Evolved genetic and phenotypic differences due to mitochondrial-nuclear interactions

Abstract

The oxidative phosphorylation (OxPhos) pathway is responsible for most aerobic ATP production and is the only pathway with both nuclear and mitochondrial encoded proteins. The importance of the interactions between these two genomes has recently received more attention because of their potential evolutionary effects and how they may affect human health and disease. In many different organisms, healthy nuclear and mitochondrial genome hybrids between species or among distant populations within a species affect fitness and OxPhos functions. However, what is less understood is whether these interactions impact individuals within a single natural population. The significance of this impact depends on the strength of selection for mito-nuclear interactions. We examined whether mito-nuclear interactions alter allele frequencies for ~11,000 nuclear SNPs within a single, natural Fundulus heteroclitus population containing two divergent mitochondrial haplotypes (mt-haplotypes). Between the two mt-haplotypes, there are significant nuclear allele frequency differences for 349 SNPs with a p-value of 1% (236 with 10% FDR). Unlike the rest of the genome, these 349 outlier SNPs form two groups associated with each mt-haplotype, with a minority of individuals having mixed ancestry. We use this mixed ancestry in combination with mt-haplotype as a polygenic factor to explain a significant fraction of the individual OxPhos variation. These data suggest that mito-nuclear interactions affect cardiac OxPhos function. The 349 outlier SNPs occur in genes involved in regulating metabolic processes but are not directly associated with the 79 nuclear OxPhos proteins. Therefore, we postulate that the evolution of mito-nuclear interactions affects OxPhos function by acting upstream of OxPhos.

Fig 1. Distribution of wF_ST values for nuclear SNPs calculated between the two mt-haplotypes within the single MK population.

Although we are examining a single population, we use the two mt-haplotypes as artificial populations for wF_ST calculations. Plot contains wF_ST values and corresponding negative log₁₀ p-values -log₁₀(0.01) = 2). Blue values are significant with a p-value <0.01, green values are significant with a 1% FDR correction, and purple values are significant with a Bonferroni correction. Histograms show wF_ST and p-value distributions.

Fig 2. Admixture Analysis on 3-population 3,700 SNP data set.

A: Plot of Admixture ancestry fractions (Q) from the 3-population SNP data set. 35 Maine individuals are blue, 38 Georgia individuals are red and the 161 MK New Jersey individuals are green. Georgia ancestry coefficients are on the x-axis, and Maine ancestry coefficients are on the y-axis. B: Individual ancestry fractions. Colors are the same as in A. Each individual is represented by a thin vertical line, which is partitioned into 3 colored segments that represent the individual’s estimated membership into one of the three populations.

Fig 3. DAPC and STRUCTURE plots.

Population structure based on 349 outlier SNPs. A) Results of the Bayesian information criterion used to infer the number of genetic clusters when using 349 outlier SNPs. B) Discriminant analysis of principal components (DAPC) based on 349 outlier SNPs. Discriminant function separates individuals into two distinct groups, which are the two mt-haplotypes. “North” is for northern mt-haplotype. “South” is for southern mt-haplotype. C) STRUCTURE plot for 349 outlier SNPs. Plot shows probability that individuals’ nuclear genetic variation belongs to one of two clusters, which are northern and southern haplotypes. Each individual is represented by a thin vertical line, which is partitioned into two colored segments that represent the individual’s estimated membership into one or the other cluster. Twenty-one individuals have a mixed ancestry (> 30% of alternate SNP alleles).

Fig 4. Density plot of F_ST values for both between mt-haplotypes within MK population and between populations.

Areas under each curve are the same. Green line is for the 349 outlier SNP F_ST values between the two mt-haplotypes within the MK population. The light purple line represents 9,440 non-outlier SNP F_ST values between the two mt-haplotypes within the MK population. Two curves compare the MK population with a separate Rutgers’ population for the same 349 outlier SNPs: red is for individuals from the MK population with the southern mt-haplotype compared to the Rutgers population, and blue is for individuals from the MK population with the northern mt-haplotype compared to the Rutgers population.

Fig 5. Mito-nuclear effects on State 3 Respiration.

State 3 OxPhos metabolism in the MK population is oxygen respiration dependent on substrates and ADP, and the data graphed are the residuals from Admixture ancestry, body mass, acclimation temperature and assay temperature [109]. A: ANCOVA (p-val = 0.0194): individuals were assigned to one of four groups based on their 34 outlier genotypes and mt-haplotypes: ‘North Mito North Nuclear’ are individuals with >70% of alleles from the 349 outlier SNPs associated with northern mt-haplotypes, “South Mito South Nuclear” with >70% of alleles from the 349 outlier SNPs associated with southern mt-haplotypes, and the two mixed ancestral groups: individuals where >30% of nuclear genotypes are associated with the opposite mt-haplotype, as defined by STRUCTURE. Means (dot) and standard errors are displayed. N = 155. Letters (“a”, “b” are significantly different based on Tukey post-hoc comparison). B: Regression of residuals of State 3 versus fraction of southern ancestory (0.0–1.0) as defined by STRUCTURE with K = 2. Linear regression is significant (p <0.0055) with an R² = 0.062