Biology subjects

Kilpinen, H.

Publications and source records attributed to Kilpinen, H..

9 recordsLinked to original sources

bioRxiv2026

INTS6 loss of function disrupts transcriptional regulation in mild intellectual disability

Pathogenic variants in genes involved in transcriptional regulation and RNA processing have emerged as points of functional convergence in neurodevelopmental disorders (NDDs), but their specific disease mechanisms remain unknown. By screening 1,562 Finnish extended families from the Northern Finland Intellectual Disability cohort affected by cognitive impairment, we discovered a family with six affected members carrying a heterozygous loss- of-function variant in INTS6. INTS6 is a conserved member of the phosphatase module of the Integrator complex, which regulates RNA polymerase II activity, with a reported role in the pathogenesis of NDDs. To determine the variants transcriptomic effects, we performed RNA-sequencing of induced pluripotent stem cells (iPSCs) and iPSC-derived neuronal cells from cases and controls, revealing transcriptome-wide splicing defects, with increased intron retention observed in genes involved in translation, cell cycle and RNA processing in variant carriers. CRISPR-Cas9 knock-in iPSCs confirmed that the variant was associated with downregulation of transcription factors and developmental processes in early neuron differentiation. In addition, downregulated genes in variant carrier neurons were enriched for synaptic genes, suggesting effects on neuronal development. These findings highlight the critical role of INTS6 in transcriptional regulation of human neurodevelopment and reinforce its association with NDDs.

genetics↗

bioRxiv2024

An in vivo and in vitro spatiotemporal atlas of human midbrain development

The dopaminergic system has key roles in human physiology and is implicated in a broad range of neurological and neuropsychiatric conditions that are increasingly investigated using induced pluripotent stem cell-derived midbrain models. To determine the similarity of such models to human systems, we undertook single cell and spatial profiling of first and second trimester fetal midbrain and compared it to in vitro midbrain models. Our initial histological analysis of second trimester fetal midbrain revealed structural complexity already similar to that of adult tissue, although this similarity did not fully extend to transcriptional activity. Moreover, we show that in vitro models recapitulate the transcriptional activity of late first trimester fetal midbrain, while 3D models replicate the spatial organization and cellular microenvironments of first and second trimester fetal midbrain. Understanding the extent of human tissue recapitulation in midbrain laboratory models is essential to justify their use as biological proxies.

neuroscience↗

bioRxiv2023

DeconV: Probabilistic Cell Type Deconvolution from Bulk RNA-sequencing Data

Bulk RNA-Seq remains a widely adopted technique to profile gene expression, primarily due to the persistent challenges associated with achieving single-cell resolution. However, a key challenge is accurately estimating the proportions of different cell types within these bulk samples. To address this issue, we introduce DeconV, a probabilistic framework for cell-type deconvolution that uses scRNA-Seq data as a reference. This approach aims to mitigate some of the limitations in existing methods by incorporating statistical frameworks developed for scRNA-Seq, thereby simplifying issues related to reference preprocessing such as normalization and marker gene selection. We benchmarked DeconV against established methods, including MuSiC, CIBERSORTx, and Scaden. Our results show that DeconV performs comparably in terms of accuracy to the best-performing method, Scaden, but provides additional interpretability by offering confidence intervals for its predictions. Furthermore, the modular design of DeconV allows for the investigation of discrepancies between bulk-sequenced samples and artificially generated pseudo-bulk samples.

bioinformatics↗

bioRxiv2023

Characterization of cortical neurodevelopment in vitro using gene expression and morphology profiles from single cells

AbstractDifferentiation of induced pluripotent stem cells (iPSC) towards neuronal lineages has enabled diverse cellular models of human neurodevelopment and related disorders. However, in vitro differentiation is a variable process that frequently leads to heterogeneous cell populations that may confound disease-relevant phenotypes. Here, we report a thorough characterization of cortical neuron differentiation from iPSCs using joint profiling of neuronal morphology and transcriptomics in single cells. We assayed 60,000 developing neurons across three timepoints with CellPainting, a high-content imaging method, and single-cell RNA-sequencing (scRNA-seq). By modeling the relationship between morphological features and gene expression within our differentiation system, we annotated image-based features with biological functions and found that while phenotypes related to cell morphology capture broader neuronal classes than scRNA-seq, they enhance our ability to quantify the biological processes that drive neuronal differentiation over time, such as mitochondrial function and cell cycle. Further, we found that while over 60% of the cells match those seen in the fetal brain, 28% represented metabolically abnormal cell states and broader neuronal classes specific to in vitro cells. Finally, we show that specific subtypes of iPSC-derived cortical neurons are a relevant model for a range of brain-related complex traits, including schizophrenia and bipolar disorder, highlighting the potential of multi-modal single cell phenotyping for disease modeling.

genomics↗

bioRxiv2022

Differentiation of human induced pluripotent stem cells into cortical neural stem cells

