Dataset Information

Temporal expression profiling identifies pathways mediating effect of causal variant on phenotype.

ABSTRACT: Even with identification of multiple causal genetic variants for common human diseases, understanding the molecular processes mediating the causal variants' effect on the disease remains a challenge. This understanding is crucial for the development of therapeutic strategies to prevent and treat disease. While static profiling of gene expression is primarily used to get insights into the biological bases of diseases, it makes differentiating the causative from the correlative effects difficult, as the dynamics of the underlying biological processes are not monitored. Using yeast as a model, we studied genome-wide gene expression dynamics in the presence of a causal variant as the sole genetic determinant, and performed allele-specific functional validation to delineate the causal effects of the genetic variant on the phenotype. Here, we characterized the precise genetic effects of a functional MKT1 allelic variant in sporulation efficiency variation. A mathematical model describing meiotic landmark events and conditional activation of MKT1 expression during sporulation specified an early meiotic role of this variant. By analyzing the early meiotic genome-wide transcriptional response, we demonstrate an MKT1-dependent role of novel modulators, namely, RTG1/3, regulators of mitochondrial retrograde signaling, and DAL82, regulator of nitrogen starvation, in additively effecting sporulation efficiency. In the presence of functional MKT1 allele, better respiration during early sporulation was observed, which was dependent on the mitochondrial retrograde regulator, RTG3. Furthermore, our approach showed that MKT1 contributes to sporulation independent of Puf3, an RNA-binding protein that steady-state transcription profiling studies have suggested to mediate MKT1-pleiotropic effects during mitotic growth. These results uncover interesting regulatory links between meiosis and mitochondrial retrograde signaling. In this study, we highlight the advantage of analyzing allele-specific transcriptional dynamics of mediating genes. Applications in higher eukaryotes can be valuable for inferring causal molecular pathways underlying complex dynamic processes, such as development, physiology and disease progression.

SUBMITTER: Gupta S

PROVIDER: S-EPMC4454590 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Temporal expression profiling identifies pathways mediating effect of causal variant on phenotype.

Gupta Saumya S Radhakrishnan Aparna A Raharja-Liu Pandu P Lin Gen G Steinmetz Lars M LM Gagneur Julien J Sinha Himanshu H

PLoS genetics 20150603 6

Even with identification of multiple causal genetic variants for common human diseases, understanding the molecular processes mediating the causal variants' effect on the disease remains a challenge. This understanding is crucial for the development of therapeutic strategies to prevent and treat disease. While static profiling of gene expression is primarily used to get insights into the biological bases of diseases, it makes differentiating the causative from the correlative effects difficult, ...[more]

PMID: 26039065

Similar Datasets

Project description:BackgroundJatropha curcas, a tropical shrub, is a promising biofuel crop, which produces seeds with high content of oil and protein. To better understand the maturation process of J. curcas seeds and to improve its agronomic performance, a two-step approach was performed in six different maturation stages of seeds: 1) generation of the entire transcriptome of J. curcas seeds using 454-Roche sequencing of a cDNA library, 2) comparison of transcriptional expression levels using a custom Agilent 8x60K oligonucleotide microarray.ResultsA total of 793,875 high-quality reads were assembled into 19,382 unique full-length contigs, of which 13,507 could be annotated with Gene Ontology (GO) terms. Microarray data analysis identified 9111 probes (out of 57,842 probes), which were differentially expressed between the six maturation stages. The expression results were validated for 75 selected transcripts based on expression levels, predicted function, pathway, and length. Result from cluster analyses showed that transcripts associated with fatty acid, flavonoid, and phenylpropanoid biosynthesis were over-represented in the early stages, while those of lipid storage were over-represented in the late stages. Expression analyses of different maturation stages of J. curcas seed showed that most changes in transcript abundance occurred between the two last stages, suggesting that the timing of metabolic pathways during seed maturation in J. curcas occurs in late stages. The co-expression results showed that the hubs (CB5-D, CDR1, TT8, DFR, HVA22) with the highest number of edges, associated with fatty acid and flavonoid biosynthesis, are showing a decrease in their expression during seed maturation. Furthermore, seed development and hormone pathways are significantly well connected.ConclusionThe obtained results revealed differentially expressed sequences (DESs) regulating important pathways related to seed maturation, which could contribute to the understanding of the complex regulatory network during seed maturation with the focus on lipid, flavonoid and phenylpropanoid biosynthesis. This study provides detailed information on transcriptional changes during J. curcas seed maturation and provides a starting point for a genomic survey of seed quality traits. The results highlighted specific genes and processes relevant to the molecular mechanisms involved in Jatropha seed maturation. These data can also be utilized regarding other Euphorbiaceae species.

Dataset Information

Temporal expression profiling identifies pathways mediating effect of causal variant on phenotype.

Publications

Temporal expression profiling identifies pathways mediating effect of causal variant on phenotype.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets