Biology subjects

Jones, A.

Publications and source records attributed to Jones, A..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

A high-quality pseudo-phased genome for Melaleuca quinquenervia shows allelic diversity of NLR-type resistance genes

BackgroundThe coastal wetland tree species Melaleuca quinquenervia (Cav.) S.T.Blake (Myrtaceae), commonly named the broad-leaved paperbark, is a foundation species in eastern Australia, Indonesia, Papua New Guinea, and New Caledonia. The species has been widely grown as an ornamental, becoming invasive in areas such as Florida in the United States. Long-lived trees must respond to a wide range pests and pathogens throughout their lifespan, and immune receptors encoded by the nucleotide- binding domain and leucine-rich repeat containing (NLR) gene family play a key role in plant stress responses. Expansion of this gene family is driven largely by tandem duplication, resulting in a clustering arrangement on chromosomes. Due to this clustering and their highly repetitive domain structure, comprehensive annotation of NLR encoding genes within genomes has been difficult. Additionally, as many genomes are still presented in their haploid, collapsed state, the full allelic diversity of the NLR gene family has not been widely published for outcrossing tree species. ResultsWe assembled a chromosome-level pseudo-phased genome for M. quinquenervia and describe the full allelic diversity of plant NLRs using the novel FindPlantNLRs pipeline. Analysis reveals variation in the number of NLR genes on each haplotype, differences in clusters and in the types and numbers of novel integrated domains. ConclusionsWe anticipate that the high quality of the genome for M. quinquenervia will provide a new framework for functional and evolutionary studies into this important tree species. Our results indicate a likely role for maintenance of NLR allelic diversity to enable response to environmental stress, and we suggest that this allelic diversity may be even more important for long-lived plants.

genomics↗

bioRxiv2023

Plant genome evolution in the genus Eucalyptus driven by structural rearrangements that promote sequence divergence

Genomes have a highly organised architecture (non-random organisation of functional and non-functional genetic elements within chromosomes) that is essential for many biological functions, particularly, gene expression and reproduction. Despite the need to conserve genome architecture, a surprisingly high level of structural variation has been observed within species. As species separate and diverge, genome architecture also diverges, becoming increasingly poorly conserved as divergence time increases. However, within plant genomes, the processes of genome architecture divergence are not well described. Here we use long-read sequencing and de novo assembly of 33 phylogenetically diverse, wild and naturally evolving Eucalyptus species, covering 1-50 million years of diverging genome evolution to measure genome architectural conservation and describe architectural divergence. The investigation of these genomes revealed that following lineage divergence genome architecture is highly fragmented by rearrangements. As genomes continue to diverge, the accumulation of mutations and subsequent divergence beyond recognition of rearrangements becomes the primary driver of genome divergence. The loss of syntenic regions also contribute to genome divergence, but at a slower pace than rearrangements. We hypothesise that duplications and translocations are potentially the greatest contributors to Eucalyptus genome divergence.

genomics↗

bioRxiv2023

Technical and biological sources of unreliability of Infinium type II probes of the Illumina MethylationEPIC BeadChip microarray

The Illumina Methylation array platform has facilitated countless epigenetic studies on DNA methylation (DNAme) in health and disease, yet relatively few studies have so studied its reliability, i.e., the consistency of repeated measures. Here we focus on the reliability of both type I and type II Infinium probes. We propose a method for excluding unreliable probes based on dynamic thresholds for mean intensity (MI) and unreliability, estimated by probe-level simulation of the influence of technical noise on methylation {beta}-values using the background intensities of negative control probes. We validate our method in several datasets, including Illumina MethylationEPIC BeadChip v1.0 data from paired whole blood samples taken six weeks apart. Our analysis revealed that specifically probes with low MI exhibit higher {beta}-value variability between repeated samples. MI was associated with the number of C-bases in the respective probe sequence and correlated negatively with unreliability scores. The unreliability scores were substantiated through validation in a new EPIC v1.0 (blood and cervix) and a publicly available 450k (blood) dataset, as they effectively captured the variability observed in {beta}-values between technical replicates. Finally, despite promising higher robustness, the newer version v2.0 of the MethylationEPIC BeadChip retained a substantial number of probes with poor unreliability scores. To enhance current pre-processing pipelines, we developed an R package to calculate MI and unreliability scores and provide guidance on establishing optimal dynamic score thresholds for a given data set.

