Biology subjects

Vu, H. T. H.

Publications and source records attributed to Vu, H. T. H..

4 recordsLinked to original sources

bioRxiv2023

CORE CONSERVED TRANSCRIPTIONAL REGULATORY NETWORKS DEFINE THE INVASIVE TROPHOBLAST CELL LINEAGE

The invasive trophoblast cell lineage in rat and human share crucial responsibilities in establishing the uterine-placental interface of the hemochorial placenta. These observations have led to the rat becoming an especially useful animal model to study hemochorial placentation. However, our understanding of similarities or differences between regulatory mechanisms governing rat and human invasive trophoblast cell populations is limited. In this study, we generated single-nucleus (sn) ATAC-seq data from gestation day (gd) 15.5 and 19.5 rat uterine-placental interface tissues and integrated the data with single-cell RNA-seq data generated at the same stages. We determined the chromatin accessibility profiles of invasive trophoblast, natural killer, macrophage, endothelial, and smooth muscle cells, and compared invasive trophoblast chromatin accessibility to extravillous trophoblast (EVT) cell accessibility. In comparing chromatin accessibility profiles between species, we found similarities in patterns of gene regulation and groups of motifs enriched in accessible regions. Finally, we identified a conserved gene regulatory network in invasive trophoblast cells. Our data, findings and analysis will facilitate future studies investigating regulatory mechanisms essential for the invasive trophoblast cell lineage.

developmental biology↗

bioRxiv2023

Unsupervised Contrastive Peak Caller for ATAC-seq

The assay for transposase-accessible chromatin with sequencing (ATAC-seq) is a common assay to identify chromatin accessible regions by using a Tn5 transposase that can access, cut, and ligate adapters to DNA fragments for subsequent amplification and sequencing. These sequenced regions are quantified and tested for enrichment in a process referred to as "peak calling". Most unsupervised peak calling methods are based on simple statistical models and suffer from elevated false positive rates. Newly developed supervised deep learning methods can be successful, but they rely on high quality labeled data for training, which can be difficult to obtain. Moreover, though biological replicates are recognized to be important, there are no established approaches for using replicates in the deep learning tools, and the approaches available for traditional methods either cannot be applied to ATAC-seq, where control samples may be unavailable, or are post-hoc and do not capitalize on potentially complex, but reproducible signal in the read enrichment data. Here, we propose a novel peak caller that uses unsupervised contrastive learning to extract shared signals from multiple replicates. Raw coverage data are encoded to obtain low-dimensional embeddings and optimized to minimize a contrastive loss over biological replicates. These embeddings are passed to another contrastive loss for learning and predicting peaks and decoded to denoised data under an autoencoder loss. We compared our Replicative Contrastive Learner (RCL) method with other existing methods on ATAC-seq data, using annotations from ChromHMM genome and transcription factor ChIP-seq as noisy truth. RCL consistently achieved the best performance.

bioinformatics↗

bioRxiv2022

Conservation at the uterine-placental interface

The hemochorial placentation site is characterized by a dynamic interplay between trophoblast cells and maternal cells. These cells cooperate to establish an interface required for nutrient delivery to promote fetal growth. In the human, trophoblast cells penetrate deep into the uterus. This is not a consistent feature of hemochorial placentation and has hindered the establishment of suitable animal models. The rat represents an intriguing model for investigating hemochorial placentation with deep trophoblast cell invasion. In this study, we used single cell RNA sequencing to characterize the transcriptome of the invasive trophoblast cell lineage, as well as other cell populations within the rat uterine-placental interface during early (gestation day, gd, 15.5) and late (gd 19.5) stages of intrauterine trophoblast cell invasion. We identified a robust set of transcripts that define invasive trophoblast cells, as well as transcripts that distinguished endothelial, smooth muscle, natural killer, and macrophage cells. Invasive trophoblast, immune, and endothelial cell populations exhibited distinct spatial relationships within the uterine-placental interface. Furthermore, the maturation stage of invasive trophoblast cell development could be determined by assessing gestation-stage dependent changes in transcript expression. Finally, and most importantly, expression of a prominent subset of rat invasive trophoblast cell transcripts is conserved in the invasive extravillous trophoblast cell lineage of the human placenta. These findings provide foundational data to identify and interrogate key conserved regulatory mechanisms essential for development and function of an important compartment within the hemochorial placentation site that is essential for a healthy pregnancy. SIGNIFICANCETrophoblast cell-guided restructuring of the uterus is an essential event in the establishment of the hemochorial placenta. Establishment of a suitable animal model for investigating regulatory mechanisms in this critical developmental process is a key to better understanding the etiology of diseases of placentation, such as early pregnancy loss, preeclampsia, intrauterine growth restriction, and preterm birth. The rat exhibits deep trophoblast cell invasion, as seen in human hemochorial placentation. Similarities are identified in the transcriptomes of rat and human invasive trophoblast cells, leading to the discovery of conserved candidate regulators of the invasive trophoblast cell lineage. This creates opportunities to test hypotheses underlying the pathophysiologic basis of trophoblast cell-guided uterine transformation and new insights into the etiology of diseases of placentation.

developmental biology↗

bioRxiv2022

Identifying novel regulators of placental development using time series transcriptomic data and network analyses

The placenta serves as a connection between the mother and the fetus during pregnancy, and provides the fetus with oxygen, nutrients, and growth hormones. However, the regulatory mechanisms and dynamic gene interaction networks underlying early placental development are understudied. Here, we generated RNA sequencing (RNA-seq) data from mouse fetal placenta tissues at embryonic day (e) 7.5, e8.5 and e9.5 to identify genes with timepoint-specific expression, then inferred gene interaction networks to analyze highly connected network modules. We determined that timepoint-specific gene network modules associated with distinct developmental processes, and with similar expression profiles to specific human placental cell populations. From each module, we obtained hub genes and their direct neighboring genes, which were predicted to govern placental functions. We confirmed that four novel candidate regulators identified through our analyses regulate cell migration in the HTR-8/SVneo cell line. Upon conclusion of this study, we were able to predict several novel regulators of placental development using network analysis of bulk RNA-seq data. Our findings and analysis approaches will be valuable for future studies investigating the transcriptional landscape of early placental development.

developmental biology↗