Biology subjects

Ballouz, S.

Publications and source records attributed to Ballouz, S..

12 recordsLinked to original sources

bioRxiv2026

Monocyte Lineage Expansion Drives Transcriptomic Individuality in Genetically Identical Armadillo Quadruplets

Genetic diversity shapes phenotypes, yet even genetically identical individuals differ. In nine-banded armadillo (Dasypus novemcinctus) quadruplets, we previously showed that allele-specific expression (ASE) imbalances provide a stable molecular fingerprint of individuality. Here, we test whether such transcriptomic individuality reflects functional biological differences. We profiled bulk blood RNA from five cohorts of genetically identical quadruplets across three time points, and found persistent gene-expression signatures that predict individual identity. Focusing on a highly variable cohort, we then performed single-cell RNA-seq and ATAC-seq. In this litter, the most stably distinct individual showed an expanded monocyte-lineage compartment and gene-expression programs enriched for inflammatory and differentiation pathways. These cell-type and regulatory differences were stable over time and robust to experimental leprosy infection. Together, our results link transcriptomic individuality to lasting differences in immune-cell composition, illustrating how early stochastic events can produce persistent, biologically meaningful divergence among genetically identical individuals. TeaserGenetically identical armadillo quadruplets are identifiable by transcriptomic signatures shaped by cellular composition variation.

molecular biology↗

bioRxiv2025

The impact of sex on the immune system explored at the single-cell level

Sex has a key role in disease susceptibility, in particular autoimmunity. Sex differences of the immune system stems from genes and their interactions with intrinsic and external factors. However, the cellular-level factors influencing sexual dimorphism is not fully understood. We thus examined immune sex differences at single-cell resolution to dissect the genetic impacts. Female-biased sex-differentially expressed genes (DEGs) in multiple immune cells were involved in TNF[a] signalling, whereas male DEGs were enriched for ribosomal-related functions. While cis-eQTLs were less common on sex chromosomes, we identified over 1000 sex-specific eQTLs and 51 sex-interacting eQTLs on autosomes. When we examined the effect of genetic control on sex-DEGs, we found genetic variants affecting the female-biased expression FCGR3A in NK cells (rs2099684) and ITGB2 in Monocytes (rs760462), both of which are associated with systemic lupus erythematosus. Our work reveals novel biases masked in bulk analyses and highlights sexually dimorphic genes and pathways at baseline.

immunology↗

bioRxiv2024

Single-cell atlas of the human immune system reveals sex-specific dynamics of immunosenescence

Immunosenescence, or immune aging, is characterized by both changes in cell type abundance and a decline in cellular function, leading to increased susceptibility to immune-related diseases. Yet, the extent to which sex influences the dynamic composition of immune cells during immunosenescence remains unknown. Here, we use single-cell RNA sequencing in peripheral blood mononuclear cells from 982 donors to uncover the sex-specific immune aging dynamics. We reveal that aging drives sexually dimorphic compositional and transcriptional shifts, with females showing stronger immune remodeling. Female-specific shifts include the expansion of three cytotoxic CD8+ T effector memory subpopulations and inflammatory monocytes. In addition, female CD4+ central memory T cells exhibit abundance shifts in subpopulations involved in autoimmunity alongside age-associated transcriptional signatures enriched for autoimmune-related pathways. Conversely, males show an age-related expansion of a B cell subpopulation associated with an asymptomatic precursor state to chronic lymphocytic leukemia. These sex-biased, functionally distinct immune subpopulations represent sex-specific hallmarks of immune aging. Our work underscores the complexity and sexual dimorphism of immunosenescence and supports the development of sex-specific strategies to promote healthy aging. Highlights- A single-cell transcriptomic atlas of >1 million PBMCs from 982 donors uncovers sex-specific immune aging trajectories. - Aging females show greater cellular remodeling and stronger transcriptional shifts than males. - Female-specific expansions with age of cytotoxic CD8+ T effector memory cells, inflammatory monocytes, and CD4+ T helper 22 cells reflect a systemic shift toward a pro-inflammatory, self-reactive immune state. - Male-specific B cell shifts reveal expansion of CD5+ clonal subpopulations linked to leukemic precursor states. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=158 SRC="FIGDIR/small/622096v2_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@161b6b1org.highwire.dtl.DTLVardef@214d55org.highwire.dtl.DTLVardef@5c3ee8org.highwire.dtl.DTLVardef@263227_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2021

