Search results for: Sanger sequencing

Authors: Asmuddin Natsir, A. Mujnisa, Syahriani Syahrir, Marhamah Nadir, Nurul Purnomo

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Bacteria, protozoa, Archaea, and fungi are the dominant microorganisms found in the rumen ecosystem that has an important role in converting feed ingredients into components that can be digested and utilized by the livestock host. This study was conducted to assess the diversity of rumen bacteria of bali cattle raised under traditional farming condition. Three adult bali cattle were used in this experiment. The rumen fluid samples from the three experimental animals were obtained by the Stomach Tube method before the morning feeding. The results of study indicated that the Illumina sequencing was successful in identifying 301,589 sequences, averaging 100,533 sequences, from three rumen fluid samples of three cattle. Furthermore, based on the SILVA taxonomic database, there were 19 kinds of phyla that had been successfully identified. Of the 19 phyla, there were only two dominant groups across the three samples, namely Bacteroidetes and Firmicutes, with an average percentage of 83.68% and 13.43%, respectively. Other groups such as Synergistetes, Spirochaetae, Planctomycetes can also be identified but in relatively small percentage. At the genus level, there were 157 sequences obtained from all three samples. Of this number, the most dominant group was Prevotella 1 with a percentage of 71.82% followed by 6.94% of Christencenellaceae R-7 group. Other groups such as Prevotellaceae UCG-001, Ruminococcaceae NK4A214 group, Sphaerochaeta, Ruminococcus 2, Rikenellaceae RC9 gut group, Quinella were also identified but with very low percentages. The sequencing results were able to detect the presence of 3.06% and 3.92% respectively for uncultured rumen bacterium and uncultured bacterium. In conclusion, the results of this experiment can provide an opportunity for a better understanding of the rumen bacterial diversity of the bali cattle raised under traditional farming condition and insight regarding the uncultured rumen bacterium and uncultured bacterium that need to be further explored.

Keywords: 16S rRNA sequencing, bali cattle, rumen microbial diversity, uncultured rumen bacterium

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Authors: J. Vinay , Kusumbati Besra, Niharika Pattnaik, Shivaram Prasad Singh, Manjusha Dixit

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Gallbladder cancer (GBC) is rare but highly malignant cancer; its prevalence is more in certain geographical regions and ethnic groups, which include the Northern and Eastern states of India. Previous studies in India have reported genetic predisposition as one of the risk factors in GBC pathogenesis. Although the matrix metalloproteinase-14 (MMP14) is a well-known modulator of the tumor microenvironment and tumorigenesis and TCGA data also suggests its upregulation yet, its role in the genetic predisposition for GBC is completely unknown. We elucidated the role of MMP14 promoter variants as genetic risk factors and their implications in expression modulation. We screened MMP14 promoter variants association with GBC using Sanger’s sequencing in approximately 300 GBC and 300 control subjects and 26 GBC tissue samples of Indian ethnicity. The immunohistochemistry was used to check the MMP14 protein expression in GBC tissue samples. The role of promoter variants on expression levels was elucidated using a luciferase reporter assay. The variants rs1004030 (p-value = 0.0001) and rs1003349 (p-value = 0.0008) were significantly associated with gallbladder cancer. The luciferase assay in two different cell lines, HEK-293 (p = 0.0006) and TGBC1TKB (p = 0.0036) showed a significant increase in relative luciferase activity in the presence of risk alleles for both the single nucleotide polymorphisms (SNPs). Similarly, genotype-phenotype correlation in patients samples confirmed that the presence of risk alleles at rs1004030 and rs1003349 increased MMP14 expression. Overall, this study unravels the genetic association of MMP14 promoter variants with gallbladder cancer, which may contribute to pathogenesis by increasing its expression.

Keywords: gallbladder cancer, matrix metalloproteinase-14, single nucleotide polymorphism, case control study, genetic association study

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Authors: Janos Juhasz, Sandor Pongor, Balazs Ligeti

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Next-generation sequencing, especially whole genome shotgun sequencing, is becoming a common approach to gain insight into the microbiomes in a culture-independent way, even in clinical practice. It does not only give us information about the species composition of an environmental sample but opens the possibility to detect antimicrobial resistance and novel, or currently unknown, pathogens. Accurately and reliably detecting the microbial strains is a challenging task. Here we present a sensitive approach for detecting pathogens in metagenomics samples with special regard to detecting novel variants of known pathogens. We have developed a pipeline that uses fast, short read aligner programs (i.e., Bowtie2/BWA) and comprehensive nucleotide databases. Taxonomic binning is based on the lowest common ancestor (LCA) principle; each read is assigned to a taxon, covering the most significantly hit taxa. This approach helps in balancing between sensitivity and running time. The program was tested both on experimental and synthetic data. The results implicate that our method performs as good as the state-of-the-art BLAST-based ones, furthermore, in some cases, it even proves to be better, while running two orders magnitude faster. It is sensitive and capable of identifying taxa being present only in small abundance. Moreover, it needs two orders of magnitude less reads to complete the identification than MetaPhLan2 does. We analyzed an experimental anthrax dataset (B. anthracis strain BA104). The majority of the reads (96.50%) was classified as Bacillus anthracis, a small portion, 1.2%, was classified as other species from the Bacillus genus. We demonstrate that the evaluation of high-throughput sequencing data is feasible in a reasonable time with good classification accuracy.

