L. Stirling Churchman

The paper shows that FASTKD4-dependent processing of mitochondrial RNA junctions is required for efficient CYB translation by removing RNA structures that hinder mitoribosome engagement.

The paper introduces AIR-seq, a method that measures RNA dynamics without chemical conversion, improving RNA velocity inference and revealing hidden regulation.

The paper identifies MTERF1 as a suppressor of mtDNA deletion pathologies by showing its loss enhances mitochondrial function through transcriptional relief.

This study shows SRSF1 regulates 3'-end site selection through mechanisms both independent and dependent on U1 snRNP, affecting RNA isoform determination in breast cancer.

The paper investigates how mitochondrial translational activators (TAs) facilitate transcript-specific translation initiation by aligning mRNAs at the small mitoribosomal subunit.

The paper identifies Attractin as the receptor for Nigritoxin, a Vibrio toxin, and shows that related toxins use this receptor but have distinct effector domains.

The paper shows neuronal activity affects RNA stability, with HuD regulating mRNA abundance and variants linked to neurodevelopmental disorders disrupting this process.

The paper identifies a molecular switch at the yeast mitoribosomal tunnel exit that regulates cytochrome b synthesis by mediating interactions between translational activators and assembly factors.

The paper shows that transcription arrest in mitochondria leads to the formation of RNA granules that protect mt-mRNAs and help restore OXPHOS balance.

This study uses direct RNA nanopore sequencing to analyze allele-specific pre-mRNA maturation in human lymphoblastoid cell lines, revealing splicing order differences and SNP-splicing associations.

This study investigates how chloramphenicol and oxazolidinone antibiotics inhibit mitochondrial ribosomes, finding context-specific stalling similar to their bacterial action.

The paper quantifies RNA flow across subcellular compartments using TimeLapse-seq and identifies factors influencing mRNA life cycles.

The paper uses long-read single-molecule accessibility mapping to reveal that human mtDNA undergoes all-or-none global compaction, with most nucleoids in an inaccessible state.

The paper uses Fiber-seq to study RNA polymerase interactions with chromatin fibers, showing Pol II pausing affects nucleosomes and coordination between nearby transcriptional elements.

The paper identifies genes involved in mitochondrial and nuclear gene regulation for OXPHOS complex synthesis using genome-wide screens and characterizes their roles in mitochondrial RNA abundance and mitoribosome assembly.

This study shows that SUPT5H mutations disrupt RNA polymerase II pausing, delaying erythroid differentiation and cell cycle progression in human cells.

The paper shows that pre-mRNA splicing order in human cells is largely predetermined and conserved across cell types and differentiation stages, ensuring splicing fidelity.

The paper quantifies how transcription elongation in yeast is regulated by multiple factors balancing Pol II activity and gene expression.

This study identifies a network of histone chaperones and elongation factors that coordinate transcriptional accuracy and chromatin structure through their physical interactions.

GeneWalk identifies gene functions relevant to a biological context using network representation learning and validates it on RNA-seq and NET-seq data from human and mouse samples.

The paper shows Xrn1, a decay factor, modulates RNA polymerase II processivity in yeast genes, affecting transcription initiation, elongation, and termination.

The paper develops nano-COP to study co-transcriptional splicing in human and Drosophila cells, revealing that splicing order is not strictly transcriptional and is influenced by cis-regulatory elements.

This study shows Spt6 represses transcription initiation at thousands of intragenic promoters and regulates initiation at most genic promoters, proposing a model of initiation-site competition.

FIDDLE integrates multiple genomic data types to infer functional data without manual feature selection, showing improved performance over single-data-type models.