genomics↗

bioRxiv2023

Discovery of a novel merbecovirus cDNA clone contaminating agricultural rice sequencing datasets from Wuhan, China

HKU4-related coronaviruses are a group of betacoronaviruses belonging to the same merbecovirus subgenus as Middle Eastern Respiratory Syndrome coronavirus (MERS-CoV), which causes severe respiratory illness in humans with a mortality rate of over 30%. The high genetic similarity between HKU4-related coronaviruses and MERS-CoV makes them an attractive subject of research for modeling potential zoonotic spillover scenarios. In this study, we identify a novel coronavirus contaminating agricultural rice RNA sequencing datasets from Wuhan, China. The datasets were generated by the Huazhong Agricultural University in early 2020. We were able to assemble the complete viral genome sequence, which revealed that it is a novel HKU4-related merbecovirus. The assembled genome is 98.38% identical to the closest known full genome sequence, Tylonycteris pachypus bat isolate BtTp-GX2012. Using in silico modeling, we identified that the novel HKU4-related coronavirus spike protein likely binds to human dipeptidyl peptidase 4 (DPP4), the receptor used by MERS-CoV. We further identified that the novel HKU4-related coronavirus genome has been inserted into a bacterial artificial chromosome in a format consistent with previously published coronavirus infectious clones. Additionally, we have found a near complete read coverage of the spike gene of the MERS-CoV reference strain HCoV-EMC/2012, and identify the likely presence of a HKU4-related-MERS chimera in the datasets. Our findings contribute to the knowledge of HKU4-related coronaviruses and document the use of a previously unpublished HKU4 reverse genetics system in apparent MERS-CoV related gain-of-function research. Our study also emphasizes the importance of improved biosafety protocols in sequencing centers and coronavirus research facilities.

genomics↗

bioRxiv2023

An epigenetic clock in an insect model system

BackgroundThe ageing process is a multifaceted phenomenon marked by the gradual deterioration of cellular and organismal functions, accompanied by an elevated susceptibility to diseases. The intricate interplay between genetic and environmental factors complicates research, particularly in complex mammalian models. In this context, simple invertebrate organisms have been pivotal, but the current models lack detectable DNA methylation limiting the exploration of this critical epigenetic ageing mechanism. This study introduces Nasonia vitripennis, the jewel wasp, as an innovative invertebrate model for investigating the epigenetics of ageing. Leveraging its advantages as a model organism and possessing a functional DNA methylation system, Nasonia emerges as a valuable addition to ageing research. ResultsWhole-genome bisulfite sequencing unveiled dynamic alterations in DNA methylation, with differentially methylated CpGs between distinct time points in both male and female wasps. These changes were associated with numerous genes, enriching for functions related to telomere maintenance, histone methylation, and mRNA catabolic processes. Additionally, other CpGs were found to be variably methylated at each timepoint. Sex-specific effects on epigenetic entropy were observed, indicating differential patterns in the loss of epigenetic stability over time. Constructing an epigenetic clock containing 19 CpGs revealed a robust correlation between epigenetic age and chronological age. ConclusionsNasonia vitripennis emerges as a promising model for investigating the epigenetics of ageing, shedding light on the intricate dynamics of DNA methylation and their implications for age-related processes. This research not only expands the repertoire of ageing models but also opens avenues for deeper exploration of epigenetic mechanisms in the context of ageing.

genomics↗

bioRxiv2023

Optimizing the design of spatial genomic studies

Spatially-resolved genomic technologies have shown promise for studying the relationship between the structural arrangement of cells and their functional behavior. While numerous sequencing and imaging platforms exist for performing spatial transcriptomics and spatial proteomics profiling, these experiments remain expensive and labor-intensive. Thus, when performing spatial genomics experiments using multiple tissue slices, there is a need to select the tissue cross sections that will be maximally informative for the purposes of the experiment. In this work, we formalize the problem of experimental design for spatial genomics experiments, which we generalize into a problem class that we call structured batch experimental design. We propose approaches for optimizing these designs in two types of spatial genomics studies: one in which the goal is to construct a spatially-resolved genomic atlas of a tissue and another in which the goal is to localize a region of interest in a tissue, such as a tumor. We demonstrate the utility of these optimal designs, where each slice is a two-dimensional plane, on several spatial genomics datasets.