Keywords: metagenomics, taxonomy binning, pathogens, microbiome, B. anthracis

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Authors: Mariia A. Parfenenko, Ilya S. Dantsev, Sergei V. Bochenkov, Natalia V. Vinogradova, Olga S. Groznova, Victoria Yu. Voinova

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Introduction: Autism is the most common neurodevelopmental disorder. Autism is characterized by difficulties in social interaction and adherence to stereotypic behavioral patterns and frequently co-occurs with epilepsy, intellectual disabilities, connective tissue disorders, and other conditions. CHD8 codes for chromodomain-helicase-DNA-binding protein 8 - a chromatin remodeler that regulates cellular proliferation and neurodevelopment in embryogenesis. CHD8 is one of the genes most frequently involved in autism. Patients and methods: 2 unrelated male patients, P3 and P12, aged 3 and 12 years old, underwent whole genome sequencing, which determined that they both had different likely pathogenic variants, both previously undescribed in literature. Sanger sequencing later determined that P12 inherited the variant from his affected mother. Results: P3 and P12 presented with autism, a developmental delay, ataxia, sleep disorders, overgrowth, and macrocephaly, as well as other clinical features typically present in patients with causative variants in CHD8. The mother of P12 also has autistic traits, as well as ataxia, hypotonia, sleep disorders, and other symptoms. However, P3 and P12 also have different cardiac abnormalities. P3 had signs of a repolarization disorder: a flattened T wave in the III and aVF derivations and a negative T wave in the V1-V2 derivations. He also had structural valve anomalies with associated regurgitation, local contractility impairment of the left ventricular, and diastolic dysfunction of the right ventricle. Meanwhile, P12 had Wolff-Parkinson-White syndrome and underwent radiofrequency ablation at the age of 2 years. At the time of observation, P12 had mild sinus arrhythmia and an incomplete right bundle branch block, as well as arterial hypertension. Discussion: Cardiac abnormalities were not previously reported in patients with causative variants in CHD8. The underlying mechanism for the formation of those abnormalities is currently unknown. However, the two hypotheses are either a disordered interaction with CHD7 – another chromodomain remodeler known to be directly involved in the cardiophenotype of CHARGE syndrome – a rare condition characterized by coloboma, heart defects and growth abnormalities, or the disrupted functioning of CHD8 as an A-Kinase Anchoring Protein, which are known to modulate cardiac function. Conclusion: We observed 2 unrelated autistic males with likely pathogenic variants in CHD8 that presented with typical symptoms of CHD8-related neurodevelopmental disorder, as well as cardiac abnormalities. Cardiac abnormalities have, until now, been considered uncharacteristic for patients with causative variants in CHD8. Further accumulation of data, including experimental evidence of the involvement of CHD8 in heart formation, will elucidate the mechanism underlying the cardiophenotype of those patients. Acknowledgements: Molecular genetic testing of the patients was made possible by the Charity Fund for medical and social genetic aid projects «Life Genome.»

Keywords: autism spectrum disorders, chromodomain-helicase-DNA-binding protein 8, neurodevelopmental disorder, cardio phenotype

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Authors: Manasvi Pinnaka, Brianna Chrisman

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Cystic fibrosis patients often develop lung infections that range anywhere in severity from mild to life-threatening due to the presence of thick and sticky mucus that fills their airways. Since many of these infections are chronic, they not only affect a patient’s ability to breathe but also increase the chances of mortality by respiratory failure. With a publicly available dataset of DNA sequences from bacterial species in the lung microbiome of cystic fibrosis patients, the correlations between different microbial species in the lung and the extent of deterioration of lung function were investigated. 16S sequencing technologies were used to determine the microbiome composition of the samples in the dataset. For the statistical analyses, referencing helped distinguish between taxonomies, and the proportions of certain taxa relative to another were determined. It was found that the Fusobacterium, Actinomyces, and Leptotrichia microbial types all had a positive correlation with the FEV1 score, indicating the potential displacement of these species by pathogens as the disease progresses. However, the dominant pathogens themselves, including Pseudomonas aeruginosa and Staphylococcus aureus, did not have statistically significant negative correlations with the FEV1 score as described by past literature. Examining the lung microbiology of cystic fibrosis patients can help with the prediction of the current condition of lung function, with the potential to guide doctors when designing personalized treatment plans for patients.

Keywords: bacterial infections, cystic fibrosis, lung microbiome, 16S sequencing

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Authors: Mustafa M. Bob, Siti Izaidah Azmi, Mohd Hakim Ab Halim, Nur Syahida Abdul Jamal, Aznah Nor-Anuar, Zaini Ujang

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In this research, the formation and development of aerobic granular sludge (AGS) for domestic wastewater treatment application in hot climate conditions was studied using a sequencing batch reactor (SBR). The performance of the developed AGS in the removal of organic matter and nutrients from wastewater was also investigated. The operation of the reactor was based on the sequencing batch system with a complete cycle time of 3 hours that included feeding, aeration, settling, discharging and idling. The reactor was seeded with sludge collected from the municipal wastewater treatment plant in Madinah city, Saudi Arabia and operated at a temperature of 40ºC using synthetic wastewater as influent. Results showed that granular sludge was developed after an operation period of 30 days. The developed granular sludge had a good settling ability with the average size of the granules ranging from 1.03 to 2.42 mm. The removal efficiency of chemical oxygen demand (COD), ammonia nitrogen (NH3-N) and total phosphorus (TP) were 87.31%, 91.93% and 61.25% respectively. These results show that AGS can be developed at elevated temperatures and it is a promising technique to treat domestic wastewater in hot and low humidity climate conditions such as those encountered in Saudi Arabia.

Keywords: aerobic granular sludge, hot climate, sequencing batch reactor, domestic wastewater treatment

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Authors: Amin Mojiri, Akiyoshi Ohashi, Tomonori Kindaichi

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Synthetic domestic wastewater was treated via combining treatment methods, including electrochemical oxidation, adsorption, and sequencing batch reactor (SBR). In the upper part of the reactor, an anode and a cathode (Ti/RuO₂-IrO₂) were organized in parallel for the electrochemical oxidation procedure. Sodium sulfate (Na₂SO₄) with a concentration of 2.5 g/L was applied as the electrolyte. The voltage and current were fixed on 7.50 V and 0.40 A, respectively. Then, 15% working value of the reactor was filled by activated sludge, and 85% working value of the reactor was added with synthetic wastewater. Powdered cockleshell, 1.5 g/L, was added in the reactor to do ion-exchange. Response surface methodology was employed for statistical analysis. Reaction time (h) and pH were considered as independent factors. A total of 97.0% biochemical oxygen demand, 99.9% phosphorous and 88.6% cadmium were eliminated at the optimum reaction time (80.0 min) and pH (6.4).

