Biology subjects

Greenstreet, L.

Publications and source records attributed to Greenstreet, L..

8 recordsLinked to original sources

bioRxiv2024

Single-cell transcriptomics reveals evolutionary reconfiguration of embryonic cell fate specification in the sea urchin Heliocidaris erythrogramma

Altered regulatory interactions during development likely underlie a large fraction of phenotypic diversity within and between species, yet identifying specific evolutionary changes remains challenging. Analysis of single-cell developmental transcriptomes from multiple species provides a powerful framework for unbiased identification of evolutionary changes in developmental mechanisms. Here, we leverage a "natural experiment" in developmental evolution in sea urchins, where a major life history switch recently evolved in the lineage leading to Heliocidaris erythrogramma, precipitating extensive changes in early development. Comparative analyses of scRNA-seq developmental time courses from H. erythrogramma and Lytechinus variegatus (representing the derived and ancestral states respectively) reveals numerous evolutionary changes in embryonic patterning. The earliest cell fate specification events, and the primary signaling center are co-localized in the ancestral dGRN but remarkably, in H. erythrogramma they are spatially and temporally separate. Fate specification and differentiation are delayed in most embryonic cell lineages, although in some cases, these processes are conserved or even accelerated. Comparative analysis of regulator-target gene co-expression is consistent with many specific interactions being preserved but delayed in H. erythrogramma, while some otherwise widely conserved interactions have likely been lost. Finally, specific patterning events are directly correlated with evolutionary changes in larval morphology, suggesting that they are directly tied to the life history shift. Together, these findings demonstrate that comparative scRNA-seq developmental time courses can reveal a diverse set of evolutionary changes in embryonic patterning and provide an efficient way to identify likely candidate regulatory interactions for subsequent experimental validation.

evolutionary biology↗

bioRxiv2023

Time- and lineage-resolved transcriptional profiling uncovers gene expression programs and clonal relationships that underlie human T lineage specification

T cells develop from multi-potent hematopoietic progenitors in the thymus and provide adaptive protection against pathogens and cancer. However, the emergence of human T cell-competent blood progenitors, and their subsequent specification to the T lineage, has been challenging to capture in real time. Here, we leveraged a pluripotent stem cell differentiation system to understand the transcriptional dynamics and cell fate restriction events that underlie this critical developmental process. Time-resolved single cell RNA sequencing revealed that cell-cycle exit, downregulation of the multipotent hematopoietic program, and upregulation of >90 lineage-associated transcription factors all occur within a highly co-ordinated and narrow developmental window. Computational gene-regulatory network inference elucidated the transcriptional logic of T lineage specification, uncovering an important role for YBX1. We mapped the differentiation cell fate hierarchy using transcribed lineage barcoding and mathematical trajectory inference and discovered that mast and myeloid potential bifurcate from each other early in haematopoiesis, upstream of T lineage restriction. Collectively, our analyses provide a quantitative, time-resolved model of human T cell specification with relevance for regenerative medicine and developmental immunology.

immunology↗

bioRxiv2022

Brassinosteroid gene regulatory networks at cellular resolution

Brassinosteroids (BRs) are plant steroid hormones that regulate diverse processes such as cell division and cell elongation. BRs control thousands of genes through gene regulatory networks that vary in space and time. By using time-series single-cell RNA-sequencing to identify BR-responsive gene expression specific to different cell types and developmental stages of the Arabidopsis root, we uncovered the elongating cortex as a site where BRs trigger a shift from proliferation to elongation associated with increased expression of cell wall-related genes. Our analysis revealed HAT7 and GTL1 as BR-responsive transcription factors that regulate cortex cell elongation. These results establish the cortex as an important site for BR-mediated growth and unveil a BR signaling network regulating the transition from proliferation to elongation, illuminating new aspects of spatiotemporal hormone response.

plant biology↗

bioRxiv2022

The DNA-based global positioning system--a theoretical framework for large-scale spatial genomics

We present GPS-seq, a theoretical framework that enables massively scalable, optics-free spatial transcriptomics. GPS-seq combines data from high-throughput sequencing with manifold learning to obtain the spatial transcriptomic landscape of a given tissue section without optical microscopy. In this framework, similar to technologies like Slide-seq and 10X Visium, tissue samples are stamped on a surface of randomly-distributed DNA-barcoded spots (or beads). The transcriptomic sequences of proximal cells are fused to DNA barcodes, enabling the recovery of a transcriptomic pixel image by high-throughput sequencing. The barcode spots serve as "anchors" which also capture spatially diffused "satellite" barcodes, and therefore allow computational reconstruction of spot positions without optical sequencing or depositing barcodes to pre-specified positions. In theory, it could generate 100 mm x 100 mm spatial transcriptomic images with 10-20 m resolution by localizing 108 DNA-barcoded pixels with a single Illumina NovaSeq run. The general framework of GPS-seq is also compatible with standard single-cell (or single-nucleus) capture methods, and any modality of single-cell genomics, such as sci-ATAC-seq, could be transformed into spatial genomics in this strategy. We envision that GPS-seq will lead to breakthrough discoveries in diverse areas of biology by enabling organ-scale imaging of multiple genomic statuses at single-cell resolution for the first time.

