The single-cell expression profile of transposable elements and transcription factors in human early biparental and uniparental embryonic development

Dynamic dysregulation of retrotransposons in neurodegenerative diseases at the single-cell level

Retrotransposable elements (RTEs) are common mobile genetic elements comprising ∼42% of the human genome. RTEs play critical roles in gene regulation and function, but how they are specifically involved in complex diseases is largely unknown. Here, we investigate the cellular heterogeneity of RTEs using 12 single-cell transcriptome profiles covering three neurodegenerative diseases, Alzheimer's disease (AD), Parkinson's disease, and multiple sclerosis. We identify cell type marker RTEs in neurons, astrocytes, oligodendrocytes, and oligodendrocyte precursor cells that are related to these diseases. The differential expression analysis reveals the landscape of dysregulated RTE expression, especially L1s, in excitatory neurons of multiple neurodegenerative diseases. Machine learning algorithms for predicting cell disease stage using a combination of RTE and gene expression features suggests dynamic regulation of RTEs in AD. Furthermore, we construct a single-cell atlas of retrotransposable elements in neurodegenerative disease (scARE) using these data sets and features. scARE has six feature analysis modules to explore RTE dynamics in a user-defined condition. To our knowledge, scARE represents the first systematic investigation of RTE dynamics at the single-cell level within the context of neurodegenerative diseases.

MATES: a deep learning-based model for locus-specific quantification of transposable elements in single cell

Transposable elements (TEs) are crucial for genetic diversity and gene regulation. Current single-cell quantification methods often align multi-mapping reads to either 'best-mapped' or 'random-mapped' locations and categorize them at the subfamily levels, overlooking the biological necessity for accurate, locus-specific TE quantification. Moreover, these existing methods are primarily designed for and focused on transcriptomics data, which restricts their adaptability to single-cell data of other modalities. To address these challenges, here we introduce MATES, a deep-learning approach that accurately allocates multi-mapping reads to specific loci of TEs, utilizing context from adjacent read alignments flanking the TE locus. When applied to diverse single-cell omics datasets, MATES shows improved performance over existing methods, enhancing the accuracy of TE quantification and aiding in the identification of marker TEs for identified cell populations. This development facilitates the exploration of single-cell heterogeneity and gene regulation through the lens of TEs, offering an effective transposon quantification tool for the single-cell genomics community.

Longitudinal profiling of human androgenotes through single-cell analysis unveils paternal gene expression dynamics in early embryo development

STUDY QUESTION

How do transcriptomics vary in haploid human androgenote embryos at single cell level in the first four cell cycles of embryo development?

SUMMARY ANSWER

Gene expression peaks at the fourth cell cycle, however some androcytes exhibit unique transcriptional behaviors.

WHAT IS KNOWN ALREADY

The developmental potential of an embryo is determined by the competence of the oocyte and the sperm. However, studies of the contribution of the paternal genome using pure haploid androgenotes are very scarce.

STUDY DESIGN, SIZE, DURATION

This study was performed analyzing the single-cell transcriptomic sequencing of 38 androcytes obtained from 10 androgenote bioconstructs previously produced in vitro (de Castro et al., 2023). These results were analyzed through different bioinformatics software such as g: Profiler, GSEA, Cytoscape, and Reactome.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Single cell sequencing was used to obtain the transcriptomic profiles of the different androcytes. The results obtained were compared between the different cycles studied using the DESeq2 program and functional enrichment pathways using g: Profiler, Cytoscape, and Reactome.

MAIN RESULTS AND THE ROLE OF CHANCE

A wave of paternally driven transcriptomic activation was found during the third-cell cycle, with 1128 upregulated and 225 downregulated genes and the fourth-cell cycle, with 1373 upregulated and 286 downregulated genes, compared to first-cell cycle androcytes. Differentially expressed routes related to cell differentiation, DNA-binding transcription, RNA biosynthesis and RNA polymerase II transcription regulatory complex, and cell death were found in the third and fourth with respect to the first-cell cycle. Conversely, in the fourth cell cycle, 153 downregulated and 332 upregulated genes were found compared with third cell cycle, associated with differentially expressed processes related to E-box binding and zinc finger protein 652 (ZNF652) transcription factor. Further, significant overexpression of LEUTX, PRAMEF1, DUXA, RFPL4A, TRIM43, and ZNF675 found in androgenotes, compared to biparental embryos, highlights the paternal contributions to zygote genome activation.

LARGE SCALE DATA

All raw sequencing data are available through the Gene Expression Omnibus (GEO) under accessions number: GSE216501.

LIMITATIONS, REASONS FOR CAUTION

Extrapolation of biological events from uniparental constructs to biparental embryos should be done with caution. Maternal and paternal genomes do not act independently of each other in a natural condition. The absence of one genome may affect gene transcription of the other. In this sense, the haploid condition of the bioconstructs could mask the transcriptomic patterns of the single cells.

WIDER IMPLICATIONS OF THE FINDINGS

The results obtained demonstrated the level of involvement of the human paternal haploid genome in the early stages of embryo development as well as its evolution at the transcriptomic level, laying the groundwork for the use of these bioconstructs as reliable models to dispel doubts about the genetic role played by the paternal genome in the early cycles of embryo development.

STUDY FUNDING/COMPETING INTEREST(S)

This study was funded by Instituto de Salud Carlos III (ISCIII) through the project 'PI22/00924', co-funded by European Regional Development Fund (ERDF); 'A way to make Europe'. F.D. was supported by the Spanish Ministry of Economy and Competitiveness through the Miguel Servet program (CPII018/00002). M.J.E. was supported by Instituto de Salud Carlos III (PI19/00577 [M.J.E.]) and FI20/00086. P.dC. was supported by a predoctoral grant for training in research into health (PFIS PI19/00577) from the Instituto de Salud Carlos III. All authors declare having no conflict of interest with regard to this trial.

HervD Atlas: a curated knowledgebase of associations between human endogenous retroviruses and diseases

Human endogenous retroviruses (HERVs), as remnants of ancient exogenous retrovirus infected and integrated into germ cells, comprise ∼8% of the human genome. These HERVs have been implicated in numerous diseases, and extensive research has been conducted to uncover their specific roles. Despite these efforts, a comprehensive source of HERV-disease association still needs to be added. To address this gap, we introduce the HervD Atlas (https://ngdc.cncb.ac.cn/hervd/), an integrated knowledgebase of HERV-disease associations manually curated from all related published literature. In the current version, HervD Atlas collects 60 726 HERV-disease associations from 254 publications (out of 4692 screened literature), covering 21 790 HERVs (21 049 HERV-Terms and 741 HERV-Elements) belonging to six types, 149 diseases and 610 related/affected genes. Notably, an interactive knowledge graph that systematically integrates all the HERV-disease associations and corresponding affected genes into a comprehensive network provides a powerful tool to uncover and deduce the complex interplay between HERVs and diseases. The HervD Atlas also features a user-friendly web interface that allows efficient browsing, searching, and downloading of all association information, research metadata, and annotation information. Overall, the HervD Atlas is an essential resource for comprehensive, up-to-date knowledge on HERV-disease research, potentially facilitating the development of novel HERV-associated diagnostic and therapeutic strategies.