Massive Parallel Regression: A Précis of Genetic Mechanisms for Vision Loss in Diving Beetles

Massive Parallel Regression: A Précis of Genetic Mechanisms for Vision Loss in Diving Beetles Abstract Two tribes of subterranean dytiscid diving beetles independently colonized groundwater systems of the Western Australian arid zone, a habitat transition that was most likely driven by the contraction of surface water bodies following late Neogene aridification of the Australian continent. These “stygofauna” are now trapped within discrete calcrete aquifers that have formed in paleodrainage valleys, resulting in the world’s most diverse radiations of subterranean dytiscid beetles. Approximately 100 species from three genera exhibit partial or fully regressed visual systems and are essentially blind. This unique study system, with multiple independent transitions to subterranean life enables regressive and adaptive evolutionary processes to be studied in parallel at an unheralded comparative scale. Here we provide an overview of the progression of dytiscid beetle research and undertake a literature survey of published research within the field of regressive evolution as it applies to eye loss. We detail our exploration of insect vision genes for signatures of adaptive and neutral evolutionary mechanisms related to eye regression, largely within photoreceptor and eye pigment genes. Our project makes use of transcriptome data from five representative dytiscid beetle species (two surface and three subterranean) in order to design a customized set of RNA baits for use in a hybrid-capture method to target a pool of vision genes sequenced using high-throughput Illumina platforms. This methodological design permits the assessment of modifications in the genomic sequence of beetle vision genes at a much broader scale than Sanger sequencing, enabling a higher number of both target species and genes to be simultaneously assessed relative to research time-investments. Based on our literature search criteria of the research field (“regressive evolution” + “eyes”), 81 papers have been published since the late 1980s accruing an h-index of 27 and a mean citation rate of 24.57. Collective annual citations for this field of research have surged over the past 5 years, an indication that broader scientific community interest is gaining momentum. The majority of publications (75%) have focused on the chordate clade Actinopterygii. Historically, research on variant subterranean taxa has faced difficulties inferring the evolutionary mechanisms of eye regression (and vision loss) using molecular approaches because only a handful of target genes could be feasibly addressed within grant funding cycles. From a comparative phylogenetic perspective, next-generation sequencing approaches applied to stygobiontic dytiscid beetles hold the potential to greatly improve our understanding of the genetic mechanisms underlying regressive evolution generally. Introduction Evolution is often perceived as a process of progressive refinement or improvement, which may explain why the regressive loss of functional phenotypic traits persists as one of evolutionary biology’s most notably anomalies. The evolutionary loss of vision is particularly intriguing because the Paleozoic origin of eyes is posited to have had a catalytic evolutionary impact leading to the explosion of animal diversity in the Cambrian (Parker 1998, 2011). Understanding the fitness advantages of the reduction and loss of eyes in aphotic (lightless) environments, where vision appears to serve no selective advantage, makes intuitive theoretical sense. Yet the establishment of a unilateral empirically supported Neo-Darwinian mechanistic explanation for regressive evolution remains elusive and continues to generate vigorous debate. Stygofauna are cave-dwelling animals that are dark-adapted and live in groundwater—the prefix “stygo” derives from the Greek mythological underworld river Styx. Courtesy of their natural history, a complex of stygobiontic dytiscid water beetles may provide unique opportunities to help solve one of evolutionary biology’s greatest riddles—the long-term consequences to the genome that result from regressive evolution. The subterranean diving beetles of the Australian arid zone represent an unusual group of organisms for understanding the proximate factors of regressive evolution, because their natural history is notably different to the majority of animal systems that have been used to explore the loss of eyes and vision generally. Their evolutionary history involved recurrent independent colonizations of disjunct groundwater habitats by a relatively small number of geographically widespread species inhabiting either bodies of surface-water or interstitial niches at the groundwater/surface-water interface (Leys et al 2003; Leijs et al 2012; Watts et al. 