Biology subjects

Baird, L.

Publications and source records attributed to Baird, L..

8 recordsLinked to original sources

bioRxiv2024

A diverse landscape of FGFR alterations and co-mutations defines novel therapeutic strategies in pediatric low-grade gliomas

Alterations in Fibroblast growth factor receptor (FGFR)-family proteins frequently occur as oncogenes in many cancers, including a subset of pediatric gliomas. Here, we performed a genomic analysis of 11,635 gliomas across ages and found that 4.5% of all gliomas harbor FGFR alterations including structural variants (SV) and single nucleotide variants (SNV), with an incidence of almost 10% in pediatric gliomas. FGFR family members are differentially enriched by age, tumor grade, and histological subtype, with FGFR1-alterations associated with glioneuronal histologies and pediatric low-grade gliomas. Across development, we find FGFR1 expression in both neuronal and glial precursors, while FGFR3 expression is largely restricted to astrocytic lineages. Leveraging novel isogenic model systems, we confirm FGFR1 alterations to be sufficient to activate MAPK and mTOR signaling, drive gliomagenesis, activate neuronal transcriptional programs and exhibit sensitivity to MAPK pathway inhibitors, including pan-FGFR inhibitors. Models driven by FGFR1 SVs exhibited different patterns of sensitivity compared to those driven by SNVs. Finally, we performed a retrospective analysis of clinical responses in children diagnosed with FGFR-driven gliomas and found that targeted MAPK or FGFR-inhibition with currently available inhibitors is largely associated with stability of disease. This study provides key insights into the biology of FGFR1-altered gliomas, therapeutic strategies to target them and associated challenges that still need to be overcome.

cancer biology↗

bioRxiv2024

Single-cell multidimensional profiling of tumor cell heterogeneity in supratentorial ependymomas

Supratentorial ependymomas are aggressive childhood brain cancers that retain features of neurodevelopmental cell types and segregate into molecularly and clinically distinct subgroups, suggesting different developmental roots. The developmental signatures as well as microenvironmental factors underlying aberrant cellular transformation and behavior across each supratentorial ependymoma subgroup are unknown. Here we integrated single cell- and spatial transcriptomics, as well as in vitro and in vivo live-cell imaging to define supratentorial ependymoma cell states, spatial organization, and dynamic behavior within the neural microenvironment. We find that individual tumor subgroups harbor two distinct progenitor-like cell states reminiscent of early human brain development and diverge in the extent of neuronal or ependymal differentiation. We further uncover several modes of spatial organization of these tumors, including a high order architecture influenced by mesenchymal and hypoxia signatures. Finally, we identify an unappreciated role for brain-resident cells in shifting supratentorial ependymoma cellular heterogeneity towards neuronal-like cells that co-opt immature neuronal morphology and invasion mechanisms. Collectively, these findings provide a multidimensional framework to integrate transcriptional and phenotypic characterization of tumor heterogeneity in supratentorial ependymoma and its potential clinical implications.

cancer biology↗

bioRxiv2022

Genomic Structural Equation Modeling Reveals Latent Phenotypes in the Human Cortex with Distinct Genetic Architecture