Cross-tissue analysis of allelic X-chromosome inactivation ratios resolves features of human development

X-chromosome inactivation (XCI) is a random, permanent, and developmentally early epigenetic event that occurs during mammalian embryogenesis. We harness these features of XCI to investigate characteristics of early lineage specification events during human development. We initially assess the consistency of X-inactivation and establish a robust set of XCI-escape genes. By analyzing variance in XCI ratios across tissues and individuals, we find that XCI is completed prior to tissue specification and at a time when 6-16 cells are fated for all tissue lineages. Additionally, we exploit tissue specific variability to characterize the number of cells present at the time of each tissues lineage commitment, ranging from approximately 20 cells in liver and whole blood tissues to 80 cells in brain tissues. By investigating variance of XCI ratios using adult tissue, we resolve key features of human development otherwise difficult to ascertain experimentally and develop scalable methods easily applicable to future data.

developmental biology↗

bioRxiv2020

Virtue as the mean: Pan-human consensus genome significantly improves the accuracy of RNA-seq analyses

The Human Reference Genome serves as the foundation for modern genomic analyses. However, in its present form, it does not adequately represent the vast genetic diversity of the human population. In this study, we explored the consensus genome as a potential successor of the current Reference genome and assessed its effect on the accuracy of RNA-seq read alignment. In order to find the best haploid genome representation, we constructed consensus genomes at the Pan-human, Super-population and Population levels, utilizing variant information from the 1000 Genomes project. Using personal haploid genomes as the ground truth, we compared mapping errors for real RNA-seq reads aligned to the consensus genomes versus the Reference genome. For reads overlapping homozygous variants, we found that the mapping error decreased by a factor of ~2-3 when the Reference was replaced with the Pan-human consensus genome. Interestingly, we also found that using more population-specific consensuses resulted in little to no increase over using the Pan-human consensus, suggesting a limit in the utility of incorporating more specific genomic variation. To assess the functional impact, we compared splice junction expression in the different genomes and found that the Pan-human consensus increases accuracy of splice junction quantification for hundreds of splice junctions.

bioinformatics↗

bioRxiv2020

CoCoCoNet: Conserved and Comparative Co-expression Across a Diverse Set of Species

Co-expression analysis has provided insight into gene function in organisms from Arabidopsis to Zebrafish. Comparison across species has the potential to enrich these results, for example by prioritizing among candidate human disease genes based on their network properties, or by finding alternative model systems where their co-expression is conserved. Here, we present CoCoCoNet as a tool for identifying conserved gene modules and comparing co-expression networks. CoCoCoNet is a resource for both data and methods, providing gold-standard networks and sophisticated tools for on-the-fly comparative analyses across 14 species. We show how CoCoCoNet can be used in two use cases. In the first, we demonstrate deep conservation of a nucleolus gene module across very divergent organisms, and in the second, we show how the heterogeneity of autism mechanisms in humans can be broken down by functional groups, and translated to model organisms. CoCoCoNet is free to use and available to all at https://milton.cshl.edu/CoCoCoNet, with data and R scripts available at ftp://milton.cshl.edu/data.

bioinformatics↗

bioRxiv2019

The transcriptional legacy of developmental stochasticity

Genetic variation, epigenetic regulation and major environmental stimuli are key contributors to phenotypic variation, but the influence of minor perturbations or "noise" has been difficult to assess in mammals. In this work, we uncover one major axis of random variation with a large and permanent influence: developmental stochasticity. By assaying the transcriptome of wild monozygotic quadruplets of the nine-banded armadillo, we find that persistent changes occur early in development, and these give rise to clear transcriptional signatures which uniquely characterize individuals relative to siblings. Comparing these results to human twins, we find the transcriptional signatures which define individuals exhibit conserved co-expression, suggesting a substantial fraction of phenotypic and disease discordance within mammals arises from developmental stochasticity. One sentence summaryLongitudinal gene expression in identical armadillo quadruplets reveals a major role for developmental stochasticity.

genomics↗

bioRxiv2019

Co-expression of calcium channels and delayed rectifier potassium channels protects the heart from proarrhythmic events

