III · Examine the evidence

The evidence, case by case

Four questions per case, the same every time. Each statement is labelled by how settled it is and linked to its source. Criticisms and replies are both included.

Established Measured or observed repeatedly; not in serious dispute.Active research An open research question, or a claim that specialists still dispute.Speculative A proposed explanation that has not yet been tested directly.

Evidence and debate

Protein folding and sequence space

Addresses: The origin of biological informationBiological evolution

01 What is observed?

  • EstablishedMany small proteins refold on their own after being unfolded: the amino-acid sequence carries the information for the structure. (Anfinsen 1973)
  • EstablishedProteins fold in microseconds to seconds, far faster than a random trial of every conformation would allow (Levinthal's paradox). Folding is a biased descent down a funnel-shaped energy landscape, not a random search. (Levinthal 1969; Zwanzig et al. 1992; Dill & Chan 1997)
  • EstablishedSequences are constrained unevenly: in λ repressor, buried positions tolerated few substitutions while most surface positions tolerated many. (Reidhaar-Olson & Sauer 1990)
  • EstablishedFrom a library of 6 × 10¹² random 80-residue proteins, in vitro selection recovered four unrelated families that bind ATP. (Keefe & Szostak 2001)
  • Active researchWorking from a weakened β-lactamase, Axe estimated that about 1 in 10⁶⁴ sequences consistent with that fold's hydropathic pattern form a working domain, and that the prevalence of sequences performing a specific function by any domain-sized fold may be as low as 1 in 10⁷⁷. (Axe 2004)
  • Active researchA co-evolution model of ten natural protein families found that the number of sequences able to fold to a given structure is enormous (more than Avogadro's number even for small domains), but that as a fraction of all sequences it is tiny and falls steeply with length. (Tian & Best 2017)
  • EstablishedMost proteins are only marginally stable, many mutations destabilise them further, and extra stability makes a protein more tolerant of new mutations. (Taverna & Goldstein 2002; Bloom et al. 2006; Tokuriki & Tawfik 2009)
  • EstablishedStructures can now be predicted accurately from sequence for most single-domain proteins, and some functional proteins have no fixed fold at all. (Jumper et al. 2021; Dyson & Wright 2005)

02 What does evolutionary theory propose?

03 What are the unresolved questions and criticisms?

  • Active researchHow rare are functional folds? Published figures differ by more than 60 orders of magnitude, largely because they measure different things: binding any ATP, catalysing a reaction, adopting a particular fold. Which definition matters for a given evolutionary step is itself disputed. (Keefe & Szostak 2001; Axe 2004; Tian & Best 2017)
  • Active researchAxe, and Gauger & Axe, argue that functional folds are too rare, and too isolated from each other, to be reached by mutation and selection. Mainstream researchers have generally not accepted the extrapolation from one enzyme to protein space in general. (Axe 2004; Gauger & Axe 2011)
  • EstablishedAn evolution experiment that began with a random 139-residue polypeptide climbed easily to the middle of its fitness landscape, but the landscape above that was rugged; the authors concluded that 'an enormous range of sequence diversity' would be needed to climb further. (Hayashi et al. 2006)
  • EstablishedInteractions between mutations (epistasis) close off most mutational paths: of 120 possible orders for five β-lactamase mutations, 102 were inaccessible to selection. (Weinreich et al. 2006)
  • SpeculativeThe first proteins, before any existed to duplicate, belong to the origin-of-life question, and no tested account of them exists. (Koonin & Novozhilov 2009)

04 What evidence would help distinguish competing explanations?

  • Measurements of the functional fraction for several folds and lengths, all using the same definition of function. This would show whether the gap between estimates is real or a matter of definitions.
  • Laboratory evolution of a genuinely new fold, not just a new activity in an existing one, from an unrelated or random sequence.
  • Resurrected ancestral sequences tested for activity at each step of a proposed path between two different folds.
  • De novo genes in natural populations shown to encode stable, folded proteins with a selectable function.

Established Measured or observed repeatedly; not in serious dispute.Active research An open research question, or a claim that specialists still dispute.Speculative A proposed explanation that has not yet been tested directly.

Open the interactive protein folding and sequence space module →

Evidence and debate

The bacterial flagellum

Addresses: The emergence of molecular machinesBiological evolution

01 What is observed?

  • EstablishedIn E. coli and Salmonella the flagellum is built from about two dozen structural proteins, and its gene clusters can include more than 50 genes when assembly and regulation are counted. (Liu & Ochman 2007; Macnab 2003)
  • EstablishedTorque comes from stator units (MotA/MotB, or PomA/PomB in sodium-driven motors) that pass ions across the inner membrane. E. coli motors hold at least 11 stator units, and strains lacking stator proteins build flagella that cannot turn. (Reid et al. 2006; Berg 2003)
  • EstablishedEach stator unit is a ring of five MotA around two MotB (A₅B₂). The same architecture appears in other ion-driven bacterial motors. (Santiveri et al. 2020; Deme et al. 2020)
  • EstablishedAssembly runs from the inside out. The export apparatus at the base sends rod, hook and filament subunits up the hollow centre to the growing tip, and assembly checkpoints control the order in which genes switch on. (Macnab 2003; Chevance & Hughes 2008)
  • EstablishedExport is driven mainly by the proton-motive force. Cells lacking the FliI ATPase can still export, weakly. (Minamino & Namba 2008; Paul et al. 2008)
  • EstablishedThe flagellar export apparatus is homologous to the injectisome (non-flagellar type III secretion system) that many pathogens use to inject proteins into host cells. Its ATPase, FliI, closely resembles the α/β subunits of F₁-ATP synthase, and FliJ resembles that enzyme's γ subunit. (Abby & Rocha 2012; Wagner et al. 2018; Imada et al. 2007; Ibuki et al. 2011)
  • EstablishedMotors differ between species: some have wider stator rings and extra scaffolding that produce more torque. (Beeby et al. 2016; Minamino & Imada 2015; Johnson et al. 2021)
  • EstablishedThe archaeal 'flagellum' is an unrelated machine whose structure resembles bacterial type IV pili. It has been renamed the archaellum. (Jarrell & Albers 2012)

