Biology subjects

Rezaie, N.

Publications and source records attributed to Rezaie, N..

11 recordsLinked to original sources

bioRxiv2024

Long-read sequencing transcriptome quantification with lr-kallisto

RNA abundance quantification has become routine and affordable thanks to high-throughput "short-read" technologies that provide accurate molecule counts at the gene level. Similarly accurate and affordable quantification of definitive fulllength, transcript isoforms has remained a stubborn challenge, despite its obvious biological significance across a wide range of problems. "Long-read" sequencing platforms now produce data-types that can, in principle, drive routine definitive isoform quantification. However some particulars of contemporary long-read datatypes, together with isoform complexity and genetic variation, present bioinformatic challenges. We show here, using ONT data, that fast and accurate quantification of long-read data is possible and that it is improved by exome capture. To perform quantifications we developed lr-kallisto, which adapts the kallisto bulk and single-cell RNA-seq quantification methods for long-read technologies.

bioinformatics↗

bioRxiv2024

The ENCODE mouse postnatal developmental time course identifies regulatory programs of cell types and cell states

Postnatal genomic regulation significantly influences tissue and organ maturation but is under-studied relative to existing genomic catalogs of adult tissues or prenatal development in mouse. The ENCODE4 consortium generated the first comprehensive single-nucleus resource of postnatal regulatory events across a diverse set of mouse tissues. The collection spans seven postnatal time points, mirroring human development from childhood to adulthood, and encompasses five core tissues. We identified 30 cell types, further subdivided into 69 subtypes and cell states across adrenal gland, left cerebral cortex, hippocampus, heart, and gastrocnemius muscle. Our annotations cover both known and novel cell differentiation dynamics ranging from early hippocampal neurogenesis to a new sex-specific adrenal gland population during puberty. We used an ensemble Latent Dirichlet Allocation strategy with a curated vocabulary of 2,701 regulatory genes to identify regulatory "topics," each of which is a gene vector, linked to cell type differentiation, subtype specialization, and transitions between cell states. We find recurrent regulatory topics in tissue-resident macrophages, neural cell types, endothelial cells across multiple tissues, and cycling cells of the adrenal gland and heart. Cell-type-specific topics are enriched in transcription factors and microRNA host genes, while chromatin regulators dominate mitosis topics. Corresponding chromatin accessibility data reveal dynamic and sex-specific regulatory elements, with enriched motifs matching transcription factors in regulatory topics. Together, these analyses identify both tissue-specific and common regulatory programs in postnatal development across multiple tissues through the lens of the factors regulating transcription.

genomics↗

bioRxiv2024

Identification of robust cellular programs using reproducible LDA that impact sex-specific disease progression in different genotypes of a mouse model of AD

The gene expression profiles of distinct cell types reflect complex genomic interactions among multiple simultaneous biological processes within each cell that can be altered by disease progression as well as genetic background. The identification of these active cellular programs is an open challenge in the analysis of single-cell RNA-seq data. Latent Dirichlet Allocation (LDA) is a generative method used to identify recurring patterns in counts data, commonly referred to as topics that can be used to interpret the state of each cell. However, LDAs interpretability is hindered by several key factors including the hyperparameter selection of the number of topics as well as the variability in topic definitions due to random initialization. We developed Topyfic, a Reproducible LDA (rLDA) package, to accurately infer the identity and activity of cellular programs in single-cell data, providing insights into the relative contributions of each program in individual cells. We apply Topyfic to brain single-cell and single-nucleus datasets of two 5xFAD mouse models of Alzheimers disease crossed with C57BL6/J or CAST/EiJ mice to identify distinct cell types and states in different cell types such as microglia. We find that 8-month 5xFAD/Cast F1 males show higher level of microglial activation than matching 5xFAD/BL6 F1 males, whereas female mice show similar levels of microglial activation. We show that regulatory genes such as TFs, microRNA host genes, and chromatin regulatory genes alone capture cell types and cell states. Our study highlights how topic modeling with a limited vocabulary of regulatory genes can identify gene expression programs in singlecell data in order to quantify similar and divergent cell states in distinct genotypes.