bioinformatics↗

bioRxiv2021

Hematopoiesis at single cell resolution spanning human development and maturation

Hematopoiesis is a process of constitutive regeneration whereby hematopoietic stem and progenitor cells (HSPCs) replenish mature blood cells. During maturation and aging, HSPCs shift their output to support the demands of prenatal development and postnatal maturation both at homeostasis and in response to stress. How HSPC ontogeny changes throughout life is unknown; studies to date have largely focused on specific individual ages, particularly at single cell resolution. Here, we performed single cell RNA-seq of human HSPCs from early prenatal development into mature adulthood. We observed shifts in HSPC transcriptional states and differentiation trajectories over time. We identified age-specific gene expression patterns throughout human maturation and developed methods for identifying, prospectively purifying, and functionally validating age-specific HSC states. Together, our findings define the temporal maturation of human HSPCs and uncover principles applicable to age-biased blood diseases. SummarySingle cell RNA sequencing reveals that the mechanisms of human hematopoietic stem and progenitor cell (HSPC) fate commitment change over a lifetime from gestation to mature adulthood.

developmental biology↗

bioRxiv2021

Functional Connectivity of the World's Protected Areas

Rapid environmental change threatens to isolate the worlds wildlife populations and intensify biodiversity loss. Global policies have called for expanding and connecting the worlds protected areas (PAs) to curtail the crisis, yet how well PA networks currently support wildlife movement, and where connectivity conservation or restoration is most critical, have never been mapped globally. Here, we map the functional connectivity (how animals move through landscapes) of the worlds terrestrial PAs for the first time. Also, going beyond existing global connectivity indices, we quantify national PA-connectedness using an approach that meaningfully represents animal movement through anthropogenic landscapes. We find that reducing the human footprint may improve national PA-connectivity more than adding new PAs; however, both strategies are critical for improving and preserving connectivity in places where the predicted flow of animal movement is highly concentrated. We show that the majority of critical connectivity areas (CCAs) (defined as globally important areas of concentrated animal movements) remain unprotected. Of these, 72% overlap with previously-identified global conservation priority areas, while 3% of CCAs occur within moderate to heavily modified lands. Conservation and restoration of CCAs could safeguard connectivity of the worlds PAs, and dovetail with previously identified global conservation priorities.

ecology↗

bioRxiv2021

Optimal transport analysis reveals trajectories in steady-state systems

Understanding how cells change their identity and behaviour in living systems is an important question in many fields of biology. The problem of inferring cell trajectories from single-cell measurements has been a major topic in the single-cell analysis community, with different methods developed for equilibrium and non-equilibrium systems (e.g. haematopoeisis vs. embryonic development). We show that optimal transport analysis, a technique originally designed for analysing time-courses, may also be applied to infer cellular trajectories from a single snapshot of a population in equilibrium. Therefore optimal transport provides a unified approach to inferring trajectories, applicable to both stationary and non-stationary systems. Our method, StationaryOT, is mathematically motivated in a natural way from the hypothesis of a Waddingtons epigenetic landscape. We implemented StationaryOT as a software package and demonstrate its efficacy when applied to simulated data as well as single-cell data from Arabidopsis thaliana root development.

bioinformatics↗

bioRxiv2020

Developmental Single-cell transcriptomics in the Lytechinus variegatus 1 Sea Urchin Embryo

Here we employed scRNA-seq coupled with computational approaches to examine molecular changes in cells during specification and differentiation. We examined the first 24 hours of development of the sea urchin Lytechinus variegatus (Lv) with 18 time points during which the embryo develops to the larval stage. Using Waddington-OT, the time points were computationally "stitched" together to calculate developmental trajectories. Skeletogenic cells displayed the expected immediate early divergence while other lineages diverged asynchronously, with many cells retaining an intermediate specification status until late in gastrulation. The Lv-scRNA-seq dataset was compared to the developmental Gene Regulatory Network (dGRN) model of specification in Strongylocentrotus purpuratus (Sp). 79 of 80 genes (98%) in that dGRN are present in the Lv-scRNA-seq dataset, and expressed in the correct lineages in which the dGRN circuits operate. Surprisingly, however, many heterochronies in timing of first expression of dGRN genes have evolved between the two species. Replotting the two dGRNs with precise attention to time of expression revealed a number of feedback inputs that likely buffer the dGRNs, allowing them to maintain function in the face of accumulating heterochronies. Summary statementThe early development of the sea urchin embryo was followed using scRNA-seq plus computational methods to trace lineage diversifications. These were matched to gene regulatory network changes over time.

developmental biology↗