In this study, Ishigohoka and colleagues tackle an important, yet often overlooked, question on the causes of genetic variation. While genome-wide patterns represent population structure, local variation is often associated with selection. Authors propose that an alternative cause for variation in individual loci is reduced recombination rate.

To test this hypothesis, authors perform local Principal Component Analysis (PCA) (Li & Ralph, 2019) to identify local deviations in population structure in the Eurasian blackcap (Sylvia atricapilla) (Ishigohoka et al. 2022). This approach is typically used to detect chromosomal rearrangements or any long region of linked loci (e.g., due to reduced recombination or selection) (Mérot et al. 2021). While other studies investigated the effect of low recombination on genetic variation (Booker et al. 2020), here authors provide a comprehensive analysis of the effect of recombination to local PCA patterns both in empirical and simulated data sets. Findings demonstrate that low recombination (and not selection) can be the sole explanatory variable for outlier windows. The study also describes patterns of genetic variation along the genome of Eurasian blackcaps, localising at least two polymorphic inversions (Ishigohoka et al. 2022).

Further investigations on the effect of model parameters (e.g., window sizes and thresholds for defining low-recombining regions), as well as the use of powerful neutrality tests are in need to clearly assess whether outlier regions experience selection and reduced recombination, and to what extent.

References

Booker, T. R., Yeaman, S., & Whitlock, M. C. (2020). Variation in recombination rate affects detection of outliers in genome scans under neutrality. Molecular Ecology, 29 (22), 4274–4279. https://doi.org/10.1111/mec.15501

Ishigohoka, J., Bascón-Cardozo, K., Bours, A., Fuß, J., Rhie, A., Mountcastle, J., Haase, B., Chow, W., Collins, J., Howe, K., Uliano-Silva, M., Fedrigo, O., Jarvis, E. D., Pérez-Tris, J., Illera, J. C., Liedvogel, M. (2022) Distinct patterns of genetic variation at low-recombining genomic regions represent haplotype structure. bioRxiv 2021.12.22.473882, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2021.12.22.473882

Li, H., & Ralph, P. (2019). Local PCA Shows How the Effect of Population Structure Differs Along the Genome. Genetics, 211 (1), 289–304. https://doi.org/10.1534/genetics.118.301747

Mérot, C., Berdan, E. L., Cayuela, H., Djambazian, H., Ferchaud, A.-L., Laporte, M., Normandeau, E., Ragoussis, J., Wellenreuther, M., & Bernatchez, L. (2021). Locally Adaptive Inversions Modulate Genetic Variation at Different Geographic Scales in a Seaweed Fly. Molecular Biology and Evolution, 38 (9), 3953–3971. https://doi.org/10.1093/molbev/msab143

Despite advances in genomic research, many views of genome evolution are still based on what we know from a handful of species, such as humans. This also applies to our knowledge of sex chromosomes. We've apparently been too much used to the situation in which a highly degenerate Y chromosome coexists with an almost normal X chromosome to be able to fully grasp all the questions implied by this situation. Lately, many more sex chromosomes have been studied in other organisms, such as in plants, and the view is changing radically: there is a large diversity of situations, ranging from young highly divergent sex chromosomes to old ones that are so similar that they're hard to detect. Undoubtedly inspired by these recent findings, a few theoretical studies have been published around 2 years ago that put an entirely new light on the evolution of sex chromosomes. The differences between these models have however remained somewhat difficult to appreciate by non-specialists. 

In particular, the models by Lenormand & Roze (2022) and by Jay et al. (2022) seemed quite similar. Indeed, both rely on the same mechanism for initial recombination suppression: a ``lucky'' inversion, i.e. one with less deleterious mutations than the population average, encompassing the sex-determination locus, is initially selected. However, as it doesn't recombine, it will quickly accumulate deleterious mutations lowering its fitness. And it's at this point the models diverge: according to Lenormand & Roze (2022), nascent dosage compensation not only limits the deleterious effects on fitness by the ongoing degeneration, but it actually opposes recombination restoration as this would lead gene expression away from the optimum that has been reached. On the other hand, in the model by Jay et al. (2022), no additional ingredient is required: they argue that once an inversion had been fixed, reversions that restore recombination are extremely unlikely.