02 What does evolutionary theory propose?

  • Active researchThe core axial proteins (rod, hook, filament) are related to one another, which suggests they arose by repeated duplication and modification of a few precursor genes, or even a single one. (Liu & Ochman 2007)
  • SpeculativeThe flagellum was assembled from parts that first served other functions (co-option, or exaptation): a protein-export system, an ion channel, adhesive filaments. On this view no 'leap' is needed. (Pallen & Matzke 2006; Pallen & Gophna 2007; Miller 2004)
  • Active researchPhylogenomic analysis of more than 1,000 genomes indicates that the injectisome evolved from the flagellum, not the other way round. Machines can be repurposed into new, equally complex machines. (Abby & Rocha 2012; Gophna et al. 2003)

03 What are the unresolved questions and criticisms?

  • Active researchBehe argued that a system of several interacting parts, each needed for the basic function, cannot be produced directly by numerous successive slight modifications. He called such systems irreducibly complex, with the flagellum as his example. Knockouts do abolish motility: without stators the filament does not turn, and without the export apparatus nothing beyond the base is built. (Behe 1996; Reid et al. 2006; Macnab 2003)
  • Active researchCritics reply that the argument rules out only direct routes. Indirect routes, in which parts are borrowed from other systems and change function along the way, are not excluded, and homologies show that many parts do have relatives elsewhere. (Miller 2004; Pallen & Matzke 2006)
  • Active researchHomology shows that parts share ancestry; it does not by itself show a pathway in which every intermediate worked and was selected. No such step-by-step pathway has been demonstrated experimentally. Pallen & Matzke described what an experimental programme might look like. (Pallen & Matzke 2006)
  • Active researchIf the injectisome is derived from the flagellum, it cannot be the flagellum's ancestor. What the export system did before the flagellum existed is not known. (Abby & Rocha 2012)

04 What evidence would help distinguish competing explanations?

  • Laboratory evolution of motility from a cell given only part of the system.
  • Natural intermediate systems with a demonstrated, selectable function. Abby & Rocha describe an intermediate form of the injectisome that still exists in Myxococcales.
  • Resurrected ancestral axial and export proteins, tested for the activities a proposed pathway requires.
  • For each proposed step, an estimate of how many coordinated changes it needs. Those numbers can then go into the Probability Simulator's population-genetics model.

Established Measured or observed repeatedly; not in serious dispute.Active research An open research question, or a claim that specialists still dispute.Speculative A proposed explanation that has not yet been tested directly.

Open the interactive the bacterial flagellum module →

Evidence and debate

Genetic information and mutation

Addresses: The origin of biological informationBiological evolutionThe origin of life

01 What is observed?

  • EstablishedThe standard genetic code assigns 61 codons to 20 amino acids and 3 to 'stop'. It is nearly universal, with a few known variants. (Koonin & Novozhilov 2009)
  • EstablishedThe code limits the damage from errors: a mistaken codon usually codes for the same or a similar amino acid. Under one weighting, only about one in a million random alternative codes did better. (Freeland & Hurst 1998)
  • EstablishedMutation rates have been measured directly: about 1 × 10⁻³ per genome per generation in E. coli, and 1.2 × 10⁻⁸ per nucleotide per generation in humans. (Lee et al. 2012; Kong et al. 2012)
  • EstablishedMost mutations that affect fitness are harmful, and the proportions vary by organism and gene. In one RNA virus up to 40% of random single-base changes were lethal. (Eyre-Walker & Keightley 2007; Sanjuán et al. 2004)
  • EstablishedSickle-cell haemoglobin is a single-base change (Glu → Val at position 6). One copy protects against severe malaria; two cause disease. (Ingram 1957; Allison 1954)
  • Established'Silent' synonymous changes are not always neutral: they can affect splicing, mRNA stability and translation. (Chamary et al. 2006)
  • EstablishedIn Lenski's long-term experiment, one population evolved the ability to grow on citrate in oxygen after tens of thousands of generations, through earlier 'potentiating' mutations followed by a later one. (Blount et al. 2008)

