Science Hub

Molecular Biology

Welcome to Nordic BioSite's Life Science Blog. Here, we will provide commentary on current events and trends in biological sciences, interesting stories about important scientists, technical tips and suggestions, and much more. Read on and learn something new.
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Size Selection for NGS

In previous posts about next generation sequencing (NGS), we covered the key steps in library preparation (for RNA-seq), top tips for NGS success, and the ins and outs of long-read DNA sequencing. This time we will look more closely at size selection.

One-Step RT-PCR

Anyone working with gene expression, transcriptional regulation or cDNA cloning will undoubtedly have used reverse-transcription PCR (RT-PCR) at some point in their workflow.

RT-PCR is usually carried out as a two-step process: first, total or mRNA-enriched RNA is converted to complementary DNA (cDNA) by a reverse transcriptase (RT) enzyme. The cDNA is then used as a template for PCR.

Gene Expression Analysis: RNA-Seq or Real-Time PCR?

If you’ve been following our blog posts over the last few months, you’ll have noticed our series on RNA-seq and real-time PCR. Although the underlying principles behind these two techniques are different, both can provide information about the amount (absolute or relative) of mRNA isolated from any sample type.

Multiplex Real-Time PCR for Beginners

In case the name doesn’t give it away, multiplex real-time PCR involves amplifying multiple DNA or RNA targets simultaneously in a single PCR reaction. This requires the presence of a specific pair of primers and a complementary DNA-binding probe for each target under study.

Size Matters! Long-Read DNA Sequencing

Modern genomics seems to be undergoing a shift from using short-read technologies to sequence large numbers of genomes with the aim of detecting SNPs, to sequencing fewer genomes using long-read technologies that can resolve more complex events, e.g., structural rearrangements, copy number variations, and repeat expansions.

RNA-Seq 5: Data Validation

RNA-seq generates vast amounts of data and when all of this is sorted out and boiled down to results, the researcher is usually left with lists and heat maps showing transcripts that are expressed, upregulated or downregulated across the experimental conditions tested. Exactly how and in what situations this data should be validated is a topic of debate among researchers.