Browsing by Author "van Heusden, Peter"

Now showing 1 - 4 of 4
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    The combat-tb workbench: Making powerful Mycobacterium tuberculosis bioinformatics accessible
    (American Society for Microbiology, 2022) van Heusden, Peter; Mashologu, Ziphozakhe; Lose, Thoba
    Whole-genome sequencing (WGS) is a powerful method for detecting drug resistance, genetic diversity, and transmission dynamics of Mycobacterium tuberculosis. Implementation of WGS in public health microbiology laboratories is impeded by a lack of user-friendly, automated, and semiautomated pipelines. We present the COMBAT-TB Workbench, a modular, easy-to-install application that provides a web-based environment for Mycobacterium tuberculosis bioinformatics. The COMBAT-TB Workbench is built using two main software components: the IRIDA platform for its web-based user interface and data management capabilities and the Galaxy bioinformatics workflow platform for workflow execution.
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    Establishing minion sequencing and genome assembly procedures for the analysis of the rooibos (aspalathus linearis) genome
    (MDPI, 2022) Mgwatyu, Yamkela; Cornelissen, Stephanie; van Heusden, Peter
    While plant genome analysis is gaining speed worldwide, few plant genomes have been sequenced and analyzed on the African continent. Yet, this information holds the potential to transform diverse industries as it unlocks medicinally and industrially relevant biosynthesis pathways for bioprospecting. Considering that South Africa is home to the highly diverse Cape Floristic Region, local establishment of methods for plant genome analysis is essential. Long-read sequencing is becoming standard procedure for plant genome research, as these reads can span repetitive regions of the DNA, substantially facilitating reassembly of a contiguous genome. With the MinION, Oxford Nanopore offers a cost-efficient sequencing method to generate long reads; however, DNA purification protocols must be adapted for each plant species to generate ultra-pure DNA, essential for these analyses.
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    Galaxy training: A powerful framework for teaching!
    (NLM (Medline), 2023) Hiltemann, Saskia; Rasche, Helena; van Heusden, Peter
    There is an ongoing explosion of scientific datasets being generated, brought on by recent technological advances in many areas of the natural sciences. As a result, the life sciences have become increasingly computational in nature, and bioinformatics has taken on a central role in research studies. However, basic computational skills, data analysis, and stewardship are still rarely taught in life science educational programs, resulting in a skills gap in many of the researchers tasked with analysing these big datasets. In order to address this skills gap and empower researchers to perform their own data analyses, the Galaxy Training Network (GTN) has previously developed the Galaxy Training Platform (https://training.galaxyproject.org), an open access, community-driven framework for the collection of FAIR (Findable, Accessible, Interoperable, Reusable) training materials for data analysis utilizing the user-friendly Galaxy framework as its primary data analysis platform.
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    Transcriptomics of the Rooibos (Aspalathus linearis) Species Complex
    (MDPI, 2020) Stander, Emily Amor; Williams, Wesley; Mgwatu, Yamkela; Hesse, Uljana; van Heusden, Peter
    Rooibos (Aspalathus linearis), widely known as a herbal tea, is endemic to the Cape Floristic Region of South Africa (SA). It produces a wide range of phenolic compounds that have been associated with diverse health-promoting properties of the plant. The species comprises several growth forms that differ in their morphology and biochemical composition, only one of which is cultivated and used commercially. Here, we established methodologies for non-invasive transcriptome research of wild-growing South African plant species, including (1) harvesting and transport of plant material suitable for RNA sequencing; (2) inexpensive, high-throughput biochemical sample screening; (3) extraction of high-quality RNA from recalcitrant, polysaccharide- and polyphenol-rich plant material; and (4) biocomputational analysis of Illumina sequencing data, together with the evaluation of programs for transcriptome assembly (Trinity, IDBA-Trans, SOAPdenovo-Trans, CLC), protein prediction, as well as functional and taxonomic transcript annotation. In the process, we established a biochemically characterized sample pool from 44 distinct rooibos ecotypes (1–5 harvests) and generated four in-depth annotated transcriptomes (each comprising on average ≈86,000 transcripts) from rooibos plants that represent distinct growth forms and differ in their biochemical profiles. These resources will serve future rooibos research and plant breeding endeavors.