Cardiac electrical activity is controlled by the carefully orchestrated activity of more than a dozen different ion conductances. Yet, there is considerable variability in cardiac ion channel expression levels both within and between subjects. In this study we tested the hypothesis that variations in ion channel expression between individuals are not random but rather there are modules of co-expressed genes and that these modules make electrical signaling in the heart more robust. Meta-analysis of 3653 public RNA-Seq datasets identified a strong correlation between expression of CACNA1C (L-type calcium current, ICaL) and KCNH2 (rapid delayed rectifier K+ current, IKr), which was verified in mRNA extracted from human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM). In silico modeling, validated with functional measurements in hiPSC-CM, indicates that the co-expression of CACNA1C and KCNH2 limits the variability in action potential duration and reduces susceptibility to early afterdepolarizations, a surrogate marker for pro-arrhythmia. Impact StatementCoexpressed levels of potassium and calcium ion channel genes in the heart encode more robust cardiac electrophysiology and provide insights into genetic basis of arrhythmic risk

biophysics↗

bioRxiv2019

Is it time to change the reference genome?

The use of the human reference genome has shaped methods and data across modern genomics. This has offered many benefits while creating a few constraints. In the following piece, we outline the history, properties, and pitfalls of the current human reference genome. In a few illustrative analyses, we focus on its use for variant-calling, highlighting its nearness to a "type specimen". We suggest that switching to a consensus reference offers important advantages over the current reference with few disadvantages.

genomics↗

bioRxiv2017

The fractured landscape of RNA-seq alignment: The default in our STARs

Many tools are available for RNA-seq alignment and expression quantification, with comparative value being hard to establish. Benchmarking assessments often highlight methods good performance, but are focused on either model data or fail to explain variation in performance. This leaves us to ask, what is the most meaningful way to assess different alignment choices? And importantly, where is there room for progress? In this work, we explore the answers to these two questions by performing an exhaustive assessment of the STAR aligner. We assess STARs performance across a range of alignment parameters using common metrics, and then on biologically focused tasks. We find technical metrics such as fraction mapping or expression profile correlation to be uninformative, capturing properties unlikely to have any role in biological discovery. Surprisingly, we find that changes in alignment parameters within a wide range have little impact on both technical and biological performance. Yet, when performance finally does break, it happens in difficult regions, such as X-Y paralogs and MHC genes. We believe improved reporting by developers will help establish where results are likely to be robust or fragile, providing a better baseline to establish where methodological progress can still occur.

bioinformatics↗

bioRxiv2017

Addressing the looming identity crisis in single cell RNA-seq

Single cell RNA-sequencing technology (scRNA-seq) provides a new avenue to discover and characterize cell types, but the experiment-specific technical biases and analytic variability inherent to current pipelines may undermine the replicability of these studies. Meta-analysis of rapidly accumulating data is further hampered by the use of ad hoc naming conventions. Here we demonstrate our replication framework, MetaNeighbor, that allows researchers to quantify the degree to which cell types replicate across datasets, and to rapidly identify clusters with high similarity for further testing. We first measure the replicability of neuronal identity by comparing more than 13 thousand individual scRNA-seq transcriptomes, then assess cross-dataset evidence for novel pyramidal neuron and cortical interneuron subtypes identified by scRNA-seq. We find that 24/45 cortical interneuron subtypes and 10/48 pyramidal neuron subtypes have evidence of replication in at least one other study. Identifying these putative replicates allows us to re-analyze the data for differential expression and provide lists of robust candidate marker genes. Across tasks we find that large sets of variably expressed genes can identify replicable cell types and subtypes with high accuracy, indicating many of the transcriptional changes characterizing cell identity are pervasive and easily detected.

bioinformatics↗

bioRxiv2017

Not by systems alone: identifying functional outliers in rare disease pedigrees

In characterizing a disease, it is common to search for dysfunctional genes by assaying the transcriptome. The resulting differentially expressed genes are typically assessed for shared features, such as functional annotation or co-expression. While useful, the reliability of these systems methods is hard to evaluate. To better understand shared disease signals, we assess their replicability by first looking at gene-level recurrence and then pathway-level recurrence along with co-expression signals across six pedigrees of a rare homogeneous X-linked disorder, TAF1 syndrome. We find most differentially expressed genes are not recurrent between pedigrees, making functional enrichment largely distinct in each pedigree. However, we find two highly recurrent \"functional outliers\" (CACNA1I and IGFBP3), genes acting atypically with respect to co-expression and therefore absent from a systems-level assessment. We show this occurs in re-analysis of Huntingtons disease, Parkinsons disease and schizophrenia. Our results suggest a significant role for genes easily missed in systems approaches.

systems biology↗