Estimating the Fitness Effect of Deleterious Mutations During the Two Phases of the Life Cycle: A New Method Applied to the Root-Rot Fungus Heterobasidion parviporum.

Clergeot PH, Rode NO, Glémin S, Brandström Durling M, Ihrmark K, Olson Å

Genetics 211 (3) 963-976 [2019-03-00; online 2018-12-31]

Many eukaryote species, including taxa such as fungi or algae, have a lifecycle with substantial haploid and diploid phases. A recent theoretical model predicts that such haploid-diploid lifecycles are stable over long evolutionary time scales when segregating deleterious mutations have stronger effects in homozygous diploids than in haploids and when they are partially recessive in heterozygous diploids. The model predicts that effective dominance-a measure that accounts for these two effects-should be close to 0.5 in these species. It also predicts that diploids should have higher fitness than haploids on average. However, an appropriate statistical framework to conjointly investigate these predictions is currently lacking. In this study, we derive a new quantitative genetic model to test these predictions using fitness data of two haploid parents and their diploid offspring, and genome-wide genetic distance between haploid parents. We apply this model to the root-rot basidiomycete fungus Heterobasidion parviporum-a species where the heterokaryotic (equivalent to the diploid) phase is longer than the homokaryotic (haploid) phase. We measured two fitness-related traits (mycelium growth rate and the ability to degrade wood) in both homokaryons and heterokaryons, and we used whole-genome sequencing to estimate nuclear genetic distance between parents. Possibly due to a lack of power, we did not find that deleterious mutations were recessive or more deleterious when expressed during the heterokaryotic phase. Using this model to compare effective dominance among haploid-diploid species where the relative importance of the two phases varies should help better understand the evolution of haploid-diploid life cycles.

NGI Uppsala (SNP&SEQ Technology Platform) [Service]

National Genomics Infrastructure [Service]

PubMed 30598467

DOI 10.1534/genetics.118.301855

Crossref 10.1534/genetics.118.301855

pii: genetics.118.301855
pmc: PMC6404244
figshare: 10.25386/genetics.6941477