Viral gastroenteritis in Tocantins, Brazil: characterizing the diversity of human adenovirus F through next-generation sequencing and bioinformatics

Human enteric adenovirus species F (HAdV-F) is one of the most common pathogens responsible for acute gastroenteritis worldwide. Brazil is a country with continental dimensions where continuous multiregional surveillance is vital to establish a more complete picture of the epidemiology of HAdV-F. The aim of the current study was to investigate the molecular epidemiology of HAdV-F using full-genome data in rural and low-income urban areas in northern Brazil. This will allow a genetic comparison between Brazilian and global HAdV-F strains. The frequency of HAdV-F infections in patients with gastroenteritis and molecular typing of positive samples within this period was also analysed. A total of 251 stool samples collected between 2010 and 2016 from patients with acute gastroenteritis were screened for HAdV-F using next-generation sequencing techniques. HAdV-F infection was detected in 57.8 % (145/251) of samples. A total of 137 positive samples belonged to HAdV-F41 and 7 to HAdV-F40. HAdV-F40/41 dual infection was found in one sample. Detection rates did not vary significantly according to the year. Single HAdV-F infections were detected in 21.9 % (55/251) of samples and mixed infections in 37.4 % (94/251), with RVA/HAdV-F being the most frequent association (21.5 %; 54/251). Genetic analysis indicated that the HAdV-F strains circulating in Brazil were closely related to worldwide strains, and the existence of some temporal order was not observed. This is the first large-scale HAdV-F study in Brazil in which whole-genome data and DNA sequence analyses were used to characterize HAdV-F strains. Expanding the viral genome database could improve overall genotyping success and assist the National Center for Biotechnology Information (NCBI)/GenBank in standardizing the HAdV genome records by providing a large set of annotated HAdV-F genomes.

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Diagnostic value of a combination of next-generation sequencing, chorioretinal imaging and metabolic analysis: lessons from a consanguineous Chinese family with gyrate atrophy of the choroid and retina stemming from a novel OAT variant

British Journal of Ophthalmology ◽

10.1136/bjophthalmol-2018-312347 ◽

2018 ◽

Vol 103 (3) ◽

pp. 428-435 ◽

Cited By ~ 5

Author(s):

Junting Huang ◽

Jiewen Fu ◽

Shangyi Fu ◽

Lisha Yang ◽

Kailai Nie ◽

...

Keyword(s):

Next Generation Sequencing ◽

Low Income ◽

Autosomal Recessive ◽

Diagnostic Value ◽

Consanguineous Marriage ◽

Chinese Family ◽

Next Generation ◽

Gyrate Atrophy ◽

Metabolic Analysis ◽

Generation Sequencing

Background/AimGyrate atrophy of the choroid and retina (GACR) is an extremely rare autosomal recessive inherited disorder characterised by progressive vision loss. To identify the disease-causing gene in a consanguineous Chinese pedigree with GACR, we aimed to accurately diagnose patients with GACR through a combination of next-generation sequencing (NGS) genetic diagnosis, clinical imaging and amino acid metabolic analysis.MethodsA consanguineous Chinese pedigree with GACR, including two patients, was recruited and a comprehensive ophthalmological evaluation was performed. DNA was extracted from a proband and her family members, and the sample from the proband was analysed using targeted NGS. Variants ‎detected by NGS were confirmed by Sanger sequencing and subjected to segregation analysis. Tandem mass spectrometry (MS/MS) was subsequently performed for metabolic assessment.ResultsWe identified a ‎novel, deleterious, homologous ornithine aminotransferase (OAT) variant, c.G248A: p.S83N, which contributes to ‎the progression of GACR in patients. Our results showed that the p.S83N autosomal recessive ‎variant of OAT is most likely ‎pathogenic, with changes in protein stability drastically decreasing functionality. MS/MS verified that ornithine levels in patients were significantly elevated.ConclusionsRecruitment of a third-degree first cousin consanguineous marriage family with GACR allowed us to identify a novel pathogenicOATvariant in the Chinese population, broadening the mutation spectrum. Our findings reported the diagnostic value of a combination of NGS, retinal imaging and metabolic analysis of consanguineous marriage pedigrees in low-income/middle-income and low-incidence countries, including China, and may help to guide accurate diagnosis and ‎treatment of this disease.