Keywords: adsorption, electrochemical oxidation, metals, SBR

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Authors: Eyup Ozkan, Ozkan U. Nalbantoglu, Aycan Gundogdu, Mehmet Hora, A. Emre Onuk

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The human microbiome has been associated with cardiological conditions and this relationship is becoming to be defined beyond the gastrointestinal track. In this study, we investigate the alteration in circulatory microbiota in the context of Coronary Artery Disease (CAD). We received circulatory blood samples from suspected CAD patients and maintain 16S ribosomal RNA sequencing to identify each patient’s microbiome. It was found that Corynebacterium and Methanobacteria genera show statistically significant differences between healthy and CAD patients. The overall biodiversities between the groups were observed to be different revealed by machine learning classification models. We also achieve and demonstrate the performance of a diagnostic method using circulatory blood microbiome-based estimation.

Keywords: coronary artery disease, blood microbiome, machine learning, angiography, next-generation sequencing

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Authors: Mohammed Ali

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A flexible manufacturing system has been studied under different manufacturing strategies. The aim of this paper is to test the impact of number of pallets and routing flexibility (design strategy) on system performance operating at different sequencing and dispatching rules (control strategies) at unbalanced load condition (planning strategies). A computer simulation model is developed to evaluate the effects of aforementioned strategies on the make-span time, which is taken as the system performance measure. The impact of number of pallets is shown with the different levels of routing flexibility. In this paper, the same manufacturing system is modeled under different combination of sequencing and dispatching rules. The result of the simulation shows that there is definite range of pallets for each level of routing flexibility at which the systems performs satisfactorily.

Keywords: flexible manufacturing system, manufacturing, strategy, makespan

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Authors: Hammad Khan, Wookeun Bae

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Major concerns regarding nitritation of low-strength ammonium wastewaters include low ammonium loading rates (usually below 0.2 kg/m3-d) and uncertainty about long-term stability of the process. The purpose of this study was to test a sequencing batch reactor (SBR) filled with cell-immobilized polyethylene glycol (PEG) pellets to see if it could achieve efficient and stable nitritation under various environmental conditions. SBR was fed with synthetic ammonium wastewater of 30±2 mg-N/L and pH: 8±0.05, maintaining the dissolved oxygen concentration of 1.7±0.2 mg/L and the temperature at 30±1oC. The reaction was easily converted to partial nitrification mode within a month by feeding relatively high ammonium substrate (~100 mg-N/L) in the beginning. We observed stable nitritation over 300 days with high ammonium loading rates (as high as ~1.1 kg-N/m3-d), nitrite accumulation rates (mostly over 97%) and ammonium removal rate (mostly over 95%). DO was a major limiting substrate when the DO concentration was below ~4 mg/L and the NH4+-N concentration was above 5 mg/L, giving almost linear increase in the ammonium oxidation rate with the bulk DO increase. Low temperatures mainly affected the reaction rate, which could be compensated for by increasing the pellet volume (i.e. biomass). Our results demonstrated that an SBR filled with small cell-immobilized PEG pellets could achieve very efficient and stable nitritation of a low-strength ammonium wastewater.

Keywords: ammonium loading rate (ALR), cell-immobilization, long-term nitritation, sequencing batch reactor (SBR), sewage treatment

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Authors: Alisa Kazarina, Guntis Gerhards, Elina Petersone-Gordina, Ilva Pole, Viktorija Igumnova, Janis Kimsis, Valentina Capligina, Renate Ranka

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Human body is inhabited by a vast number of microorganisms, collectively known as the human microbiome, and there is a tremendous interest in evolutionary changes in human microbial ecology, diversity and function. The field of paleomicrobiology, study of ancient human microbiome, is powered by modern techniques of Next Generation Sequencing (NGS), which allows extracting microbial genomic data directly from archaeological sample of interest. One of the major techniques is 16S rRNA gene sequencing, by which certain 16S rRNA gene hypervariable regions are being amplified and sequenced. However, some limitations of this method exist including the taxonomic precision and efficacy of different regions used. The aim of this study was to evaluate the phylogenetic sensitivity of different 16S rRNA gene hypervariable regions for microbiome studies in the archaeological samples. Towards this aim, archaeological bone samples and corresponding soil samples from each burial environment were collected in Medieval cemeteries in Latvia. The Ion 16S™ Metagenomics Kit targeting different 16S rRNA gene hypervariable regions was used for library construction (Ion Torrent technologies). Sequenced data were analysed by using appropriate bioinformatic techniques; alignment and taxonomic representation was done using Mothur program. Sequences of most abundant genus were further aligned to E. coli 16S rRNA gene reference sequence using MEGA7 in order to identify the hypervariable region of the segment of interest. Our results showed that different hypervariable regions had different discriminatory power depending on the groups of microbes, as well as the nature of samples. On the basis of our results, we suggest that wider range of primers used can provide more accurate recapitulation of microbial communities in archaeological samples. Acknowledgements. This work was supported by the ERAF grant Nr. 1.1.1.1/16/A/101.