Genetic contributions to human cortical structure manifest pervasive pleiotropy. This pleiotropy may be harnessed to identify unique genetically-informed parcellations of the cortex that are neurobiologically distinct from anatomical, functional, cytoarchitectural, or other cortical parcellation schemes. We investigated genetic pleiotropy by applying genomic structural equation modeling (SEM) to model the genetic architecture of cortical surface area (SA) and cortical thickness (CT) of 34 brain regions recently reported in the ENIGMA cortical GWAS. Genomic SEM uses the empirical genetic covariance estimated from GWAS summary statistics with LD score regression (LDSC) to discover factors underlying genetic covariance. Genomic SEM can fit a multivariate GWAS from summary statistics, which can subsequently be used for LD score regression (LDSC). We found the best-fitting model of cortical SA was explained by 6 latent factors and CT was explained by 4 latent factors. The multivariate GWAS of these latent factors identified 74 genome-wide significant (GWS) loci (p<5x10-8), including many previously implicated in neuroimaging phenotypes, behavioral traits, and psychiatric conditions. LDSC of latent factor GWAS results found that SA-derived factors had a positive genetic correlation with bipolar disorder (BPD), and major depressive disorder (MDD), and a negative genetic correlation with attention deficit hyperactivity disorder (ADHD), MDD, and insomnia, while CT factors displayed a negative genetic correlation with alcohol dependence. Jointly modeling the genetic architecture of complex traits and investigating multivariate genetic links across phenotypes offers a new vantage point for mapping genetically informed cortical networks. HIGHLIGHTSO_LIGenomic SEM can examine genetic correlation across cortical regions. C_LIO_LIWe inferred regional genetic networks of cortical thickness and surface area. C_LIO_LINetwork-associated variants have been implicated in multiple traits. C_LIO_LIThese networks are genetically correlated with several psychiatric disorders including MDD, bipolar, ADHD, and alcohol dependence. C_LI

genomics↗

bioRxiv2021

The Mutational Dynamics of Short Tandem Repeats in Large, Multigenerational Families

Short tandem repeats (STRs) are tandemly repeated sequences of 1-6 bp motifs. STRs compose approximately 3% of the genome, and mutations at STR loci have been linked to dozens of human diseases including amyotrophic lateral sclerosis, Friedreich ataxia, Huntington disease, and fragile X syndrome. Improving our understanding of these mutations would increase our knowledge of the mutational dynamics of the genome and may uncover additional loci that contribute to disease. Here, to estimate the genome-wide pattern of mutations at STR loci, we analyzed blood-derived whole-genome sequencing data for 544 individuals from 29 three-generation CEPH pedigrees. These pedigrees contain both sets of grandparents, the parents, and an average of 9 grandchildren per family. Using HipSTR we identified de novo STR mutations in the 2nd generation of these pedigrees. Analyzing ~1.6 million STR loci, we estimate the empircal de novo STR mutation rate to be 5.24*10-5 mutations per locus per generation. We find that perfect repeats mutate ~2x more often than imperfect repeats. De novo STRs are significantly enriched in Alu elements (p < 2.2e-16). Approximately 30% of STR mutations occur within Alu elements, which compose only ~11% of the genome, and ~10% are found in LINE-1 insertions, which compose ~17% of the genome. Phasing these de novo mutations to the parent of origin shows that parental transmission biases vary among families. We estimate the average number of de novo genome-wide STR mutations per individual to be ~85, which is similar to the average number of observed de novo single nucleotide variants.

genomics↗

bioRxiv2020

Stretch-activated ion channels identified in the touch-sensitive structures of carnivorous Droseraceae plants

In response to touch, some carnivorous plants such as the Venus flytrap have evolved spectacular movements to capture animals for nutrient acquisition. However, the molecules that confer this sensitivity remain unknown. We used comparative transcriptomics to show that expression of three genes encoding homologs of the MscS-Like (MSL) and OSCA/TMEM63 family of mechanosensitive ion channels are localized to touch-sensitive trigger hairs of Venus flytrap. We focus here on the candidate with the most enriched expression in trigger hairs, the MSL homolog FLYCATCHER1 (FLYC1). We show that FLYC1 transcripts are localized to mechanosensory cells within the trigger hair, transfecting FLYC1 induces chloride-permeable stretch-activated currents in naive cells, and transcripts coding for FLYC1 homologs are expressed in touch-sensing cells of Cape sundew, a related carnivorous plant of the Droseraceae family. Our data suggest that the mechanism of prey recognition in carnivorous Droseraceae evolved by co-opting ancestral mechanosensitive ion channels to sense touch.

plant biology↗

bioRxiv2020

De novo structural mutation rates and gamete-of-origin biases revealed through genome sequencing of 2,396 families