02 What does evolutionary theory propose?

03 What are the unresolved questions and criticisms?

  • SpeculativeHow the genetic code arose. Stereochemical, coevolution and error-minimisation hypotheses each explain part of the pattern, and none is established. This is an origin-of-life question, not one that natural selection among organisms can answer. (Koonin & Novozhilov 2009)
  • Active researchBehe reviewed experimental-evolution studies and argued that most adaptive mutations break or blunt existing genes ('the first rule of adaptive evolution'). Others point to gains such as the citrate innovation and de novo genes. How common gain-of-function adaptation is remains debated. (Behe 2010; Blount et al. 2008; Carvunis et al. 2012)
  • Active researchHow long it takes to acquire changes that only work together. Durrett & Schmidt modelled two coordinated changes in a regulatory sequence and found a few million years enough for Drosophila but more than 100 million years for humans. Behe and the authors disagreed in an exchange of letters about what the result implies. (Durrett & Schmidt 2008; Behe 2009)

04 What evidence would help distinguish competing explanations?

  • Across many experimental-evolution studies, measured rates of gain-of-function versus loss-of-function adaptive mutations.
  • Laboratory evolution of new functions that need several coordinated changes, timed and compared with population-genetics predictions.
  • Experimental tests of proposed routes to the genetic code using prebiotic chemistry.

Established Measured or observed repeatedly; not in serious dispute.Active research An open research question, or a claim that specialists still dispute.Speculative A proposed explanation that has not yet been tested directly.

Open the interactive genetic information and mutation module →

Evidence and debate

Molecular machinery: ATP synthase and kinesin

Addresses: The emergence of molecular machinesThe origin of life

01 What is observed?

02 What does evolutionary theory propose?

  • SpeculativeRotary ATPases began as membrane protein translocases, which in turn evolved from RNA translocases. In those ancestors the translocated polymer sat where the central stalk is now. (Mulkidjanian et al. 2007)
  • Active researchKinesins and myosins descend from a common ancestral nucleotide-binding motor and diverged to walk on different tracks. (Kull et al. 1996; Vale & Milligan 2000)
  • SpeculativeCoupling to ion gradients (chemiosmosis) may go back to natural proton gradients at alkaline hydrothermal vents. (Lane & Martin 2012)

03 What are the unresolved questions and criticisms?

  • Active researchNo stepwise route to ATP synthase in which each stage is shown to work has been reconstructed. Homology identifies related parts; it does not by itself show the path. (Mulkidjanian et al. 2007)
  • Active researchTurning proton flow into rotation needs the a subunit and the c-ring to work together. How that coupling arose in stages is an open question. (The Lab's summary.)
  • Active researchAlmost all cells use ATP synthase to make the ATP that their other machinery, including the machinery that builds ATP synthase, depends on. Its origin is therefore bound up with the origin of life. (Lane & Martin 2012)

04 What evidence would help distinguish competing explanations?

  • Resurrected ancestral rotary-ATPase subunits, tested for the partial functions proposed for them.
  • Simpler rotary systems in nature that work with fewer parts.
  • Laboratory experiments that couple an ion channel to a ring ATPase and select for rotation or transport.

Established Measured or observed repeatedly; not in serious dispute.Active research An open research question, or a claim that specialists still dispute.Speculative A proposed explanation that has not yet been tested directly.

Open the interactive molecular machinery: atp synthase and kinesin module →

Evidence and debate

Genetic entropy: does the genome decay?

Addresses: Biological evolutionThe origin of biological information

01 What is observed?

  • EstablishedEach person carries about 70 new mutations not present in either parent (Keightley's estimate; Kong et al. measured about 1.2 × 10⁻⁸ per nucleotide). How many of them affect fitness is much less certain. (Keightley 2012; Kong et al. 2012)
  • EstablishedOf mutations that change fitness, most are harmful. Their effects span many orders of magnitude, with a long tail of very slight effects. (Eyre-Walker & Keightley 2007)
  • Active researchFor amino-acid changes in humans, a gamma distribution with shape 0.23 fits the data: more than half reduce fitness by between 0.1% and 10%, and fewer than 15% are strongly harmful. Larger samples suggest even more are only weakly harmful (|s| < 0.001). (Eyre-Walker et al. 2006; Kim et al. 2017)
  • EstablishedLines kept through single-individual bottlenecks, which nearly switches off selection, steadily lose fitness in many organisms. (Halligan & Keightley 2009)
  • EstablishedMuller's ratchet has been seen directly in asexual lineages: an RNA virus, and Salmonella, in which 1% of 444 bottlenecked lineages had visibly lost fitness after 1,700 generations. Endosymbiotic bacteria, which live asexually in small populations, show the accelerated sequence change it predicts. (Chao 1990; Andersson & Hughes 1996; Moran 1996)
  • EstablishedToo many mutations can kill a population. A 9.7-fold rise in mutation rate caused by the drug ribavirin cut poliovirus infectivity by 99.3% in a single round of infection. (Crotty et al. 2001)
  • EstablishedDegradation can be reversed. Mutationally degraded C. elegans lines returned to full mean fitness in fewer than 80 generations once kept in large populations, partly through compensatory mutations. (Estes & Lynch 2003)
  • Active researchThe human H1N1 influenza lineage accumulated about 1,400 point mutations between 1918 and its disappearance in 2009, while its mortality rate fell. Carter and Sanford read this as genetic attenuation. A common alternative, here in the Lab's own words, is that rising immunity and better medicine lowered mortality. (Carter & Sanford 2012)