Keywords: 16S rRNA gene, ancient human microbiome, archaeology, bioinformatics, genomics, microbiome, molecular biology, next-generation sequencing

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Authors: Rozeena Baig, R. Rehana Rehman, Rifat Ahmed

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Background: Osteoporosis, characterized by low bone mineral density, poses a global health concern. Diagnosis increases the likelihood of developing osteoporosis, a multifactorial disorder marked by low bone mass, elevating the risk of fractures in the lumbar spine, femoral neck, hip, vertebras, and distal forearm, particularly in postmenopausal women due to bone loss influenced by various pathophysiological factors. Objectives: The aim is to investigate the association of serum cytokine, bone turnover marker, bone mineral density and TLR4 gene polymorphism in pre and post-menopausal women and to find if any of these can be the potential predictor of osteoporosis in postmenopausal women. Material and methods: The study participants consisted of Group A (n=91) healthy pre-menopausal women and Group B (n=102) healthy postmenopausal women having ≥ 5 years’ history of menopause. ELISA was performed for cytokine (TNFα) and bone turnover markers (carboxytelopeptides), respectively. Bone Mineral Density (BMD)was measured through a dual X-ray absorptiometry (DEXA) scan. Toll-like Receptors 4 (TLR4) gene polymorphisms (A896G; Asp299Gly) and (C1196T; Thr399Ile) were investigated by PCR and Sanger sequencing. Results: Statistical analysis reveals a positive correlation of age and BMI with T scores in the premenopausal group, whereas in post-menopausal group found a significant negative correlation between age and T-score at hip (r = - 0.352**), spine (r = - .306**), and femoral neck (r = - 0.344**) and a significant negative correlation of BMI with TNF-α (- 0.316**). No association and significant differences were observed for TLR4 genotype and allele frequencies among studied groups However, both SNPs exhibited significant association with each other. Conclusions: This study concludes that BMI, BMD and TNF-α are the potential predictors of osteoporosis in post-menopausal women. However, CTX and TLR4 gene polymorphism did not appear as potential predictors of bone loss in this study and apparently cannot help in predicting bone loss in post-menopausal women.

Keywords: osteoporosis, post-menopausal, pre-menopausal woemn, genetics mutaiont, TLR4 genepolymorphsum

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Authors: Cheng-Yang Lee, Petrus Tang, Tzu-Hao Chang

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Copy number variations (CNVs) have played an important role in many kinds of human diseases, such as Autism, Schizophrenia and a number of cancers. Many diseases are found in genome coding regions and whole exome sequencing (WES) is a cost-effective and powerful technology in detecting variants that are enriched in exons and have potential applications in clinical setting. Although several algorithms have been developed to detect CNVs using WES and compared with other algorithms for finding the most suitable methods using their own samples, there were not consistent datasets across most of algorithms to evaluate the ability of CNV detection. On the other hand, most of algorithms is using command line interface that may greatly limit the analysis capability of many laboratories. We create a series of simulated WES datasets from UCSC hg19 chromosome 22, and then evaluate the CNV detective ability of 19 algorithms from OMICtools database using our simulated WES datasets. We compute the sensitivity, specificity and accuracy in each algorithm for validation of the exome-derived CNVs. After comparison of 19 algorithms from OMICtools database, we construct a platform to install all of the algorithms in a virtual machine like VirtualBox which can be established conveniently in local computers, and then create a simple script that can be easily to use for detecting CNVs using algorithms selected by users. We also build a table to elaborate on many kinds of events, such as input requirement, CNV detective ability, for all of the algorithms that can provide users a specification to choose optimum algorithms.

Keywords: whole exome sequencing, copy number variations, omictools, pipeline

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Authors: Priyanka Dargode, Suhas Gore, Manju Sharma, Arvind Lali

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Anaerobic digestion has been widely used for production of methane from different biowastes. However, the complexity of microbial communities involved in the process is poorly understood. The performance of biogas production process concerning the process productivity is closely coupled to its microbial community structure and syntrophic interactions amongst the community members. The present study aims at understanding taxonomic variations occurring in any starter inoculum when acclimatised to different lignocellulosic biomass (LBM) feedstocks relating to time of digestion. The work underlines use of high throughput Next Generation Sequencing (NGS) for validating the changes in taxonomic patterns of microbial communities. Biomethane Potential (BMP) batches were set up with different pretreated and non-pretreated LBM residues using the same microbial consortium and samples were withdrawn for studying the changes in microbial community in terms of its structure and predominance with respect to changes in metabolic profile of the process. DNA of samples withdrawn at different time intervals with reference to performance changes of the digestion process, was extracted followed by its 16S rRNA amplicon sequencing analysis using Illumina Platform. Biomethane potential and substrate consumption was monitored using Gas Chromatography(GC) and reduction in COD (Chemical Oxygen Demand) respectively. Taxonomic analysis by QIIME server data revealed that microbial community structure changes with different substrates as well as at different time intervals. It was observed that biomethane potential of each substrate was relatively similar but, the time required for substrate utilization and its conversion to biomethane was different for different substrates. This could be attributed to the nature of substrate and consequently the discrepancy between the dominance of microbial communities with regards to different substrate and at different phases of anaerobic digestion process. Knowledge of microbial communities involved would allow a rational substrate specific consortium design which will help to reduce consortium adaptation period and enhance the substrate utilisation resulting in improved efficacy of biogas process.

