{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T23:01:20Z","timestamp":1790722880832,"version":"4.1.0"},"reference-count":42,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T00:00:00Z","timestamp":1790726400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Genet."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>MicroRNAs (miRNAs) regulate gene expression post-transcriptionally through sequence-specific targeting of messenger RNAs. Reliable mapping of miRNA-mRNA interactions remains challenging because available methods differ widely and systematic cross-method comparisons are lacking.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Method<\/jats:title>\n                    <jats:p>Using mouse miR-214-3p as a model, we systematically compared three approaches: bioinformatic prediction (TargetScan, miRDB, miRWalk), Argonaute-dependent experimental detection (qCLASH on mouse lung tissue), and artificial intelligence-driven structural modeling (AlphaFold3). Gene lists were harmonized to Ensembl release 116 (GRCm39) Gene IDs; overlaps were evaluated against a transcriptome background using Fisher\u2019s exact tests with Benjamini\u2013Hochberg correction, and the three-tool consensus was assessed by 1,000,000 Monte Carlo simulations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Only 95 target genes were commonly predicted by all three bioinformatic tools, and at most 6 of the 15 Ensembl-mappable qCLASH genes were captured by any prediction algorithm. Nevertheless, all observed overlaps were significantly enriched relative to random expectation (O\/E ratios 24.52\u201380.6; adjusted q &amp;lt; 0.05), and the 95-gene consensus fell far outside the simulated null distribution (P \u223c MC\u223c &amp;lt; 10\n                      <jats:sup>\u22126<\/jats:sup>\n                      ). AlphaFold3 produced high-confidence models (ipTM \u22650.6) for 80.95% of qCLASH-derived interactions, but a substantial fraction of bioinformatically predicted sites failed to form structurally plausible complexes.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>Bioinformatic prediction, qCLASH, and AlphaFold3 thus capture distinct and complementary layers of miRNA targeting (sequence-defined potential, context-dependent occupancy, and spatial feasibility) rather than converging on a single landscape. High AlphaFold3 confidence scores, for instance, did not guarantee biologically functional conformations; even models meeting the thresholds often displayed non-canonical architectures incompatible with silencing. In our mouse lung miR-214-3p model system, our findings support an integrative approach: method selection should align with the specific research question, and multi-layer integration is key to constructing reliable miRNA-target maps in a given biological context.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fgene.2026.1924314","type":"journal-article","created":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T22:10:13Z","timestamp":1790719813000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Bioinformatic prediction, qCLASH, and AlphaFold3 reveal non-overlapping layers of the miR-214-3p\u2013mRNA interactome"],"prefix":"10.3389","volume":"17","author":[{"given":"Jia","family":"Yao","sequence":"first","affiliation":[{"name":"School of Pharmacy, Jiangxi University of Chinese Medicine","place":["Nanchang, Jiangxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bingqiao","family":"Huang","sequence":"additional","affiliation":[{"name":"Evidence-Based Medicine Research Center, Jiangxi University of Chinese Medicine","place":["Nanchang, Jiangxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenyu","family":"Chang","sequence":"additional","affiliation":[{"name":"Evidence-Based Medicine Research Center, Jiangxi University of Chinese Medicine","place":["Nanchang, Jiangxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziqi","family":"Lin","sequence":"additional","affiliation":[{"name":"Evidence-Based Medicine Research Center, Jiangxi University of Chinese Medicine","place":["Nanchang, Jiangxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinyue","family":"Lei","sequence":"additional","affiliation":[{"name":"School of Pharmacy, Jiangxi University of Chinese Medicine","place":["Nanchang, Jiangxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weifeng","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Pharmacy, Jiangxi University of Chinese Medicine","place":["Nanchang, Jiangxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mo","family":"Lisha","sequence":"additional","affiliation":[{"name":"The Affiliated Hospital of Jiangxi University of Chinese Medicine","place":["Nanchang, Jiangxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tielong","family":"Xu","sequence":"additional","affiliation":[{"name":"Evidence-Based Medicine Research Center, Jiangxi University of Chinese Medicine","place":["Nanchang, Jiangxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,30]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"493","DOI":"10.1038\/s41586-024-07487-w","article-title":"Accurate structure prediction of biomolecular interactions with AlphaFold 3","volume":"630","author":"Abramson","year":"2024","journal-title":"Nature"},{"key":"B2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-1-4939-9207-2_1","article-title":"A practical guide to miRNA target prediction","volume":"1970","author":"Akhtar","year":"2019","journal-title":"Methods Mol. 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