bioinformatics↗

bioRxiv2023

Improvements to the Gulf Pipefish Syngnathus scovelli Genome

The Gulf pipefish Syngnathus scovelli has emerged as an important species in the study of sexual selection, development, and physiology, among other topics. The fish family Syngnathidae, which includes pipefishes, seahorses, and seadragons, has become an increasingly attractive target for comparative research in ecological and evolutionary genomics. These endeavors depend on having a high-quality genome assembly and annotation. However, the first version of the S. scovelli genome assembly was generated by short-read sequencing and annotated using a small set of RNA-sequence data, resulting in limited contiguity and a relatively poor annotation. Here, we present an improved genome assembly and an enhanced annotation, resulting in a new official gene set for S. scovelli. By using PacBio long-read high-fidelity (Hi-Fi) sequences and a proximity ligation (Hi-C) library, we fill small gaps and join the contigs to obtain 22 chromosome-level scaffolds. Compared to the previously published genome, the gaps in our novel genome assembly are smaller, the N75 is much larger (13.3 Mb), and this new genome is around 95% BUSCO complete. The precision of the gene models in the NCBIs eukaryotic annotation pipeline was enhanced by using a large body of RNA-Seq reads from different tissue types, leading to the discovery of 28,162 genes, of which 8,061 were non-coding genes. This new genome assembly and the annotation are tagged as a RefSeq genome by NCBI and thus provide substantially enhanced genomic resources for future research involving S. scovelli.

genomics↗

bioRxiv2023

Identification of Candidate Mitochondrial Inheritance Determinants Using the Mammalian Cell-Free System

The degradation of sperm-borne mitochondria after fertilization is a conserved event. This process known as post-fertilization sperm mitophagy, ensures exclusively maternal inheritance of the mitochondria-harbored mitochondrial DNA genome. This mitochondrial degradation is in part carried out by the ubiquitin-proteasome system. In mammals, ubiquitin-binding pro-autophagic receptors such as SQSTM1 and GABARAP have also been shown to contribute to sperm mitophagy. These systems work in concert to ensure the timely degradation of the sperm-borne mitochondria after fertilization. We hypothesize that other receptors, cofactors, and substrates are involved in post-fertilization mitophagy. Mass spectrometry was used in conjunction with a porcine cell-free system to identify other autophagic cofactors involved in post-fertilization sperm mitophagy. This porcine cell-free system is able to recapitulate early fertilization proteomic interactions. Altogether, 185 proteins were identified as statistically different between control and cell-free treated spermatozoa. Six of these proteins were further investigated, including MVP, PSMG2, PSMA3, FUNDC2, SAMM50, and BAG5. These proteins were phenotyped using porcine in vitro fertilization, cell imaging, proteomics, and the porcine cell-free system. The present data confirms the involvement of known mitophagy determinants in the regulation of mitochondrial inheritance and provides a master list of candidate mitophagy co-factors to validate in the future hypothesis-driven studies.

cell biology↗

bioRxiv2023

FcyRIIB is a novel immune checkpoint in the tumor microenvironment limiting activity of Treg-targeting antibodies

Despite pre-clinical murine data supporting T regulatory (Treg) cell depletion as a major mechanism by which anti-CTLA-4 antibodies function in vivo, the two main antibodies tested in patients (ipilimumab and tremelimumab) have failed to demonstrate similar effects. We report analogous findings in an immunocompetent murine model humanized for CTLA-4 and Fcy receptors (hCTLA-4/hFcyR mice), where both ipilimumab and tremelimumab fail to show appreciable Treg depletion. Immune profiling of the tumor microenvironment (TME) in both mice and human samples revealed upregulation of the inhibitory Fcy receptor, FcyRIIB, which limits the ability of the antibody Fc fragment of human anti-CTLA-4 antibodies to induce effective antibody dependent cellular cytotoxicty/phagocytosis (ADCC/ADCP). Blocking FcyRIIB in humanized mice rescues Treg depleting capacity and anti-tumor activity of ipilimumab. For another target, CC motif chemokine receptor 8 (CCR8), which is selectively expressed on tumor infiltrating Tregs, we show that Fc engineering to enhance binding to activating Fc receptors, while limiting binding to the inhibitory Fc receptor, leads to consistent Treg depletion and single-agent activity across multiple tumor models, including B16, MC38 and MB49. These data reveal the importance of reducing engagement to the inhibitory Fc receptor to optimize Treg depletion by TME targeting antibodies. Our results define the inhibitory FcyRIIB receptor as a novel immune checkpoint limiting antibody-mediated Treg depletion in tumors, and demonstrate Fc variant engineering as a means to overcome this limitation and augment efficacy for a repertoire of antibodies currently in use or under clinical evaluation in oncology. Highlights- Fully human anti-CTLA-4 antibodies are limited in their capacity to deplete T regulatory cells and drive durable anti-tumor immunity in humanized FcyR/hCTLA-4 mice - The inhibitory Fcy receptor, FcyRIIB, is upregulated in the tumor microenvironment in patients and in humanized FcyR/hCTLA-4 mice - Blocking FcyRIIB leads to rescue of Treg depletion in humanized murine models - Fc engineering can improve the depleting capacity and in vivo anti-tumor activity of anti-CTLA and anti-CCR8 antibodies targeting tumor infiltrating Tregs