Keywords: amplicon sequencing, biomethane potential, community predominance, taxonomic analysis

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Authors: Elizabeth Starzycka-Korbas, Michal Starzycki, Wojciech Rybinski, Mirosława Dabert

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For a few years, the populations of pathogenic fungi occurring in winter oilseed rape in Malyszyn were analyzed. Brassica napus L. in Poland and in the world is a source of energy for both the men (oil), and animals, as post-extraction middling, as well as a motor fuel (oil, biofuel) therefore studies of this type are very important. The species composition of pathogenic fungi can be an indicator of seed yield. The occurrence of oilseed rape pathogens during several years were analyzed using the sequencing method DNA ITS. The results were compared in the gene bank using the program NCBI / BLAST. In field conditions before harvest of oilseed rape presence of pathogens infesting B. napus has been assessed. For example, in 2015, 150 samples have been isolated and applied to PDA medium for the identification of belonging species. From all population has been selected mycelium of 83 isolates which were sequenced. Others (67 isolates) were pathogenic fungi of the genus Alternaria which are easily to recognize. The population of pathogenic species on oilseed rape have been identified after analyzing the DNA ITS and include: Leptosphaeria sp. 38 (L. maculans 25, L. biglobosa 13), Alternaria sp. 29, Fusarium sp. 3, Sclerotinia sclerotiorum 7, heterogeneous 6, total of 83 isolates. The genus Alternaria sp. fungi wear the largest share of B. napus pathogens in particular years. Another dangerous species for oilseed rape was Leptosphaeria sp. Populations of pathogens in each year were different. The number of pathogens occurring in the field and their composition is very important for breeders and farmers because of the possible selection of the most resistant genotypes for sowing in the next growing season.

Keywords: B. napus, DNA ITS Sequencing, pathogenic fungi, population

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Authors: Shalini TV, Gangadharan GG, Sriranjini S Jaideep, ASN Seshasayee, Awadhesh Pandit

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Introduction: Prakriti (body-mind constitution of an individual) is a conventional, customized and unique understanding of which is essential for the personalized medicine described in Ayurveda, Indian System of Medicine. Based on the Doshas( functional, bio humoral unit in the body), individuals are categorized into three major Prakriti- Vata, Pitta, and Kapha. The human gut microbiome hosts plenty of highly diverse and metabolically active microorganisms, mainly dominated by the bacteria, which are known to influence the physiology of an individual. Few researches have shown the correlation between the Prakriti and the biochemical parameters. In this study, an attempt was made to explore any correlation between the Prakriti (phenotype of an individual) with the Genetic makeup of the gut microbiome in healthy individuals. Materials and methods: 270 multi-ethnic, healthy volunteers of both sex with the age group between 18 to 40 years, with no history of antibiotics in the last 6 months were recruited into three groups of Vata, Pitta, and Kapha. The Prakriti of the individual was determined using Ayusoft, a software designed by CDAC, Pune, India. The volunteers were subjected to initial screening for the assessment of their height, weight, Body Mass Index, Vital signs and Blood investigations to ensure they are healthy. The stool and saliva samples of the recruited volunteers were collected as per the standard operating procedure developed, and the bacterial DNA was isolated using Qiagen kits. The extracted DNA was subjected to 16s rRNA sequencing using the Illumina kits. The sequencing libraries are targeting the variable V3 and V4 regions of the 16s rRNA gene. Paired sequencing was done on the MiSeq system and data were analyzed using the CLC Genomics workbench 11. Results: The 16s rRNA sequencing of the V3 and V4 regions showed a diverse pattern in both the oral and stool microbial DNA. The study did not reveal any specific pattern of bacterial flora amongst the Prakriti. All the p-values were more than the effective alpha values for all OTUs in both the buccal cavity and stool samples. Therefore, there was no observed significant enrichment of an OTU in the patient samples from either the buccal cavity or stool samples. Conclusion: In healthy volunteers of multi-ethnicity, due to the influence of the various factors, the correlation between the Prakriti and the gut microbiome was not seen.

Keywords: gut microbiome, ayurveda Prakriti, sequencing, multi-ethnic urban population

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Authors: Tarek Aboueldahab, Hanan Farag

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Parallel Job Shop Scheduling Problem (JSP) is a multi-objective and multi constrains NP- optimization problem. Traditional Artificial Intelligence techniques have been widely used; however, they could be trapped into the local minimum without reaching the optimum solution, so we propose a hybrid Artificial Intelligence model (AI) with Discrete Breeding Swarm (DBS) added to traditional Artificial Intelligence to avoid this trapping. This model is applied in the cost minimization of the Car Sequencing and Operator Allocation (CSOA) problem. The practical experiment shows that our model outperforms other techniques in cost minimization.

Keywords: parallel job shop scheduling problem, artificial intelligence, discrete breeding swarm, car sequencing and operator allocation, cost minimization

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Authors: Ali Alattabi, Clare Harris, Rafid Alkhaddar, Ali Alzeyadi

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Petroleum refinery wastewater (PRW) can be considered as one of the most significant source of aquatic environmental pollution. It consists of oil and grease along with many other toxic organic pollutants. In recent years, a new technique was implemented using different types of membranes and sequencing batch reactors (SBRs) to treat PRW. SBR is a fill and draw type sludge system which operates in time instead of space. Many researchers have optimised SBRs’ operating conditions to obtain maximum removal of undesired wastewater pollutants. It has gained more importance mainly because of its essential flexibility in cycle time. It can handle shock loads, requires less area for operation and easy to operate. However, bulking sludge or discharging floating or settled sludge during the draw or decant phase with some SBR configurations are still one of the problems of SBR system. The main aim of this study is to develop and innovative design for the SBR optimising the process variables to result is a more robust and efficient process. Several experimental tests will be developed to determine the removal percentages of chemical oxygen demand (COD), Phenol and nitrogen compounds from synthetic PRW. Furthermore, the dissolved oxygen (DO), pH and oxidation-reduction potential (ORP) of the SBR system will be monitored online to ensure a good environment for the microorganisms to biodegrade the organic matter effectively.

Keywords: petroleum refinery wastewater, sequencing batch reactor, hydraulic retention time, Phenol, COD, mixed liquor suspended solids (MLSS)

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Authors: Mohammed Ali

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In this paper, evaluation of flexible manufacturing system is made under different manufacturing strategies. The objective of this paper is to test the impact of pallets and routing flexibility on system performance operating at different sequencing rules, dispatching rules and at unbalanced load condition. A computer simulation model is developed to evaluate the effects of aforementioned manufacturing strategies on the make-span performance of flexible manufacturing system. The impact of number of pallets is shown with the different levels of routing flexibility. In this paper, the same manufacturing system is modeled under different combination of sequencing and dispatching rules. A series of simulation experiments are conducted and results analyzed. The result of the simulation shows that there is impact of pallets and routing flexibility on the performance of the system.