02 What does evolutionary theory propose?

  • EstablishedMutations that selection can see reach a balance at which they are removed as fast as they arrive. With multiplicative effects, mean fitness settles near e^−U, whatever the size of each effect. (Haldane 1937; Muller 1950; Kimura & Maruyama 1966)
  • EstablishedSex and recombination break up linked mutations, which stops Muller's ratchet and lets selection act on each mutation separately. (Muller 1964; Felsenstein 1974; Kondrashov 1988)
  • Active researchA high load need not shrink a population if selection acts on relative fitness (soft selection), or if mutations interact so that selection removes several at once. On this view a deleterious rate of about 2.2 per generation is tolerable. (Wallace 1975; Keightley 2012; Lesecque et al. 2012; Agrawal & Whitlock 2012)
  • Active researchBeneficial and compensatory mutations can offset the slow fixation of slightly harmful ones. Above a critical effective size, likely a few hundred, populations hold their fitness on average. (Whitlock 2000; Poon & Otto 2000)
  • EstablishedSmall populations are genuinely at risk. Drift fixes harmful mutations, fewer offspring survive, numbers fall, and drift grows stronger: a mutational meltdown. (Gabriel et al. 1993; Lynch et al. 1995; Lynch et al. 1995)
  • Active researchSome mainstream geneticists also expect decline in modern humans, because medicine and small families relax selection, possibly measurably within a few generations. (Lynch 2016)

03 What are the unresolved questions and criticisms?

  • Active researchSanford argues that most mutations are slightly harmful, that selection cannot see them (especially when survival is noisy), and that the human genome is therefore degenerating. He bases this on simulations with Mendel's Accountant. Most population geneticists dispute the premises and the conclusion. (Sanford 2005; Sanford et al. 2007; Gibson et al. 2013)
  • Active researchKondrashov identified a 'dangerous range' of effects, between 1/genome size and 1/4Nₑ, in which mutations accumulate almost freely yet together could carry a large load. He called the resulting paradox real and proposed soft selection or synergistic epistasis as possible ways out. (Kondrashov 1995)
  • Active researchHow much of the genome is functional? About 8.2% of the human genome shows evidence of constraint. If that is right, most new mutations are neutral. If, as Sanford argues, nearly all of the genome matters, the harmful rate is far higher. (Rands et al. 2014)
  • Active researchThe weakest effects, the ones that matter most here, are the hardest to measure. Estimates of the distribution's tail depend on demographic models and sample size. (Kim et al. 2017; Eyre-Walker & Keightley 2007)
  • Active researchIs selection in real populations mostly hard or mostly soft? The answer decides whether a low 'mean fitness' number means fewer survivors or just a different ranking. (Wallace 1975; Agrawal & Whitlock 2012)
  • Active researchHow common are beneficial mutations, and do they keep pace? Estimates range from about 1 in a million (the figure in Sanford's lecture) to about 1 in 100 (from beneficial mutation rates measured in E. coli). (Perfeito et al. 2007; Lee et al. 2012)
  • Active researchBasener and Sanford argue that, once mutations are included, Fisher's fundamental theorem does not guarantee that fitness rises. (Basener & Sanford 2018)
  • Active researchLoad estimates across human populations with very different histories are similar, which constrains how fast recent changes alter load. (Simons et al. 2014)

04 What evidence would help distinguish competing explanations?

  • Standardised, multigenerational measurements of fitness-related human traits, as Lynch (2016) calls for.
  • Long mutation-accumulation and recovery experiments in large sexual populations, run for thousands of generations, that measure absolute fitness and not only growth rate relative to an ancestor.
  • Direct estimates of how many harmful mutations have effects below 10⁻⁴, from very large samples.
  • Time series of mutation load from ancient DNA within one lineage.
  • Fitness assays, not only sequence counts, along the H1N1 lineage and other long-studied viral lineages.
  • Whether species with long-term small populations (island endemics, endosymbionts) show the predicted decline, and how fast.

Established Measured or observed repeatedly; not in serious dispute.Active research An open research question, or a claim that specialists still dispute.Speculative A proposed explanation that has not yet been tested directly.

Open the interactive genetic entropy: does the genome decay? module →

How this page was put together

Sources and labels

  • Every citation was checked against Crossref for title, journal, volume, pages and DOI, and each quoted finding against the paper's abstract. Books and book chapters are marked, because they are not peer-reviewed journal articles; so is BIO-Complexity, a journal founded by intelligent-design researchers.
  • "Established" means measured or observed repeatedly. It does not mean that every interpretation of the measurement is settled.
  • The cases address different questions: biological evolution; the origin of life; the origin of biological information; the emergence of molecular machines. Evidence on one does not automatically carry over to another.
  • Found an error or a missing source? Tell us.

