing embeddings as both the k-mer size and vocabulary increase. Finally, the shortcomings of natural language processing embedding algorithms in performing genomic tasks are discussed.

Keywords: word embeddings, k-mer embedding, dimensionality reduction

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Authors: Feng Zhang

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Kashin-Beck disease (KBD) is a chronic osteochondropathy. The mechanism of hand growth and development failure of KBD remains elusive now. In this study, we conducted a two-stage genome-wide association study (GWAS) of palmar length-width ratio (LWR) of KBD, totally involving 493 Chinese Han KBD patients. Affymetrix Genome Wide Human SNP Array 6.0 was applied for SNP genotyping. Association analysis was conducted by PLINK software. Imputation analysis was performed by IMPUTE against the reference panel of the 1000 genome project. In the GWAS, the most significant association was observed between palmar LWR and rs2071358 of COL2A1 gene (P value = 4.68×10-8). Imputation analysis identified 3 SNPs surrounding rs2071358 with significant or suggestive association signals. Replication study observed additional significant association signals at both rs2071358 (P value = 0.017) and rs4760608 (P value = 0.002) of COL2A1 gene after Bonferroni correction. Our results suggest that COL2A1 gene was a novel susceptibility gene involved in the growth and development failure of hand of KBD.

Keywords: Kashin-Beck disease, genome-wide association study, COL2A1, hand

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Authors: Fei Xu, Guofan Zhang, Xiao Liu

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Many major marine invertebrate phyla are characterized by indirect development. These animals transit from planktonic larvae to benthic adults via settlement and metamorphosis, which has many advantages for organisms to adapt marine environment. Studying the biological process of metamorphosis is thus a key to understand the origin and evolution of indirect development. Although the mechanism of metamorphosis has been largely studied on their relationships with the marine environment, microorganisms, as well as the neurohormones, little is known on the gene regulation network (GRN) during metamorphosis. We treated competent oyster pediveligers with epinephrine, which was known to be able to effectively induce oyster metamorphosis, and analyzed the dynamics of gene and proteins with transcriptomics and proteomics methods. The result indicated significant upregulation of protein synthesis system, as well as some transcription factors including Homeobox, basic helix-loop-helix, and nuclear receptors. The result suggested the GRN complexity of the transition stage during oyster metamorphosis.

Keywords: indirect development, gene regulation network, protein synthesis, transcription factors

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Authors: Han-Qin Zheng, Yi-Fan Chiang-Hsieh, Chia-Hung Chien, Wen-Chi Chang

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As the most important non-vascular plants, algae have many research applications, including high species diversity, biofuel sources, adsorption of heavy metals and, following processing, health supplements. With the increasing availability of next-generation sequencing (NGS) data for algae genomes and transcriptomes, an integrated resource for retrieving gene expression data and metabolic pathway is essential for functional analysis and systems biology in algae. However, gene expression profiles and biological pathways are displayed separately in current resources, and making it impossible to search current databases directly to identify the cellular response mechanisms. Therefore, this work develops a novel AlgaePath database to retrieve gene expression profiles efficiently under various conditions in numerous metabolic pathways. AlgaePath, a web-based database, integrates gene information, biological pathways, and next-generation sequencing (NGS) datasets in Chlamydomonasreinhardtii and Neodesmus sp. UTEX 2219-4. Users can identify gene expression profiles and pathway information by using five query pages (i.e. Gene Search, Pathway Search, Differentially Expressed Genes (DEGs) Search, Gene Group Analysis, and Co-Expression Analysis). The gene expression data of 45 and 4 samples can be obtained directly on pathway maps in C. reinhardtii and Neodesmus sp. UTEX 2219-4, respectively. Genes that are differentially expressed between two conditions can be identified in Folds Search. Furthermore, the Gene Group Analysis of AlgaePath includes pathway enrichment analysis, and can easily compare the gene expression profiles of functionally related genes in a map. Finally, Co-Expression Analysis provides co-expressed transcripts of a target gene. The analysis results provide a valuable reference for designing further experiments and elucidating critical mechanisms from high-throughput data. More than an effective interface to clarify the transcript response mechanisms in different metabolic pathways under various conditions, AlgaePath is also a data mining system to identify critical mechanisms based on high-throughput sequencing.

Keywords: next-generation sequencing (NGS), algae, transcriptome, metabolic pathway, co-expression

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Authors: Anida Causevic-Ramosevac, Sabina Semiz

