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Gleeson, J.

Publications and source records attributed to Gleeson, J..

2 recordsLinked to original sources

Nanopore direct RNA sequencing detects differential expression between human cell populations

Accurately quantifying gene and isoform expression changes is essential to understanding cell functions, differentiation and disease. Therefore, a crucial requirement of RNA sequencing is identifying differential expression. The recent development of long-read direct RNA (dRNA) sequencing has the potential to overcome many limitations of short and long-read sequencing methods that require RNA fragmentation, cDNA synthesis or PCR. dRNA sequences native RNA and can encompass an entire RNA in a single read. However, its ability to identify differential gene and isoform expression in complex organisms is poorly characterised. Using a mixture of synthetic controls and human SH-SY5Y cell differentiation into neuron-like cells, we show that dRNA sequencing accurately quantifies RNA expression and identifies differential expression of genes and isoforms. We generated [~]4 million dRNA reads with a median length of 991 nt. On average, reads covered 74% of SH-SY5Y transcripts and 29% were full-length. Measurement of expression and fold changes between synthetic control RNAs confirmed accurate quantification of genes and isoforms. Differential expression of 231 genes, 291 isoforms, plus 27 isoform switches were detected between undifferentiated and differentiated SH-SY5Y cells and samples clustered by differentiation state at the gene and isoform level. Genes upregulated in neuron-like cells were associated with neurogenesis. We further identified >30,000 expressed transcripts including thousands of novel splice isoforms and transcriptional units. Our results establish the ability of dRNA sequencing to identify biologically relevant differences in gene and isoform expression and perform the key capabilities of expression profiling methodologies.

genomics

Negative selection on human genes causing severe inborn errors depends on disease outcome and both the mode and mechanism of inheritance

BackgroundGenetic variants underlying severe diseases are less likely to be transmitted to the next generation, and are thus gradually and selectively eliminated from the population through negative selection. Here, we study the determinants of this evolutionary process in genes underlying severe diseases in humans. ResultsWe propose a novel approach, CoNeS, integrating known negative selection scores through principal component projection. We compare evidence for negative selection at 319 genes underlying inborn errors of immunity (IEI), which are life-threatening monogenic disorders. We find that genes underlying autosomal dominant (AD) or X-linked IEI are under stronger negative selection than those underlying autosomal recessive (AR) IEI, which are under no stronger selection than genes not known to be disease-causing. However, we find that genes with mutations causing AR IEI that are lethal before reproductive maturity and that display complete penetrance are under stronger negative selection than other genes underlying AR IEI. We also find that genes underlying AD IEI by haploinsufficiency are under stronger negative selection than other genes underlying AD IEI. Finally, we replicate these results in a study of 1,140 genes causing inborn errors of neurodevelopment. ConclusionsThese findings collectively show that the clinical outcomes of inborn errors, together with the mode and mechanism of inheritance of these errors, determine the strength of negative selection acting on severe disease-causing genes. These findings suggest that estimating the intensity of negative selection with CoNeS may facilitate the selection of candidate genes in patients suspected to carry an inborn error.

genetics