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Next generation sequencing of RB1gene for the molecular diagnosis of ethnic minority with retinoblastoma in Yunnan

10.21203/rs.2.24190/v1 ◽

2020 ◽

Author(s):

Huaiyu Gu ◽

Zhen Zhang ◽

Yi-shuang Xiao ◽

Ru Shen ◽

Hong-chao Jiang ◽

...

Keyword(s):

Genetic Testing ◽

Next Generation Sequencing ◽

Low Income ◽

Eastern China ◽

Low Income Countries ◽

Next Generation ◽

Single Nucleotide Variants ◽

Bioinformatics Pipeline ◽

Generation Sequencing

Abstract Background: Retinoblastoma is a rare intraocular malignancy and typically initiated by inactivating biallelic mutations of RB1 gene. Each year, ~8,000 children worldwide are diagnosed for retinoblastoma. In high-income countries, patient survival is over 95% while low-income countries is ~30%.If disease is diagnosed early and treated in centers specializing in retinoblastoma, the survival might exceed 95% and many eyes could be safely treated and support a lifetime of good vision. In China, approximate 1,100 newly diagnosed cases are expected annually and 28 hospitals covering 25 provinces established centers classified by expertise and resources for better treatment options and follow-up. Comparing with other province of eastern China, Yunnan province is remote geographically. This might result that healthcare staff have low awareness of the role of genetic testing in management and screening in families.Methods: The patients with retinoblastoma were selected in Yunnan. DNA from blood was used for targeted gene sequencing. Then, an in-house bioinformatics pipeline was done to detect both single nucleotide variants and small insertions/deletions. The pathogenic mutations were identified and further confirmed by conventional methods and cosegregation in families.Results: Using our approach, targeted next generation sequencing was used to detect the mutation of these 12 probands. Bioinformatic predictions showed that nine mutations were found in our study and four were novel pathogenic variants in these nine mutations.Conclusions: It’s the first report to describe RB1 mutations in Yunnan children with retinoblastoma. This study would improve role of genetic testing for management and family screening.

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ICT Aspects of Next-Generation-Sequencing Applied to Molecular Diagnostics

Handbook of Research on ICTs and Management Systems for Improving Efficiency in Healthcare and Social Care ◽

10.4018/978-1-4666-3990-4.ch047 ◽

2013 ◽

pp. 912-921

Author(s):

Saskia Biskup

Keyword(s):

Next Generation Sequencing ◽

Molecular Diagnostics ◽

Next Generation ◽

Detection Rates ◽

Genetic Causes ◽

Next Generation Sequencing Ngs ◽

Generation Sequencing

Next-Generation-Sequencing (NGS) techniques are currently on the rise. This is seen as a revolution by (most) geneticists. The wealth of data stemming from Next-Generation-Sequencing will without a doubt lead to significant advances in the field of molecular diagnostics. On the clinical side, this will be higher detection rates of the genetic causes of particular diseases in patients. On the scientific side, NGS techniques will lead to the discovering of genes related to certain diseases (see, for example, Mardis, et al., 2009; Haack, et al., 2010; Lupski, et al., 2010). However, these advances come at a price: geneticists will be confronted with different and new ICT issues related to NGS. Because of the so far unknown amount of data stemming from NGS, these ICT issues need to be taken seriously. The purpose of this chapter is to give an overview on the different ICT aspects that come with the introduction of Next-Generation-Sequencing in molecular diagnostics.

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Big Data Analysis Techniques for Visualization of Genomics in Medicinal Plants

Biotechnology ◽

10.4018/978-1-5225-8903-7.ch032 ◽

2019 ◽

pp. 804-837

Author(s):

Hithesh Kumar ◽

Vivek Chandramohan ◽

Smrithy M. Simon ◽

Rahul Yadav ◽

Shashi Kumar

Keyword(s):

Big Data ◽

Data Analysis ◽

Next Generation Sequencing ◽

Medicinal Plants ◽

Big Data Analysis ◽

Next Generation ◽

Genome Data ◽

Huge Data ◽

Transcriptomics Data ◽

Generation Sequencing

In this chapter, the complete overview and application of Big Data analysis in the field of health care industries, Clinical Informatics, Personalized Medicine and Bioinformatics is provided. The major tools and databases used for the Big Data analysis are discussed in this chapter. The development of sequencing machines has led to the fast and effective ways of generating DNA, RNA, Whole Genome data, Transcriptomics data, etc. available in our hands in just a matter of hours. The complete Next Generation Sequencing (NGS) huge data analysis work flow for the medicinal plants are discussed in the chapter. This chapter serves as an introduction to the big data analysis in Next Generation Sequencing and concludes with a summary of the topics of the remaining chapters of this book.