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The aim of this study was to investigate the association of four single nucleotide polymorphisms (SNPs) - rs673548, rs693 in ApoB gene, rs1800775 in CETP gene and rs4846914 in GALNT2 gene with parameters of type 2 diabetes (T2D) and diabetic dyslipidemia in the population of Bosnia and Herzegovina (BH). Materials and methods: Our study involved 352 patients with T2D and 156 healthy subjects. Biochemical and anthropometric parameters were measured in all participants. DNA was extracted from the peripheral blood for the purpose of genetic testing. Polymorphisms in ApoB (rs673548, rs693), CETP (rs1800775) and GALNT2 (rs4846914) genes were analyzed by using Sequenom IPLEX platform. Results: Our results demonstrated significant associations for rs180075 polymorphism in CETP gene with levels of fasting insulin (p = 0.020; p = 0.027; p = 0.044), triglycerides (p = 0.046) and ALT (p = 0.031) activity in control group. In group of diabetic patients, results showed a significant association of rs673548 in ApoB gene with levels of fasting insulin (p = 0.008), HOMA-IR (p = 0.013), VLDL-C (p = 0.037) and CRP (p = 0.029) and rs693 in ApoB gene with BMI (p = 0.025), systolic blood pressure (p = 0.027), fasting insulin (p = 0.037) and HOMA-IR (p = 0.023) levels. Significant associations were also observed for rs1800775 in CETP gene with triglyceride (p = 0.023) levels and rs4846914 in GALNT2 gene with HbA1C (p = 0.013) and triglyceride (p = 0.043) levels. Conclusion: In conclusion, this is the first study that examined the impact of variations of candidate genes on a wide range of metabolic parameters in BH population. Our results suggest an association of variations of ApoB, CETP and GALNT2 genes with specific markers of T2D and dyslipidemia. Further studies would be needed in order to confirm these genetic effects in other ethnic groups as well.

Keywords: ApoB, CETP, dyslipidemia, GALNT2, type 2 diabetes

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Authors: Anjan Hazra, Nirjhar Dasgupta, Chandan Sengupta, Sauren Das

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Tea (Camellia sinensis) has received substantial attention from the scientific world time to time, not only for its commercial importance, but also for its demand to the health-conscious people across the world for its extensive use as potential sources of antioxidant supplement. These health-benefit traits primarily rely on some regulatory networks of different metabolic pathways. Development of microsatellite markers from the conserved genomic regions is being worthwhile for studying the genetic diversity of closely related species or self-pollinated species. Although several SSR markers have been reported, in tea the trait-specific Simple Sequence Repeats (SSRs) are yet to be identified, which can be used for marker assisted breeding technique. MicroRNAs are endogenous, noncoding, short RNAs directly involved in regulating gene expressions at the post-transcriptional level. It has been found that diversity in miRNA gene interferes the formation of its characteristic hair pin structure and the subsequent function. In the present study, the precursors of small regulatory RNAs (microRNAs) has been fished out from tea Expressed Sequence Tag (EST) database. Furthermore, the simple sequence repeat motifs within the putative miRNA precursor genes are also identified in order to experimentally validate their existence and function. It is already known that genic-SSR markers are very adept and breeder-friendly source for genetic diversity analysis. So, the potential outcome of this in-silico study would provide some novel clues in understanding the miRNA-triggered polymorphic genic expression controlling specific metabolic pathways, accountable for tea quality.

Keywords: micro RNA, simple sequence repeats, tea quality, trait specific marker

Procedia PDF Downloads 281

Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

Abstract:

Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Marija Ratkova Manovska, Mirko Prodanov, Dean Jankuloski, Katerina Blagoevska

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Staphylococci, which are widely found in the environment, animals, humans, and food products, include Staphylococcus aureus (S. aureus), the most significant pathogenic species in this genus. The virulence and toxicity of S. aureus are primarily attributed to the presence of specific genes responsible for producing toxins, biofilms, invasive components, and antibiotic resistance. Staphylococcal food poisoning, caused by the production of staphylococcal enterotoxins (SEs) by these strains in food, is a common occurrence. Globally, S. aureus food intoxications are typically ranked as the third or fourth most prevalent foodborne intoxications. For this study, a total of 333 milk samples and 1160 dairy product samples were analyzed between 2016 and 2020. The strains were isolated and confirmed using the ISO 6888-1:1999 "Horizontal method for enumeration of coagulase-positive staphylococci." Molecular analysis of the isolates, conducted using conventional PCR, involved detecting the 23s gene of S. aureus, the nuc gene, the mecA gene, and 11 genes responsible for producing enterotoxins (sea, seb, sec, sed, see, seg, seh, sei, ser, sej, and sep). The 23s gene was found in 93 (75.6%) out of 123 isolates of Staphylococcus spp. obtained from milk. Among the 76 isolates from dairy products, either S. aureus or the 23s gene was detected in 49 (64.5%) of them. The mecA gene was identified in three isolates from raw milk and five isolates from cheese samples. The nuc gene was present in 98.9% of S. aureus strains from milk and 97.9% from dairy products. Other Staphylococcus strains carried the nuc gene in 26.7% of milk strains and 14.8% of dairy product strains. Genes associated with SEs production were detected in 85 (69.1%) strains from milk and 38 (50%) strains from dairy products. In this study, 10 out of the 11 SEs genes were found, with no isolates carrying the see gene. The most prevalent genes detected were seg and sei, with some isolates containing up to five different SEs genes. These findings indicate the presence of enterotoxigenic staphylococci strains in the tested samples, emphasizing the importance of implementing proper sanitation and hygienic practices, utilizing safe raw materials, and ensuring adequate handling of finished products. Continued monitoring for the presence of SEs is necessary to ensure food safety and prevent intoxication.