Keywords: flexibility, flexible manufacturing system, pallets, make-span, simulation

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Authors: Huajuan Shi

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Background: The biopsy of the preimplantation embryo may increase the potential risk and concern of embryo viability. Clinically discarded spent embryo medium (SEM) has entered the view of researchers, sparking an interest in noninvasive embryo screening. However, one of the major restrictions is the extremelty low quantity of cf-RNA, which is difficult to efficiently and unbiased amplify cf-RNA using traditional methods. Hence, there is urgently need to an efficient and low bias amplification method which can comprehensively and accurately obtain cf-RNA information to truly reveal the state of SEM cf-RNA. Result: In this present study, we established an agarose PCR amplification system, and has significantly improved the amplification sensitivity and efficiency by ~90 fold and 9.29 %, respectively. We applied agarose to sequencing library preparation (named AG-seq) to quantify and characterize cf-RNA in SEM. The number of detected cf-RNAs (3533 vs 598) and coverage of 3' end were significantly increased, and the noise of low abundance gene detection was reduced. The increasing percentage 5' end adenine and alternative splicing (AS) events of short fragments (< 400 bp) were discovered by AG-seq. Further, the profiles and characterizations of cf-RNA in spent cleavage medium (SCM) and spent blastocyst medium (SBM) indicated that 4‐mer end motifs of cf-RNA fragments could remarkably differentiate different embryo development stages. Significance: This study established an efficient and low-cost SEM amplification and library preparation method. Not only that, we successfully described the characterizations of SEM cf-RNA of preimplantation embryo by using AG-seq, including abundance features fragment lengths. AG-seq facilitates the study of cf-RNA as a noninvasive embryo screening biomarker and opens up potential clinical utilities of trace samples.

Keywords: cell-free RNA, agarose, spent embryo medium, RNA sequencing, non-invasive detection

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Authors: Jean Paul M. Milambo

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Purpose: Aromatase inhibitors (AIs) are indicated in the treatment of hormone-receptive breast cancer in postmenopausal women in various settings. Studies have shown cardiovascular events in some developed countries. To date the data is sparce for evidence-based recommendations in African clinical settings due to lack of cancer registries, capacity building and surveillance systems. Therefore, this study was conducted to assess the feasibility of HyBeacon® probe genotyping adjunctive to standard care for timely prediction and diagnosis of Aromatase inhibitors (AIs) associated adverse events in breast cancer survivors in Africa. Methods: Cross sectional study was conducted to assess the knowledge of POCT among six African countries using online survey and telephonically contacted. Incremental cost effectiveness ratio (ICER) was calculated, using diagnostic accuracy study. This was based on mathematical modeling. Results: One hundred twenty-six participants were considered for analysis (mean age = 61 years; SD = 7.11 years; 95%CI: 60-62 years). Comparison of genotyping from HyBeacon® probe technology to Sanger sequencing showed that sensitivity was reported at 99% (95% CI: 94.55% to 99.97%), specificity at 89.44% (95% CI: 87.25 to 91.38%), PPV at 51% (95%: 43.77 to 58.26%), and NPV at 99.88% (95% CI: 99.31 to 100.00%). Based on the mathematical model, the assumptions revealed that ICER was R7 044.55. Conclusion: POCT using HyBeacon® probe genotyping for AI-associated adverse events maybe cost effective in many African clinical settings. Integration of preventive measures for early detection and prevention guided by different subtype of breast cancer diagnosis with specific clinical, biomedical and genetic screenings may improve cancer survivorship. Feasibility of POCT was demonstrated but the implementation could be achieved by improving the integration of POCT within primary health cares, referral cancer hospitals with capacity building activities at different level of health systems. This finding is pertinent for a future envisioned implementation and global scale-up of POCT-based initiative as part of risk communication strategies with clear management pathways.

Keywords: breast cancer, diagnosis, point of care, South Africa, aromatase inhibitors

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Authors: Mpho Mokoatle, Darlington Mapiye, 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

Procedia PDF Downloads 133

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

Procedia PDF Downloads 122

Authors: Swarkar Sharma, Ekta Rai, Ankit Mahajan, Parvinder Kumar, Manoj K Dhar, Sushil Razdan, Kumarasamy Thangaraj, Carol Wise, Shiro Ikegawa M.D., K.K. Pandita M.D.

Abstract:

Rare disorders are poorly understood hence, remain uncharacterized or patients are misdiagnosed and get poor medical attention. A rare mysterious skeletal disorder that remained unidentified for decades and rendered many people physically challenged and disabled for life has been reported in an isolated remote village ‘Arai’ of Poonch district of Jammu and Kashmir. This village is located deep in mountains and the population residing in the region is highly consanguineous. In our survey of the region, 70 affected people were reported, showing similar phenotype, in the village with a population of approximately 5000 individuals. We were able to collect samples from two multi generational extended families from the village. Through Whole Exome sequencing (WES), we identified a rare variation NM_003880.3:c.156C>A NP_003871.1:p.Cys52Ter, which results in introduction of premature stop codon in WISP3 gene. We found this variation perfectly segregating with the disease in one of the family. However, this variation was absent in other family. Interestingly, a novel splice site mutation at position c.643+1G>A of WISP3 gene, perfectly segregating with the disease was observed in the second family. Thus, exploiting WES and putting different evidences together (familial histories and genetic data, clinical features, radiological and biochemical tests and findings), the disease has finally been diagnosed as a very rare recessive hereditary skeletal disease “Progressive Pseudorheumatoid Arthropathy of Childhood” (PPAC) also known as “Spondyloepiphyseal Dysplasia Tarda with Progressive Arthropathy” (SEDT-PA). This genetic characterization and identification of the disease causing mutations will aid in genetic counseling, critically required to curb this rare disorder and to prevent its appearance in future generations in the population. Further, understanding of the role of WISP3 gene the biological pathways should help in developing treatment for the disorder.