genomics↗

bioRxiv2023

The ENCODE4 long-read RNA-seq collection reveals distinct classes of transcript structure diversity

The majority of mammalian genes encode multiple transcript isoforms that result from differential promoter use, changes in exonic splicing, and alternative 3 end choice. Detecting and quantifying transcript isoforms across tissues, cell types, and species has been extremely challenging because transcripts are much longer than the short reads normally used for RNA-seq. By contrast, long-read RNA-seq (LR-RNA-seq) gives the complete structure of most transcripts. We sequenced 264 LR-RNA-seq PacBio libraries totaling over 1 billion circular consensus reads (CCS) for 81 unique human and mouse samples. We detect at least one full-length transcript from 87.7% of annotated human protein coding genes and a total of 200,000 full-length transcripts, 40% of which have novel exon junction chains. To capture and compute on the three sources of transcript structure diversity, we introduce a gene and transcript annotation framework that uses triplets representing the transcript start site, exon junction chain, and transcript end site of each transcript. Using triplets in a simplex representation demonstrates how promoter selection, splice pattern, and 3 processing are deployed across human tissues, with nearly half of multitranscript protein coding genes showing a clear bias toward one of the three diversity mechanisms. Evaluated across samples, the predominantly expressed transcript changes for 74% of protein coding genes. In evolution, the human and mouse transcriptomes are globally similar in types of transcript structure diversity, yet among individual orthologous gene pairs, more than half (57.8%) show substantial differences in mechanism of diversification in matching tissues. This initial large-scale survey of human and mouse long-read transcriptomes provides a foundation for further analyses of alternative transcript usage, and is complemented by short-read and microRNA data on the same samples and by epigenome data elsewhere in the ENCODE4 collection.

genomics↗

bioRxiv2022

PyWGCNA: A Python package for weighted gene co-expression network analysis

MotivationWeighted gene co-expression network analysis (WGCNA) is frequently used to identify modules of genes that are co-expressed across many RNA-seq samples. However, the current R implementation is slow, not designed to compare modules between multiple WGCNA networks, and results are hard to interpret and visualize. We introduce the PyWGCNA Python package designed to identify and compare co-expression modules from RNA-seq data. ResultsWe apply PyWGCNA to two distinct datasets of brain bulk RNA-seq from MODEL-AD to identify modules associated with the genotypes. We compare the resulting modules to each other to find modules with significant overlap across the datasets. AvailabilityThe PyWGCNA library for Python 3 is available on PyPi at https://pypi.org/project/PyWGCNA and on GitHub at https://github.com/mortazavilab/PyWGCNA.

bioinformatics↗

bioRxiv2022

A Trem2*R47H mouse model without cryptic splicing drives age- and disease-dependent tissue damage and synaptic loss in response to plaques

Genome-Wide Association Studies revealed the TREM2 R47H variant as one of the strongest genetic risk factors for late-onset Alzheimers Disease (AD). Unfortunately, many current TREM2*R47H mouse models are associated with cryptic mRNA splicing of the mutant allele that produces a confounding reduction in protein product. We have developed the Trem2R47H NSS (Normal Splice Site) mouse model where the Trem2 allele is expressed at a similar level to the wild-type Trem2 allele, without evidence of cryptic splicing products, and appropriate inflammatory responses to cuprizone challenge. Utilizing the 5xFAD mouse model, we report age- and disease-dependent changes in response to pathology. At an early disease stage (4 mo), homozygous Trem2R47H NSS; hemizygous 5xFAD (Trem2R47H NSS ; 5xFAD) mice have reduced size and number of microglia plus impaired interaction with plaques, that is associated with increased dystrophic neurites and axonal damage detected through plasma neurofilament light chain (NfL) level and suppressed inflammation. However, homozygosity for Trem2R47H NSS suppressed LTP deficits and presynaptic puncta loss caused by the 5xFAD transgene array. At a more advanced disease stage (12 mo,) Trem2R47H NSS ; 5xFAD mice no longer display impaired plaque-microglia interaction or suppressed inflammatory gene expression, although NfL levels remain elevated, and a unique interferon-related gene expression signature is seen. Furthermore, Trem2R47H NSS ; 5xFAD mice also display robust LTP deficits and exacerbated presynaptic loss. Collectively, we provide a Trem2R47H variant mouse without cryptic splicing, and demonstrate it has disease stage dependent effects when combined with a plaque bearing model, with an initial loss of function that ultimately resolves, giving rise to a unique interferon signature and associated tissue damage.

