Biology subjects

Norton, S.

Publications and source records attributed to Norton, S..

7 recordsLinked to original sources

bioRxiv2025

Scaling up orphan crop research: A global genetic perspective of cowpea (Vigna unguiculata) diversity from 10,617 accessions

Cowpea (Vigna unguiculata L. Walp) is a dryland legume crop, providing essential food and nutritional security for millions of people across the semi-arid tropics, in Africa, Asia, and Latin America. However, as a typical "orphan crop", cowpea has long remained underrepresented in global genomic research to support crop improvement. Here, we conducted the largest genetic diversity analysis of cowpea to date, comprising 10,617 accessions sourced from seven international collections. Using genotyping-by-sequencing, we characterized the global patterns of genetic diversity, assessed redundancy within and across collections, and examined the geographic structure of the cowpea global allele pool. Our results revealed nine distinct genetic groups with clear geographic associations and fine-scale population differentiation, reflecting dispersal history, regional adaptation and the influence of modern breeding. Duplication across collections was detected, highlighting the need for improved curation and integration of germplasm resources. Landraces from sub-Saharan Africa do not fully capture the genetic diversity present in several other geographic regions, indicating the existence of abundant and untapped genetic resources worldwide. These findings not only provide insights into the genetic structure and evolutionary history of cowpea but also offer a valuable foundation for harnessing global germplasm diversity to enhance breeding potential and accelerate crop improvement.

plant biology↗

bioRxiv2023

Enhancer-driven regulatory network of forebrain human development provides insights into autism

Cell differentiation is orchestrated by transcription factors (TFs) binding to enhancers, shaping gene regulatory networks that drive neuronal lineage specification. Deciphering these enhancer-driven networks in human forebrain development is essential for understanding the genetic basis of neurodevelopmental disorders. Through integrative epigenomic and transcriptomic analyses of human forebrain organoids derived from 10 individuals with autism spectrum disorder (ASD) and their neurotypical fathers, we constructed a comprehensive enhancer-driven gene regulatory network (GRN) of early neurodevelopment. This GRN revealed hierarchical regulatory transitions guiding neuronal differentiation and was experimentally validated via CRISPR interference (CRISPRi) and loss-of-function analyses. A subnetwork linked ASD-associated transcriptomic alterations to dysregulated TF activity, implicating FOXG1, BHLHE22, EOMES, and NEUROD2 as key regulators of excitatory neuron specification in macrocephalic ASD. These findings suggest that ASD disrupts enhancer-driven regulatory frameworks, altering neuronal cell fate decisions in the developing fetal brain.

genomics↗

bioRxiv2023

Characterization of enhancer activity in early human neurodevelopment using Massively parallel reporter assay (MPRA) and forebrain organoids

AO_SCPLOWBSTRACTC_SCPLOWRegulation of gene expression through enhancers is one of the major processes shaping the structure and function of the human brain during development. High-throughput assays have predicted thousands of enhancers involved in neurodevelopment, and confirming their activity through orthogonal functional assays is crucial. Here, we utilized Massively Parallel Reporter Assays (MPRAs) in stem cells and forebrain organoids to evaluate the activity of [~]7,000 gene-linked enhancers previously identified in human fetal tissues and brain organoids. We used a Gaussian mixture model to evaluate the contribution of background noise in the measured activity signal to confirm the activity of [~]35% of the tested enhancers, with most showing temporal-specific activity, suggesting their evolving role in neurodevelopment. The temporal specificity was further supported by the correlation of activity with gene expression. Our findings provide a valuable gene regulatory resource to the scientific community. AO_SCPLOWUTHORC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWSUMMARYC_SCPLOWEnhancers are non-coding elements that play a crucial role in the regulation of gene expression during brain development. Despite the availability of various techniques available to identify enhancers, their functional activity is relatively less understood, leaving a gap in our understanding of how enhancer behavior might regulate complex transitions of neurodevelopment. To address this, we utilized forebrain organoids, a 3D model system which closely mimics the complex cellular environment of the developing human brain, and employed Massively Parallel Reporter Assay (MPRA) to validate enhancer activity at various stages of forebrain differentiation, from induced pluripotent stem cells (iPSCs) to neuronal progenitors and cortical neurons. Our study provides a comprehensive catalog of over 2,300 enhancers, showcasing their temporal activity profiles during early neuronal development and offering valuable insights into their likely biological functions. This research advances our understanding of enhancer dynamics in brain development and offers new avenues for further investigations in this field.