Each human genome includes de novo mutations that arose during gametogenesis. While these germline mutations represent a fundamental source of new genetic diversity, they can also create deleterious alleles that impact fitness. The germline mutation rate for single nucleotide variants and factors that significantly influence this rate, such as parental age, are now well established. However, far less is known about the frequency, distribution, and features that impact de novo structural mutations. We report a large, family-based study of germline mutations, excluding aneuploidy, that affect genome structure among 572 genomes from 33 families in a multigenerational CEPH-Utah cohort and 2,363 cases of non-familial autism spectrum disorder (ASD), 1,938 unaffected siblings, and both parents (9,599 genomes in total). We find that de novo structural mutations detected by alignment-based, short-read WGS occurred at an overall rate of at least 0.160 events per genome in unaffected individuals and was significantly higher (0.206 per genome) in ASD cases. In both probands and unaffected samples, nearly 73% of de novo structural mutations arose in paternal gametes, and predict most de novo structural mutations to be caused by mutational mechanisms that do not require sequence homology. After multiple testing correction we did not observe a statistically significant correlation between parental age and the rate of de novo structural variation in offspring. These results highlight that a spectrum of mutational mechanisms contribute to germline structural mutations, and that these mechanisms likely have markedly different rates and selective pressures than those leading to point mutations.

genomics↗

bioRxiv2019

Large, three-generation CEPH families reveal post-zygotic mosaicism and variability in germline mutation accumulation

The number of de novo mutations (DNMs) found in an offsprings genome is known to increase with both paternal and maternal age. But does the rate of mutation accumulation in parental gametes differ across families? To answer this question, we analyzed DNMs in 33 large, three-generation families collected in Utah by the Centre dEtude du Polymorphisme Humain (CEPH) consortium. We observed significant variability in parental age effects on DNM counts across families, ranging from 0.24 to 3.33 additional DNMs per year. Using up to 14 grandchildren in these families, we find that 3% of DNMs originated following primordial germ cell specification (PGCS) in a parent, and differ from non-mosaic germline DNMs in their mutational spectra. We also identify a median of 3 gonosomal mutations per sample in the F1 generation, which, along with post-PGCS DNMs, occur at equivalent frequencies on the paternal and maternal haplotypes. These results demonstrate that the rate of germline mutation accumulation varies among families with similar ancestry, and confirm that parental mosaicism is a substantial source of de novo mutations in children. Data and code availabilityCode used for statistical analysis and figure generation has been deposited on GitHub as a collection of annotated Jupyter Notebooks: https://github.com/quinlan-lab/ceph-dnm-manuscript. Data files containing germline de novo mutations, as well as the gonosomal and post-primordial germ cell specification (PGCS) mosaic mutations, are included with these Notebooks. To mitigate compatibility/version issues, we have also made all notebooks available in a Binder environment, accessible at the above GitHub repository.

genetics↗

bioRxiv2018

Pedigree-based estimation of human mobile element retrotransposition rates

Germline mutation rates in humans have been estimated for a variety of mutation types, including single nucleotide and large structural variants. Here we directly measure the germline retrotransposition rate for the three active retrotransposon elements: L1, Alu, and SVA. We utilized three tools for calling Mobile Element Insertions (MEIs) (MELT, RUFUS, and TranSurVeyor) on blood-derived whole genome sequence (WGS) data from 603 CEPH individuals, comprising 33 three-generation pedigrees. We identified 27 de novo MEIs in 440 births. The retrotransposition rate estimates for Alu elements, one in 40, is roughly half the rate estimated using phylogenetic analyses, a difference in magnitude similar to that observed for single nucleotide variants. The L1 retrotransposition rate is one in 62 births and is within range of previous estimates (1:20-1:200 births). The SVA retrotransposition rate, one in 55 births, is much higher than the previous estimate of one in 900 births. Our large, three-generation pedigrees allowed us to assess parent-of-origin effects and the timing of insertion events in either gametogenesis or early embryonic development. We find a statistically significant paternal bias in Alu retrotransposition. Our study represents the first in-depth analysis of the rate and dynamics of human retrotransposition from WGS data in three-generation human pedigrees.

genetics↗