Biology subjects

Rentoft, M.

Publications and source records attributed to Rentoft, M..

3 recordsLinked to original sources

bioRxiv2022

Arabidopsis mutants representing each of the four Mediator modules reveal unique functions in the transcriptional response to salt stress

Changes in growth environment trigger stress responses in most organisms. The mechanisms mediating these responses are only partly understood and involve signaling pathways and transcription factors. Mediator is a conserved co-regulator complex required for transcriptional regulation of all eukaryotic protein-encoding genes. However, its function in abiotic stress responses is elusive. We here describe global gene expression changes triggered by salt stress in Arabidopsis. To explore the involvement of Mediator in salt stress response we characterized med9, med16, med18, and cdk8 mutants representing each of the four modules of Mediator. Our transcriptome data revealed enrichment of shared and specific cis-elements corresponding to unique transcription factors in promoters of mis-regulated genes for each mutant. We show that individual Mediator subunits interact with specific transcription factors to generate a transcriptional stress response and that the mutant phenotypes support the transcriptome data. med16 and med18, and to some extent cdk8, display defects in abscisic acid and anthocyanin metabolism and we identify signal molecules, transcription factors and target genes involved in these pathways as dysregulated in the Mediator mutants. Our results reveal how signals from different stress response pathways are dependent on and integrated by Mediator subunits to coordinate a functional response to salt stress.

genomics↗

bioRxiv2021

A new pipeline for the normalization and pooling of metabolomics data

Pooling metabolomics data across studies is often desirable to increase the statistical power of the analysis. However, this can raise methodological challenges as several preanalytical and analytical factors could introduce differences in measured concentrations and variability between datasets. Specifically, different studies may use variable sample types (e.g., serum versus plasma) collected, treated and stored according to different protocols, and assayed in different laboratories using different instruments. To address these issues, a new pipeline was developed to normalize and pool metabolomics data through a set of sequential steps: (i) exclusions of the least informative observations and metabolites and removal of outliers; imputation of missing data; (ii) identification of the main sources of variability through PC-PR2 analysis; (iii) application of linear mixed models to remove unwanted variability, including samples originating study and batch, and preserve biological variations while accounting for potential differences in the residual variances across studies. This pipeline was applied to targeted metabolomics data acquired using Biocrates AbsoluteIDQ kits in eight case-control studies nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Comprehensive examination of metabolomics measurements indicated that the pipeline improved the comparability of data across the studies. Our pipeline can be adapted to normalize other molecular data, including biomarkers as well as proteomics data, and could be used for pooling molecular datasets, for example in international consortia, to limit biases introduced by inter-study variability. This versatility of the pipeline makes our work of potential interest to molecular epidemiologists.

bioinformatics↗

bioRxiv2020

A whole-genome sequenced control population in northern Sweden reveals subregional genetic differences.

The number of national reference populations that are whole-genome sequenced are rapidly increasing. Partly driving this development is the fact that genetic disease studies benefit from knowing the genetic variation typical for the geographical area of interest. A whole-genome sequenced Swedish national reference population (n=1000) has been recently published but with few samples from northern Sweden. In the present study we have whole-genome sequenced a control population (n=300) (ACpop) from Vasterbotten County, a sparsely populated region in northern Sweden previously shown to be genetically different from southern Sweden. The aggregated variant frequencies within ACpop are publicly available (DOI 10.17044/NBIS/G000005) to function as a basic resource in clinical genetics and for genetic studies. Our analysis of ACpop, representing approximately 0.11% of the population in Vasterbotten, indicates the presence of a genetic substructure within the county. Furthermore, a demographic analysis showed that the population from which samples were drawn was to a large extent geographically stationary, a finding that was corroborated in the genetic analysis down to the level of municipalities. Including ACpop in the reference population when imputing unknown variants in a Vasterbotten cohort resulted in a strong increase in the number of high-confidence imputed variants (up to 81% for variants with minor allele frequency < 5%). ACpop was initially designed for cancer disease studies, but the genetic structure within the cohort will be of general interest for all genetic disease studies in northern Sweden.

genetics↗