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Unveiling Viruses Associated with Gastroenteritis Using a Metagenomics Approach

Viruses ◽

10.3390/v12121432 ◽

2020 ◽

Vol 12 (12) ◽

pp. 1432

Author(s):

Xavier Fernandez-Cassi ◽

Sandra Martínez-Puchol ◽

Marcelle Silva-Sales ◽

Thais Cornejo ◽

Rosa Bartolome ◽

...

Keyword(s):

Next Generation Sequencing ◽

Acute Gastroenteritis ◽

Clinical Analysis ◽

Viral Metagenomics ◽

Next Generation ◽

Sequencing Data ◽

Viral Pathogens ◽

Viral Pathogen ◽

Infectious Gastroenteritis ◽

Generation Sequencing

Acute infectious gastroenteritis is an important illness worldwide, especially on children, with viruses accounting for approximately 70% of the acute cases. A high number of these cases have an unknown etiological agent and the rise of next generation sequencing technologies has opened new opportunities for viral pathogen detection and discovery. Viral metagenomics in routine clinical settings has the potential to identify unexpected or novel variants of viral pathogens that cause gastroenteritis. In this study, 124 samples from acute gastroenteritis patients from 2012–2014 previously tested negative for common gastroenteritis pathogens were pooled by age and analyzed by next generation sequencing (NGS) to elucidate unidentified viral infections. The most abundant sequences detected potentially associated to acute gastroenteritis were from Astroviridae and Caliciviridae families, with the detection of norovirus GIV and sapoviruses. Lower number of contigs associated to rotaviruses were detected. As expected, other viruses that may be associated to gastroenteritis but also produce persistent infections in the gut were identified including several Picornaviridae members (EV, parechoviruses, cardioviruses) and adenoviruses. According to the sequencing data, astroviruses, sapoviruses and NoV GIV should be added to the list of viral pathogens screened in routine clinical analysis.

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Next Generation Sequencing Based In-house HIV Genotyping Method: Validation Report

10.21203/rs.3.rs-386721/v1 ◽

2021 ◽

Author(s):

Alisen Ayitewala ◽

Isaac Ssewanyana ◽

Charles Kiyaga

Keyword(s):

Drug Resistance ◽

Quality Control ◽

Next Generation Sequencing ◽

Low Income ◽

Rna Extraction ◽

Clinical Samples ◽

Small Range ◽

Next Generation ◽

Genotyping Method ◽

Generation Sequencing

Abstract BackgroundHIV genotyping has had a significant impact on care and treatment of HIV/AIDS. At clinical level, the test guides physicians on the choice of treatment regimens. At surveillance level, it informs policy on consolidated treatment guidelines and microbial resistance control strategies. Until recently, the conventional test has utilized Sanger sequencing (SS) method. Unlike Next Generation Sequencing (NGS), SS is limited by low data throughput and the inability of detecting low abundant drug resistant variants. NGS has the capacity to improve sensitivity and quantitatively identify low-abundance variants; in addition, it has the potential to improve efficiency as well as lowering costs when samples are batched. Despite the NGS benefits, its utilization in clinical drug resistance profiling is faced with mixed reactions. These are largely based on lack of a consensus regarding the quality control strategy. Nonetheless, transitional views suggest validating the method against the gold-standard SS. Therefore, we present a validation report of an NGS-based in-house HIV genotyping method against SS method in Uganda. ResultsSince there were no established proficiency test panels for NGS-based HIV genotyping, fifteen (15) clinical plasma samples for routine care were utilized. The use of clinical samples allowed for accuracy and precision studies. The workflow involved four (4) main steps; viral RNA extraction, targeted amplicon generation, amplicon sequencing and data analysis. Accuracy of 98% with an average percentage error of 3% was reported for the NGS based assay against the SS platform demonstrating similar performance. The coefficient of variation (CV) findings for both the inter-run and inter-personnel precision showed no variability (CV ≤0%) at the relative abundance of ≥20%. For both inter-run and inter-personnel, variation that affected the precision was observed at 1% frequency. Overall, for all the frequencies, CV registered a small range of (0-2%).Conclusion The NGS-based in-house HIV genotyping method fulfilled the minimum requirements that support its utilization for drug resistance profiling in a clinical setting of a low-income country. For more inclusive quality control studies, well characterized wet panels need to be established.

