siPOOLs: robust reagents for gene silencing

siPOOLs: robust reagents for gene silencing

Although we talk a lot about off-targets, one of the main advantages of siPOOLs (complex siRNA pools) compared to single siRNAs or mini-pools (Dharmacon) is that they provide near optimum silencing of target genes. Two siPOOLs for the same gene give very similar knock down levels, and their silencing is around the best of any single siRNA. Given how many candidate siRNAs there are for a gene, and how difficult it is to accurately predict silencing levels, this makes siPOOLs Read More

Cutting the Gordian Knot of RNAi off-targets

Cutting the Gordian Knot of RNAi off-targets

The C911 siRNA control generated a lot of excitement in the RNAi world when it emerged ~11 years ago. A former colleague, who was a pioneer in the commercialisation of RNAi, described it then as the biggest breakthrough in the last 10 years of RNAi research. The idea of the C911 control is to get rid of the on-target effect of the siRNA by using the complement of bases 9-11, while retaining any off-target (seed-based) effects of the siRNA, which Read More

Our Team’s Favorite RNA Molecules🧬

Our Team’s Favorite RNA Molecules🧬

At siTOOLs we are celebrating RNA day (Aug. 1st) the entire month with a focus on all things RNA and a promotion on siPOOLs and riboPOOLs. RNA day is celebrated the 1st of August, since the RNA codon that initiates protein synthesis is made of the following nucleotides: adenine (A), uracil (U), and guanine (G). AUG codes for the amino acid methionine (Met) in eukaryotes and formyl methionine (fMet) in prokaryotes. RNA is one of the most versatile biomolecules in Read More

RNAi vs CRISPR: RNAi even better at finding essential genes

RNAi vs CRISPR: RNAi even better at finding essential genes

Which technology is better, RNAi or CRISPR? The best answer to this question, like so many others is, it depends. If cells can adapt and compensate for loss of the gene, or you want to titrate gene levels (important in drug discovery), then RNAi will be better. If a gene’s transcripts have lots of secondary structure and must be silenced to 99.9% in order to see an assay phenotype, then CRISPR may be better. We have used two large datasets Read More

Chemical modifications only shift the siRNA seed profile

Chemical modifications only shift the siRNA seed profile

In the last post, we saw that chemically modified ON-TARGETplus siRNAs still have a strong seed effect. The seed-based off-target effects (measured by correlation of reagents with the same 7mer seed) were as strong for chemically modified ON-TARGETplus (R = 0.50) and Silencer Select (R = 0.59) as what we typically see with unmodified siRNAs (Qiagen, siGENOME, or Silencer). Chemical modification must not prevent seed-based target recognition, because RISC uses the seed to scan the transcriptome for target sites. Because Read More

ON-TARGETplus siRNAs have strong off-target effects (despite chemical modification)

ON-TARGETplus siRNAs have strong off-target effects (despite chemical modification)

History of chemical modifications Chemical modification has long been proposed as a way to limit the off-target effects of siRNAs. The earliest siRNAs from the two main commercial suppliers (siGENOME from Dharmacon/Horizon Discovery, and Silencer from Ambion/ThermoFisher) were quickly replaced with new chemically-modified siRNAs (ON-TARGETplus from Dharmacon, and Silencer Select from Ambion). We have already seen that Silencer Select siRNAs, despite their chemical modification, maintain a strong off-target seed effect. The phenotypic correlation between siGENOME (unmodified) and ON-TARGETplus (chemically modified) Read More

A journey into the gut microbial control center: small RNA’s influence on Bacteroides thetaiotaomicron’s metabolism

A journey into the gut microbial control center: small RNA’s influence on Bacteroides thetaiotaomicron’s metabolism

Bacteroides thetaiotaomicron is a commensal bacterium that inhabits primarily the human large intestine and is considered one of the most important members of this microbial community. B. thetaiotaomicron is a highly versatile microbe, capable of utilizing a wide range of carbohydrates including those that are indigestible by human enzymes. It breaks down complex polysaccharides from plant cell walls and other dietary sources, producing short-chain fatty acids (SCFAs) that are an important energy source for humans. Furthermore, it has also been Read More

The Hidden World of Microbiomes and Their Impact on Our Lives

The Hidden World of Microbiomes and Their Impact on Our Lives

Microbiomes are the diverse communities of microorganisms that inhabit different parts of our bodies, as well as the environment around us. In recent years, research has revealed the vast and complex hidden world of microbiomes and their impact on our lives, from influencing our digestion and immune system to potentially affecting our mood and behavior. Advances in technology have enabled scientists to study microbiomes in unprecedented detail, leading to new insights into their diversity and functions. Understanding the microbiome and Read More

Microbiome May Blog Series

Microbiome May Blog Series

Hi there and welcome to our May blog series inspired by microbiomes🧫👾! We’re excited to announce that we will be launching a new blog series on microbiomes, featuring topics ranging from skin microbiomes to gut microbiomes. Our riboPOOLs kits have been used in numerous studies exploring the intricacies of microbiomes, and we’re thrilled to share our knowledge with you.  Additionally, as May is the month of microbiomes, we are offering a 15% discount on all of our microorganism riboPOOLs kits and probes (24 and 96 reactions). Read More

Similar seed effects in independent siRNA screens

Similar seed effects in independent siRNA screens

A 2013 study on Parkin translocation used genome-wide siRNA libraries from Ambion (single Silencer Select siRNAs) and Dharmacon (pools of 4 siGENOME siRNAs). The correlation between results for the same on-target gene from the two libraries was very low (R = 0.09). (Each point in the following plot is for a gene.) The correlation between results for the same 7mer seed were higher (0.26), providing another example of the Iron Law of RNAi Screening. (Each point in the following plot Read More

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