2016). From a comparative evolutionary perspective, these repeated entries into a novel niche collectively provide a large number of independent contrasts between photic and aphotic lineages with inherent statistical power. There are numerous cases of sympatric sister species that potentially evolved from a stygobiontic common ancestor within the calcrete aquifer, allowing an assessment of genomic changes (shared among the sister taxa) in the very early phase of colonization of, and evolution within, the calcretes. The recent application of high-throughput sequence tools, combined with the relatively detailed understanding of the physiology and evolutionary development of eyes and their genetic underpinnings, therefore permits a rigorous and integrative approach to one of the enduring quandaries in evolutionary biology (Dobzhansky 1970; Culver and Wilkens 2000; Porter and Crandall 2003; Jeffery 2009; Romero 2009; Wilkens 2010). Many of the vanguard of this new phase of technologically empowered research are represented in the current issue of this publication (W. R. Jeffery; J. L. Pérez-Moreno; M. L. Porter; M. Protas; A. S. Riviera; D. B. Stern and K. A. Crandall; L. H. Sumner-Rooney), and in particular Friedrich (2013a) whom opined that we have now entered the era of Speleogenomics (derived from the Greek “spēlaion” for cave). Current research on Australian dytiscid beetles (Coleoptera: Dytiscidae: Bidessini, Hydroporini) is concerned with the genomic-level interrogation of a broad swathe of genes related to invertebrate phototransduction (Tierney et al. 2012, 2015, 2017). The specific objective is to make use of the aforementioned natural experiment by comparing the molecular structure and expression patterns of focal genes among phylogenetically related surface and subterranean species. Namely, have these genes accumulated mutations that would lead to a loss of function in the translated proteins (i.e., major deletions, frameshift mutations, stop codons, or elevated rates of amino acid substitutions) or, in the extreme case, completely excised the functional vision genes present in their closest surface relatives? Our core interest is whether any identified differences can meaningfully inform our understanding of the mechanistic process of regression from Neo-Darwinian perspectives of direct natural selection, indirect pleiotropic selection, or an absence of selection (neutral theory); and if neutral processes are at play, how many genes can actually evolve by neutral processes, when they may have other pleiotropic functions not related to vision. A further goal is to make inroads toward a truly integrative understanding of organismal biology and evolutionary fitness (reviewed by Tierney et al. 2017). That is, can the change in light environment experienced by an organism be interconnected with structural (both genetic and phenotypic) and behavioral variation when contrasted with closely related organisms obligatorily inhabiting discretely different photic niches—ideally, bright daylight versus a complete absence of light, or gradations thereof. Evolutionary transitions in light environment Speciation is often driven by a change in the physical environment leading to the creation of a novel habitat that is colonized by organisms, which subsequently adapt to and diversify within their new surrounds, as exemplified by adaptive radiations (e.g., Seehausen et al. 2008). The regressive evolution of eyes and eventual loss of vision is predominantly driven by a transition in photic environment, moving from a brightly lit to dim-light to completely aphotic environments. Regressive evolution is typically associated with shallow subterranean (<10 m) and cave dwelling organisms, and the field of biospeleology (White and Culver 2012; Culver and Pipan 2014). Cave biologists often delineate these variant light environments into discrete photic zones, beginning at the cave “entrance zone” through a series of transitional and increasingly dimmer light zones and culminating in the “dark zone,” the deep regions of a cave wherein there is a complete absence of light in addition to relatively constant temperature and humidity levels that are less affected by surface climate variation (e.g., Howarth 1980). Similar parallels can be drawn with transitional light environments at different depths of the water column (e.g., disphotic zone receives light that is insufficient for plants to photosynthesize), as well as transitions from diurnal to nocturnal behavioral activity (Tierney et al. 2017). It is important to note that the Australian calcrete aquifers occupied by dytiscid beetles are currently isolated from the surface (no cave entrances and no surface connectivity post-colonization) and are therefore aphotic both above and below the cave water column (Humphreys 2006, 2008). These limestone depositions (explained in