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SHR Neuro Krebs Kardio Lipid Stoffw Microb

Krappinger, JC; Radkohl, A; Schusterbauer, V; Emmerstorfer-Augustin, A; Feichtinger, J.
Pichia pastoris RNA-Sequencing and Data Analysis.
Methods Mol Biol. 2026; 2697: 55-75. Doi: 10.1007/978-1-0716-4779-0_4
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Führende Autor*innen der Med Uni Graz
Feichtinger Julia
Krappinger Julian Christopher
Co-Autor*innen der Med Uni Graz
Schusterbauer Veronika
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Abstract:
RNA sequencing (RNA-seq) allows for transcriptome profiling, usually with the goal of comparing the gene expression between conditions of interest. Transcriptome profiling helped to understand and improve the use of microbes in industrial processes, as exemplified numerous times for the biotechnologically relevant yeast Komagataella phaffii. A typical RNA-seq experiment begins with (a) experimental design, (b) RNA extraction, and (c) library preparation and sequencing and continues with its data analysis, including (d) quality control and preprocessing, (e) alignment, (f) quantification, and (g) differential gene expression analysis. In particular, experimental design should be considered carefully, while RNA extraction is relatively straightforward, and library preparation and sequencing are commonly purchased as a service. RNA-seq data analysis can be carried out in a number of ways and comprises a sequence of steps with many aspects to consider. Here, we provide a protocol for RNA extraction, a summary of aspects to consider for experimental design, library preparation, and sequencing, as well as the basics of a data analysis workflow.
Find related publications in this database (using NLM MeSH Indexing)
Gene Library - administration & dosage
Gene Expression Profiling - methods
Sequence Analysis, RNA - methods
RNA, Fungal - genetics, isolation & purification
Saccharomycetales - genetics
Data Analysis - administration & dosage
Transcriptome - administration & dosage
High-Throughput Nucleotide Sequencing - methods
RNA-Seq - methods
Workflow - administration & dosage

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