This is what Lenormand & Roze (2024) now call a ``constraint'': in Jay et al.'s model, recombination restoration is impossible for mechanistic reasons. Lenormand & Roze (2024) argue such constraints cannot explain long-term recombination suppression. Instead, a mechanism should evolve to limit the negative fitness effects of recombination arrest, otherwise recombination is either restored, or the population goes extinct due to a dramatic drop in the fitness of the heterogametic sex. These two arguments work together: given the huge fitness cost of the lack of ongoing degeneration of the non-recombining Y, in the absence of compensatory mechanisms, there is a very strong selection for the restoration of recombination, so that even when restoration a priori is orders of magnitude less likely than inversion (leading to recombination suppression), it will eventually happen. 

One way the negative fitness effects of recombination suppression can be limited, is the way the authors propose in their own model: dosage compensation evolves through regulatory evolution right at the start of recombination suppression. This changes our classical, simplistic view that dosage compensation evolves in response to degeneration: rather, Lenormand & Roze (2024) argue, that degeneration can only happen when dosage compensation is effective.

The reasoning is convincing and exposes the difference between the models to readers without a firm background in mathematical modelling. Although Lenormand & Roze (2024) target the "constraint theory", it seems likely that other theories for the maintenance of recombination suppression that don't imply the compensation of early degeneration are subject to the same criticism. Indeed, they mention the widely-cited "sexual antagonism" theory, in which mutations with a positive effect in males but a negative in females will select for recombination suppression that will link them to the sex-determining gene on the Y. However, once degeneration starts, the sexually-antagonistic benefits should be huge to overcome the negative effects of degeneration, and it's unlikely they'll be large enough.

A convincing argument by Lenormand & Roze (2024) is that there are many ways recombination could be restored, allowing to circumvent the possible constraints that might be associated with reverting an inversion. First, reversions don't have to be exact to restore recombination. Second, the sex-determining locus can be transposed to another chromosome pair, or an entirely new sex-determining locus might evolve, leading to sex-chromosome turnover which has effectively been observed in several groups.

These modelling studies raise important questions that need to be addressed with both theoretical and empirical work. First, is the regulatory hypothesis proposed by Lenormand & Roze (2022) the only plausible mechanism for the maintenance of long-term recombination suppression? The female- and male-specific trans regulators of gene expression that are required for this model, are they readily available or do they need to evolve first? Both theoretical work and empirical studies of nascent sex chromosomes will help to answer these questions. However, nascent sex chromosomes are difficult to detect and dosage compensation is difficult to reveal.

Second, how many species today actually have "stable" recombination suppression? Maybe many species are in a transient phase, with different populations having different inversions that are either on their way to being fixed or starting to get counterselected. The models have now shown us some possibilities qualitatively but can they actually be quantified to be able to fit the data and to predict whether an observed case of recombination suppression is transient or stable? 

The debate will continue, and we need the active contribution of theoretical biologists to help clarify the underlying hypotheses of the proposed mechanisms. 

Conflict of interest statement: I did co-author a manuscript with D. Roze in 2023, but do not consider this a conflict of interest. The manuscript is the product of discussions that have taken place in a large consortium mainly in 2019. It furthermore deals with an entirely different topic of evolutionary biology.

References

Jay P, Tezenas E, Véber A, and Giraud T. (2022) Sheltering of deleterious mutations explains the stepwise extension of recombination suppression on sex chromosomes and other supergenes. PLoS Biol.;20:e3001698. https://doi.org/10.1371/journal.pbio.3001698
 
Lenormand T and Roze D. (2022) Y recombination arrest and degeneration in the absence of sexual dimorphism. Science;375:663-6. https://doi.org/10.1126/science.abj1813
 
Lenormand T and Roze D. (2024) Can mechanistic constraints on recombination reestablishment explain the long-term maintenance of degenerate sex chromosomes? bioRxiv, ver. 5 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2023.02.17.528909

