Machine learning-optimized targeted detection of alternative splicing.

RNA sequencing (RNA-seq) is widely adopted for transcriptome analysis but has inherent biases that hinder the comprehensive detection and quantification of alternative splicing. To address this, we present an efficient targeted RNA-seq method that greatly enriches for splicing-informative junction-spanning reads. Local splicing variation sequencing (LSV-seq) utilizes multiplexed reverse transcription from highly scalable pools of primers anchored near splicing events of interest.

Insights into the structure of NLR family member X1: Paving the way for innovative drug discovery.

Nucleotide-binding oligomerization domain, leucine rich repeat containing X1 (NLRX1) is a negative regulator of the nuclear factor kappa-light-chain-enhancer of activated B cells (NFκB) pathway, with a significant role in the context of inflammation. Altered expression of NLRX1 is prevalent in inflammatory diseases leading to interest in NLRX1 as a drug target. There is a lack of structural information available for NLRX1 as only the leucine-rich repeat domain of NLRX1 has been crystallised.

Machine learning-optimized targeted detection of alternative splicing.

RNA-sequencing (RNA-seq) is widely adopted for transcriptome analysis but has inherent biases which hinder the comprehensive detection and quantification of alternative splicing. To address this, we present an efficient targeted RNA-seq method that greatly enriches for splicing-informative junction-spanning reads. Local Splicing Variation sequencing (LSV-seq) utilizes multiplexed reverse transcription from highly scalable pools of primers anchored near splicing events of interest.