All references

  1. Abby SS, Rocha EPC (2012). The non-flagellar type III secretion system evolved from the bacterial flagellum and diversified into host-cell adapted systems. PLoS Genetics 8:e1002983. doi:10.1371/journal.pgen.1002983
  2. Abrahams JP, Leslie AGW, Lutter R, Walker JE (1994). Structure at 2.8 Å resolution of F1-ATPase from bovine heart mitochondria. Nature 370:621–628. doi:10.1038/370621a0
  3. Agrawal AF, Whitlock MC (2012). Mutation load: the fitness of individuals in populations where deleterious alleles are abundant. Annual Review of Ecology, Evolution, and Systematics 43:115–135. doi:10.1146/annurev-ecolsys-110411-160257
  4. Allison AC (1954). Protection afforded by sickle-cell trait against subtertian malarial infection. BMJ 1:290–294. doi:10.1136/bmj.1.4857.290
  5. Andersson DI, Hughes D (1996). Muller's ratchet decreases fitness of a DNA-based microbe. PNAS 93:906–907. doi:10.1073/pnas.93.2.906
  6. Anfinsen CB (1973). Principles that govern the folding of protein chains. Science 181:223–230. doi:10.1126/science.181.4096.223
  7. Axe DD (2004). Estimating the prevalence of protein sequences adopting functional enzyme folds. Journal of Molecular Biology 341:1295–1315. doi:10.1016/j.jmb.2004.06.058
  8. Basener WF, Sanford JC (2018). The fundamental theorem of natural selection with mutations. Journal of Mathematical Biology 76:1589–1622. doi:10.1007/s00285-017-1190-x
  9. Beeby M, Ribardo DA, Brennan CA, et al. (2016). Diverse high-torque bacterial flagellar motors assemble wider stator rings using a conserved protein scaffold. PNAS 113:E1917–E1926. doi:10.1073/pnas.1518952113
  10. Behe MJ (1996). Darwin's Black Box: The Biochemical Challenge to Evolution. Free Press. Book, not a peer-reviewed journal article.
  11. Behe MJ (2009). Waiting longer for two mutations. Genetics 181:819–820 (letter; with the authors' reply). doi:10.1534/genetics.108.098905
  12. Behe MJ (2010). Experimental evolution, loss-of-function mutations, and “the first rule of adaptive evolution”. The Quarterly Review of Biology 85:419–445. doi:10.1086/656902
  13. Berg HC (2003). The rotary motor of bacterial flagella. Annual Review of Biochemistry 72:19–54. doi:10.1146/annurev.biochem.72.121801.161737
  14. Bloom JD, Labthavikul ST, Otey CR, Arnold FH (2006). Protein stability promotes evolvability. PNAS 103:5869–5874. doi:10.1073/pnas.0510098103
  15. Blount ZD, Borland CZ, Lenski RE (2008). Historical contingency and the evolution of a key innovation in an experimental population of Escherichia coli. PNAS 105:7899–7906. doi:10.1073/pnas.0803151105
  16. Boyer PD (1997). The ATP synthase: a splendid molecular machine. Annual Review of Biochemistry 66:717–749. doi:10.1146/annurev.biochem.66.1.717
  17. Carter RW, Sanford JC (2012). A new look at an old virus: patterns of mutation accumulation in the human H1N1 influenza virus since 1918. Theoretical Biology and Medical Modelling 9:42. doi:10.1186/1742-4682-9-42 Both authors are affiliated with the FMS Foundation, which Sanford founded.
  18. Carvunis AR, Rolland T, Wapinski I, et al. (2012). Proto-genes and de novo gene birth. Nature 487:370–374. doi:10.1038/nature11184
  19. Chamary JV, Parmley JL, Hurst LD (2006). Hearing silence: non-neutral evolution at synonymous sites in mammals. Nature Reviews Genetics 7:98–108. doi:10.1038/nrg1770
  20. Chao L (1990). Fitness of RNA virus decreased by Muller's ratchet. Nature 348:454–455. doi:10.1038/348454a0
  21. Chevance FFV, Hughes KT (2008). Coordinating assembly of a bacterial macromolecular machine. Nature Reviews Microbiology 6:455–465. doi:10.1038/nrmicro1887
  22. Crotty S, Cameron CE, Andino R (2001). RNA virus error catastrophe: direct molecular test by using ribavirin. PNAS 98:6895–6900. doi:10.1073/pnas.111085598
  23. Deme JC, Johnson S, Vickery O, et al. (2020). Structures of the stator complex that drives rotation of the bacterial flagellum. Nature Microbiology 5:1553–1564. doi:10.1038/s41564-020-0788-8
  24. Dill KA, Chan HS (1997). From Levinthal to pathways to funnels. Nature Structural Biology 4:10–19. doi:10.1038/nsb0197-10
  25. Durrett R, Schmidt D (2008). Waiting for two mutations: with applications to regulatory sequence evolution and the limits of Darwinian evolution. Genetics 180:1501–1509. doi:10.1534/genetics.107.082610
  26. Dyson HJ, Wright PE (2005). Intrinsically unstructured proteins and their functions. Nature Reviews Molecular Cell Biology 6:197–208. doi:10.1038/nrm1589
  27. Estes S, Lynch M (2003). Rapid fitness recovery in mutationally degraded lines of Caenorhabditis elegans. Evolution 57:1022–1030. doi:10.1111/j.0014-3820.2003.tb00313.x
