{"doi":"10.1101/2022.08.31.505974","title":"Mapping mitonuclear epistasis using a novel recombinant yeast population","abstract":"Abstract Natural genetic variation in mitochondrial and nuclear genomes can influence phenotypes by perturbing coadapted mitonuclear interactions. Mitonuclear epistasis, i.e. non-additive phenotype effects of interacting mitochondrial and nuclear alleles, is emerging as a general feature in eukaryotes, yet very few mitonuclear loci have been identified. Here, we present a novel advanced intercrossed population of S. cerevisiae yeasts, called the Mitonuclear Recombinant Collection (MNRC), designed explicitly for detecting mitonuclear loci contributing to complex traits, and use this population to map the genetic basis to mtDNA loss. In yeast, spontaneous deletions within mtDNAs lead to the petite phenotype that heralded mitochondrial research. We show that in natural populations, rates of petite formation are variable and influenced by genetic variation in nuclear, mtDNAs and mitonuclear interactions. We then mapped nuclear and mitonuclear alleles contributing mtDNA stability using the MNRC by integrating mitonuclear epistasis into a genome-wide association model. We found that associated mitonuclear loci play roles in mitotic growth most likely responding to retrograde signals from mitochondria, while associated nuclear loci with main effects are involved in genome replication. We observed a positive correlation between growth rates and petite frequencies, suggesting a fitness tradeoff between mitotic growth and mtDNA stability. We also found that mtDNA stability was influenced by a mobile mitochondrial GC-cluster that is expanding in certain populations of yeast and that selection for nuclear alleles that stabilize mtDNA may be rapidly occurring. The MNRC provides a powerful tool for identifying mitonuclear interacting loci that will help us to better understand genotype-phenotype relationships and coevolutionary trajectories. Author Summary Genetic variation in mitochondrial and nuclear genomes can perturb mitonuclear interactions and lead to phenotypic differences between individuals and populations. Despite their importance to most complex traits, it has been difficult to identify the interacting loci. Here, we created a novel population of yeast designed explicitly for mapping mitonuclear loci contributing to complex traits and used this population to map genes influencing the stability of mitochondrial DNA (mtDNA). We found that mitonuclear interacting loci were involved in mitotic growth while non-interacting loci were involved in genome replication. We also found evidence that selection for mitonuclear loci that stabilize mtDNAs occurs rapidly. This work provides insight into mechanisms underlying maintenance of mtDNAs. The mapping population presented here is an important new resource that will help to understand genotype/phenotype relationships and coevolutionary trajectories.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2022,"id":301780,"datarank":0.19898504486572552,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"self_citation_contribution":0.16479184330021646,"citation_network_contribution":0.03419320156550906,"self_endowment_contribution":0.16479184330021646,"citer_contribution":0.03419320156550906,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":2,"citers_with_citation_signal":2,"citers_with_endowment":2,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.7286,"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":993809,"name":"Austen Tinz-Burdick","orcid":null,"position":1,"is_corresponding":false},{"id":993810,"name":"Meghan Lenhardt","orcid":null,"position":2,"is_corresponding":false},{"id":993811,"name":"Margaret Geertz","orcid":null,"position":3,"is_corresponding":false},{"id":993812,"name":"Franchesca Ramirez","orcid":null,"position":4,"is_corresponding":false},{"id":660039,"name":"Mark Schwartz","orcid":"0000-0002-6847-5593","position":5,"is_corresponding":false},{"id":993813,"name":"Michael Toledano","orcid":null,"position":6,"is_corresponding":false},{"id":993814,"name":"Brooke Bonney","orcid":null,"position":7,"is_corresponding":false},{"id":993815,"name":"Benjamin Gaebler","orcid":null,"position":8,"is_corresponding":false},{"id":993239,"name":"Weiwei Liu","orcid":"0000-0001-6036-9641","position":9,"is_corresponding":false},{"id":921513,"name":"John F. Wolters","orcid":"0000-0002-5477-4250","position":10,"is_corresponding":false},{"id":993240,"name":"Ken C. Chiu","orcid":"0000-0002-2226-1039","position":11,"is_corresponding":false},{"id":993241,"name":"Anthony C. Fiumera","orcid":"0000-0003-3865-4053","position":12,"is_corresponding":false},{"id":476845,"name":"Heather L. Fiumera","orcid":"0000-0001-9068-5979","position":13,"is_corresponding":false},{"id":476843,"name":"Tuc H. M. Nguyen","orcid":"0000-0001-9223-3749","position":0,"is_corresponding":true}],"reference_count":108,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T00:32:06.309890Z","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":[]}