Servicio de Información Comunitario sobre Investigación y Desarrollo - CORDIS

Final Report Summary - PRANA (Protein-RNA networks ALS)

During her Marie Curie post-doctoral Intra-European fellowship, Lilach took on herself to analyze extensive human brain exon arrays expression dataset collected by the UK brain brank and the National American brain bank to study the mechanisms responsible for age-related changes in RNA expression and alternative splicing alterations in the brain. Throughout her fellowship, Lilach developed computational analysis pipelines through programming, and applied a variety of data mining and statistical approaches to analyse the data produced by multiple technologies and platforms. She found pronounced expression changes, both region specific and cross regional, in the ageing brains, including in RNA binding proteins such as FUS, which are involved in amyotrophic lateral sclerosis (ALS) and in marker genes of specific neural cell types (including neuronal and glial ones). Through cross-regional analysis she was able to detect a common signature of expression alterations in 10 brain regions upon ageing. Following the observation that cell-type specific expression pattern alterations are involved in ageing RNA expression changes, selected subset of the brain samples were subjected to sectioning and staining by different antibodies specific for certain brain cell types, including oligodendrocytes, microglia and astrocytes and the stained images were subjected to high resolution scanning. Lilach developed a machine learning based analysis pipeline for the analysis of the large scale imaging data in order to quantify and characterize alterations in specific cell populations numbers and other morphogenic parameters (such as cells size and shape).
Lilach then examined gene expression to understand how cognitively normal ageing relates to neurodegenerative diseases. She analyzed RNA sequencing data from amyotrophic lateral sclerosis (ALS) mice model (FUS knock out), publically available microarray data from ALS patients carrying mutations in either FUS or SOD1, as well as RNA-seq data produced in the hosting laboratory from ALS patients stem cells and from brain samples of AD model mice (all the predicted splicing events were successfully validated by experimental techniques). This led to the identification of common signatures of expression and mutation-dependent alternative splicing changes in samples from patients carried mutation in either FUS or SOD1 genes, which she have found as differentially expressed upon ageing in the human brain.

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