ABSTRACT: Dennert et al. 2018; Conservation tillage and organic farming induce minor variations in Pseudomonas abundance, their antimicrobial function and soil disease resistance
Project description:Hartman et al. 2018; Cropping practices manipulate abundance patterns of root and soil microbiome members paving the way to smart farming
Project description:VSMCs expressing SCA1 have increased proliferative capacity (Dobnikar et al, 2018; Worssam et al, 2022; Pan et al, 2020). We therefore, mapped chromatin accessibility changes using bulk ATAC-seq for SCA1+ and SCA1- lineage traced VSMCs.
Project description:Canonical auxin signalling starts with auxin binding to the receptor complex, followed by modulation of gene transcription and protein abundance (Tan et al., 2007; Chapman and Estelle, 2009; Slade et al., 2017). However, recent studies also showed an alternative mechanism in roots involving intra-cellular auxin perception, but not transcriptional reprogramming (Fendrych et al., 2018). Despite knowledge on effects of auxin on Arabidopsis root growth at the protein and phosphorylation level is increasing (Zhang et al., 2013; Mattei et al., 2013; Slade et al., 2017), it still remains incomplete. To address this gap in our knowledge, we explored the impact of auxin on the root tip proteome and phosphoproteome.
Project description:In this study, we profiled for LINE1 binding loci in RSeT+DT naïve hES cells with the Chromatin Isolation by RNA Purification (ChIRP)-seq strategy. We followed a previously published ChIRP protocol described (Percharde et al. 2018; Lu et al. 2020).
2024-09-09 | GSE263289 | GEO
Project description:raw data UCEs minute wasps Cruaud et al. 2018
Project description:While DNA methylation is an important gene regulatory mechanism in mammals (Razin and Riggs 1980; Moore, Le, and Fan 2013), its function in arthropods remains poorly understood. Studies in eusocial insects have argued for its role in caste development by regulating gene expression and splicing (Elango et al. 2009; Lyko et al. 2010; Bonasio et al. 2012; Flores et al. 2012; Foret et al. 2012; Li-Byarlay et al. 2013; Marshall, Lonsdale, and Mallon 2019; Shi et al. 2013)(Alvarado et al. 2015; Kucharski et al. 2008). However, such findings are not always consistent across studies, and have therefore remained controversial (Arsenault, Hunt, and Rehan 2018; Cardoso-Junior et al. 2021; Harris et al. 2019; Herb et al. 2012; Libbrecht et al. 2016; Oldroyd and Yagound 2021b; Patalano et al. 2015). Here we use CRISPR/Cas9 to mutate the maintenance DNA methyltransferase DNMT1 in the clonal raider ant, Ooceraea biroi. Mutants have greatly reduced DNA methylation but no obvious developmental phenotypes, demonstrating that, unlike mammals (Brown and Robertson 2007; En Li, Bestor, and Jaenisch 1992; Jackson-Grusby et al. 2001; Panning and Jaenisch 1996), ants can undergo normal development without DNMT1 or DNA methylation. Additionally, we find no evidence of DNA methylation regulating caste development. However, mutants are sterile, while in wildtypes, DNMT1 is localized to the ovaries and maternally provisioned into nascent oocytes. This supports the idea that DNMT1 plays a crucial but unknown role in the insect germline (Amukamara et al. 2020; Arsala et al. 2021; Bewick et al. 2019; Schulz et al. 2018; Ventós-Alfonso et al. 2020; Washington et al. 2020).
Project description:DNA damage can promote altered RNA splicing and decreased gene expression (Gregersen and Svejstrup, 2018; Milek et al., 2017; Munoz et al., 2009; Shkreta and Chabot, 2015), and aberrant splicing is implicated in neurodegenerative diseases including amyotrophic lateral sclerosis (ALS), Fragile X syndrome and spinal muscular atrophy (SMA) (Conlon et al., 2016; Jia et al., 2012; Loomis et al., 2014; Qiu et al., 2014; Scotti and Swanson, 2016). Therefore, we used RNA-seq data to assess RNA-splicing in double-mutant brain tissue using multivariate analysis of transcriptional splicing (rMATS) (Shen et al., 2014) and a splicing deficiency score algorithm (Bai et al., 2013) to assess intron retention.
Project description:We examined all transcriptome-level expressions in three initial cell-population densities (862, 1724 and 5172 cells/cm2) in the first two days of differentiation in N2B27. We collected cells in 10-mL tubes and centrifuged them using a pre-cooled centrifuge. We then extracted RNA from each cell-pellet using the PureLink RNA Mini Kit (Ambion, Life Technologies) according to its protocol. We next prepared the cDNA library with the 3′ mRNASeq library preparation kit (Quant-Seq, Lexogen) according to its protocol. We then loaded the cDNA library onto an Illumina MiSeq system using the MiSeq Reagent Kit v3 (Illumina) according to its protocol. We analyzed the resulting RNA-seq data as previously described (Trapnell et al., Nat Protoc 2012). We performed the read alignment using TopHat, read assembly using Cufflinks and analyses of differential gene expression data using Cuffdiff. We used the reference genome for Mus musculus from UCSC (mm10). We performed enrichment analysis of genes based on their FPKM values (e.g., more than 2-fold expressed when two initial population densities are compared) by using GO-terms from PANTHER (Mi et al., Nucl Acids Res 2019) and custom MATLAB script (MathWorks). We visualized results of pre-sorted, Yap1-related genes (LeBlanc et al., Elife 2018; Mugahid et al., Elife 2020; Yu et al., Oncogene 2018; Huh et al., Cells 2019; Zhu et al., Nature Sci Rep 2018; Zhou et al., Int J Mol Sci 2016; Vigneron & Vousden, EMBO J 2012; Kim et al., Cell 2015) into heat maps that displays the normalized expression value (row Z-score) for each gene and each condition.
Project description:Long RNA-seq analysis on cellular and extracellular samples from a KRAS mutant colorectal cancer cell model, in association with Hinger et al 2018