neuroscience↗

bioRxiv2021

Single-cell and nucleus RNA-seq in a mouse model of AD reveal activation of distinct glial subpopulations in the presence of plaques and tangles

Multiple mouse models have been generated that strive to recapitulate human Alzheimers disease (AD) pathological features to investigate disease mechanisms and potential treatments. The 3xTg-AD mouse presents the two major hallmarks of AD, which are plaques and tangles that increase during aging. While behavioral changes and the accumulation of plaques and tangles have been well described in the 3xTg-AD mice, the subpopulations of neurons and glial cells present throughout disease progression have not been characterized. Here, we used single-cell RNA-seq to investigate changes in subpopulations of microglia, and single-nucleus RNA-seq to explore subpopulations of neurons, astrocytes, and oligodendrocytes in the hippocampus and cortex of aging 3xTg-AD as well as 5xFAD mice for comparison. We recovered a common path of age-associated astrocyte activation between the 3xTg-AD and the 5xFAD models and found that 3xTg-AD-derived astrocytes seem to be less activated. We identified multiple subtypes of microglia, including a subpopulation with a distinct transcription factor expression profile that showed an early increase in Csf1 expression before the switch to disease associated microglia (DAM). We used bulk RNA-seq in the hippocampus of 3xTg-AD mice across their lifespan to identify distinct modules of genes whose expression increases with aging and worsening pathology. Finally, scATAC-seq revealed multiple subpopulations of cells with accessible chromatin in regions around genes associated with glial activation. Overall, differences between the main glial groups point to a slower activation process in the 3xTg-AD model when compared to the 5xFAD. Our study contributes to the identification of progressive transcriptional changes of glial cells in a mouse model that has plaques and tangles, thus providing information to aid in targeted AD therapeutics that could translate into positive clinical outcomes.

genomics↗

bioRxiv2021

Somatic point mutations are enriched in long non-coding RNAs with possible regulatory function in breast cancer

De novo somatic point mutations identified in breast cancer are predominantly non-coding and typically attributed to altered regulatory elements such as enhancers and promoters. However, while the non-coding RNAs (ncRNAs) form a large portion of the mammalian genome, their biological functions are mostly poorly characterized in cancers. In this study, using a newly developed tool, SomaGene, we reanalyze de novo somatic point mutations from the International Cancer Genome Consortium (ICGC) whole-genome sequencing data of 1,855 breast cancers. We identify 929 candidates of ncRNAs that are significantly and explicitly mutated in breast cancer samples. By integrating data from the ENCODE regulatory features and FANTOM5 expression atlas, we show that the candidate ncRNAs in breast cancer samples significantly enrich for active chromatin histone marks (1.9 times), CTCF binding sites (2.45 times), DNase accessibility (1.76 times), HMM predicted enhancers (2.26 times) and eQTL polymorphisms (1.77 times). Importantly, we show that the 929 ncRNAs contain a much higher level (3.64 times) of breast cancer-associated genome-wide association (GWAS) single nucleotide polymorphisms (SNPs) than genome-wide expectation. Such enrichment has not been seen with GWAS SNPs from other diseases. Using breast tissue related Hi-C data we then show that 82% of our candidate ncRNAs (1.9 times) significantly interact with the promoter of protein-coding genes, including previously known cancer-associated genes, suggesting the critical role for candidate ncRNA genes in activation of essential regulators of development and differentiation in breast cancer. We provide an extensive web-based resource (http://ncrna.ictic.sharif.edu), to communicate our results with the research community. Our list of breast cancer-specific ncRNA genes has the potential to provide a better understanding of the underlying genetic causes of breast cancer. Lastly, the tool developed in this study can be used in the analysis of somatic mutations in all cancers.