  28. Eyre-Walker A, Keightley PD (2007). The distribution of fitness effects of new mutations. Nature Reviews Genetics 8:610–618. doi:10.1038/nrg2146
  29. Eyre-Walker A, Woolfit M, Phelps T (2006). The distribution of fitness effects of new deleterious amino acid mutations in humans. Genetics 173:891–900. doi:10.1534/genetics.106.057570
  30. Felsenstein J (1974). The evolutionary advantage of recombination. Genetics 78:737–756. doi:10.1093/genetics/78.2.737
  31. Freeland SJ, Hurst LD (1998). The genetic code is one in a million. Journal of Molecular Evolution 47:238–248. doi:10.1007/pl00006381
  32. Gabriel W, Lynch M, Bürger R (1993). Muller's ratchet and mutational meltdowns. Evolution 47:1744–1757. doi:10.1111/j.1558-5646.1993.tb01266.x
  33. Gauger AK, Axe DD (2011). The evolutionary accessibility of new enzyme functions: a case study from the biotin pathway. BIO-Complexity 2011(1). doi:10.5048/bio-c.2011.1 BIO-Complexity was founded by intelligent-design researchers.
  34. Gibson P, Baumgardner JR, Brewer WH, Sanford JC (2013). Can purifying natural selection preserve biological information?. In Marks RJ II, Behe MJ, Dembski WA, Gordon BL, Sanford JC (eds) Biological Information: New Perspectives, pp. 232–263 (World Scientific). doi:10.1142/9789814508728_0010 Book chapter, not a peer-reviewed journal article. From a 2011 symposium organised largely by intelligent-design researchers.
  35. Gophna U, Ron EZ, Graur D (2003). Bacterial type III secretion systems are ancient and evolved by multiple horizontal-transfer events. Gene 312:151–163. doi:10.1016/s0378-1119(03)00612-7
  36. Haldane JBS (1937). The effect of variation on fitness. The American Naturalist 71:337–349. doi:10.1086/280722
  37. Halligan DL, Keightley PD (2009). Spontaneous mutation accumulation studies in evolutionary genetics. Annual Review of Ecology, Evolution, and Systematics 40:151–172. doi:10.1146/annurev.ecolsys.39.110707.173437
  38. Hayashi Y, Aita T, Toyota H, Husimi Y, Urabe I, Yomo T (2006). Experimental rugged fitness landscape in protein sequence space. PLoS ONE 1:e96. doi:10.1371/journal.pone.0000096
  39. Ibuki T, Imada K, Minamino T, et al. (2011). Common architecture of the flagellar type III protein export apparatus and F- and V-type ATPases. Nature Structural & Molecular Biology 18:277–282. doi:10.1038/nsmb.1977
  40. Imada K, Minamino T, Tahara A, Namba K (2007). Structural similarity between the flagellar type III ATPase FliI and F1-ATPase subunits. PNAS 104:485–490. doi:10.1073/pnas.0608090104
  41. Ingram VM (1957). Gene mutations in human haemoglobin: the chemical difference between normal and sickle cell haemoglobin. Nature 180:326–328. doi:10.1038/180326a0
  42. Jarrell KF, Albers SV (2012). The archaellum: an old motility structure with a new name. Trends in Microbiology 20:307–312. doi:10.1016/j.tim.2012.04.007
  43. Johnson S, Furlong EJ, Deme JC, et al. (2021). Molecular structure of the intact bacterial flagellar basal body. Nature Microbiology 6:712–721. doi:10.1038/s41564-021-00895-y
  44. Jumper J, Evans R, Pritzel A, et al. (2021). Highly accurate protein structure prediction with AlphaFold. Nature 596:583–589. doi:10.1038/s41586-021-03819-2
  45. Keefe AD, Szostak JW (2001). Functional proteins from a random-sequence library. Nature 410:715–718. doi:10.1038/35070613
  46. Keightley PD (2012). Rates and fitness consequences of new mutations in humans. Genetics 190:295–304. doi:10.1534/genetics.111.134668
  47. Kim BY, Huber CD, Lohmueller KE (2017). Inference of the distribution of selection coefficients for new nonsynonymous mutations using large samples. Genetics 206:345–361. doi:10.1534/genetics.116.197145
  48. Kimura M, Maruyama T (1966). The mutational load with epistatic gene interactions in fitness. Genetics 54:1337–1351. doi:10.1093/genetics/54.6.1337
  49. Kimura M (1968). Evolutionary rate at the molecular level. Nature 217:624–626. doi:10.1038/217624a0
  50. Knopp M, Andersson DI (2018). No beneficial fitness effects of random peptides. Nature Ecology & Evolution 2:1046–1047 (comment on Neme et al.). doi:10.1038/s41559-018-0585-4
  51. Knopp M, Gudmundsdottir JS, Nilsson T, et al. (2019). De novo emergence of peptides that confer antibiotic resistance. mBio 10:e00837-19. doi:10.1128/mbio.00837-19
  52. Kondrashov AS (1988). Deleterious mutations and the evolution of sexual reproduction. Nature 336:435–440. doi:10.1038/336435a0
  53. Kondrashov AS (1995). Contamination of the genome by very slightly deleterious mutations: why have we not died 100 times over?. Journal of Theoretical Biology 175:583–594. doi:10.1006/jtbi.1995.0167
