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Anders Krogh

Publications and source records attributed to Anders Krogh.

2 recordsLinked to original sources

Highly accessible AU-rich regions in 3′ untranslated regions are hotspots for binding of proteins and miRNAs

BackgroundMicroRNAs (miRNAs) are endogenous short non-coding RNAs involved in the regulation of gene expression at the post-transcriptional level typically by promoting destabilization or translational repression of target RNAs. Sometimes this regulation is absent or different, which likely is the result of interactions with other post-transcriptional factors, particularly RNA-binding proteins (RBPs). Despite the importance of the interactions between RBPs and miRNAs, little is known about how they affect post-transcriptional regulation in a global scale.\n\nResultsIn this study, we have analyzed CLIP datasets of 49 RBPs in HEK293 cells with the aim of understanding the interplay between RBPs and miRNAs in post-transcriptional regulation. Our results show that RBPs bind preferentially in conserved regulatory hotspots that frequently contain miRNA target sites. This organization facilitates the competition and cooperation among RBPs and the regulation of miRNA target site accessibility. In some cases RBP enrichment on target sites correlates with miRNA expression, suggesting coordination between the regulatory factors. However, in most cases, competition among factors is the most plausible interpretation of our data. Upon AGO2 knockdown, transcripts that contain such hotspots that overlap target sites of expressed miRNAs in 3UTRs are significantly less up-regulated than transcripts without them, suggesting that RBP binding limits miRNA accessibility.\n\nConclusionsWe show that RBP binding is concentrated in regulatory hotspots in 3UTRs. The presence of these hotspots facilitates the interaction among post-transcriptional regulators, that interact or compete with each other under different conditions. These hotspots are enriched in genes with regulatory functions such as DNA binding and RNA binding. Taken together, our results suggest that hotspots are important regulatory regions that define an extra layer of auto-regulatory control of post-transcriptional regulation.

Bioinformatics

Kaiju: Fast and sensitive taxonomic classification for metagenomics

The constantly decreasing cost and increasing out-put of current sequencing technologies enable large scale metagenomic studies of microbial communities from diverse habitats. Therefore, fast and accurate methods for taxonomic classification are needed, which can operate on increasingly larger datasets and reference databases. Recently, several fast metagenomic classifiers have been developed, which are based on comparison of genomic k-mers. However, nucleotide comparison using a fixed k-mer length often lacks the sensitivity to overcome the evolutionary distance between sampled species and genomes in the reference database. Here, we present the novel metagenome classifier Kaiju for fast assignment of reads to taxa. Kaiju finds maximum exact matches on the protein-level using the Borrows-Wheeler transform, and can optionally allow amino acid substitutions in the search using a greedy heuristic. We show in a genome exclusion study that Kaiju can classify more reads with higher sensitivity and similar precision compared to fast k-mer based classifiers, especially in genera that are underrepresented in reference databases. We also demonstrate that Kaiju classifies more than twice as many reads in ten real metagenomes compared to programs based on genomic k-mers. Kaiju can process up to millions of reads per minute, and its memory footprint is below 6 GB of RAM, allowing the analysis on a standard PC. The program is available under the GPL3 license at: http://bioinformatics-centre.github.io/kaiju

Bioinformatics