Two evolutionary processes have been shown in theory to enhance the effects of natural selection in purging deleterious mutations from a population (here ""natural"" selection is defined as ""selection other than sexual selection""). First, inbreeding, especially self-fertilization, facilitates the removal of deleterious recessive alleles, the effects of which are largely hidden from selection in heterozygotes when mating is random. Second, sexual selection can facilitate the removal of deleterious alleles of arbitrary dominance, with little or no demographic cost, provided that deleterious effects are greater in males than in females (""genic capture""). Inbreeding (especially selfing) and sexual selection are often negatively correlated in nature. Empirical tests of the role of sexual selection in purging deleterious mutations have been inconsistent, potentially due to the positive relationship between sexual selection and intersexual genetic conflict.
In their preprint, Noël et al. [1] report a cleverly designed, and impressively long-term, experimental evolution study designed to tease apart the relative contributions of selfing and sexual selection in purging deleterious mutations, using the self-compatible hermaphroditic snail Physa acuta. Hermaphroditism relieves at least some of the potential conflict between males and females because each individual expresses traits of each sex. The authors report a 50-generation (ten years!) evolution experiment with four experimental treatments: Control (C), in which snails reproduced by mass mating (allowing sexual selection) and the next generation was sampled randomly from offspring in proportion to maternal family size; Male-selection (M) in which snails reproduced by mass mating but maternal family size was held constant, removing the opportunity for fertility selection; Female fertility selection (F) in which snails mated monogamously but fertility selection was imposed, and selfing (S), in which snails reproduced by selfing every other generation, alternating with monogamy + fertility selection. Juvenile survival was taken as the proxy for fitness and was measured for offspring of self-fertilization and of outcross matings. Each line type (C, M, F, S) was replicated twice.
The results are enviably clear-cut: after 50 generations of evolution, outcross fitness dropped precipitously in the F treatment (monogamy+female fertility selection) and remained at ancestral levels in the other three treatments. Clearly, sexual selection in males is more efficient at purging deleterious alleles than is female fertility selection. Similarly, inbreeding depression was reduced in the S lines relative to the other treatments, indicating that, unsurprisingly, deleterious recessive mutations of large effect are purged under strong inbreeding. Outcross fitness in the S lines did not decline, in contrast to the F lines, which indicates that deleterious mutations are on average slightly recessive.
Taken as a whole, this study by Noël et al. [1] provides a compelling empirical demonstration of the efficacy of both sexual selection and strong inbreeding as mechanisms of purging, and implicates sexual conflict as a potentially important factor in studies in which relaxation of sexual selection fails to result in purging.

References

[1] Noël, E., Fruitet, E., Lelaurin, D., Bonel, N., Segard, A., Sarda, V., Jarne, P., & David P. (2018). Sexual selection and inbreeding: two efficient ways to limit the accumulation of deleterious mutations. bioRxiv, 273367, ver. 3 recommended and peer-reviewed by PCI Evol Biol. doi: 10.1101/273367

Accurate information flow is central to living systems. The continuity of genomes through generations as well as the reproducible functioning and survival of the individual organisms require a faithful information transfer during replication, transcription and translation. The differential efficiency of natural selection against “mistakes” results in decreasing fidelity rates for replication, transcription and translation. At each level in the information flow chain (replication, transcription, translation), numerous complex molecular systems have evolved and been selected for preventing, identifying and, when possible, correcting or removing such “mistakes” arising during information transfer.

However, fidelity cannot be improved ad infinitum. First, because of the limits imposed by the physical nature of the processes of copying and recoding information over different molecular supports: all mechanisms ensuring fidelity during biological information transfer ultimately rely on chemical kinetics and thermodynamics. The more accurate a copying process is, the lower the synthesis rate and the higher the energetic cost of correcting errors. Second, because of the limits imposed by random genetic drift: natural selection cannot effectively act on an allele that contributes with a small differential advantage unless effective population size is large. If s <1/Ne (or s <1/(2Ne) in diploids) the allele frequency in the population is de facto subject to neutral drift processes.