Keywords: dairy products, milk, Staphylococci, enterotoxins, SE genes

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Authors: Sarah Almuhayya, Andrew Mcbain, Gavin Humphreys

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Background. The microbiome of the upper respiratory tract (URT) has received less research attention than other body sites. This study aims to investigate the microbial ecology of the human URT with a focus on the antagonism between the corynebacteria and staphylococci. Methods. Mucosal swabs were collected from the anterior nares and nasal turbinates of 20 healthy adult subjects. Genomic DNA amplification targeting the (V4) of the 16Sr RNA gene was conducted and analyzed using QIIME. Nasal swab isolates were cultured and identified using near full-length sequencing of the 16S rRNA gene. Isolates identified as corynebacteria or staphylococci were typed using (rep-PCR). Antagonism was determined using an agar-based inhibition assay. Results. Four major bacterial phyla (Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria) were identified from all volunteers. The typing of cultured staphylococci and corynebacteria suggested that intra-individual strain diversity was limited. Analysis of generated nasal microbiota profiles suggested an inverse correlation in terms of relative abundance between staphylococci and corynebacteria. Despite the apparent antagonism between these genera, it was limited when investigated on agar. Of 1000 pairwise interactions, observable zones of inhibition were only reported between a single strain of C.pseudodiphtheriticum and S.aureus. Imaging under EM revealed this effect to be bactericidal with clear lytic effects on staphylococcal cell morphology. Conclusion. Nasal microbiota is complex, but culturable staphylococci and corynebacteria were limited in terms of clone type. Analysis of generated nasal microbiota profiles suggested an inverse correlation in terms of relative abundance between these genera suggesting an antagonism or competition between these taxonomic groups.

Keywords: nasal, microbiota, S.aureus, microbioal interaction

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Authors: Mondal Indranil, Bhakat Debjyoti, Mukhopadayay Asish K., Chatterjee Nabendu S.

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CS6 is the prevalent CF in our region and deciphering its molecular regulators would play a pivotal role in reducing the burden of ETEC pathogenesis. In prokaryotes, most of the genes are under the control of one operon and the promoter present upstream of the gene regulates the transcription of that gene. Here the promoter of CS6 was characterized by computational method and further analyzed by β-galactosidase assay and sequencing. Promoter constructs and deletions were prepared as required to analyze promoter activity. The effect of different additives on the CS6 promoter was analysed by the β-galactosidase assay. Bioinformatics analysis done by Softberry/BPROM predicted fur, lrp, and crp boxes, -10 and -35 region upstream of the CS6 gene. The promoter construction in no promoter plasmid pTL61T showed that region -573 to +1 is actually the promoter region as predicted. Sequential deletion of the region upstream of CS6 revealed that promoter activity remains the same when -573bp to -350bp is deleted. But after the deletion of the upstream region -350 bp to -255bp, promoter expression decreases drastically to 26%. Further deletion also decreases promoter activity up to a little range. So the region -355bp to -255bp holds the promoter sequence for the CS6 gene. Additives like iron, NaCl, etc., modulate promoter activity in a dose-dependent manner. From the promoter analysis, it can be said that the minimum region lies between -254 and +1. Important region(s) lies between -350 bp to -255 bp upstream in the promoter, which might have important elements needed to control CS6 gene expression.

Keywords: microbiology, promoter, colonization factor, ETEC

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Authors: Mukolwe D. Lubembe, Odongo O. David, Githaka Naftali, Kanduma Esther, Marinda Oosthuizen, Kgomotso P. Sibeko

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Theileriosis is a tick-borne disease of cattle caused by an apicomplexan protozoan parasite of the genus Theileria. In eastern and southern Africa, Theileria infections in cattle are caused by the species Theileria parva whose natural reservoir is the African buffalo (Syncerus caffer). Currently, East Coast Fever (ECF) caused by the cattle-derived Theileria parva is still a major problem in eastern Africa and some parts of southern Africa but not in South Africa following its eradication in the 1950s. However, Corridor disease (CD) caused by the buffalo-derived Theileria parva still remains a concern in South Africa. The diversity of Theileria parva in South Africa in comparison to other affected countries is poorly defined yet its known to be the survival strategy of this parasite. We assessed the antigenic diversity of Theileria parva isolates from Buffalo and cattle at the wildlife-livestock interface comparing samples from South Africa, Zimbabwe, Kenya, Tanzania, and Uganda. Antigenic epitopes of eight schizont antigen genes (Tp1, Tp3, Tp4, Tp5, Tp6, Tp7, Tp8 and Tp10) were amplified by PCR from genomic DNA extracted from blood samples collected from cattle and buffalo at the wildlife-livestock interface. Amplicons were purified and then sequenced on NGS platform. Full length open reading frames (ORFs) of two schizont antigen genes (Tp2 and Tp9) and one sporozoite antigen gene, p67 were also amplified from genomic DNA. Amplicons were then purified and cloned for sequencing. Analysis was based on sequence differences in the genes. Preliminary results show an extensively diverse population of Theileria parva circulating in buffalo and cattle populations at the wildlife-livestock interface. Diversity of the antigen genes contributes to the evasion of the immune system of the host by Theileria parva. This possess a concern in that, some of the Theileria parva populations may re-assort and become adapted to cattle to cause a form of theileriosis that is as fatal as ECF in areas where ECF was eradicated or is absent

