{"doi":"10.1101/2022.04.19.488786","title":"Predicting gene expression from cell morphology in human induced pluripotent stem cells","abstract":"Abstract Purification is essential before differentiating human induced pluripotent stem cells (hiPSCs) into cells that fully express particular differentiation marker genes. High-quality iPSC clones are typically purified through gene expression profiling or visual inspection of the cell morphology; however, the relationship between the two methods remains unclear. We investigated the relationship between gene expression levels and morphology by analyzing live-cell phase-contrast images and mRNA profiles collected during the purification process. We employed this data and an unsupervised image feature extraction method to build a model that predicts gene expression levels from morphology. As a benchmark, we confirmed that the method can predict the gene expression levels from tissue images for cancer genes, performing as well as state-of-the-art methods. We then applied the method to iPSCs and identified two genes that are well-predicted from cell morphology. Although strong batch effects resulting from the reprogramming process preclude the ability to use the same model to predict across batches, prediction within a reprogramming batch is sufficiently robust to provide a practical approach for estimating expression levels of a few genes and monitoring the purification process.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2022,"id":297681,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":8,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.956,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":986226,"name":"Mitsuru Negishi","orcid":null,"position":1,"is_corresponding":false},{"id":986227,"name":"Yuta Murakami","orcid":null,"position":2,"is_corresponding":false},{"id":986228,"name":"Shunsuke Tominaga","orcid":null,"position":3,"is_corresponding":false},{"id":985804,"name":"Yasushi Shiraishi","orcid":"0000-0002-9862-2566","position":4,"is_corresponding":false},{"id":11498,"name":"Anne E. Carpenter","orcid":"0000-0003-1555-8261","position":5,"is_corresponding":false},{"id":18821,"name":"Shantanu Singh","orcid":"0000-0003-3150-3025","position":6,"is_corresponding":false},{"id":986229,"name":"Hideo Segawa","orcid":null,"position":7,"is_corresponding":false},{"id":985803,"name":"Takashi Wakui","orcid":"0000-0003-2704-070X","position":0,"is_corresponding":true}],"reference_count":28,"raw_metadata":null,"created_at":"2026-07-19T00:31:26.161109Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}