cancer biology↗

bioRxiv2021

Systematic Phenotyping and Characterization of the 5xFAD mouse model of Alzheimer's Disease

Mouse models of human diseases are invaluable tools for studying pathogenic mechanisms and testing interventions and therapeutics. For disorders such as Alzheimers disease in which numerous models are being generated, a challenging first step is to identify the most appropriate model and age to effectively evaluate new therapeutic approaches. Here we conducted a detailed phenotypic characterization of the 5xFAD model on a congenic C57BL/6J strain background, across its lifespan - including a seldomly analyzed 18-month old time point to provide temporally correlated phenotyping of this model and a template for characterization of new models of LOAD as they are generated. This comprehensive analysis included quantification of plaque burden, A{beta} biochemical levels, and neuropathology, neurophysiological measurements and behavioral and cognitive assessments, and evaluation of microglia, astrocytes, and neurons. Analysis of transcriptional changes was conducted using bulk-tissue generated RNA-seq data from microdissected cortices and hippocampi as a function of aging, which can be explored at the UCI Mouse Explorer and AD Knowledge Portal. This deep-phenotyping pipeline identified novel aspects of age-related pathology in the 5xFAD model.

neuroscience↗

bioRxiv2020

Unravelling resilience mechanisms in forests: role of non-structural carbohydrates in responding to extreme weather events

O_LIExtreme weather events are increasing in frequency and intensity due to global climate change. We hypothesized that these have a strong impact on the stem radial growth and the dynamic of non-structural carbohydrates (NSCs). C_LIO_LIIn order to assess the effects on mature trees of a late frost occurred in spring 2016 and a drought event characterizing the summer 2017, we monitored the phenology, the radial growth and the dynamic of starch and soluble sugars in a Mediterranean beech forest. C_LIO_LIGrowth was much more reduced by spring late frost than by summer drought, while NSCs dynamic was deeply involved in counteracting the negative effects of both events, supporting plant survival and buffering source-sink imbalances under such stressful conditions, resulting in a strong trade-off between growth and NSCs dynamic in trees. C_LIO_LIOverall, our results highlight the key role of NSCs on trees resilience to extreme weather events, confirming the relevant adaptability to stressful conditions. Such an insight is useful to assess how forests may respond to the potential impacts of climate change on ecosystem processes and to define how future management strategies can help adaptation of beech forests in the Mediterranean area. C_LI

ecology↗

bioRxiv2019

The cold and the drought: effects of extreme weather events on Stem Carbon dynamic in a Mediterranean beech forest

The effects of short-term extreme events on tree functioning and physiology are still rather elusive. European beech is one of the most sensitive species to late frost and water shortage. We investigated the intra-annual C dynamics in stems under such conditions. Wood formation and stem CO2 efflux were monitored in a Mediterranean beech forest for three years (2015-2017), including a late frost (2016) and a summer drought (2017). The late frost reduced radial growth and, consequently, the amount of carbon fixed in the stem biomass by 80%. Stem carbon efflux in 2016 was reduced by 25%, which can be attributed to the reduction of effluxes due to growth respiration. Counter to our expectations, we found no effects of the 2017 summer drought on radial growth and stem carbon efflux. The studied extreme weather events had various effects on tree growth. Even though late spring frost had a devastating impact on beech radial growth in the current year, trees fully recovered in the following growing season, indicating high resilience of beech to this stressful event.

physiology↗