Keywords: Theileria parva, east coast fever, corridor diseases, antigen genes, diversity

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Authors: Binder Hans

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Cancer is no longer seen as solely a genetic disease where genetic defects such as mutations and copy number variations affect gene regulation and eventually lead to aberrant cell functioning which can be monitored by transcriptome analysis. It has become obvious that epigenetic alterations represent a further important layer of (de-)regulation of gene activity. For example, aberrant DNA methylation is a hallmark of many cancer types, and methylation patterns were successfully used to subtype cancer heterogeneity. Hence, unraveling the interplay between different omics levels such as genome, transcriptome and epigenome is inevitable for a mechanistic understanding of molecular deregulation causing complex diseases such as cancer. This objective requires powerful downstream integrative bioinformatics methods as an essential prerequisite to discover the whole genome mutational, transcriptome and epigenome landscapes of cancer specimen and to discover cancer genesis, progression and heterogeneity. Basic challenges and tasks arise ‘beyond sequencing’ because of the big size of the data, their complexity, the need to search for hidden structures in the data, for knowledge mining to discover biological function and also systems biology conceptual models to deduce developmental interrelations between different cancer states. These tasks are tightly related to cancer biology as an (epi-)genetic disease giving rise to aberrant genomic regulation under micro-environmental control and clonal evolution which leads to heterogeneous cellular states. Machine learning algorithms such as self organizing maps (SOM) represent one interesting option to tackle these bioinformatics tasks. The SOMmethod enables recognizing complex patterns in large-scale data generated by highthroughput omics technologies. It portrays molecular phenotypes by generating individualized, easy to interpret images of the data landscape in combination with comprehensive analysis options. Our image-based, reductionist machine learning methods provide one interesting perspective how to deal with massive data in the discovery of complex diseases, gliomas, melanomas and colon cancer on molecular level. As an important new challenge, we address the combined portrayal of different omics data such as genome-wide genomic, transcriptomic and methylomic ones. The integrative-omics portrayal approach is based on the joint training of the data and it provides separate personalized data portraits for each patient and data type which can be analyzed by visual inspection as one option. The new method enables an integrative genome-wide view on the omics data types and the underlying regulatory modes. It is applied to high and low-grade gliomas and to melanomas where it disentangles transversal and longitudinal molecular heterogeneity in terms of distinct molecular subtypes and progression paths with prognostic impact.

Keywords: integrative bioinformatics, machine learning, molecular mechanisms of cancer, gliomas and melanomas

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Authors: Ireneusz Majsterek, Karolina Przybylowska, Lukasz Dziki, Adam Dziki, Jacek Kabzinski

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Colorectal cancer (CRC) is one of the deadliest cancers. Every year we see an increase in the number of cases, and in spite of intensive research etiology of the disease remains unknown. For many years, researchers are seeking to associate genetic factors with an increased risk of CRC, so far it has proved to be a compelling link between the MMR system of DNA repair and hereditary nonpolyposis colorectal cancers (HNPCC). Currently, research is focused on finding the relationship between the remaining DNA repair systems and an increased risk of developing colorectal cancer. The aim of the study was to determine the relationship between gene polymorphisms Ser835Ser of XPF gene and Gly23Ala of XPA gene–elements of NER DNA repair system, and modulation of the risk of colorectal cancer in the Polish population. Determination of the molecular basis of carcinogenesis process and predicting increased risk will allow qualifying patients to increased risk group and including them in preventive program. We used blood collected from 110 patients diagnosed with colorectal cancer. The control group consisted of equal number of healthy people. Genotyping was performed by TaqMan method. The obtained results indicate that the genotype 23Gly/Ala of XPA gene is associated with an increased risk of colorectal cancer, while 23Ala/Ala as well as TCT allele of Ser835Ser of XPF gene may reduce the risk of CRC.

Keywords: NER, colorectal cancer, XPA, XPF, polymorphisms

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Authors: Irshad Ali Khan, Jian-Ping Lu, Xiao-Hong Liu, Fu-Cheng Lin

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This study reports the functional analysis of a gene MoNUC1 in M. oryzae, which is homologous to the Saccharomyces cerevisiae NUC1 encoding a mitochondrial nuclease protein. The MoNUC1 having a gene locus MGG_05324 is 1002-bp in length and encodes an identical protein of 333 amino acids. We disrupted the gene through gene disruption strategy and isolated two mutants confirmed by southern blotting. The deleted mutants were then used for phenotypic studies and their phenotypes were compared to those of the Guy-11 strain. The mutants were first grown on CM medium to find the effect of MoNUC1 gene disruption on colony growth and the mutants were found to show normal culture colony growth similar to that of the Guy-11 strain. Conidial germination and appressorial formation were also similar in both the mutants and Guy-11 strains showing that this gene plays no significant role in these phenotypes. For pathogenicity, the mutants and Guy-11 mycelium blocks were inoculated on blast susceptible barley seedlings and it was found that both the strains exhibited full pathogenicity showing coalesced and necrotic blast lesions suggesting that this gene is not involved in pathogenicity. Mating of the mutants with 2539 strain formed numerous perithecia showing that MoNUC1 is not essential for sexual reproduction in M. oryzae. However, the mutants were found to form reduced conidia (1.06±8.03B and 1.08±9.80B) than those of the Guy-11 strain (1.46±10.61A) and we conclude that this protein is not required for the blast fungus to cause pathogenicity but plays significant role in conidiation. Proteins of signal transduction pathways that could be disrupted/ intervened genetically or chemically could lead to antifungal products of important fungal cereal diseases and reduce rice yield losses. Tipping the balance toward understanding the whole of pathogenesis, rather than simply conidiation will take some time, but clearly presents the most exciting challenge of all.