immunology↗

bioRxiv2022

Plastid Genome Assembly Using Long-read Data (ptGAUL)

Although plastid genome (plastome) structure is highly conserved across most seed plants, investigations during the past two decades revealed several disparately related lineages that experienced substantial rearrangements. Most plastomes contain a large, inverted repeat and two single-copy regions and few dispersed repeats, however the plastomes of some taxa harbor long repeat sequences (>300 bp). These long repeats make it difficult to assemble complete plastomes using short-read data leading to misassemblies and consensus sequences that have spurious rearrangements. Single-molecule, long-read sequencing has the potential to overcome these challenges, yet there is no consensus on the most effective method for accurately assembling plastomes using long-read data. We generated a pipeline, plastid Genome Assembly Using Long-read data (ptGAUL), to address the problem of plastome assembly using long-read data from Oxford Nanopore Technologies (ONT) or Pacific Biosciences platforms. We demonstrated the efficacy of the ptGAUL pipeline using 16 published long-read datasets. We showed that ptGAUL produces accurate and unbiased assemblies. Additionally, we employed ptGAUL to assemble four new Juncus (Juncaceae) plastomes using ONT long reads. Our results revealed many long repeats and rearrangements in Juncus plastomes compared with basal lineages of Poales.

bioinformatics↗

bioRxiv2022

Subset-specific mitochondrial and DNA damage shapes T cell responses to fever and inflammation

Heat is a cardinal feature of inflammation. Despite temperature variability and dependence of enzymes and complexes, how heat and fever affect immune cells remains uncertain. We found that heat broadly increased inflammatory activity of CD4+ T cell subsets and decreased Treg suppressive function. Th1 cells, however, also selectively developed mitochondrial dysfunction with high levels of ROS production and DNA damage. This led Th1 cells to undergo Tp53-dependent death, which was required to minimize the accumulation of mutations in heat and inflammation. Th1 cells with similar DNA damage signatures were also detected in Crohns disease and rheumatoid arthritis. Fever and inflammation-associated heat thus selectively induce mitochondrial stress and DNA damage in activated Th1 cells that requires p53 to maintain genomic integrity of the T cell repertoire. One Sentence SummaryFever temperatures augment CD4+ T cell-mediated inflammation but induce differential metabolic stress and DNA damage in T cell subsets, with Th1 cells selectively sensitive and dependent on p53 to induce apoptosis and maintain genomic integrity.

immunology↗

bioRxiv2022

Statistical challenges for inferring multiple SARS-CoV-2 spillovers with early outbreak phylodynamics

Understanding how SARS-CoV-2 entered the human population, thereby causing the COVID-19 pandemic, is one of the most urgent questions in science today. Two hypotheses are widely acknowledged as being most likely to explain the pandemics origin in late 2019: (i) the "natural origin" hypothesis that one or more cross-species transmissions from animals into humans occurred, most likely at the Huanan Seafood Market in Wuhan, China; (ii) the "laboratory origin" hypothesis, that scientific research activities led to the unintentional leak of SARS-CoV-2 from a laboratory into the general population. A recent analysis of SARS-CoV-2 genomes by Pekar et al. [Science 377:960-966 (2022)] claims to establish at least two separate spillover events from animals into humans, thus claiming to provide strong evidence for the natural origin hypothesis. However, here we use outbreak simulations to show that the findings of Pekar et al. are heavily impacted by two methodological artifacts: the dubious exclusion of informative SARS-CoV-2 genomes, and their reliance on unrealistic phylodynamic models of SARS-CoV-2. Absent models that incorporate these effects, one cannot conclude multiple SARS-CoV-2 spillovers into humans. Our results cast doubt on a primary point of evidence in favor of the natural origin hypothesis. Lay SummaryIt is not known if SARS-CoV-2 spilled over from animals into humans at the Huanan Seafood Market, or arose as a result of research activities studying bat coronaviruses. Two recent papers had claimed to answer this question, but here we show those papers are both inconclusive as they fail to account for biases in how medical managers became alerted to SARS-CoV-2 and how public health authorities sampled early cases. Additionally, key data points conflicting with the authors conclusions were improperly excluded from the analysis. The papers methods do not justify their conclusions, and the origin of SARS-CoV-2 remains an urgent, open question for science.