Keywords: whole exome sequencing, Next Generation Sequencing, rare disorders

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Authors: Ayman K. El Essawy, Amal M. Hosny, Hala M. Abu Shady

Abstract:

The rapid detection of TB and drug resistance, both optimizes treatment and improves outcomes. In the current study, respiratory specimens were collected from 155 patients. Conventional susceptibility testing and MIC determination were performed for rifampicin (RIF) and isoniazid (INH). Genotype MTBDRplus assay, which is a molecular genetic assay based on the DNA-STRIP technology and specific gene sequencing with primers for rpoB, KatG, and mab-inhA genes were used to detect mutations associated with resistance to rifampicin and isoniazid. In comparison to other categories, most of rifampicin resistant (61.5%) and isoniazid resistant isolates (47.1%) were from patients relapsed in treatment. The genotypic profile (using Genotype MTBDRplus assay) of multi-drug resistant (MDR) isolates showed missing of katG wild type 1 (WT1) band and appearance of mutation band katG MUT2. For isoniazid mono-resistant isolates, 80% showed katG MUT1, 20% showed katG MUT1, and inhA MUT1, 20% showed only inhA MUT1. Accordingly, 100% of isoniazid resistant strains were detected by this assay. Out of 17 resistant strains, 16 had mutation bands for katG distinguished high resistance to isoniazid. The assay could clearly detect rifampicin resistance among 66.7% of MDR isolates that showed mutation band rpoB MUT3 while 33.3% of them were considered as unknown. One mono-resistant rifampicin isolate did not show rifampicin mutation bands by Genotype MTBDRplus assay, but it showed an unexpected mutation in Codon 531 of rpoB by DNA sequence analysis. Rifampicin resistance in this strain could be associated with a mutation in codon 531 of rpoB (based on molecular sequencing), and Genotype MTBDRplus assay could not detect the associated mutation. If the results of Genotype MTBDRplus assay and sequencing were combined, this strain shows hetero-resistance pattern. Gene sequencing of eight selected isolates, previously tested by Genotype MTBDRplus assay, could detect resistance mutations mainly in codon 315 (katG gene), position -15 in inhA promotes gene for isoniazid resistance and codon 531 (rpoB gene) for rifampicin resistance. Genotyping techniques allow distinguishing between recurrent cases of reinfection or reactivation and supports epidemiological studies.

Keywords: M. tuberculosis, rpoB, KatG, inhA, genotype MTBDRplus

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Authors: Lata Kumari Dhanesh Tiwary, Pradeep Kumar Mishra

Abstract:

The effluent coming from various industries such as textile, carpet, food, pharmaceutical and many other industries is big challenge due to its recalcitrant and xenobiotiocs in nature. Recently, biodegradation of dye wastewater through biological means was widely used due to eco-friendly and cost effective with the higher percentage of removal of dye from wastewater. The present study deals with the biodegradation and decolourization of Direct Red 23 dye using indigenously isolated bacterial consortium. The bacterial consortium was isolated from soil sample from dye contaminated site near a cluster of Carpet industries of Bhadohi, Uttar Pradesh, India. The bacterial strain formed consortia were identified and characterized by morphological, biochemical and 16S rRNA gene sequence analysis. The bacterial strain mainly Staphylococcus saprophyticus strain BHUSS X3 (KJ439576), Microbacterium sp. BHUMSp X4 (KJ740222) and Staphylococcus saprophyticus strain BHUSS X5 (KJ439576) were used as consortia for further studies of dye decolorization. Experimental investigations were made in a Sequencing Air- lift bioreactor using the synthetic solution of Direct Red 23 dye by optimizing various parameters for efficient degradation of dye. The effect of several operating parameters such as flow rate, pH, temperature, initial dye concentration and inoculums size on removal of dye was investigated. The efficiency of isolated bacterial consortia from dye contaminated area in Sequencing Air- lift Bioreactor with different concentration of dye between 100-1200 mg/l at different hydraulic rate (HRTs) 26h and 10h. The maximum percentage of dye decolourization 98% was achieved when operated at HRT of 26h. The percentage of decolourization of dye was confirmed by using UV-Vis spectrophotometer and HPLC.

Keywords: carpet industry, bacterial consortia, sequencing air-lift bioreactor

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Authors: Po-Jung Huang, Chi-Ching Lee, Bertrand Chin-Ming Tan, Yuan-Ming Yeh, Julie Lichieh Chu, Tin-Wen Chen, Cheng-Yang Lee, Ruei-Chi Gan, Hsuan Liu, Petrus Tang

Abstract:

Whole-exome sequencing focuses on the protein coding regions of disease/cancer associated genes based on a priori knowledge is the most cost-effective method to study the association between genetic alterations and disease. Recent advances in high throughput sequencing technologies and proteomic techniques has provided an opportunity to integrate genomics and proteomics, allowing readily detectable mutated peptides corresponding to mutated genes. Since sequence database search is the most widely used method for protein identification using Mass spectrometry (MS)-based proteomics technology, a mutant proteome database is required to better approximate the real protein pool to improve disease-associated mutated protein identification. Large-scale whole exome/genome sequencing studies were launched by National Cancer Institute (NCI), Broad Institute, and The Cancer Genome Atlas (TCGA), which provide not only a comprehensive report on the analysis of coding variants in diverse samples cell lines but a invaluable resource for extensive research community. No existing database is available for the collection of mutant protein sequences related to the identified variants in these studies. CMPD is designed to address this issue, serving as a bridge between genomic data and proteomic studies and focusing on protein sequence-altering variations originated from both germline and cancer-associated somatic variations.

