Calvo, S. E. & Mootha, V. K. The mitochondrial proteome and human disease. Annu. Rev. Genomics Hum. Genet. 11, 25–44 (2010).
Google Scholar
Lane, N. Mitonuclear match: optimizing fitness and fertility over generations drives ageing within generations. BioEssays 33, 860–869 (2011).
Google Scholar
Bar-Yaacov, D. et al. Mitochondrial involvement in vertebrate speciation? The case of mito-nuclear genetic divergence in chameleons. Genome Biol. Evol. 7, 3322–3336 (2015).
Google Scholar
Hill, G. E. Mitonuclear Ecology (Oxford Univ. Press, 2019).
Ballard, J. W. O. & Whitlock, M. C. The incomplete natural history of mitochondria. Mol. Ecol. 13, 729–744 (2004).
Google Scholar
Morales, H. E. et al. Concordant divergence of mitogenomes and a mitonuclear gene cluster in bird lineages inhabiting different climates. Nat. Ecol. Evol. 2, 1258–1267 (2018).
Google Scholar
Hill, G. E. et al. Assessing the fitness consequences of mitonuclear interactions in natural populations. Biol. Rev. 94, 1089–1104 (2019).
Google Scholar
Barreto, F. S. & Burton, R. S. Elevated oxidative damage is correlated with reduced fitness in interpopulation hybrids of a marine copepod. Proc. R. Soc. B Biol. Sci. 280, 20131521 (2013).
Google Scholar
Healy, T. M. & Burton, R. S. Strong selective effects of mitochondrial DNA on the nuclear genome. Proc. Natl Acad. Sci. U.S.A. 117, 6616–6621 (2020).
Google Scholar
Burton, R. S., Pereira, R. J. & Barreto, F. S. Cytonuclear genomic interactions and hybrid breakdown. Annu. Rev. Ecol. Evol. Syst. 44, 281–302 (2013).
Google Scholar
Hill, G. E. The mitonuclear compatibility species concept. Auk 134, 393–409 (2017).
Google Scholar
Burton, R. S. & Barreto, F. S. A disproportionate role for mtDNA in Dobzhansky-Muller incompatibilities? Mol. Ecol. 21, 4942–4957 (2012).
Google Scholar
Weir, J. T. & Schluter, D. Ice sheets promote speciation in boreal birds. Proc. R. Soc. B Biol. Sci. 271, 1881–1887 (2004).
Google Scholar
Hewitt, G. M. Post-glacial re-colonization of European biota. Biol. J. Linn. Soc. 68, 87–112 (1999).
Google Scholar
Hewitt, G. The genetic legacy of the quaternary ice ages. Nature 405, 907–913 (2000).
Google Scholar
Innocenti, P., Morrow, E. H. & Dowling, D. K. Experimental evidence supports a sex-specific selective sieve in mitochondrial genome evolution. Science 332, 845–848 (2011).
Google Scholar
Harada, A. E., Healy, T. M. & Burton, R. S. Variation in thermal tolerance and its relationship to mitochondrial function across populations of Tigriopus californicus. Front. Physiol. 10, 213 (2019).
Google Scholar
Acevedo, P. et al. Range dynamics driven by quaternary climate oscillations explain the distribution of introgressed mtDNA of Lepus timidus origin in hares from the Iberian Peninsula. J. Biogeogr. 42, 1727–1735 (2015).
Google Scholar
Elgvin, T. O. et al. The genomic mosaicism of hybrid speciation. Sci. Adv. 3, e1602996 (2017).
Google Scholar
Schumer, M., Cui, R., Powell, D. L., Rosenthal, G. G. & Andolfatto, P. Ancient hybridization and genomic stabilization in a swordtail fish. Mol. Ecol. 25, 2661–2679 (2016).
Google Scholar
Rieseberg, L. H. Hybrid origins of plant species. Annu. Rev. Ecol. Syst. 28, 359–389 (2002).
Google Scholar
Barton, N. H. The role of hybridization in evolution. Mol. Ecol. 10, 551–568 (2001).
Google Scholar
Gagnaire, P. A., Normandeau, E. & Bernatchez, L. Comparative genomics reveals adaptive protein evolution and a possible cytonuclear incompatibility between European and American Eels. Mol. Biol. Evol. 29, 2909–2919 (2012).
Google Scholar
Sambatti, J. B. M., Ortiz-Barrientos, D., Baack, E. J. & Rieseberg, L. H. Ecological selection maintains cytonuclear incompatibilities in hybridizing sunflowers. Ecol. Lett. 11, 1082–1091 (2008).
Google Scholar
Baris, T. Z. et al. Evolved genetic and phenotypic differences due to mitochondrial-nuclear interactions. PLoS Genet. 13, e1006517 (2017).