  54. Kong A, Frigge ML, Masson G, et al. (2012). Rate of de novo mutations and the importance of father's age to disease risk. Nature 488:471–475. doi:10.1038/nature11396
  55. Koonin EV, Novozhilov AS (2009). Origin and evolution of the genetic code: the universal enigma. IUBMB Life 61:99–111. doi:10.1002/iub.146
  56. Kull FJ, Sablin EP, Lau R, Fletterick RJ, Vale RD (1996). Crystal structure of the kinesin motor domain reveals a structural similarity to myosin. Nature 380:550–555. doi:10.1038/380550a0
  57. Lane N, Martin WF (2012). The origin of membrane bioenergetics. Cell 151:1406–1416. doi:10.1016/j.cell.2012.11.050
  58. Lee H, Popodi E, Tang H, Foster PL (2012). Rate and molecular spectrum of spontaneous mutations in the bacterium Escherichia coli as determined by whole-genome sequencing. PNAS 109:E2774–E2783. doi:10.1073/pnas.1210309109
  59. Lesecque Y, Keightley PD, Eyre-Walker A (2012). A resolution of the mutation load paradox in humans. Genetics 191:1321–1330. doi:10.1534/genetics.112.140343
  60. Levinthal C (1969). How to fold graciously. In Debrunner P, Tsibris JCM, Münck E (eds) Mössbauer Spectroscopy in Biological Systems, University of Illinois Press, pp. 22–24. Conference proceedings, not a peer-reviewed journal article.
  61. Liu R, Ochman H (2007). Stepwise formation of the bacterial flagellar system. PNAS 104:7116–7121. doi:10.1073/pnas.0700266104
  62. Lynch M (2016). Mutation and human exceptionalism: our future genetic load. Genetics 202:869–875. doi:10.1534/genetics.115.180471
  63. Lynch M, Conery J, Bürger R (1995). Mutational meltdowns in sexual populations. Evolution 49:1067–1080. doi:10.1111/j.1558-5646.1995.tb04434.x
  64. Lynch M, Conery J, Bürger R (1995). Mutation accumulation and the extinction of small populations. The American Naturalist 146:489–518. doi:10.1086/285812
  65. Macnab RM (2003). How bacteria assemble flagella. Annual Review of Microbiology 57:77–100. doi:10.1146/annurev.micro.57.030502.090832
  66. Miller KR (2004). The flagellum unspun: the collapse of 'irreducible complexity'. In Dembski WA, Ruse M (eds) Debating Design, pp. 81–97, Cambridge University Press. doi:10.1017/cbo9780511804823.006 Book chapter, not a peer-reviewed journal article.
  67. Minamino T, Imada K (2015). The bacterial flagellar motor and its structural diversity. Trends in Microbiology 23:267–274. doi:10.1016/j.tim.2014.12.011
  68. Minamino T, Namba K (2008). Distinct roles of the FliI ATPase and proton motive force in bacterial flagellar protein export. Nature 451:485–488. doi:10.1038/nature06449
  69. Moran NA (1996). Accelerated evolution and Muller's rachet in endosymbiotic bacteria. PNAS 93:2873–2878. doi:10.1073/pnas.93.7.2873
  70. Mulkidjanian AY, Makarova KS, Galperin MY, Koonin EV (2007). Inventing the dynamo machine: the evolution of the F-type and V-type ATPases. Nature Reviews Microbiology 5:892–899. doi:10.1038/nrmicro1767
  71. Muller HJ (1950). Our load of mutations. American Journal of Human Genetics 2:111–176 (PMID 14771033).
  72. Muller HJ (1964). The relation of recombination to mutational advance. Mutation Research 1:2–9. doi:10.1016/0027-5107(64)90047-8
  73. Neme R, Amador C, Yildirim B, McConnell E, Tautz D (2017). Random sequences are an abundant source of bioactive RNAs or peptides. Nature Ecology & Evolution 1:0127. doi:10.1038/s41559-017-0127
  74. Noji H, Yasuda R, Yoshida M, Kinosita K (1997). Direct observation of the rotation of F1-ATPase. Nature 386:299–302. doi:10.1038/386299a0
  75. Pallen MJ, Gophna U (2007). Bacterial flagella and type III secretion: case studies in the evolution of complexity. Genome Dynamics 3:30–47. doi:10.1159/000107602
  76. Pallen MJ, Matzke NJ (2006). From The Origin of Species to the origin of bacterial flagella. Nature Reviews Microbiology 4:784–790. doi:10.1038/nrmicro1493
  77. Paul K, Erhardt M, Hirano T, Blair DF, Hughes KT (2008). Energy source of flagellar type III secretion. Nature 451:489–492. doi:10.1038/nature06497
  78. Perfeito L, Fernandes L, Mota C, Gordo I (2007). Adaptive mutations in bacteria: high rate and small effects. Science 317:813–815. doi:10.1126/science.1142284
  79. Poon A, Otto SP (2000). Compensating for our load of mutations: freezing the meltdown of small populations. Evolution 54:1467–1479. doi:10.1111/j.0014-3820.2000.tb00693.x
  80. Rands CM, Meader S, Ponting CP, Lunter G (2014). 8.2% of the human genome is constrained: variation in rates of turnover across functional element classes in the human lineage. PLoS Genetics 10:e1004525. doi:10.1371/journal.pgen.1004525
  81. Reid SW, Leake MC, Chandler JH, et al. (2006). The maximum number of torque-generating units in the flagellar motor of Escherichia coli is at least 11. PNAS 103:8066–8071. doi:10.1073/pnas.0509932103