Efficient and effective methods for converting human induced pluripotent stem cells (iPSC) into differentiated derivatives are critical for performing robust, large-scale studies of development and disease modelling, and for providing a source of cells for regenerative medicine. Here, we describe a 14-day neural differentiation protocol which allows for the scalable, simultaneous differentiation of multiple iPSC lines into cortical neural stem cells (NSCs). We currently employ this protocol to differentiate and compare sets of engineered iPSC lines carrying loss of function alleles in developmental disorder associated genes, alongside isogenic wildtype controls. Using RNA sequencing (RNA-Seq), we can examine the changes in gene expression brought about by each disease gene knockout, to determine its impact on neural development and explore mechanisms of disease. The 10-day Neural Induction period uses the well established dual-SMAD inhibition approach combined with Wnt/{beta}-Catenin inhibition to selectively induce formation of cortical NSCs. This is followed by a 4-day Neural Maintenance period facilitating NSC expansion and rosette formation, and NSC cryopreservation. We also describe methods for thawing and passaging the cryopreserved NSCs, which are useful in confirming their viability for further culture. Routine implementation of ICC Quality Control confirms the presence of PAX6-positive and/or FOXG1-positive NSCs and the absence of OCT4-positive iPSCs after differentiation. RNA-Seq, flow cytometry, immunocytochemistry (ICC) and RT-qPCR provide additional confirmation of robust presence of NSC markers in the differentiated cells. The broader utility and application of our protocol is demonstrated by the successful differentiation of wildtype iPSC lines from five additional independent donors. This paper thereby describes an efficient method for the production of large numbers of high purity cortical NSCs, which are widely applicable for downstream research into developmental mechanisms, further differentiation into postmitotic cortical neurons, or other applications such as large-scale drug screening experiments.

developmental biology↗

bioRxiv2022

Effects of somatic mutations on cellular differentiation in iPSC models of neurodevelopment

The use of induced pluripotent stem cells (iPSC) as models for development and human disease has enabled the study of otherwise inaccessible tissues. A remaining challenge in developing reliable models is our limited understanding of the factors driving irregular in vitro differentiation of iPSCs, particularly the impact of acquired somatic mutations. We leveraged data from a pooled dopaminergic neuron differentiation experiment of 238 iPSC lines profiled with single-cell and whole-exome sequencing to study how somatic mutations affect differentiation outcomes. Differentiation was tracked at three time points corresponding to neural progenitors, early neurons and mature neurons. We found that deleterious somatic mutations in key developmental genes, notably the BCOR gene, are strongly associated with failure in dopaminergic neuron differentiation, with lines carrying such mutations also showing larger proliferation rate in culture. We further identified broad differences in cell type composition between failed and successfully differentiating lines, as well as significant changes in gene expression contributing to the inhibition of neurogenesis, a functional process also targeted by deleterious mutations in failed lines. Our work highlights the need to routinely measure the burden of deleterious mutations in iPSC lines and calls for caution in interpreting differentiation-related phenotypes in disease-modelling experiments.

genomics↗

bioRxiv2021

PAC: Highly accurate quantification of allelic gene expression for population and disease genetics

Analysis of allele-specific gene expression (ASE) is a powerful approach for studying gene regulation. However, detection of ASE events relies on accurate alignment of RNA-sequencing reads, where challenges still remain. We have developed PAC, a method that combines multiple steps to improve the quantification of allelic reads, including personalised (i.e. diploid) read alignment with improved allocation of multi-mapping reads. We show that PAC outperforms standard alignment approaches for ASE detection in both accuracy and in the number of sites it can reliably quantify.

genomics↗

bioRxiv2018

Population-scale proteome variation in human induced pluripotent stem cells

Realising the potential of human induced pluripotent stem cell (iPSC) technology for drug discovery, disease modelling and cell therapy requires an understanding of variability across iPSC lines. While previous studies have characterized iPS cell lines genetically and transcriptionally, little is known about the variability of the iPSC proteome. Here, we present the first comprehensive proteomic iPSC dataset, analysing 202 iPSC lines derived from 151 donors. We characterise the major genetic determinants affecting proteome and transcriptome variation across iPSC lines and identify key regulatory mechanisms affecting variation in protein abundance. Our data identified >700 human iPSC protein quantitative trait loci (pQTLs). We mapped trans regulatory effects, identifying an important role for protein-protein interactions. We discovered that pQTLs show increased enrichment in disease-linked GWAS variants, compared with RNA-based eQTLs.

genomics↗

bioRxiv2017

Molecular and functional variation in iPSC-derived sensory neurons

Induced pluripotent stem cells (iPSCs), and cells derived from them, have become key tools to model biological processes and disease mechanisms, particularly in cell types such as neurons that are difficult to access from living donors. Here, we present the first map of regulatory variants in an iPSC-derived cell type. To investigate genetic contributions to human sensory function, we performed 123 differentiations of iPSCs from 103 unique donors to a sensory neuronal fate, and measured gene expression, chromatin accessibility, and neuronal excitability. Compared with primary dorsal root ganglion, where sensory nerves collect near the spinal cord, gene expression was more variable across iPSC-derived neuronal cultures, particularly in genes related to differentiation and nervous system development. Single cell RNA-sequencing revealed that although the majority of cells are neuronal and express the expected marker genes, a substantial fraction have a fibroblast-like expression profile. By applying an allele-specific method we identify 3,778 quantitative trait loci influencing gene expression, 6,318 for chromatin accessibility, and 2,097 for RNA splicing at FDR 10%. A number of these overlap with common disease associations, and suggest candidate causal variants and target genes. These include known causal variants at SNCA for Parkinsons disease and TNFRSF1A for multiple sclerosis, as well as new candidates for migraine, Parkinsons disease, and schizophrenia.

genomics↗