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Factors Impacting Clinically Relevant RNA Fusion Assays Using Next-Generation Sequencing

Archives of Pathology & Laboratory Medicine ◽

10.5858/arpa.2020-0415-oa ◽

2021 ◽

Author(s):

Nisha S. Ramani ◽

Keyur P. Patel ◽

Mark J. Routbort ◽

Hector Alvarez ◽

Russell Broaddus ◽

...

Keyword(s):

Next Generation Sequencing ◽

Core Needle Biopsy ◽

Needle Biopsy ◽

Rna Extraction ◽

Next Generation ◽

Success Rates ◽

Detection Rates ◽

Core Needle ◽

Rna Quality ◽

Generation Sequencing

Context.— RNA-based next-generation sequencing (NGS) assays are being used with increasing frequency for comprehensive molecular profiling of solid tumors. Objective.— To evaluate factors that might impact clinical assay performance. Design.— A 4-month retrospective review of cases analyzed by a targeted RNA-based NGS assay to detect fusions was performed. RNA extraction was performed from formalin-fixed, paraffin-embedded tissue sections and/or cytology smears of 767 cases, including 493 in-house and 274 outside referral cases. The types of samples included 422 core needle biopsy specimens (55%), 268 resection specimens (35%), and 77 cytology samples (10%). Results.— Successful NGS fusion testing was achieved in 697 specimens (90.9%) and correlated positively with RNA yield (P < .001) and negatively with specimen necrosis (P = .002), decalcification (P < .001), and paraffin block age of more than 2 years (P = .001). Of the 697 cases that were successfully sequenced, 50 (7.2%) had clinically relevant fusions. The testing success rates and fusion detection rates were similar between core needle biopsy and cytology samples. In contrast, RNA fusion testing was often less successful using resection specimens (P = .007). Testing success was independent of the tumor percentage in the specimen, given that at least 20% tumor cellularity was present. Conclusions.— The success of RNA-based NGS testing is multifactorial and is influenced by RNA quality and quantity. Identification of preanalytical factors affecting RNA quality and yield can improve NGS testing success rates.

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BURST enables mathematically optimal short-read alignment for big data

10.1101/2020.09.08.287128 ◽

2020 ◽

Author(s):

Gabriel Al-Ghalith ◽

Dan Knights

Keyword(s):

Next Generation Sequencing ◽

Dna Sequences ◽

Heuristic Algorithms ◽

Database Search ◽

Next Generation Sequencing Data ◽

Next Generation ◽

Genome Database ◽

Short Read ◽

Lowest Common Ancestor ◽

Generation Sequencing

AbstractOne of the fundamental tasks in analyzing next-generation sequencing data is genome database search, in which DNA sequences are compared to known reference genomes for identification or annotation. Although algorithms exist for optimal database search with perfect sensitivity and specificity, these have largely been abandoned for next-generation sequencing (NGS) data in favor of faster heuristic algorithms that sacrifice alignment quality. Virtually all DNA alignment tools that are commonly used in genomic and metagenomic database search use approximate methods that sometimes report the wrong match, and sometimes fail to find a valid match when present. Here we introduce BURST, a high-throughput DNA short-read aligner that uses several new synergistic optimizations to enable provably optimal alignment in NGS datasets. BURST finds all equally good matches in the database above a specified identity threshold and can either report all of them, pick the most likely among tied matches, or provide lowest-common-ancestor taxonomic annotation among tied matches. BURST can align, disambiguate, and assign taxonomy at a rate of 1,000,000 query sequences per minute against the RefSeq v82 representative prokaryotic genome database (5,500 microbial genomes, 19GB) at 98% identity on a 32-core computer, representing a speedup of up to 20,000-fold over current optimal gapped alignment techniques. This may have broader implications for clinical applications, strain tracking, and other situations where fast, exact, extremely sensitive alignment is desired.

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