In their preprint “Random genetic drift sets an upper limit on mRNA splicing accuracy in metazoans”, Bénitière, Necsulea and Duret explore the validity of this last mentioned “drift barrier” hypothesis for the case study of alternative splicing diversity in eukaryotes (Bénitière et al. 2022). Splicing refers to an ensemble of eukaryotic molecular processes mediated by a large number of proteins and ribonucleoproteins and involving nucleotide sequence recognition, that uses as a molecular substrate a precursor messenger RNA (mRNA), directly transcribed from the DNA, and produces a mature mRNA by removing introns and joining exons (Chow et al. 1977). Alternative splicing refers to the case in which different molecular species of mature mRNAs can be produced, either by cis-splicing processes acting on the same precursor mRNA, e.g. by varying the presence/absence of different exons or by varying the exon-exon boundaries, or by trans-splicing processes, joining exons from different precursor mRNA molecules.

The diversity of mRNA molecular species generated by alternative splicing enlarges the molecular phenotypic space that can be generated from the same genotype. In humans, alternative splicing occurs in around 95% of the ca. 20,000 genes, resulting in ca. 100,000 medium-to-high abundance transcripts (Pan et al. 2008). In multicellular organisms, the frequency of alternatively spliced mRNAs varies between tissues and across ontogeny, often in a switch-like pattern (Wang et al. 2008). In the molecular and cell biology community, it is commonly accepted that splice variants contribute with specific functions (Marasco and Kornblihtt 2023) although there exists a discussion around the functional nature of low-frequency splice variants (see for instance the debate between Tress et al. 2017 and Blencowe 2017). The origin, diversity, regulation and evolutionary advantage of alternative splicing constitutes thus a playground of the selectionist-neutralist debate, with one extreme considering that most splice variants are mere “mistakes” of the splicing process (Pickrell et al. 2010), and the other extreme considering that alternative splicing is at the core of complexity in multicellular organisms, as it increases the genome coding potential and allows for a large repertoire of cell types (Chen et al. 2014).

In their manuscript, Bénitière, Necsulea and Duret set the cursor towards the neutralist end of the gradient and test the hypothesis of whether the high alternative splice rate in “complex” organisms corresponds to a high rate of splicing “mistakes”, arising from the limit imposed by the drift barrier effect on the power of natural selection to increase accuracy (Bush et al. 2017). In their preprint, the authors convincingly show that in metazoans a fraction of the variation of alternative splicing rate is explained by variation in proxies of population size, so that species with smaller Ne display higher alternative splice rates. They communicate further that abundant splice variants tend to preserve the reading frame more often than low-frequency splice variants, and that the nucleotide splice signals in abundant splice variants display stronger evidence of purifying selection than those in low-frequency splice variants. From all the evidence presented in the manuscript, the authors interpret that “variation in alternative splicing rate is entirely driven by variation in the efficacy of selection against splicing errors”.

The authors honestly present some of the limitations of the data used for the analyses, regarding i) the quality of the proxies used for Ne (i.e. body length, longevity and dN/dS ratio); ii) the heterogeneous nature of the RNA sequencing datasets (full organisms, organs or tissues; different life stages, sexes or conditions); and iii) mostly short RNA reads that do not fully span individual introns. Further, data from bacteria do not verify the herein communicated trends, as it has been shown that bacterial species with low population sizes do not display higher transcription error rates (Traverse and Ochman 2016). Finally, it will be extremely interesting to introduce a larger evolutionary perspective on alternative splicing rates encompassing unicellular eukaryotes, in which an intriguing interplay between alternative splicing and gene duplication has been communicated (Hurtig et al. 2020).

The manuscript from Bénitière, Necsulea and Duret makes a significant advance to our understanding of the diversity, the origin and the physiology of post-transcriptional and post-translational mechanisms by emphasising the fundamental role of non-adaptive evolutionary processes and the upper limits to splicing accuracy set by genetic drift.

