scholarly journals Performance comparison of gel and capillary electrophoresis-based microsatellite genotyping strategies in a population research and kinship testing framework

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Julissa J. Sánchez-Velásquez ◽  
Lorenzo E. Reyes-Flores ◽  
Carmen Yzásiga-Barrera ◽  
Eliana Zelada-Mázmela
Keyword(s):  
Genetic Diversity ◽  
Capillary Electrophoresis ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Polyacrylamide Gel Electrophoresis ◽  
Allelic Diversity ◽  
Genomic Data ◽  
Performance Comparison ◽  
Molecular Techniques ◽  
Population Research

Abstract Objective The advancement of molecular techniques in an era in which high-throughput sequencing has revolutionized biology renders old-fashioned alternatives to high-throughput methods obsolete. Such advanced molecular techniques, however, are not yet accessible to economically disadvantaged region-based laboratories that still obtain DNA profiles using gel-based techniques. To explore whether cost-efficient techniques can produce results that are as robust as those obtained using high-throughput methods, we compared the performance of polyacrylamide gel electrophoresis (PAGE)- and capillary electrophoresis (CE)-derived genomic data in estimating genetic diversity and inferring relatedness using 70 individuals of fine flounder (Paralichthys adspersus) selected from a hatchery population and genotyped for five microsatellite loci. Results Here, we show that PAGE- and CE-derived genomic datasets yield comparable genetic diversity levels regarding allelic diversity measures and heterozygosity. However, relatedness inferred from each dataset showed that the categorization of dyads in the different relationship categories strongly differed. This suggests that while scientists can reliably use PAGE-derived genomic data to estimate genetic diversity, they cannot use the same for parentage testing. The findings could help laboratories committed to population research not be discouraged from using the PAGE system if high-throughput technologies are unavailable and the method is adequate to address the biological question.

scholarly journals Assessing and Maximizing Cultivated Diversity with Plate-Wash PCR and High Throughput Sequencing

2020 ◽  
Author(s):  
Emily N. Junkins ◽  
Bradley S. Stevenson
Keyword(s):  
High Throughput ◽  
Drug Targets ◽  
High Throughput Sequencing ◽  
Multidrug Resistant ◽  
Molecular Techniques ◽  
Bioactive Metabolites ◽  
Plate Count ◽  
Molecular Tools ◽  
Vast Number ◽  
Sequencing Studies

AbstractMolecular techniques continue to reveal a growing disparity between the immense diversity of microbial life and the small proportion that is in pure culture. The disparity, originally dubbed “the great plate count anomaly” by Staley and Konopka, has become even more vexing given our increased understanding of the importance of microbiomes to a host and the role of microorganisms in the vital biogeochemical functions of our biosphere. Searching for novel antimicrobial drug targets often focuses on screening a broad diversity of microorganisms. If diverse microorganisms are to be screened, they need to be cultivated. Recent innovative research has used molecular techniques to assess the efficacy of cultivation efforts, providing invaluable feedback to cultivation strategies for isolating targeted and/or novel microorganisms. Here, we aimed to determine the efficiency of cultivating representative microorganisms from a non-human, mammalian microbiome, identify those microorganisms, and determine the bioactivity of isolates. Molecular methods indicated that around 57% of the ASVs detected in the original inoculum were cultivated in our experiments, but nearly 53% of the total ASVs that were present in our cultivation experiments were not detected in the original inoculum. In light of our controls, our data suggests that when molecular tools were used to characterize our cultivation efforts, they provided a more complete, albeit more complex, understanding of which organisms were present compared to what was eventually cultivated. Lastly, about 3% of the isolates collected from our cultivation experiments showed inhibitory bioactivity against a multidrug-resistant pathogen panel, further highlighting the importance of informing and directing future cultivation efforts with molecular tools.ImportanceCultivation is the definitive tool to understand a microorganism’s physiology, metabolism, and ecological role(s). Despite continuous efforts to hone this skill, researchers are still observing yet-to-be cultivated organisms through high-throughput sequencing studies. Here, we use the very same tool that highlights biodiversity to assess cultivation efficiency. When applied to drug discovery, where screening a vast number of isolates for bioactive metabolites is common, cultivating redundant organisms is a hindrance. However, we observed that cultivating in combination with molecular tools can expand the observed diversity of an environment and its community, potentially increasing the number of microorganisms to be screened for natural products.

scholarly journals High-Throughput Sequencing Reveals Further Diversity of Little Cherry Virus 1 with Implications for Diagnostics

