Of interst: Chen et al. "Transcript level is a key factor affecting RNAi efficiency"

Pestic Biochem Physiol. 2021 Jul;176:104872. doi: 10.1016/j.pestbp.2021.104872.

Transcript level is a key factor affecting RNAi efficiency.

Chen J, Peng Y, Zhang H, Wang K, Tang Y, Gao J, Zhao C, Zhu G, Palli SR, Han Z

Abstract:

Efficiency is the basis for the application of RNA interference (RNAi) technology. Actually, RNAi efficiency varies greatly among insect species, tissues and genes. Previous efforts have revealed the mechanisms for variation among insect species and tissues. Here, we investigated the reason for variable  efficiency among the target genes in the same insect. First, we tested the genes sampled randomly from Tribolium castaneum, Locusta migratoria and Drosophila S2 cells for both their expression levels and sensitivity to RNAi. The results indicated that the genes with higher expression levels were more sensitive to RNAi. Statistical analysis showed that the correlation coefficients between transcript levels and knockdown efficiencies were 0.8036 (n = 90), 0.7255 (n = 18) and 0.9505 (n = 13), respectively in T. castaneum, L. migratoria and Drosophila S2 cells. Subsequently, ten genes with varied expression level in
different tissues (midgut and carcass without midgut) of T. castaneum were tested. The results indicated that the higher knockdown efficiency was always obtained in the tissue where the target gene expressed higher. In addition, three genes were tested in different developmental stages, larvae and pupae of T. castaneum. The results found that when the expression level increased after insect pupation, these genes became more sensitive to RNAi. Thus, all the proofs support unanimously that transcript level is a key factor affecting RNAi sensitivity. This finding allows for a better understanding of the RNAi efficiency variation and lead to effective or efficient use of RNAi technology.

DOI: 10.1016/j.pestbp.2021.104872
PMID: 34119217 [Indexed for MEDLINE]

Study uses transcriptomics and in vivo RNAi follow-up to explore sleep

Tomita J, Ueno T, Mitsuyoshi M, Kume S, Kume K. The NMDA Receptor Promotes Sleep in the Fruit Fly, Drosophila melanogaster. PLoS One. 2015 May 29;10(5):e0128101. PMID: 26023770; PMCID: PMC4449117.  

From the abstract: "... sleep is essential for learning and memory. Drosophila melanogaster has emerged as a novel model for studying sleep. ... we carried out a microarray analysis comparing mRNA expression in heads of fmn and control flies and found that 563 genes are differentially expressed. Next, using the pan-neuronal Gal4 driver elav-Gal4 and UAS-RNA interference (RNAi) to knockdown individual genes, we performed a functional screen. We found that knockdown of the NMDA type glutamate receptor channel gene (Nmdar1) (also known as dNR1) reduced sleep. ..."

Over-expression of transcription factors--resource and screen paper from Deplancke lab

Early online at Genome Research:  A large-scale, in vivo transcription factor screen defines bivalent chromatin as a key property of regulatory factors mediating Drosophila wing development. Claus Schertel, Monica Albarca, Claudia Rockel-Bauer, Nicholas W Kelley, Johannes Bischof, Korneel Hens, Erik van Nimwegen, Konrad Basler and Bart Deplancke. 2015.

From the abstract: "... We generated 596 site-directed transgenic Drosophila lines that contain integrations of individual UAS-TF constructs to facilitate spatio-temporally controlled misexpression in vivo. All transgenes were expressed in the developing wing and two thirds induced specific phenotypic defects. In vivo knock-down of the same genes yielded a phenotype for 50%, with both methods indicating a great potential for misexpression to characterize novel functions in wing growth, patterning and development. Thus, our UAS-TF library provides an important addition to the genetic toolbox of Drosophila research ..."

DRSC announces launch of FlyPrimerBank online resource

The DRSC is pleased to announce the launch of FlyPrimerBank.

FlyPrimerBank is built around a database of three precomputed qPCR primer pairs per Drosophila gene. Online search output includes information about the primer pairs and when available, validation test results from our group or the community at large.

For details please see our paper, just out in the journal G3. You can also check out the documentation page.

Important for RNAi studies, FlyPrimerBank can report overlap between the primers and RNAi reagents in public collections. This helps you avoid choosing primers that could amplify the reagent.

As always, your feedback on the online resource is welcome.

FlyPrimerBank also makes it possible for you to indicate which qPCR primers in FlyPrimerBank have or have not worked for them, or to upload the sequences of good primer pairs not already in the database.

With your help, the utility of the resource will further increase over time.

RNAi and RNA analysis. Cell cycle study. Breaking report.

These authors follow RNAi screening for DNA content in S2 cells with transcriptional profiling to uncover transcriptional networks. Bonke M, Turunen M, Sokolova M, Vähärautio A, Kivioja T, Taipale M, Björklund M, Taipale J. Transcriptional networks controlling the cell cycle. G3 (Bethesda). 2013 Jan;3(1):75-90. doi: 10.1534/g3.112.004283. PubMed PMID: 23316440.

Breaking Report: DRSC screen for modifiers of Notch transcriptional activity

On my desk today? A report of a screen performed using the DRSC full-genome library.

Mourikis et al. (2010) Modifiers of notch transcriptional activity identified by genome-wide RNAi. BMC Developmental Biology. http://www.biomedcentral.com/1471-213X/10/107

Breaking Report: RNAi on RNA

On my desk today? A report that uses RNAi to study an aspect of RNA biology--in this case, knockdown of specific exosome factors followed by genome-wide analysis of mRNAs is used to gain insight into exosome functions.

Kiss & Andrulis (2010) Genome-wide analysis reveals distinct substrate specificities of Rrp6, Dis3, and core exosome subunits. RNA 16: 781-791. doi: 10.1261/rna.1906710