greater detail below—Unusual Study System section) are relatively shallow (up to 10 m below the surface) compared with most other cave systems. It is plausible that individual calcretes may be subject to surface cracking which would then subject them to light environment categorization akin to Howarth’s (1980) zonations. In the majority of cases the stygobiontic beetles are assumed to have evolved in complete darkness, however, it is possible that the beetles may have evolved initially in interstitial environments (e.g., gravels in ephemeral river or creek systems), as evident for several other dytiscid species in Australia (e.g., Watts et al. 2016). The finding of negative-phototactic behavior in the stygobiontic species Paroster macrosturtensis (Langille et al. 2018; Fig. 1) may be representative of a behavior that has been retained by chance from an ancestral interstitial species. Fig. 1 View largeDownload slide Subterranean beetle sister species triplet. Exemplar of a recurrent diversification pattern wherein multiple stygobiontic species, most commonly triplets, are restricted within isolated calcrete aquifers situated in ancient paleodrainage valleys of the western Australian arid zone. Paroster Sharp (Dytiscidae: Hydroporini) species nomens from left to right: P. macrosturtensis, P. mesosturtensis, and P. microsturtensis (Watts and Humphreys 2006, 2009; Leys and Watts 2008). Photo credit: Chris Watts and Howard Hamon, South Australian Museum. Fig. 1 View largeDownload slide Subterranean beetle sister species triplet. Exemplar of a recurrent diversification pattern wherein multiple stygobiontic species, most commonly triplets, are restricted within isolated calcrete aquifers situated in ancient paleodrainage valleys of the western Australian arid zone. Paroster Sharp (Dytiscidae: Hydroporini) species nomens from left to right: P. macrosturtensis, P. mesosturtensis, and P. microsturtensis (Watts and Humphreys 2006, 2009; Leys and Watts 2008). Photo credit: Chris Watts and Howard Hamon, South Australian Museum. Movile cave in Romania is the only other comparable cave system under study, with regard to the nature of discrete pockets of calcrete that contain groundwater and lack surface connections. These systems differ from the Australian calcretes, in that they are outlets for hydrothermal fluids that react with cave substrates to produce nutrients incorporated by chemolithotrophic bacteria—which in turn supply a primary nutrient source for the resident cave invertebrates (Kumaresan et al. 2014). Taxonomic groups used for the study of regressive evolution We undertook a survey of the primary literature for animal study systems that have been used to explore the regressive evolution of eyes. We searched the electronic database Web of Science v5.28 Core Collection (Clarivate Analytics—accessed March 2018) using the Basic Search option with the Topic term: “regressive evolution.” We then restricted output to Articles, Proceedings Papers, and Meeting Abstracts published over the last 100 years (1919–2018), excluded physical and social science categories, and refined the remaining publications for the term “eyes.” Our search returned 81 publications that have been cited 1990 times (mean = 24.57 ± s.e. 3.01; absolute maximum citation = 122; research field citation h-index = 27). Collective annual citations of the field remained below 50 per year until 2006, but then increase considerably peaking at more than 300 per annum in 2016 (Fig. 2; Supplementary Table S1), suggesting that neo-Darwinian interest in the field is gaining momentum. Citations derive from the following scientific fields: Evolutionary Biology (38.3%), Genetics Heredity (25.9%), Ecology (21%), Multidisciplinary Sciences (17.2%), Zoology (17.2%), Developmental Biology (16%), and Biochemistry Molecular Biology (12.3%); which constitute Web of Science Categories with at least 10 entries. The majority of publications arose from research laboratories in the Americas (United States of America 55.6%, Mexico 4.9%, Canada 3.9%), Europe (Germany 25.9%, England 8.6%, France 4.9%, Austria 3.7%, Switzerland 3.7%), Australia (4.9%), and People's Republic of China (3.7%). Table 1 summarizes publications by taxonomic classification (class, order, family, and common name) for taxa listed in titles or abstracts of the 81 surveyed publications. The table indicates whether high-throughput sequencing techniques have been applied to these study systems; we also listed cases where parallel sequencing results were screened post hoc, or the potential of genomic application has been reviewed (all respective studies are cited in the legend of Table 1). Under our search filters, publications arose in 1988 and are predominantly focused on chordates (Actinopterygii comprise 75% of all publications), and aside from work on spring- and cave-dwelling amphipods, it is not