evolutionary biology↗

bioRxiv2022

A neuroepithelial wave of BMP signalling drives anteroposterior specification of the tuberal hypothalamus

The tuberal hypothalamus houses several major hypothalamic nuclei, dozens of transcriptionally distinct cell types, and clinically relevant cell populations implicated in obesity and related metabolic disorders. Building on recent advances in the field, here we draw upon transcriptional, signalling, and fate mapping analyses of chicken embryos and neuroepithelial explants to analyze tuberal hypothalamic development. We show that a wave of BMP signalling sweeps through early floor plate-like progenitors overlying prospective Rathkes pouch as they track anteriorly. The timing of BMP signalling correlates with cell fate, with anterior tuberal specification complete by Hamilton-Hamburger (HH) stage 10 but posterior tuberal progenitors requiring BMPs after this point. scRNA-Seq profiling of FGF10-expressing cells, a proxy for cells with active BMP signalling, through HH8-21 reveals transcriptional differences that may underlie their differing response to BMPs, and the switch from neuroepithelial progenitors to stem-like radial glial cells. This study provides an integrated account of the development of the tuberal hypothalamus.

developmental biology↗

bioRxiv2022

Linking histology and molecular state across human tissues

Histological imaging and molecular profiling of human tissues both offer information-rich characterizations of biological structure and function. Each of these modalities has been used to characterize the organization and dysregulation of a variety of tissues and cell types. While large-scale studies of each modality in isolation have been conducted, it remains largely unknown the extent to which these two views of a tissue relate to one another. Understanding how cellular states are encoded in cellular morphology would increase the utility and interpretability of imaging data; conversely, understanding the state of the cells within histology images would give deeper insights into the types and states of cells that constitute these tissue samples. To this end, we jointly analyzed 13, 360 human tissue samples with paired bulk gene expression profiles and histology images across 935 donors from the Genotype and Tissue Expression (GTEx) Consortium v8 study. This analysis reveals relationships among gene expression and cellular morphology through shared sources of expression and morphological heterogeneity both within and between tissue types. We describe shared sources of variation including cell-type heterogeneity, sample ischemic time, and donor health and demographics. We find specific correlated effects in both morphology and transcription linked to specific donor characteristics, such as their use of mechanical ventilation. This paired understanding adds value to each data modality on their own by enabling a more precise characterization of the alternative modality in the absence of those data.

genomics↗

bioRxiv2022

Androgen receptor inhibition induces metabolic reprogramming and increased reliance on oxidative mitochondrial metabolism in prostate cancer

Prostate cancer cells that survive clinical androgen receptor (AR) blockade mediate disease progression and lethality. Reprogrammed metabolic signaling is one mechanism by which tumor cells can survive treatment. However, how AR inhibition reprograms metabolism, and whether altered metabolism can be exploited to eradicate cells that survive AR blockade, remains unclear. Here, we comprehensively characterized the effect of AR blockade on prostate cancer metabolism using transcriptomics, metabolomics, and bioenergetics approaches. AR inhibition maintains oxidative mitochondrial metabolism and reduces glycolytic signaling, through hexokinase II downregulation and decreased MYC activity. Robust elongation of mitochondria via reduced DRP1 activity supports cell fitness after AR blockade. In addition, AR inhibition enhances sensitivity to complex I inhibitors in several models, suggesting that AR blockade increases reliance on oxidative mitochondrial metabolism. Our study provides an enhanced understanding of how AR inhibition alters metabolic signaling and highlights the potential of therapies that target metabolic vulnerabilities in AR-inhibited cells.

cancer biology↗

bioRxiv2022

A Poisson reduced-rank regression model for association mapping in sequencing data