  82. Reidhaar-Olson JF, Sauer RT (1990). Functionally acceptable substitutions in two α-helical regions of λ repressor. Proteins 7:306–316. doi:10.1002/prot.340070403
  83. Sanford JC (2005). Genetic Entropy & the Mystery of the Genome. Ivan Press / FMS Publications (later editions titled Genetic Entropy). Book, not a peer-reviewed journal article.
  84. Sanford J, Baumgardner J, Brewer W, Gibson P, ReMine W (2007). Using computer simulation to understand mutation accumulation dynamics and genetic load. In Computational Science – ICCS 2007, Lecture Notes in Computer Science 4488:386–392 (Springer). doi:10.1007/978-3-540-72586-2_55 Conference proceedings, not a peer-reviewed journal article. Describes the Mendel's Accountant program.
  85. Sanjuán R, Moya A, Elena SF (2004). The distribution of fitness effects caused by single-nucleotide substitutions in an RNA virus. PNAS 101:8396–8401. doi:10.1073/pnas.0400146101
  86. Santiveri M, Roa-Eguiara A, Kühne C, et al. (2020). Structure and function of stator units of the bacterial flagellar motor. Cell 183:244–257. doi:10.1016/j.cell.2020.08.016
  87. Schnitzer MJ, Block SM (1997). Kinesin hydrolyses one ATP per 8-nm step. Nature 388:386–390. doi:10.1038/41111
  88. Simons YB, Turchin MC, Pritchard JK, Sella G (2014). The deleterious mutation load is insensitive to recent population history. Nature Genetics 46:220–224. doi:10.1038/ng.2896
  89. Stock D, Leslie AGW, Walker JE (1999). Molecular architecture of the rotary motor in ATP synthase. Science 286:1700–1705. doi:10.1126/science.286.5445.1700
  90. Svoboda K, Schmidt CF, Schnapp BJ, Block SM (1993). Direct observation of kinesin stepping by optical trapping interferometry. Nature 365:721–727. doi:10.1038/365721a0
  91. Tautz D, Domazet-Lošo T (2011). The evolutionary origin of orphan genes. Nature Reviews Genetics 12:692–702. doi:10.1038/nrg3053
  92. Taverna DM, Goldstein RA (2002). Why are proteins marginally stable?. Proteins 46:105–109. doi:10.1002/prot.10016
  93. Tian P, Best RB (2017). How many protein sequences fold to a given structure? A coevolutionary analysis. Biophysical Journal 113:1719–1730. doi:10.1016/j.bpj.2017.08.039
  94. Tokuriki N, Tawfik DS (2009). Stability effects of mutations and protein evolvability. Current Opinion in Structural Biology 19:596–604. doi:10.1016/j.sbi.2009.08.003
  95. Tokuriki N, Tawfik DS (2009). Protein dynamism and evolvability. Science 324:203–207. doi:10.1126/science.1169375
  96. Vale RD, Milligan RA (2000). The way things move: looking under the hood of molecular motor proteins. Science 288:88–95. doi:10.1126/science.288.5463.88
  97. Wagner S, Grin I, Malmsheimer S, et al. (2018). Bacterial type III secretion systems: a complex device for the delivery of bacterial effector proteins into eukaryotic host cells. FEMS Microbiology Letters 365:fny201. doi:10.1093/femsle/fny201
  98. Walker JE, Saraste M, Runswick MJ, Gay NJ (1982). Distantly related sequences in the α- and β-subunits of ATP synthase, myosin, kinases and other ATP-requiring enzymes and a common nucleotide binding fold. The EMBO Journal 1:945–951. doi:10.1002/j.1460-2075.1982.tb01276.x
  99. Wallace B (1975). Hard and soft selection revisited. Evolution 29:465–473. doi:10.1111/j.1558-5646.1975.tb00836.x
  100. Watt IN, Montgomery MG, Runswick MJ, Leslie AGW, Walker JE (2010). Bioenergetic cost of making an adenosine triphosphate molecule in animal mitochondria. PNAS 107:16823–16827. doi:10.1073/pnas.1011099107
  101. Weinreich DM, Delaney NF, DePristo MA, Hartl DL (2006). Darwinian evolution can follow only very few mutational paths to fitter proteins. Science 312:111–114. doi:10.1126/science.1123539
  102. Weisman CM, Eddy SR (2017). Gene evolution: getting something from nothing. Current Biology 27:R661–R663. doi:10.1016/j.cub.2017.05.056
  103. Whitlock MC (2000). Fixation of new alleles and the extinction of small populations: drift load, beneficial alleles, and sexual selection. Evolution 54:1855–1861. doi:10.1111/j.0014-3820.2000.tb01232.x
  104. Yasuda R, Noji H, Kinosita K, Yoshida M (1998). F1-ATPase is a highly efficient molecular motor that rotates with discrete 120° steps. Cell 93:1117–1124. doi:10.1016/s0092-8674(00)81456-7
  105. Yasuda R, Noji H, Yoshida M, Kinosita K, Itoh H (2001). Resolution of distinct rotational substeps by submillisecond kinetic analysis of F1-ATPase. Nature 410:898–904. doi:10.1038/35073513
  106. Yildiz A, Tomishige M, Vale RD, Selvin PR (2004). Kinesin walks hand-over-hand. Science 303:676–678. doi:10.1126/science.1093753
  107. Zwanzig R, Szabo A, Bagchi B (1992). Levinthal's paradox. PNAS 89:20–22. doi:10.1073/pnas.89.1.20