Keywords: appressorium formation, conidiation, NUC1, Magnaporthe oryzae, pathogenicity

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Authors: Negin Parsamanesh, Saman Ameri-Mahabadi, Ali Nikfar, Mojdeh Mansouri, Hossein Chiti, Gita Fatemi Abhari

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Duchenne muscular dystrophy (DMD) is a severe progressive X-linked neuromuscular illness that affects movement through mutations in dystrophin gene. The mutation leads to insufficient, lack of or dysfunction of dystrophin. The cause of DMD was determined in an Iranian family. Exome sequencing was carried out along with a complete physical examination of the family. In silico methods were applied to find the alteration in the protein structure. The homozygous variant in DMD gene (NM-004006.2) was defined as c.2732-2733delTT (p.Phe911CysfsX8) in exon 21. In addition, phylogenetic conservation study of the human dystrophin protein sequence revealed that phenylalanine 911 is one of the evolutionarily conserved amino acids. In conclusion, our study indicated a new deletion in the DMD gene in the affected family. This deletion with an X-linked inheritance pattern is new in Iran. These findings could facilitate genetic counseling for this family and other patients in the future.

Keywords: duchenne muscular dystrophy, whole exome sequencing, iran, metabolic syndrome

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Authors: Supriya Ambawat, Subaran Singh, C. Tara Satyavathi, B. S. Rajpurohit, Ummed Singh, Balraj Singh

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Pearl millet [Pennisetum glaucum (L.) R. Br.] is an important staple food of the arid and semiarid tropical regions of Asia, Africa, and Latin America. It is rightly termed as nutricereal as it has high nutrition value and a good source of carbohydrate, protein, fat, ash, dietary fiber, potassium, magnesium, iron, zinc, etc. Pearl millet has low prolamine fraction and is gluten free which is useful for people having a gluten allergy. It has several health benefits like reduction in blood pressure, thyroid, diabe¬tes, cardiovascular and celiac diseases but its direct consumption as food has significantly declined due to several reasons. Keeping this in view, it is important to reorient the ef¬forts to generate demand through value-addition and quality improvement and create awareness on the nutritional merits of pearl millet. In India, through Indian Council of Agricultural Research-All India Coordinated Research Project on Pearl millet, multilocational coordinated trials for developed hybrids were conducted at various centers. The gene banks of pearl millet contain varieties with high levels of iron and zinc which were used to produce new pearl millet varieties with elevated iron levels bred with the high‐yielding varieties. Thus, using breeding approaches and biochemical analysis, a total of 167 hybrids and 61 varieties were identified and released for cultivation in different agro-ecological zones of the country which also includes some biofortified hybrids rich in Fe and Zn. Further, using several biotechnological interventions such as molecular markers, next-generation sequencing (NGS), association mapping, nested association mapping (NAM), MAGIC populations, genome editing, genotyping by sequencing (GBS), genome wide association studies (GWAS) advancement in millet improvement has become possible by identifying and tagging of genes underlying a trait in the genome. Using DArT markers very high density linkage maps were constructed for pearl millet. Improved HHB67 has been released using marker assisted selection (MAS) strategies, and genomic tools were used to identify Fe-Zn Quantitative Trait Loci (QTL). The draft genome sequence of millet has also opened various ways to explore pearl millet. Further, genomic positions of significantly associated simple sequence repeat (SSR) markers with iron and zinc content in the consensus map is being identified and research is in progress towards mapping QTLs for flour rancidity. The sequence information is being used to explore genes and enzymatic pathways responsible for rancidity of flour. Thus, development and application of several biotechnological approaches along with biofortification can accelerate the genetic gain targets for pearl millet improvement and help improve its quality.

Keywords: Biotechnological approaches, genomic tools, malnutrition, MAS, nutricereal, pearl millet, sequencing.

