Abstract
The placenta is critical for fetal development and mediates effects of pregnancy complications on offspring metabolic health yet remains poorly characterized in genomic studies. Existing transcriptomic analyses rely on adult tissue reference annotations, overlooking developmentally important splicing diversity. Using largest-in-class long-read RNA-seq (n = 72), we create a comprehensive placental transcriptome reference identifying 37,661 high-confidence isoforms (14,985 previously unannotated) across 12,302 genes (2,759 previously unannotated). Contrary to characterizations of the placenta as a transcriptomic void, we find transcriptional breadth and complexity comparable to adult tissues, with high splicing diversity of obesity- and growth-related gene transcripts, including 108 distinct CSH1 (placental lactogen) isoforms. Applying this reference to short-read RNA-seq from diverse populations (n = 352) reduced inferential uncertainty in isoform quantification by approximately 30%. We find placental transcription mediated 36% of gestational diabetes mellitus effects on birth weight, with ancestry-specific effects including previously unannotated CSH1 isoforms mediating larger effects in European (24.4%) than Asian (13.4%) populations. These findings illustrate the importance of tissue-matched, long-read annotations for isoform-resolved transcriptomics.
Data availability
Datasets required to reproduce the analyses conducted in this study are available in the associated Supplementary Data or have been deposited in a Zenodo repository under https://doi.org/10.5281/zenodo.18841087. The repository includes the high-confidence placenta and GTEx v9 reference transcriptome GTFs, SQANTI3 classification tables, and the raw and InfRV-adjusted expression matrices for the GUSTO and Gen3G short-read datasets, quantified against each assembly described in this study. Oxford Nanopore long reads generated in this study are publicly accessible through the NCBI Sequence Read Archive (BioProject accession PRJNA1373130). All accessions for validation datasets used in transcriptome annotation filtering are available in Supplementary Dataset 16. An interactive Shiny application for visualizing transcript structures and exploring differential expression and GDM–birth weight mediation results is available at https://github.com/sbresnahan/lr-placenta-transcriptome-viz. GTEx v9 Oxford Nanopore long-read and Illumina short-read sequencing data are available under controlled access via dbGaP (accession phs000424.v9.p2 [https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v9.p2]) and on AnVIL (https://anvil.terra.bio/#workspaces/anvil-datastorage/AnVIL_GTEx_V9_hg38), with access granted to authorized researchers for biomedical research purposes as per dbGaP procedures. Short-read data from GTEx tissues were used for isoform quantification and for splice junction validation of transcript models called from the associated long-read data. Illumina short reads from Gen3G, along with associated sample covariates, are available under controlled access via dbGaP (accession phs003151.v1.p1 [https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003151.v1.p1]); access requests are reviewed by the Gen3G data access committee, with decisions typically communicated within 4–6 weeks, and approved researchers must sign a data use agreement restricting use to the approved research purpose. Illumina short reads from GUSTO, along with associated sample covariates, are available under restricted access due to privacy and regulatory requirements governing human participant data; access requests should be submitted via https://gustodatavault.sg/about/request-for-data and will be reviewed by the GUSTO data access committee within 4–8 weeks, with approved researchers required to sign a data use agreement limiting use to the specified research purpose and prohibiting participant re-identification. Source data for graphs presented in the main text and supplementary materials are provided with this paper. Source data are provided with this paper.
Code availability
All custom scripts and analysis pipelines used in this study are publicly available at https://github.com/sbresnahan/lr-placenta-transcriptome and archived at https://doi.org/10.5281/zenodo.18841087. This repository includes code for dataset preparation, Oxford Nanopore data processing and transcriptome assembly using ESPRESSO, SQANTI3-based annotation and quality control filtering, and short-read analyses in prospective prebirth cohorts including differential gene and transcript expression, mediation analysis, and GO enrichment analysis.
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Acknowledgments
The authors would like to thank the GUSTO, Gen3G, and NUH prebirth cohort study participants and their families, and the related staff and study teams, without whom this study would not be possible. We also thank members of both the Bhattacharya and Huang labs for critical reading of our manuscript, and members of the Love lab for feedback on methods. The GUSTO study is supported by the National Research Foundation (NRF) under its Translational and Clinical Research (TCR) Flagship Program (NMRC/TCR/004-NUS/2008 and NMRC/TCR/012-NUHS/2014 to S.-Y.C.) and the Open Fund-Large Collaborative Grant (MOH-000504 to S.-Y.C.) administered by the Singapore Ministry of Health’s National Medical Research Council (NMRC) and the Agency for Science, Technology and Research (A*STAR). Additional funding is provided by the Institute for Human Development and Potential (IHDP), A*STAR. The Gen3G study was initially supported by a Fonds de recherche du Québec—Santé operating grant (20697 to M.-F.H.), Canadian Institute of Health Research (CIHR) operating grants (MOP 115071 to M.-F.H.) and a Diabète Québec grant, and placental short-read RNA sequencing was supported by NICHD (R01HD94150 to M.-F.H.). Placental long-read RNA sequencing was supported by an NMRC Open Fund-Young Individual Research Grant (MOH-000550-00 to J.Y.H.). J.Y.H. was also supported by an A*STAR Human Health and Potential–Prenatal/Early Childhood Grant (H24P2M0002) and Pilot Projects Program funding from the NIMHD RCMI-CC (U24MD015970).
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S.T.B., J.Y.H., and A.B. designed the study. M.-F.H. managed the Gen3G study and S.-Y.C. managed the GUSTO study. H.E.J.Y., J.K.Y.C., F.W., and P.-E.J. managed data from these studies. S.T.B. directed bioinformatic and statistical analyses and wrote the initial draft of the manuscript. W.H.W. and S.L. contributed to bioinformatic and statistical analyses. A.N. designed the Shiny app. M.I.L. consulted on bioinformatic and statistical analyses. All authors contributed to the writing and editing of the final manuscript.
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Bresnahan, S.T., Yong, H.E.J., Nemani, A. et al. Long-read assembly reveals vast transcriptional complexity in the placenta associated with metabolic and endocrine function. Nat Commun (2026). https://doi.org/10.1038/s41467-026-71303-4
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DOI: https://doi.org/10.1038/s41467-026-71303-4