genomics↗

bioRxiv2023

Massively parallel characterization of psychiatric disorder-associated and cell-type-specific regulatory elements in the developing human cortex

Nucleotide changes in gene regulatory elements are important determinants of neuronal development and disease. Using massively parallel reporter assays in primary human cells from mid-gestation cortex and cerebral organoids, we interrogated the cis-regulatory activity of 102,767 sequences, including differentially accessible cell-type specific regions in the developing cortex and single-nucleotide variants associated with psychiatric disorders. In primary cells, we identified 46,802 active enhancer sequences and 164 disorder-associated variants that significantly alter enhancer activity. Activity was comparable in organoids and primary cells, suggesting that organoids provide an adequate model for the developing cortex. Using deep learning, we decoded the sequence basis and upstream regulators of enhancer activity. This work establishes a comprehensive catalog of functional gene regulatory elements and variants in human neuronal development. One Sentence SummaryWe identify 46,802 enhancers and 164 psychiatric disorder variants with regulatory effects in the developing cortex and organoids.

genomics↗

bioRxiv2022

ASD modelling in organoids reveals imbalance of excitatory cortical neuron subtypes during early neurogenesis

There is no clear genetic etiology or convergent pathophysiology for autism spectrum disorders (ASD). Using cortical organoids and single-cell transcriptomics, we modeled alterations in the formation of the forebrain between sons with idiopathic ASD and their unaffected fathers in thirteen families. Alterations in the transcriptome suggest that ASD pathogenesis in macrocephalic and normocephalic probands involves an opposite disruption of the balance between the excitatory neurons of the dorsal cortical plate and other lineages such as the early-generated neurons from the putative preplate. The imbalance stemmed from a divergent expression of transcription factors driving cell fate during early cortical development. While we did not find probands genomic variants explaining the observed transcriptomic alterations, a significant overlap between altered transcripts and reported ASD risk genes affected by rare variants suggests a degree of gene convergence between rare forms of ASD and developmental transcriptome in idiopathic ASD.

neuroscience↗

bioRxiv2018

LeafCutter vs. MAJIQ and comparing software in the fast-moving field of genomics

In a recent publication, Li et al. introduced LeafCutter, a new method for detecting and quantifying differential splicing of RNA from RNASeq data. In this work, Li et al. first compared LeafCutter to existing methods, then used it for a study of splicing variations and sQTL analysis from a large set of GTEx samples. While the study was elaborate and comprehensive, we want to highlight several issues with the comparative analysis performed by Li et al. We argue these issues created an inaccurate and misleading representation of other tools, namely MAJIQ and rMATS. More broadly, we believe the points we raise regarding the comparative analysis by Li et al. are representative of general issues we all, as authors, editors, and reviewers, are faced with and must address in the current times of fast paced genomics and computational research.

bioinformatics↗

bioRxiv2017

Outlier detection for improved differential splicing quantification from RNA-Seq experiments withreplicates

A key component in many RNA-Seq based studies is the production of multiple replicates for varying experimental conditions. Such replicates allow to capture underlying biological variability and control for experimental ones. However, during data production researchers often lack clear definitions to what constitutes a \"bad\" replicate which should be discarded and if data from failed replicates is published downstream analysis by groups using this data can be hampered. Here we develop a probability model to weigh a given RNA-Seq experiment as a representative of an experimental condition when performing alternative splicing analysis. Using both synthetic and real life data we demonstrate that this model detects outlier samples which are consistently and significantly different compared to samples from the same condition. Using both synthetic and real life data we perform extensive evaluation of the algorithm in different scenarios involving perturbed samples, mislabeled samples, no-signal groups, and different levels of coverage, and show it compares favorably with current state of the art tools.\n\nAvailabilityProgram and code will be available at majiq.biociphers.org

bioinformatics↗