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Authors: Alyaa Abdlwahab

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Cutaneous leishmaniasis represents a serious health problem in Syria; this problem has become noticeably aggravated after the civil war in the country. Leishmania tropica parasite is the main cause of cutaneous leishmaniasis in Syria. In order to control the disease, we need an effective vaccine against leishmania parasite. DNA vaccination remains one of the favorable approaches that have been used to face cutaneous leishmaniasis. Ribosomal protein S4 is responsible for important roles in Leishmania parasite life. DNA vaccine based on S4 gene has been used against infections by many species of Leishmania parasite but leishmania tropica parasite, so this gene represents a good candidate for DNA vaccine construction. After proving the existence of ribosomal protein S4 gene in a Syrian strain of Leishmania tropica (LCED Syrian 01), sequencing it and cloning it into pCI plasmid, BALB/C mice were inoculated with pCI-S4 DNA vaccine. The immune response was determined by monitoring the lesion progression in inoculated BALB/C mice for six weeks after challenging mice with Leishmania tropica (LCED Syrian 01) parasites. IL-12, IFN-γ, and IL-4 were quantified in draining lymph nodes (DLNa) of the immunized BALB/C mice by using the RT-qPCR technique. The parasite burden was calculated in the final week for the footpad lesion and the DLNs of the mice. This study proved the existence and the expression of the ribosomal protein S4 gene in Leishmania tropica (LCED Syrian 01) promastigotes. The sequence of ribosomal protein cDNA S4 gene was determined and published in Genbank; the gene size was 822 bp. Expression was also demonstrated at the level of cDNA. Also, this study revealed that pCI-S4 DNA vaccine induces TH1\TH2 response in immunized mice; this response prevents partially developing a dermal lesion of Leishmania.

Keywords: ribosomal protein S4, DNA vaccine, Leishmania tropica, BALB\c

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Authors: Srijata Mitra, Mobina Parveen, Pranab Roy, Narayan Chandra Chattopadhyay

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Chlorinated hydrocarbon can be a major pollution problem in groundwater as well as soil. Many people interact with these chemicals on daily accidentally or by professionally in the laboratory. One of the most common sources for Chlorinated hydrocarbon contamination of soil and groundwater are industrial effluents. The wide use and discharge of Trichloroethylene (TCE), a volatile chlorohydrocarbon from chemical industry, led to major water pollution in rural areas. TCE is an mainly used as an industrial metal degreaser in industries. Biotransformation of TCE to the potent carcinogen vinyl chloride (VC) by consortia of anaerobic bacteria might have role for the above purpose. For these reasons, the aim of current study was to isolate and characterized the genes involved in TCE metabolism and also to investigate the in silico study of those genes. To our knowledge, only one aromatic dioxygenase system, the toluene dioxygenase in Pseudomonas putida F1 has been shown to be involved in TCE degradation. This is first instance where Bacillus cereus group being used in biodegradation of trichloroethylene. A novel bacterial strain 2479 was isolated from oil depot site at Rajbandh, Durgapur (West Bengal, India) by enrichment culture technique. It was identified based on polyphasic approach and ribotyping. The bacterium was gram positive, rod shaped, endospore forming and capable of degrading trichloroethylene as the sole carbon source. On the basis of phylogenetic data and Fatty Acid Methyl Ester Analysis, strain 2479 should be placed within the genus Bacillus and species cereus. However, the present isolate (strain 2479) is unique and sharply different from the usual Bacillus strains in its biodegrading nature. Fujiwara test was done to estimate that the strain 2479 could degrade TCE efficiently. The gene for TCE biodegradation was PCR amplified from genomic DNA of Bacillus cereus 2479 by using todC1 gene specific primers. The 600bp amplicon was cloned into expression vector pUC I8 in the E. coli host XL1-Blue and expressed under the control of lac promoter and nucleotide sequence was determined. The gene sequence was deposited at NCBI under the Accession no. GU183105. In Silico approach involved predicting the physico-chemical properties of deduced Tce1 protein by using ProtParam tool. The tce1 gene contained 342 bp long ORF encoding 114 amino acids with a predicted molecular weight 12.6 kDa and the theoretical pI value of the polypeptide was 5.17, molecular formula: C559H886N152O165S8, total number of atoms: 1770, aliphatic index: 101.93, instability index: 28.60, Grand Average of Hydropathicity (GRAVY): 0.152. Three differentially expressed proteins (97.1, 40 and 30 kDa) were directly involved in TCE biodegradation, found to react immunologically to the antibodies raised against TCE inducible proteins in Western blot analysis. The present study suggested that cloned gene product (TCE1) was capable of degrading TCE as verified chemically.

Keywords: cloning, Bacillus cereus, in silico analysis, TCE

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Authors: Helan Satish, M. Ramasubba Reddy

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The simulation of an endocardial cell for gene mutation in the cardiac sodium ion channel NaV1.5, encoded by SCN5A gene, is discussed. The characterization of Brugada Syndrome by loss of function effect on SCN5A mutation due to L812Q mutant present in the DII-S4 transmembrane region of the NaV1.5 channel protein and its effect in an endocardial cell is studied. Ten Tusscher model of human ventricular action potential is modified to incorporate the changes contributed by L812Q mutant in the endocardial cells. Results show that BrS-associated SCN5A mutation causes reduction in the inward sodium current by modifications in the channel gating dynamics such as delayed activation, enhanced inactivation, and slowed recovery from inactivation in the endocardial cell. A decrease in the inward sodium current was also observed, which affects depolarization phase (Phase 0) that leads to reduction in the spike amplitude of the cardiac action potential.