Single-cell RNA sequencing (scRNA-seq) technologies allow for the study of gene expression in individual cells. Often, it is of interest to understand how transcriptional activity is associated with cell-specific covariates, such as cell type, genotype, or measures of cell health. Traditional approaches for this type of association mapping assume independence between the outcome variables (or genes), and perform a separate regression for each. However, these methods are computationally costly and ignore the substantial correlation structure of gene expression. Furthermore, count-based scRNA-seq data pose challenges for traditional models based on Gaussian assumptions. We aim to resolve these issues by developing a reduced-rank regression model that identifies low-dimensional linear associations between a large number of cell-specific covariates and high-dimensional gene expression readouts. Our probabilistic model uses a Poisson likelihood in order to account for the unique structure of scRNA-seq counts. We demonstrate the performance of our model using simulations, and we apply our model to a scRNA-seq dataset, a spatial gene expression dataset, and a bulk RNA-seq dataset to show its behavior in three distinct analyses. We show that our statistical modeling approach, which is based on reduced-rank regression, captures associations between gene expression and cell- and sample-specific covariates by leveraging low-dimensional representations of transcriptional states.

bioinformatics↗

bioRxiv2022

Development of an In Vitro Test for the Optimization of Drug Diffusion in Pediatric Solid Tumors

There is significant long-term morbidity and mortality associated with the treatment of childhood cancer, and the risk of these effects continues to increase years after completion of therapy. Among childhood cancer survivors the cumulative incidence of a chronic health condition is 99% within 50 years of the original cancer diagnosis. There is a high risk for severe, disabling, or life-threatening chronic condition caused by the chemotherapy used to treat the initial malignancy. Current standards for determining chemotherapy dosage to treat solid tumor malignancies of pediatric patients is based on several factors, including the patients surface area, age, weight, and height. To reduce the long-term effects of chemotherapy in pediatric patients our group is focused on developing novel local drug delivery systems to treat solid tumors and minimize systemic effects. The aim of the current study is to develop an in vitro method to quantify drug diffusion through tumor tissue that will allow us to optimize the dose required to treat solid tumor malignancies in vivo. We hope by modeling the significant parameters that influence drug penetration of chemotherapy drugs, we can facilitate the development of innovative drug delivery methods and more effective administration of anticancer agents to better treat pediatric malignancies and improve both short-term and long-term outcomes for childhood cancer.

bioengineering↗

bioRxiv2022

Enrichment of somatic mutations in schizophrenia brain targets prenatally active transcription factor bindings sites

Schizophrenia (SCZ) is a complex neuropsychiatric disorder in which both germline genetic mutations and maternal factors, such as infection and immune activation, have been implicated, but how these two strikingly different mechanisms might converge on the same phenotype is unknown. During development, cells accumulate somatic, mosaic mutations in ways that can be shaped by the cellular environment or endogenous processes, but these early developmental mutational patterns have not been studied in SCZ. Here we analyzed deep (267x) whole-genome sequencing (WGS) of DNA from cerebral cortical neurons isolated from 61 SCZ and 25 control postmortem brains to capture mutations occurring before or during fetal neurogenesis. SCZ cases showed a >15% increase in genome-wide sSNV compared to controls (p < 2e-10). Remarkably, mosaic T>G mutations and CpG transversions (CpG>GpG or CpG>ApG) were 79- and 62-fold enriched, respectively, at transcription factor binding sites (TFBS) in SCZ, but not in controls. The pattern of T>G mutations resembles mutational processes in cancer attributed to oxidative damage that is sterically blocked from DNA repair by transcription factors (TFs) bound to damaged DNA. The CpG transversions similarly suggest unfinished DNA demethylation resulting in abasic sites that can also be blocked from repair by bound TFs. Allele frequency analysis suggests that both localized mutational spikes occur in the first trimester. We call this prenatal mutational process "skiagenesis" (from the Greek skia, meaning shadow), as these mutations occur in the shadow of bound TFs. Skiagenesis reflects as-yet unidentified prenatal factors and is associated with SCZ risk in a subset ([~]13%) of cases. In turn, mutational disruption of key TFBS active in fetal brain is well positioned to create SCZ-specific gene dysregulation in concert with germline risk genes. Skiagenesis provides a fingerprint for exploring how epigenomic regulation and prenatal factors such as maternal infection or immune activation may shape the developmental mutational landscape of human brain.

genomics↗