Optimization and comparison of different methods for RNA isolation for cDNA library construction from the reindeer lichen Cladonia rangiferina

<p>Abstract</p> <p>Background</p> <p>The reindeer lichen is the product of a mutualistic relationship between a fungus and an algae. Lichen demonstrate a remarkable capacity to tolerate dehydration. This tolerance is driven by a variety of biochemical processes and the accumulation of specific secondary metabolites that may be of relevance to the pharmaceutical, biotechnology and agriculture industries. These protective metabolites hinder <it>in vitro </it>enzymatic reactions required in cDNA synthesis. Along with the low concentrations of RNA present within lichen tissues, the process of creating a cDNA library is technically challenging.</p> <p>Findings</p> <p>An evaluation of existing commercial and published protocols for RNA extraction from plant or fungal tissues has been performed and experimental conditions have been optimised to balance the need for the highest quality total ribonucleotides and the constraints of budget, time and human resources.</p> <p>Conclusion</p> <p>We present a protocol that balances inexpensive RNA extraction methods with commercial RNA clean-up kits to yield sufficient RNA for cDNA library construction. Evaluation of the protocol and the construction of, and sampling from, a cDNA library is used to demonstrate the suitability of the RNA extraction method for expressed sequence tag production.</p

ILoReg: a tool for high-resolution cell population identification from single-cell RNA-seq data

Single-cell RNA-seq allows researchers to identify cell populations based on unsupervised clustering of the transcriptome. However, subpopulations can have only subtle transcriptomic differences and the high dimensionality of the data makes their identification challenging.\nWe introduce ILoReg, an R package implementing a new cell population identification method that improves identification of cell populations with subtle differences through a probabilistic feature extraction step that is applied before clustering and visualization. The feature extraction is performed using a novel machine learning algorithm, called iterative clustering projection (ICP), that uses logistic regression and clustering similarity comparison to iteratively cluster data. Remarkably, ICP also manages to integrate feature selection with the clustering through L1-regularization, enabling the identification of genes that are differentially expressed between cell populations. By combining solutions of multiple ICP runs into a single consensus solution, ILoReg creates a representation that enables investigating cell populations with a high resolution. In particular, we show that the visualization of ILoReg allows segregation of immune and pancreatic cell populations in a more pronounced manner compared with current state-of-the-art methods.\nILoReg is available as an R package at https://bioconductor.org/packages/ILoReg.\nSupplementary data are available at Supplementary Information and Supplementary Files 1 and 2.\nMOTIVATION\nRESULTS\nAVAILABILITY\nSUPPLEMENTARY INFORMATIO

scShaper: an ensemble method for fast and accurate linear trajectory inference from single-cell RNA-seq data

MotivationComputational models are needed to infer a representation of the cells, i.e. a trajectory, from single-cell RNA-sequencing data that model cell differentiation during a dynamic process. Although many trajectory inference methods exist, their performance varies greatly depending on the dataset and hence there is a need to establish more accurate, better generalizable methods.ResultsWe introduce scShaper, a new trajectory inference method that enables accurate linear trajectory inference. The ensemble approach of scShaper generates a continuous smooth pseudotime based on a set of discrete pseudotimes. We demonstrate that scShaper is able to infer accurate trajectories for a variety of trigonometric trajectories, including many for which the commonly used principal curves method fails. A comprehensive benchmarking with state-of-the-art methods revealed that scShaper achieved superior accuracy of the cell ordering and, in particular, the differentially expressed genes. Moreover, scShaper is a fast method with few hyperparameters, making it a promising alternative to the principal curves method for linear pseudotemporal ordering.Availability and implementationscShaper is available as an R package at https://github.com/elolab/scshaper. The test data are available at https://doi.org/10.5281/zenodo.5734488.</p

Reproducibility-optimized detection of differential DNA methylation

Compared with state-of-the-art methods, ROTS shows competitive sensitivity and specificity in detecting consistently differentially methylated regions

GSK3β Serine 389 Phosphorylation Modulates Cardiomyocyte Hypertrophy and Ischemic Injury

Prior studies show that glycogen synthase kinase 3β (GSK3β) contributes to cardiac ischemic injury and cardiac hypertrophy. GSK3β is constitutionally active and phosphorylation of GSK3β at serine 9 (S9) inactivates the kinase and promotes cellular growth. GSK3β is also phosphorylated at serine 389 (S389), but the significance of this phosphorylation in the heart is not known. We analyzed GSK3β S389 phosphorylation in diseased hearts and utilized overexpression of GSK3β carrying ser→ala mutations at S9 (S9A) and S389 (S389A) to study the biological function of constitutively active GSK3β in primary cardiomyocytes. We found that phosphorylation of GSK3β at S389 was increased in left ventricular samples from patients with dilated cardiomyopathy and ischemic cardiomyopathy, and in hearts of mice subjected to thoracic aortic constriction. Overexpression of either GSK3β S9A or S389A reduced the viability of cardiomyocytes subjected to hypoxia–reoxygenation. Overexpression of double GSK3β mutant (S9A/S389A) further reduced cardiomyocyte viability. Determination of protein synthesis showed that overexpression of GSK3β S389A or GSK3β S9A/S389A increased both basal and agonist-induced cardiomyocyte growth. Mechanistically, GSK3β S389A mutation was associated with activation of mTOR complex 1 signaling. In conclusion, our data suggest that phosphorylation of GSK3β at S389 enhances cardiomyocyte survival and protects from cardiomyocyte hypertrophy

GSK3β Serine 389 Phosphorylation Modulates Cardiomyocyte Hypertrophy and Ischemic Injury