Keywords: SCN5A gene mutation, sodium channel, Brugada syndrome, cardiac arrhythmia, action potential

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Authors: Mohammed Abdullah Alshahrani

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The research focuses on investigating the use of partial least squares (PLS) methodology for addressing challenges associated with high-dimensional correlated data. Recent technological advancements have led to experiments producing data characterized by a large number of variables compared to observations, with substantial inter-variable correlations. Such data patterns are common in chemometrics, where near-infrared (NIR) spectrometer calibrations record chemical absorbance levels across hundreds of wavelengths, and in genomics, where thousands of genomic regions' copy number alterations (CNA) are recorded from cancer patients. PLS serves as a widely used method for analyzing high-dimensional data, functioning as a regression tool in chemometrics and a classification method in genomics. It handles data complexity by creating latent variables (components) from original variables. However, applying PLS can present challenges. The study investigates key areas to address these challenges, including unifying interpretations across three main PLS algorithms and exploring unusual negative shrinkage factors encountered during model fitting. The research presents an alternative approach to addressing the interpretation challenge of predictor weights associated with PLS. Sparse estimation of predictor weights is employed using a penalty function combining a lasso penalty for sparsity and a Cauchy distribution-based penalty to account for variable dependencies. The results demonstrate sparse and grouped weight estimates, aiding interpretation and prediction tasks in genomic data analysis. High-dimensional data scenarios, where predictors outnumber observations, are common in regression analysis applications. Ordinary least squares regression (OLS), the standard method, performs inadequately with high-dimensional and highly correlated data. Copy number alterations (CNA) in key genes have been linked to disease phenotypes, highlighting the importance of accurate classification of gene expression data in bioinformatics and biology using regularized methods like PLS for regression and classification.

Keywords: partial least square regression, genetics data, negative filter factors, high dimensional data, high correlated data

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Authors: Salina Yahya Saddick

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Ovarian cancer remains the most lethal gynecological malignancy due to the lack of highly sensitive and specific screening tools for detection of early-stage disease. The OSE provides the progenitor cells for 90% of human ovarian cancers. Recent morphologic, immunohistochemical and molecular genetic studies have led to the development of a new paradigm for the pathogenesis and origin of epithelial ovarian cancer (EOC) based on a ualistic model of carcinogenesis that divides EOC into two broad categories designated Types I and II which are characterized by specific mutations, including KRAS, BRAF, ERBB2, CTNNB1, PTEN PIK3CA, ARID1A, and PPPR1A, which target specific cell signaling pathways. Type 1 tumors rarely harbor TP53. type I tumors are relatively genetically stable and typically display a variety of somatic sequence mutations that include KRAS, BRAF, PTEN, PIK3CA CTNNB1 (the gene encoding beta catenin), ARID1A and PPP2R1A but very rarely TP53 . The cancer stem cell (CSC) hypothesis postulates that the tumorigenic potential of CSCs is confined to a very small subset of tumor cells and is defined by their ability to self-renew and differentiate leading to the formation of a tumor mass. Potential protein biomarker miRNA, are promising biomarkers as they are remarkably stable to allow isolation and analysis from tissues and from blood in which they can be found as free circulating nucleic acids and in mononuclear cells. Recently, genomic anaylsis have identified biomarkers and potential therapeutic targets for ovarian cancer namely, FGF18 which plays an active role in controlling migration, invasion, and tumorigenicity of ovarian cancer cells through NF-κB activation, which increased the production of oncogenic cytokines and chemokines. This review summarizes update information on epithelial ovarian cancers and point out to the most recent ongoing research.

Keywords: epithelial ovarian cancers, somatic sequence mutations, cancer stem cell (CSC), potential protein, biomarker, genomic analysis, FGF18 biomarker

Procedia PDF Downloads 357

Authors: Hayal Akyildirim Beğen, Özgür Emi̇nağaoğlu

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DNA barcoding is the method of description of species based on gene diversity. In current studies, registration, genetic identification and protection of especially endemic plants pecies are carried out by DNA barcoding techniques. Molecular studies are based on the amplification and sequencing of the barcode gene region by the PCR method. Endemic Campanula choruhensis Kit Tan & Sorger, Campanula troegera Damboldt and Campanula betulifolia K.Koch is widespread in Artvin, Erzurum and around Çoruh valley passing through it. Intense road and dam constructions are carried out in and around the distribution area of this species. This situation harms the habitat of the species and puts its extinction. In this study, the plastid matK barcode gene regions (650 bp) of three Campanula species were created. To make the identification of this species quickly and accurately, gene sequence compared with sequences of other Campanula L. species. As a result of phylogenetic analysis, C. choruhensis is close relative to C. betulifolia. Morphologically, these species were determined to be more similar to each other with flower and leaf characters. C. troegera formed a separate branch.

Keywords: campanula, DNA barcoding, endemic, türkiye, artvin

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Authors: Rugang Tian

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In this study, we generated whole-genome sequence (WGS) data from110 native cattle. Together with whole-genome sequences from world-wide cattle populations, we estimated the genetic diversity and population genetic structure of different cattle populations. Our findings revealed clustering of cattle groups in line with their geographic locations. We identified noticeable genetic diversity between indigenous cattle breeds and commercial populations. Among all studied cattle groups, lower genetic diversity measures were found in commercial populations, however, high genetic diversity were detected in some local cattle, particularly in Rashoki and Mongolian breeds. Our search for potential genomic regions under selection in native cattle revealed several candidate genes related with immune response and cold shock protein on multiple chromosomes such as TRPM8, NMUR1, PRKAA2, SMTNL2 and OXR1 that are involved in energy metabolism and metabolic homeostasis.

