Single Nuclei Multiome Analysis of the Endometrium and Placenta in Bovine Reveals Novel Cellular Phenotypes

Haidee Tinning¹; Beatriz Fernandez-Fuertes²; José M Sánchez³; Jonathan Fenn⁴; Pat Lonergan³; Mary J O’Connell⁴; Niamh Forde¹

1.        Discovery & Translational Sciences Department, Faculty of Medicine & Health, University of Leeds, Leeds, UK.

2.        Department of Animal Reproduction, National Institute for Agriculture and Food Research and Technology (INIA-CSIC), Madrid, Spain.

3.        School of Agriculture and Food Science, University College Dublin, Belfield, Dublin 4, Ireland.

4.        Computational and Molecular Evolutionary Biology Group, School of Life Sciences, Faculty of Medicine and Health Sciences, University of Nottingham, UK.

 


Abstract Text:

Understanding the cellular composition of the endometrium and placenta are critical for 1) identifying cell specific responses to pregnancy, 2) designing in vitro culture systems, and 3) elucidating the evolution and development of these tissues. This study aimed, for the first time, to use multiome analysis on the same nuclei (i.e. matched gene expression and chromatin availability) from endometrium and term placenta in bovine – a species with specific implantation (protracted peri-implantation and superficial implantation) and placental morphology (cotyledonary).
Bovine intercaruncular endometrium from Day 16 of pregnancy (time of pregnancy recognition: n=2) was harvested from the ipsilateral horn. Term placenta (n=2) was collected following birth and the cotyledon dissected. Nuclei were isolated from snap-frozen tissue using the Chromium Nuclei Isolation Kit (10X Genomics). Nuclei and debris were assessed (Luna FX7), and ~5000 nuclei per endometrial sample and ~8000 nuclei per placental sample were targeted. Gel-bead-in-emulsions (GEM) were made in the 10X Chromium iX, and a thermal cycler used to generate barcoded cDNA and gDNA. After GEM clean-up, pre-amplification PCR and PCR clean-up, each sample was split for ATAC and gene expression libraries. For the ATAC library production, 8 cycles of PCR amplification were performed on the gDNA, and libraries constructed (10X Single Index Kit N Set A). For gene expression libraries, cDNA underwent 9-10 PCR amplification cycles, the product fragmented, and underwent end-repair, A-tailing, and size selection (200-600bp). Index sequences were added and 14 cycles of PCR performed (10X Dual Index Kit TT Set A). Libraries were sequenced on an Element AVITI (2x75 paired end reads). Data analysis was undertaken using Cellranger-arc software (AVITI patch) with the Bos taurus genome ARS_UCD1.3 annotation 112 (Ensembl).

From endometrial sample 1 and 2 we identified 2870 nuclei (14,848 median high-quality ATAC fragments and 1927 median genes per nuclei) and 3740 nuclei (13944 median high-quality ATAC fragments and 1795 median genes per nuclei) respectively. From placental samples 1 and 2 we identified 3821 nuclei (5067 median high-quality ATAC fragments and 135 median genes per nuclei) and 4176 nuclei (10078 median high-quality ATAC fragments and 1106 median genes per nuclei) respectively. For the ATAC sequencing data, endometrial samples had 81.9% and 86.2% confidently mapped read pairs, and placental samples had 79.1% and 90.2% confidently mapped read pairs.

Gene expression of endometrial samples had 94.8% and 94.7% of reads confidently mapped to genome, whereas placental samples had 88.7% and 91.7%. Cell clustering analysis revealed 8 and 10 cell type clusters in the endometrial samples, with 10 or 11 in placental samples. For endometrial sample 1 we have putatively labelled clusters as unciliated-, ciliated- , and glandular- epithelial, and stromal, based on expression of cell markers identified by other studies. In placental sample 2 (11 clusters), we have putatively labelled clusters as follows: endothelial_1, endothelial_2, uninucleate trophoblast, binucleate trophoblast, mesenchyme, and macrophages/leukocytes.

We report for the first time single nuclei multiome analysis of reproductive tissues. Future work will focus on comparative analyses of these data with that from other mammals from different clades to understand the evolution of the regulatory mechanisms controlling pregnancy success in placental mammals.