Biology subjects

Rafati, N.

Publications and source records attributed to Rafati, N..

4 recordsLinked to original sources

bioRxiv2025

Oligodendroglia vulnerability in the human dorsal striatum in Parkinson's disease

Oligodendroglia are the responsible cells for myelination in the central nervous system and their involvement in Parkinsons disease (PD) is poorly understood. We performed snRNA-seq and image-based spatial transcriptomics of human caudate nucleus and putamen (dorsal striatum) from PD and Control brain donors to elucidate the diversity of oligodendroglia and how they are affected by the disease. We have defined fifteen subclasses, from precursor to mature cells, four of which are disease-associated. These PD-specific populations are characterized by the overexpression of heat shock proteins and distinct expression signatures, including immune responses and myelination alterations. We have also identified disruptions in cell communication and oligodendrocyte development, evidenced by changes in neurotransmitter receptors expression and cell adhesion molecules. These transcriptomic changes correlated with impaired myelin integrity and altered oligodendrocyte distribution in the striatum. Thus, we uncover oligodendroglia as a critical cell type in PD and a potential new therapeutic target.

neuroscience↗

bioRxiv2022

The dynamics of adaptation to stress from standing genetic variation and de novo mutations

Adaptation from standing genetic variation is an important process underlying evolution in natural populations but we rarely get the opportunity to observe the dynamics of fitness changes in real time. Here, we used the power of microbial experimental evolution and whole population sequencing to track the phenotypic and genomic changes of genetically diverse yeast populations in environments with different stress levels. We found that populations rapidly and in parallel increased in fitness in stressful environments. The founders genetic diversity was quickly depleted, however, not to the same degree in all populations and environments. Some populations fixed all ancestral variation in < 30 generations while others maintained diversity across hundreds of generations. We also observed parallelism at the gene and pathway level. Specifically, we detected up to seven genes harbouring multiple independent mutations in different populations, and a general enrichment for mutations affecting downstream effectors of the high-osmolarity-glycerol pathway in three out of four environments. Adaptation to the most stressful environment was characterised by the fast evolution of functional haploidy, likely driven by standing genetic variation. Almost 40% of all populations contained aneuploidies (losses or gains of chromosomes) at least once during experimental evolution. Some aneuploidies were maintained for hundreds of generations in parallel in different replicates, suggesting they were adaptive. This work shows that experimental evolution is a great tool to address the interplay between standing variation and the influx of de novo mutations, leading to a better understanding of the demographic and environmental drivers and constraints of a populations capacity to adapt to environmental change.

evolutionary biology↗

bioRxiv2017

Moderate Nucleotide Diversity In The Atlantic Herring Is Associated With A Low Mutation Rate

The Atlantic herring (Clupea harengus) is one of the most abundant vertebrates on earth but its nucleotide diversity is moderate ({pi}=0.3%), only three-fold higher than in human. The expected nucleotide diversity for selectively neutral alleles is a function of population size and the mutation rate, and it is strongly affected by demographic history. Here, we present a pedigree-based estimation of the mutation rate in the Atlantic herring. Based on whole-genome sequencing of four parents and 12 offspring, the estimated mutation rate is 1.7 x 10-9 per base per generation. There was no significant difference in the frequency of paternal and maternal mutations (8 and 7, respectively). Furthermore, we observed a high degree of parental mosaicism indicating that a large fraction of these de novo mutations occurred during early germ cell development when we do not expect a strong gender effect. The now estimated mutation rate - the lowest among vertebrates analyzed to date - partially explains the discrepancy between the rather low nucleotide diversity in herring and its huge census population size (>1011). But our analysis indicates that a species like the herring will never reach its expected nucleotide diversity for selectively neutral alleles primarily because of fluctuations in population size due to climate variation during the millions of years it takes to build up a high nucleotide diversity. In addition, background selection and selective sweeps lead to reductions in nucleotide diversity at linked neutral sites.

genomics↗

bioRxiv2016

A computational method for detection of structural variants using Deviant Reads and read pair Orientation: DevRO

BackgroundNext generation sequencing (NGS) technology has made it possible to perform high-resolution screens for structural variants. Computational methods for detection of structural variants utilize paired-end mapping information, depth of coverage, split reads, or some combination of such data. The available methods are particularly designed to detect structural variants in single genomes or multiple genomes in a pairwise manner. The aim of this study was to develop a bioinformatics pipeline for detection of large structural variants using multiple pooled populations.\n\nResultsHere we describe the method \"DevRO\", developed to enable identification of structural variants using short insert paired-ends and long-range mate-pairs. DevRO uses paired-end mapping information from both types of libraries for identification of inversions, deletions and duplications followed by read depth information to screen for copy number variants. DevRO can detect structural variants in multiple populations without the need for pairwise comparisons. It uses a combined approach based on (i) paired-end mapping and (ii) depth of coverage that gives power to the study as compared to traditional methods that are based on either of these. DevRO is also designed to detect deletions in the reference assembly, which is an added functionality as compared to available methods.\n\nConclusionWe report a bioinformatics pipeline \"DevRO\" for detection of structural variants using paired-end mapping and depth of coverage methods tested on sequencing reads from multiple pooled rabbit populations. This method is useful when large numbers of populations have been re-sequenced as compared to traditional methods that can detect structural variants in a pairwise manner.

bioinformatics↗