Keywords: cattle, whole-genome, population structure, adaptation

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Authors: Kyle Phillips, Ndiko Ludidi

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Global climate change has resulted in altered rainfall patterns, which has resulted in annual losses in maize crop yields due to drought. Therefore it is important to produce maize cultivars that are more drought-tolerant, which is not an easily accomplished task as plants have a plethora of physical and biochemical adaptation methods. One such mechanism is the drought-induced expression of enzymatic and non-enzymatic proteins which assist plants to resist the effects of drought on their growth and development. One of these proteins is AtRD22 which has been identified in Arabidopsis thaliana. Using an in silico approach, a maize protein with 48% sequence homology to AtRD22 has been identified. This protein appears to be localized in the extracellular matrix, similarly to AtRD22. Promoter analysis of the encoding gene reveals cis-acting elements suggestive of induction of the gene’s expression by abscisic acid (ABA). Semi-quantitative transcriptomic analysis of the putative maize RD22 has revealed an increase in transcript levels after the exposure to drought. Current work elucidates the effect of up-regulation and silencing of the maize RD22 gene on the tolerance of maize to drought. The potential role of the maize RD22 gene in maize drought tolerance can be used as a tool to improve food security.

Keywords: abscisic acid, drought-responsive cis-acting elements, maize drought tolerance, RD22

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Authors: Annet Namusoke, Annet Namayanja, Peter Wasswa, Shakirah Nampijja

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Common bean cultivar G2333 which offers broad resistance for anthracnose has been widely used as a source of resistance in breeding for anthracnose resistance. The cultivar is pyramided with three genes namely CO-4, CO-5 and CO-7 and of these three genes, the CO-4 gene has been found to offer the broadest resistance. The main aim of this work was to identify and validate easily assayable PCR based co-dominant molecular markers for selection of the CO-4 gene in segregating populations derived from crosses of G2333 with RWR 1946 and RWR 2075, two commercial Andean cultivars highly susceptible to anthracnose. Marker sequences for the study were obtained by blasting the sequence of the COK-4 gene in the Phaseolus gene database. Primer sequence pairs that were not provided from the Phaseolus gene database were designed by the use of Primer3 software. PCR conditions were optimized and the PCR products were run on 6% HPAGE gel. Results of the polymorphism test indicated that out of 18 identified markers, only two markers namely BM588 and BM211 behaved co-dominantly. Phenotypic evaluation for reaction to anthracnose disease was done by inoculating 21days old seedlings of three parents, F1 and F2 populations with race 7 of Colletotrichum lindemuthianum in the humid chamber. DNA testing of the BM588 marker onto the F2 segregating population of the crosses RWR 1946 x G 2333 and RWR 2075 x G2333 further revealed that the marker BM588 co-segregated with disease resistance with co-dominance of two alleles of 200bp and 400bp, fitting the expected segregation ratio of 1:2:1. The BM588 marker was significantly associated with disease resistance and gave promising results for marker assisted selection of the CO-4 gene in the breeding lines. Activities to validate the BM211 marker are also underway.

Keywords: codominant, Colletotrichum lindemuthianum, MAS, Phaseolus vulgaris

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Authors: Yamunah Devi Apalasamy, Sanjay Rampal, Tin Tin Su, Foong Ming Moy, Hazreen Abdul Majid, Awang Bulgiba, Zahurin Mohamed

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Obesity is a growing global health issue. Obesity results from a combination of environmental and genetics factors. Brain-derived neurotrophic factor (BDNF), a gene encodes the BDNF protein and the BDNF gene have been linked to regulation of body weight and appetite. Genome-wide association studies have identified the BDNF variants to be related to obesity among Caucasians, East Asians, and Filipinos. However, the role of BDNF in other ethnic groups remains inconclusive. This case control study aims to investigate the associations of BDNF gene polymorphisms with obesity and metabolic parameters in Malaysian Malays. BDNF rs4074134, BDNF rs10501087 and BDNF rs6265 were genotyped using Sequenom MassARRAY. Anthropometric, body fat, fasting lipids and glucose levels were measured. A total of 663 subjects (194 obese and 469 non-obese) were included in this study. There were no significant associations association between BDNF SNPs and obesity. The allelic and genotype frequencies of the BDNF SNPs were similar in the obese and non-obese groups. After adjustment for age and sex, the BDNF variants were not associated with obesity, body fat, fasting lipids and glucose levels. Haplotypes at the BDNF gene region, were not significantly associated with obesity. The BDNF rs4074134 was in strong LD with BDNF rs10501087 (D'=0.98) and BDNF rs6265 (D'=0.87). The BDNF rs10501087 was also in strong LD with BDNF rs6265 (D'=0.91). Our findings suggest that the BDNF variants and the haplotypes of BDNF gene were not associated with obesity and metabolic traits in this study population. Further research is needed to explore other BDNF variants with a larger sample size with gene-environment interactions in multi ethnic Malaysian population.

Keywords: genomics of obesity, SNP, BMI, haplotypes

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