References

Bénitière F, Necsulea A, Duret L. 2023. Random genetic drift sets an upper limit on mRNA splicing accuracy in metazoans. bioRxiv, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.12.09.519597 

Blencowe BJ. 2017. The Relationship between Alternative Splicing and Proteomic Complexity. Trends Biochem Sci 42:407–408. https://doi.org/10.1016/j.tibs.2017.04.001

Bush SJ, Chen L, Tovar-Corona JM, Urrutia AO. 2017. Alternative splicing and the evolution of phenotypic novelty. Philos Trans R Soc Lond B Biol Sci 372:20150474. https://doi.org/10.1098/rstb.2015.0474

Chen L, Bush SJ, Tovar-Corona JM, Castillo-Morales A, Urrutia AO. 2014. Correcting for differential transcript coverage reveals a strong relationship between alternative splicing and organism complexity. Mol Biol Evol 31:1402–1413. https://doi.org/10.1093/molbev/msu083

Chow LT, Gelinas RE, Broker TR, Roberts RJ. 1977. An amazing sequence arrangement at the 5’ ends of adenovirus 2 messenger RNA. Cell 12:1–8. https://doi.org/10.1016/0092-8674(77)90180-5

Hurtig JE, Kim M, Orlando-Coronel LJ, Ewan J, Foreman M, Notice L-A, Steiger MA, van Hoof A. 2020. Origin, conservation, and loss of alternative splicing events that diversify the proteome in Saccharomycotina budding yeasts. RNA 26:1464–1480. https://doi.org/10.1261/rna.075655.120

Marasco LE, Kornblihtt AR. 2023. The physiology of alternative splicing. Nat Rev Mol Cell Biol 24:242–254. https://doi.org/10.1038/s41580-022-00545-z

Pan Q, Shai O, Lee LJ, Frey BJ, Blencowe BJ. 2008. Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing. Nat Genet 40:1413–1415. https://doi.org/10.1038/ng.259

Pickrell JK, Pai AA, Gilad Y, Pritchard JK. 2010. Noisy splicing drives mRNA isoform diversity in human cells. PLoS Genet 6:e1001236. https://doi.org/10.1371/journal.pgen.1001236

Traverse CC, Ochman H. 2016. Conserved rates and patterns of transcription errors across bacterial growth states and lifestyles. Proc Natl Acad Sci U S A 113:3311–3316. https://doi.org/10.1073/pnas.1525329113

Tress ML, Abascal F, Valencia A. 2017. Alternative Splicing May Not Be the Key to Proteome Complexity. Trends Biochem Sci 42:98–110. https://doi.org/10.1016/j.tibs.2016.08.008

Wang ET, Sandberg R, Luo S, Khrebtukova I, Zhang L, Mayr C, Kingsmore SF, Schroth GP, Burge CB. 2008. Alternative isoform regulation in human tissue transcriptomes. Nature 456:470–476. https://doi.org/10.1038/nature07509

Understanding factors explaining both intra and interspecific variation in susceptibility to infection by parasites remains a key question in evolutionary biology. Within a species variation in susceptibility is often explained by differences in behaviour affecting exposure to infection and/or resistance affecting the degree by which parasite growth is controlled (Roy & Kirchner, 2000, Behringer et al., 2000). This can vary between the sexes (Kelly et al., 2018) and may be explained by the ability of a parasite to attack different organs or tissues (Brierley et al., 2019). However, what goes on within one species is not always relevant to another, making it unclear when patterns can be scaled up and generalised across species. This is also important to understand when parasites may jump hosts, or identify species that may be susceptible to a host jump (Longdon et al., 2015). Phylogenetic distance between hosts is often an important factor explaining susceptibility to a particular parasite in plant and animal hosts (Gilbert & Webb, 2007, Faria et al., 2013). 

In two separate experiments, Roberts and Longdon (Roberts & Longdon, 2022) investigated how sex and tissue tropism affected variation in the load of Drosophila C Virus (DCV) across multiple Drosophila species. DCV load has been shown to correlate positively with mortality (Longdon et al., 2015). Overall, they found that load did not vary between the sexes; within a species males and females had similar DCV loads for 31 different species. There was some variation in levels of DCV growth in different tissue types, but these too were consistent across males for 7 species of Drosophila. Instead, in both experiments, host phylogeny or interspecific variation, explained differences in DCV load with some species being more infected than others. 

This study is neat in that it incorporates and explores simultaneously both intra and interspecific variation in infection-related life-history traits which is not often done (but see (Longdon et al., 2015, Imrie et al., 2021, Longdon et al., 2011, Johnson et al., 2012). Indeed, most studies to date explore either inter-specific differences in susceptibility to a parasite (it can or can’t infect a given species) (Davies & Pedersen, 2008, Pfenning-Butterworth et al., 2021) or intra-specific variability in infection-related traits (infectivity, resistance etc.) due to factors such as sex, genotype and environment (Vale et al., 2008, Lambrechts et al., 2006). This work thus advances on previous studies, while at the same time showing that sex differences in parasite load are not necessarily pervasive. 