Keywords: TCGA, cancer, mutant, proteome

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

Abstract:

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: Nuha Mansour Alhazmi, Magda Mohamed Aly, Fardus M. Bokhari, Ahmed Bahieldin, Sherif Edris

Abstract:

Out of 30 fungal isolates, 2 new isolates were proven to degrade poly-β-hydroxybutyrate (PHB). Enzyme assay for these isolates indicated the optimal environmental conditions required for depolymerase enzyme to induce the highest level of biopolymer degradation. The two isolates were basically characterized at the morphological level as Trichoderma asperellum (isolate S1), and Aspergillus fumigates (isolate S2) using standard approaches. The aim of the present study was to characterize these two isolates at the molecular level based on the highly diverged rRNA gene(s). Within this gene, two domains of the ribosome large subunit (LSU) namely internal transcribed spacer (ITS) and 26S were utilized in the analysis. The first domain comprises the ITS1/5.8S/ITS2 regions ( > 500 bp), while the second domain comprises the D1/D2/D3 regions ( > 1200 bp). Sanger sequencing was conducted at Macrogen (Inc.) for the two isolates using primers ITS1/ITS4 for the first domain, while primers LROR/LR7 for the second domain. Sizes of the first domain ranged between 594-602 bp for S1 isolate and 581-594 bp for S2 isolate, while those of the second domain ranged between 1228-1238 bp for S1 isolate and 1156-1291 for S2 isolate. BLAST analysis indicated 99% identities of the first domain of S1 isolate with T. asperellum isolates XP22 (ID: KX664456.1), CTCCSJ-G-HB40564 (ID: KY750349.1), CTCCSJ-F-ZY40590 (ID: KY750362.1) and TV (ID: KU341015.1). BLAST of the first domain of S2 isolate indicated 100% identities with A. fumigatus isolate YNCA0338 (ID: KP068684.1) and strain MEF-Cr-6 (ID: KU597198.1), while 99% identities with A. fumigatus isolate CCA101 (ID: KT877346.1) and strain CD1621 (ID: JX092088.1). Large numbers of other T. asperellum and A. fumigatus isolates and strains showed high level of identities with S1 and S2 isolates, respectively, based on the diversity of the first domain. BLAST of the second domain of S1 isolate indicated 99 and 100% identities with only two strains of T. asperellum namely TR 3 (ID: HM466685.1) and G (ID: KF723005.1), respectively. However, other T. species (ex., atroviride, hamatum, deliquescens, harzianum, etc.) also showed high level of identities. BLAST of the second domain of S2 isolate indicated 100% identities with A. fumigatus isolate YNCA0338 (ID: KP068684.1) and strain MEF-Cr-6 (ID: KU597198.1), while 99% identities with A. fumigatus isolate CCA101 (ID: KT877346.1) and strain CD1621 (ID: JX092088.1). Large numbers of other A. fumigatus isolates and strains showed high level of identities with S2 isolate. Overall, the results of molecular characterization based on rRNA diversity for the two isolates of T. asperellum and A. fumigatus matched those obtained by morphological characterization. In addition, ITS domain proved to be more sensitive than 26S domain in diversity profiling of fungi at the species level.

Keywords: Aspergillus fumigates, Trichoderma asperellum, PHB, degradation, BLAST, ITS, 26S, rRNA

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Authors: Jaco Oosthuizen, Nerina C. Van Der Merwe

Abstract:

The National Health Laboratory Services in Bloemfontien has been the diagnostic testing facility for 1830 patients for familial breast cancer since 1997. From the cohort, 540 were comprehensively screened using High-Resolution Melting Analysis or Next Generation Sequencing for the presence of point mutations and/or indels. Approximately 90% of these patients stil remain undiagnosed as they are BRCA1/2 negative. Multiplex ligation-dependent probe amplification was initially added to screen for copy number variation detection, but with the introduction of next generation sequencing in 2017, was substituted and is currently used as a confirmation assay. The aim was to investigate the viability of utilizing internationally designed copy number variation detection assays based on mostly European/Caucasian genomic data for use within a South African context. The multiplex ligation-dependent probe amplification technique is based on the hybridization and subsequent ligation of multiple probes to a targeted exon. The ligated probes are amplified using conventional polymerase chain reaction, followed by fragment analysis by means of capillary electrophoresis. The experimental design of the assay was performed according to the guidelines of MRC-Holland. For BRCA1 (P002-D1) and BRCA2 (P045-B3), both multiplex assays were validated, and results were confirmed using a secondary probe set for each gene. The next generation sequencing technique is based on target amplification via multiplex polymerase chain reaction, where after the amplicons are sequenced parallel on a semiconductor chip. Amplified read counts are visualized as relative copy numbers to determine the median of the absolute values of all pairwise differences. Various experimental parameters such as DNA quality, quantity, and signal intensity or read depth were verified using positive and negative patients previously tested internationally. DNA quality and quantity proved to be the critical factors during the verification of both assays. The quantity influenced the relative copy number frequency directly whereas the quality of the DNA and its salt concentration influenced denaturation consistency in both assays. Multiplex ligation-dependent probe amplification produced false positives due to ligation failure when ligation was inhibited due to a variant present within the ligation site. Next generation sequencing produced false positives due to read dropout when primer sequences did not meet optimal multiplex binding kinetics due to population variants in the primer binding site. The analytical sensitivity and specificity for the South African population have been proven. Verification resulted in repeatable reactions with regards to the detection of relative copy number differences. Both multiplex ligation-dependent probe amplification and next generation sequencing multiplex panels need to be optimized to accommodate South African polymorphisms present within the genetically diverse ethnic groups to reduce the false copy number variation positive rate and increase performance efficiency.

Keywords: familial breast cancer, multiplex ligation-dependent probe amplification, next generation sequencing, South Africa

Procedia PDF Downloads 187