Google Scholar
Boratyński, Z., Ketola, T., Koskela, E. & Mappes, T. The sex specific genetic variation of energetics in bank voles, consequences of introgression? Evol. Biol. 43, 37–47 (2016).
Google Scholar
Rohwer, S. & Wood, C. Three hybrid zones between Hermit and Townsend’s Warblers in Washington and Oregon. Auk 115, 284–310 (1998).
Google Scholar
Rohwer, S., Bermingham, E. & Wood, C. Plumage and mitochondrial DNA haplotype variation across a moving hybrid zone. Evolution 55, 405–422 (2001).
Google Scholar
Krosby, M. & Rohwer, S. A 2000 km genetic wake yields evidence for northern glacial refugia and hybrid zone movement in a pair of songbirds. Proc. R. Soc. B Biol. Sci. 276, 615–621 (2009).
Google Scholar
Krosby, M. & Rohwer, S. Ongoing movement of the hermit warbler X Townsend’s Warbler Hybrid Zone. PLoS One 5, e14164 (2010).
Google Scholar
Wang, S. et al. Selection on a small genomic region underpins differentiation in multiple color traits between two warbler species. Evol. Lett. 4–6, 502–515 (2020).
Google Scholar
Choi, Y. & Chan, A. P. PROVEAN web server: a tool to predict the functional effect of amino acid substitutions and indels. Bioinformatics 31, 2745–2747 (2015).
Google Scholar
Choi, Y., Sims, G. E., Murphy, S., Miller, J. R. & Chan, A. P. Predicting the functional effect of amino acid substitutions and indels. PLoS ONE (2012).
Murrell, B. et al. Detecting individual sites subject to episodic diversifying selection. PLoS Genet. 8, e1002764 (2012).
Google Scholar
Michaud, E. J. et al. A molecular model for the genetic and phenotypic characteristics of the mouse lethal yellow (Ay) mutation. Proc. Natl Acad. Sci. USA 91, 2562–2566 (1994).
Google Scholar
Nadeau, N. J. et al. Characterization of Japanese quail yellow as a genomic deletion upstream of the avian homolog of the mammalian ASIP (agouti) gene. Genetics 178, 777–786 (2008).
Google Scholar
Wang, S., Rohwer, S., Delmore, K. E. & Irwin, D. E. Cross-decades stability of an avian hybrid zone. J. Evol. Biol. 32, 1242–1251 (2019).
Google Scholar
Console, L. et al. The link between the mitochondrial fatty acid oxidation derangement and kidney injury. Front. Physiol. 11, 1–7 (2020).
Google Scholar
Houten, S. M. & Wanders, R. J. A. A general introduction to the biochemistry of mitochondrial fatty acid β-oxidation. J. Inherit. Metab. Dis. 33, 469–477 (2010).
Google Scholar
Clemente, F. J. et al. A selective sweep on a deleterious mutation in CPT1A in arctic populations. Am. J. Hum. Genet. 95, 584–589 (2014).
Google Scholar
Fumagalli, M. et al. Greenlandic Inuit show genetic signatures of diet and climate adaptation. Science 349, 1343–1347 (2015).
Google Scholar
Zoladz, J. A. et al. Effect of temperature on fatty acid metabolism in skeletal muscle mitochondria of untrained and endurance-trained rats. PLoS One 12, e0189456 (2017).
Google Scholar
Atkin, O. K. & Macherel, D. The crucial role of plant mitochondria in orchestrating drought tolerance. Ann. Bot. 103, 581–597 (2009).
Google Scholar
Wu, C. I. The genic view of the process of speciation. J. Evolut. Biol. 14, 851–865 (2001).
Google Scholar
Via, S. Natural selection in action during speciation. Proc. Natl Acad. Sci. USA 106, 9939–9946 (2009).
Google Scholar
Nosil, P. A. Ecological Speciation (Oxford Univ. Press, 2012).
Feder, J. L., Flaxman, S. M., Egan, S. P., Comeault, A. A. & Nosil, P. Geographic mode of speciation and genomic divergence. Annu. Rev. Ecol. Evol. Syst. 44, 73–97 (2013).
Google Scholar
Wright, S. Evolution in Mendelian populations. Genetics 16, 97–159 (1931).
Google Scholar
Fisher, R. A. The Genetical Theory of Natural Selection (Oxford Univ. Press, 1930).
Hartl, D. L. & Clark, A. Principles of Population Genetics (Sinauer Associates, 2007).
Irwin, D. E. et al. A comparison of genomic islands of differentiation across three young avian species pairs. Mol. Ecol. 27, 4839–4855 (2018).
Google Scholar
Nam, K., Mugal, C., Nabholz, C., Schielzeth, H. & Wolf, J. B. Molecular evolution of genes in avian genomes. Genome Biol. 11, R68 (2010).