References

Behringer DC, Butler MJ, Shields JD (2006) Avoidance of disease by social lobsters. Nature, 441, 421–421. https://doi.org/10.1038/441421a

Brierley L, Pedersen AB, Woolhouse MEJ (2019) Tissue tropism and transmission ecology predict virulence of human RNA viruses. PLOS Biology, 17, e3000206. https://doi.org/10.1371/journal.pbio.3000206

Davies TJ, Pedersen AB (2008) Phylogeny and geography predict pathogen community similarity in wild primates and humans. Proceedings of the Royal Society B: Biological Sciences, 275, 1695–1701. https://doi.org/10.1098/rspb.2008.0284

Faria NR, Suchard MA, Rambaut A, Streicker DG, Lemey P (2013) Simultaneously reconstructing viral cross-species transmission history and identifying the underlying constraints. Philosophical Transactions of the Royal Society B: Biological Sciences, 368, 20120196. https://doi.org/10.1098/rstb.2012.0196

Gilbert GS, Webb CO (2007) Phylogenetic signal in plant pathogen–host range. Proceedings of the National Academy of Sciences, 104, 4979–4983. https://doi.org/10.1073/pnas.0607968104

Imrie RM, Roberts KE, Longdon B (2021) Between virus correlations in the outcome of infection across host species: Evidence of virus by host species interactions. Evolution Letters, 5, 472–483. https://doi.org/10.1002/evl3.247

Johnson PTJ, Rohr JR, Hoverman JT, Kellermanns E, Bowerman J, Lunde KB (2012) Living fast and dying of infection: host life history drives interspecific variation in infection and disease risk. Ecology Letters, 15, 235–242. https://doi.org/10.1111/j.1461-0248.2011.01730.x

Kelly CD, Stoehr AM, Nunn C, Smyth KN, Prokop ZM (2018) Sexual dimorphism in immunity across animals: a meta-analysis. Ecology Letters, 21, 1885–1894. https://doi.org/10.1111/ele.13164

Lambrechts L, Chavatte J-M, Snounou G, Koella JC (2006) Environmental influence on the genetic basis of mosquito resistance to malaria parasites. Proceedings of the Royal Society B: Biological Sciences, 273, 1501–1506. https://doi.org/10.1098/rspb.2006.3483

Longdon B, Hadfield JD, Day JP, Smith SCL, McGonigle JE, Cogni R, Cao C, Jiggins FM (2015) The Causes and Consequences of Changes in Virulence following Pathogen Host Shifts. PLOS Pathogens, 11, e1004728. https://doi.org/10.1371/journal.ppat.1004728

Longdon B, Hadfield JD, Webster CL, Obbard DJ, Jiggins FM (2011) Host Phylogeny Determines Viral Persistence and Replication in Novel Hosts. PLOS Pathogens, 7, e1002260. https://doi.org/10.1371/journal.ppat.1002260

Pfenning-Butterworth AC, Davies TJ, Cressler CE (2021) Identifying co-phylogenetic hotspots for zoonotic disease. Philosophical Transactions of the Royal Society B: Biological Sciences, 376, 20200363. https://doi.org/10.1098/rstb.2020.0363

Roberts KE, Longdon B (2023) Heterogeneities in infection outcomes across species: examining sex and tissue differences in virus susceptibility. bioRxiv 2022.11.01.514663, ver. 2 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.11.01.514663 

Roy BA, Kirchner JW (2000) Evolutionary Dynamics of Pathogen Resistance and Tolerance. Evolution, 54, 51–63. https://doi.org/10.1111/j.0014-3820.2000.tb00007.x

Vale PF, Stjernman M, Little TJ (2008) Temperature-dependent costs of parasitism and maintenance of polymorphism under genotype-by-environment interactions. Journal of Evolutionary Biology, 21, 1418–1427. https://doi.org/10.1111/j.1420-9101.2008.01555.x