Viruses ◽  
2018 ◽  
Vol 10 (7) ◽  
pp. 385 ◽  
Author(s):  
Asimina Katsiani ◽  
Varvara Maliogka ◽  
Nikolaos Katis ◽  
Laurence Svanella-Dumas ◽  
Antonio Olmos ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Sour Cherry ◽  
Prunus Species ◽  
Cherry Tree ◽  
High Genetic Diversity ◽  
Viral Genomes ◽  
Virus Diversity ◽  
First Time

Little cherry virus 1 (LChV1, Velarivirus, Closteroviridae) is a widespread pathogen of sweet or sour cherry and other Prunus species, which exhibits high genetic diversity and lacks a putative efficient transmission vector. Thus far, four distinct phylogenetic clusters of LChV1 have been described, including isolates from different Prunus species. The recent application of high throughput sequencing (HTS) technologies in fruit tree virology has facilitated the acquisition of new viral genomes and the study of virus diversity. In the present work, several new LChV1 isolates from different countries were fully sequenced using different HTS approaches. Our results reveal the presence of further genetic diversity within the LChV1 species. Interestingly, mixed infections of the same sweet cherry tree with different LChV1 variants were identified for the first time. Taken together, the high intra-host and intra-species diversities of LChV1 might affect its pathogenicity and have clear implications for its accurate diagnostics.

Performance comparison of benchtop high-throughput sequencing platforms

2012 ◽  
Vol 30 (5) ◽  
pp. 434-439 ◽  
Author(s):  
Nicholas J Loman ◽  
Raju V Misra ◽  
Timothy J Dallman ◽  
Chrystala Constantinidou ◽  
Saheer E Gharbia ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Performance Comparison ◽  
Sequencing Platforms

scholarly journals SNP identification and validation on genomic DNA for studying genetic diversity in Thunnus albacares and Scomberomorus brasiliensis by combining RADseq and long read high throughput sequencing

2018 ◽  
Vol 198 ◽  
pp. 189-194 ◽  
Author(s):  
Zoila Raquel Siccha-Ramirez ◽  
Francesco Maroso ◽  
Belén G. Pardo ◽  
Carlos Fernández ◽  
Paulino Martínez ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
High Throughput ◽  
Genomic Dna ◽  
High Throughput Sequencing ◽  
Thunnus Albacares ◽  
Long Read

High-throughput sequencing analysis reveals the genetic diversity of different regions of the murine norovirus genome during in vitro replication

2016 ◽  
Vol 162 (4) ◽  
pp. 1019-1023 ◽  
Author(s):  
Axel Mauroy ◽  
Bernard Taminiau ◽  
Carine Nezer ◽  
Elsa Ghurburrun ◽  
Denis Baurain ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Sequencing Analysis ◽  
Murine Norovirus ◽  
In Vitro Replication

scholarly journals NPARS—A Novel Approach to Address Accuracy and Reproducibility in Genomic Data Science

2021 ◽  
Vol 4 ◽  
Author(s):  
Li Ma ◽  
Erich A. Peterson ◽  
Ik Jae Shin ◽  
Jason Muesse ◽  
Katy Marino ◽  
...  
Keyword(s):  
High Throughput ◽  
Quantitative Methods ◽  
Data Science ◽  
High Throughput Sequencing ◽  
Genomic Data ◽  
Scientific Data ◽  
Genomic Research ◽  
Data Sets ◽  
Novel Approach ◽  
Genomic Studies

Background: Accuracy and reproducibility are vital in science and presents a significant challenge in the emerging discipline of data science, especially when the data are scientifically complex and massive in size. Further complicating matters, in the field of genomic-based science high-throughput sequencing technologies generate considerable amounts of data that needs to be stored, manipulated, and analyzed using a plethora of software tools. Researchers are rarely able to reproduce published genomic studies.Results: Presented is a novel approach which facilitates accuracy and reproducibility for large genomic research data sets. All data needed is loaded into a portable local database, which serves as an interface for well-known software frameworks. These include python-based Jupyter Notebooks and the use of RStudio projects and R markdown. All software is encapsulated using Docker containers and managed by Git, simplifying software configuration management.Conclusion: Accuracy and reproducibility in science is of a paramount importance. For the biomedical sciences, advances in high throughput technologies, molecular biology and quantitative methods are providing unprecedented insights into disease mechanisms. With these insights come the associated challenge of scientific data that is complex and massive in size. This makes collaboration, verification, validation, and reproducibility of findings difficult. To address these challenges the NGS post-pipeline accuracy and reproducibility system (NPARS) was developed. NPARS is a robust software infrastructure and methodology that can encapsulate data, code, and reporting for large genomic studies. This paper demonstrates the successful use of NPARS on large and complex genomic data sets across different computational platforms.

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