Prior studies show that glycogen synthase kinase 3β (GSK3β) contributes to cardiac ischemic injury and cardiac hypertrophy. GSK3β is constitutionally active and phosphorylation of GSK3β at serine 9 (S9) inactivates the kinase and promotes cellular growth. GSK3β is also phosphorylated at serine 389 (S389), but the significance of this phosphorylation in the heart is not known. We analyzed GSK3β S389 phosphorylation in diseased hearts and utilized overexpression of GSK3β carrying ser→ala mutations at S9 (S9A) and S389 (S389A) to study the biological function of constitutively active GSK3β in primary cardiomyocytes. We found that phosphorylation of GSK3β at S389 was increased in left ventricular samples from patients with dilated cardiomyopathy and ischemic cardiomyopathy, and in hearts of mice subjected to thoracic aortic constriction. Overexpression of either GSK3β S9A or S389A reduced the viability of cardiomyocytes subjected to hypoxia–reoxygenation. Overexpression of double GSK3β mutant (S9A/S389A) further reduced cardiomyocyte viability. Determination of protein synthesis showed that overexpression of GSK3β S389A or GSK3β S9A/S389A increased both basal and agonist-induced cardiomyocyte growth. Mechanistically, GSK3β S389A mutation was associated with activation of mTOR complex 1 signaling. In conclusion, our data suggest that phosphorylation of GSK3β at S389 enhances cardiomyocyte survival and protects from cardiomyocyte hypertrophy

Early DNA methylation changes in children developing beta cell autoimmunity at a young age

Aims/hypothesis Type 1 diabetes is a chronic autoimmune disease of complex aetiology, including a potential role for epigenetic regulation. Previous epigenomic studies focused mainly on clinically diagnosed individuals. The aim of the study was to assess early DNA methylation changes associated with type 1 diabetes already before the diagnosis or even before the appearance of autoantibodies. Methods Reduced representation bisulphite sequencing (RRBS) was applied to study DNA methylation in purified CD4(+) T cell, CD8(+) T cell and CD4(-)CD8(-) cell fractions of 226 peripheral blood mononuclear cell samples longitudinally collected from seven type 1 diabetes-specific autoantibody-positive individuals and control individuals matched for age, sex, HLA risk and place of birth. We also explored correlations between DNA methylation and gene expression using RNA sequencing data from the same samples. Technical validation of RRBS results was performed using pyrosequencing. Results We identified 79, 56 and 45 differentially methylated regions in CD4(+) T cells, CD8(+) T cells and CD4-CD8- cell fractions, respectively, between type 1 diabetes-specific autoantibody-positive individuals and control participants. The analysis of pre-seroconversion samples identified DNA methylation signatures at the very early stage of disease, including differential methylation at the promoter of IRF5 in CD4(+) T cells. Further, we validated RRBS results using pyrosequencing at the following CpG sites: chr19:18118304 in the promoter of ARRDC2; chr21:47307815 in the intron of PCBP3; and chr14:81128398 in the intergenic region near TRAF3 in CD4(+) T cells. Conclusions/interpretation These preliminary results provide novel insights into cell type-specific differential epigenetic regulation of genes, which may contribute to type 1 diabetes pathogenesis at the very early stage of disease development. Should these findings be validated, they may serve as a potential signature useful for disease prediction and management.Peer reviewe

MiR-185-5p regulates the development of myocardial fibrosis

Background: Cardiac fibrosis stiffens the ventricular wall, predisposes to cardiac arrhythmias and contributes to the development of heart failure. In the present study, our aim was to identify novel miRNAs that regulate the development of cardiac fibrosis and could serve as potential therapeutic targets for myocardial fibrosis. Methods and results: Analysis for cardiac samples from sudden cardiac death victims with extensive myocardial fibrosis as the primary cause of death identified dysregulation of miR-185-5p. Analysis of resident cardiac cells from mice subjected to experimental cardiac fibrosis model showed induction of miR-185-5p expression specifically in cardiac fibroblasts. In vitro, augmenting miR-185-5p induced collagen production and profibrotic activation in cardiac fibroblasts, whereas inhibition of miR-185-5p attenuated collagen production. In vivo, targeting miR-185-5p in mice abolished pressure overload induced cardiac interstitial fibrosis. Mechanistically, miR-185-5p targets apelin receptor and inhibits the anti-fibrotic effects of apelin. Finally, analysis of left ventricular tissue from patients with severe cardiomyopathy showed an increase in miR-185-5p expression together with pro-fibrotic TGF-beta 1 and collagen I. Conclusions: Our data show that miR-185-5p targets apelin receptor and promotes myocardial fibrosis.Peer reviewe

A systematic comparison of FOSL1, FOSL2 and BATF-mediated transcriptional regulation during early human Th17 differentiation

Th17 cells are essential for protection against extracellular pathogens, but their aberrant activity can cause autoimmunity. Molecular mechanisms that dictate Th17 cell-differentiation have been extensively studied using mouse models. However, species-specific differences underscore the need to validate these findings in human. Here, we characterized the human-specific roles of three AP-1 transcription factors, FOSL1, FOSL2 and BATF, during early stages of Th17 differentiation. Our results demonstrate that FOSL1 and FOSL2 co-repress Th17 fate-specification, whereas BATF promotes the Th17 lineage. Strikingly, FOSL1 was found to play different roles in human and mouse. Genome-wide binding analysis indicated that FOSL1, FOSL2 and BATF share occupancy over regulatory regions of genes involved in Th17 lineage commitment. These AP-1 factors also share their protein interacting partners, which suggests mechanisms for their functional interplay. Our study further reveals that the genomic binding sites of FOSL1, FOSL2 and BATF harbour hundreds of autoimmune disease-linked SNPs. We show that many of these SNPs alter the ability of these transcription factors to bind DNA. Our findings thus provide critical insights into AP-1-mediated regulation of human Th17-fate and associated pathologies