Google Scholar
Shafer, A. B. A., Cullingham, C. I., Côté, S. D. & Coltman, D. W. Of glaciers and refugia: a decade of study sheds new light on the phylogeography of northwestern North America. Mol. Ecol. 19, 4589–4621 (2010).
Google Scholar
Rohwer, S., Bermingham, E. & Wood, C. Plumage and mitochondrial DNA haplotype variation across a moving hybrid zone. Evolution 55, 405 (2001).
Google Scholar
Pielou, E. C. After the Ice Age (University of Chicago Press, 1991).
Bandelt, H. J., Forster, P. & Röhl, A. Median-joining networks for inferring intraspecific phylogenies. Mol. Biol. Evol. 16, 37–48 (1999).
Google Scholar
Leigh, J. W. & Bryant, D. POPART: Full-feature software for haplotype network construction. Methods Ecol. Evol. 6, 1110–1116 (2015).
Google Scholar
Elshire, R. J. et al. A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS One 6, e19379 (2011).
Google Scholar
Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).
Google Scholar
Baiz, M. D., Wood, A. W., Brelsford, A., Lovette, I. J. & Toews, D. P. L. Pigmentation genes show evidence of repeated divergence and multiple bouts of introgression in Setophaga Warblers. Curr. Biol. 31, 1–7 (2021).
Google Scholar
Li, H. & Durbin, R. Fast and accurate long-read alignment with Burrows–Wheeler transform. Bioinformatics 26, 589–595 (2010).
Google Scholar
McKenna, Aaron et al. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. (2010).
Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156–2158 (2011).
Google Scholar
Zheng, X. et al. A high-performance computing toolset for relatedness and principal component analysis of SNP data. Bioinformatics 28, 3326–3328 (2012).
Google Scholar
R Core Team (2017). R: a language and environment for statistical computing. R Found. Stat. Comput. Vienna, Austria. R Foundation for Statistical Computing (2017). S0103-64402004000300015
Raj, A., Stephens, M. & Pritchard, J. K. fastSTRUCTURE: variational inference of population structure in large SNP datasets. Genetics 197, 573–589 (2014).
Google Scholar
Weir, B. S. & Cockerham, C. C. Estimating F-statistics for the analysis of population structure. Evolution 38, 1358 (1984).
Google Scholar
Aulchenko, Y. S., Ripke, S., Isaacs, A. & van Duijn, C. M. GenABEL: an R library for genome-wide association analysis. Bioinformatics 23, 1294–1296 (2007).
Google Scholar
Johnson, M. et al. NCBI BLAST: a better web interface. Nucleic Acids Res. 36, W5–W9 (2008).
Google Scholar
Bateman, A. UniProt: A worldwide hub of protein knowledge. Nucleic Acids Res. 47, D506–D515 (2019).
Google Scholar
Legendre, P. Numerical Ecology 2nd edn (Elsevier Science, 1998). https://doi.org/10.1017/CBO9781107415324.004
Korunes, L. K. & Samuk, K. pixy: unbiased estimation of nucleotide diversity and divergence in the presence of missing data. Mol. Ecol. Resour. 21, 1359–1368 (2021).
Google Scholar
Gompert, Z. & Buerkle, C. A. Bayesian estimation of genomic clines. Mol. Ecol. 20, 2111–2127 (2011).
Google Scholar
Bates, D. M., Maechler, M., Bolker, B. & Walker, S. lme4: linear mixed-effects models using S4 classes. J. Stat. Softw. 67, 48 (2015).
Google Scholar
Bernt, M. et al. MITOS: improved de novo metazoan mitochondrial genome annotation. Mol. Phylogenet. Evol. 69, 313–319 (2013).
Google Scholar
Kearse, M. et al. Geneious. Bioinformatics (Oxford, 2012).
Woolley, S., Johnson, J., Smith, M. J., Crandall, K. A. & McClellan, D. A. TreeSAAP: selection on amino acid properties using phylogenetic trees. Bioinformatics 19, 671–672 (2003).
Google Scholar
McClellan, D. A. & Ellison, D. D. Assessing and improving the accuracy of detecting protein adaptation with the TreeSAAP analytical software. Int. J. Bioinform. Res. Appl. 6, 120–133 (2010).
Google Scholar
Wang, T., Hamann, A., Spittlehouse, D. L. & Murdock, T. Q. Climate WNA-high-resolution spatial climate data for western North America. J. Appl. Meteorol. Climatol. 51, 16–29 (2012).
Google Scholar
Legendre, P. & Legendre, L. Multidimensional quantitative data. in Numerical Ecology 143–194 (Elsevier UK, 2012).
Source: Ecology - nature.com