until about 2000 that invertebrate studies begin to appear in the literature (Table 1 and Supplementary Table S1). We should note that known studies on fruit fly and cholevid carrion beetles did not appear in our refined publication list and two papers that were included (on acari and hominids) do not appear to relate specifically to eye regression per se. Table 1. Taxa used to investigate regression of animal eyes over the last 100 years Classification Common name Year published (number per year) Parallel sequencing Arthropoda  Arachnida   Trombidiformes    Tetranychidae Spider mite 1998  Insecta    Coleoptera     Carabidae Ground beetles 2016     Dytiscidae Diving beetles 2015a Transcriptomics 2005    Orthoptera   Rhaphidophoridae Cave camel cricket 2013b Review  Malacostraca   Amphipoda    Gammaridae Spring/cave amphipod 1994 1992    Paramelitidae Subterranean amphipod 2007    Hyalidae Subterranean amphipod 2007   Decapoda    Cambaridae Cave crayfish 2005    Gecarcinucidae Cave crabs 2013   Isopoda    Asellidae Cave isopod 2011  Trilobita   Ptychopariida    Conocoryphidae Blind trilobites 2003 Chordata  Actinopterygii   Characiformes    Characidae Mexican cavefish 2017 (5)c Transcriptomics 2016 (2) 2015 (2) 2014 (2) 2013 (6) Transcriptomics, review 2012 (2)b, d 2011 2009 (3) 2008 (3) 2007 (2) 2006 (2) 2005 2004 2002 1998 (2) 1997 1995 1993 (2) 1998   Cypriniformes    Cyprinidae Omani cavefish 2017 2011 2009 Somalian cavefish 2016 2015 Golden line fish 2016e Genomics 2013 (4)f Transcriptomics    Nemacheilidae Murangi ray-finned fish 2013b Review   Cyprinodontiformes    Poeciliidae Atlantic cave molly 2010 2009 2008 (2) 2007 2006 2001   Percopsiformes    Amblyopsidae Amblyopsid cavefish 2011   Siluriformes    Ictaluridae Blind catfish 1993    Loricariidae Cave armored catfish 2009  Amphibia   Caudata    Proteidae Olm salamander 2013b Review 2001  Aves   Apterygiformes    Apterygidae Kiwi 2007  Mammalia   Afrosoricida   Chrysochloridae Cape golden mole 2014g Post hoc screen   Soricomorpha    Talpidae Star nose-mole 2014g Post hoc screen   Primates    Hominidae Humans 2005   Rodentia    Bathyergidae Naked mole-rat 2014g Post hoc screen 2004    Spalacidae Blind mole-rat 2002 1990 Mollusca  Gastropoda   Vetigastropoda    Solariellidae Marine snails 2016 Classification Common name Year published (number per year) Parallel sequencing Arthropoda  Arachnida   Trombidiformes    Tetranychidae Spider mite 1998  Insecta    Coleoptera     Carabidae Ground beetles 2016     Dytiscidae Diving beetles 2015a Transcriptomics 2005    Orthoptera   Rhaphidophoridae Cave camel cricket 2013b Review  Malacostraca   Amphipoda    Gammaridae Spring/cave amphipod 1994 1992    Paramelitidae Subterranean amphipod 2007    Hyalidae Subterranean amphipod 2007   Decapoda    Cambaridae Cave crayfish 2005    Gecarcinucidae Cave crabs 2013   Isopoda    Asellidae Cave isopod 2011  Trilobita   Ptychopariida    Conocoryphidae Blind trilobites 2003 Chordata  Actinopterygii   Characiformes    Characidae Mexican cavefish 2017 (5)c Transcriptomics 2016 (2) 2015 (2) 2014 (2) 2013 (6) Transcriptomics, review 2012 (2)b, d 2011 2009 (3) 2008 (3) 2007 (2) 2006 (2) 2005 2004 2002 1998 (2) 1997 1995 1993 (2) 1998   Cypriniformes    Cyprinidae Omani cavefish 2017 2011 2009 Somalian cavefish 2016 2015 Golden line fish 2016e Genomics 2013 (4)f Transcriptomics    Nemacheilidae Murangi ray-finned fish 2013b Review   Cyprinodontiformes    Poeciliidae Atlantic cave molly 2010 2009 2008 (2) 2007 2006 2001   Percopsiformes    Amblyopsidae Amblyopsid cavefish 2011   Siluriformes    Ictaluridae Blind catfish 1993    Loricariidae Cave armored catfish 2009  Amphibia   Caudata    Proteidae Olm salamander 2013b Review 2001  Aves   Apterygiformes    Apterygidae Kiwi 2007  Mammalia   Afrosoricida   Chrysochloridae Cape golden mole 2014g Post hoc screen   Soricomorpha    Talpidae Star nose-mole 2014g Post hoc screen   Primates    Hominidae Humans 2005   Rodentia    Bathyergidae Naked mole-rat 2014g Post hoc screen 2004    Spalacidae Blind mole-rat 2002 1990 Mollusca  Gastropoda   Vetigastropoda    Solariellidae Marine snails 2016 Results are systematically categorized by class, order/clade, family, and common name and qualifies whether high-throughput parallel sequencing studies have been initiated, namely: a, Tierney et al. (2015); b, Friedrich (2013); c, Stahl and Gross (2017); d, Gross et al. (2013); e, Yang et al. (2016); f, Meng et al. (2013); g, Emerling and Springer (2014). Source data are provided in Supplementary Table S1. Table 1. Taxa used to investigate regression of animal eyes over the last 100 years Classification Common name Year published (number per year) Parallel sequencing Arthropoda  Arachnida   Trombidiformes    Tetranychidae Spider mite 1998  Insecta    Coleoptera     Carabidae Ground beetles 2016     Dytiscidae Diving beetles 2015a Transcriptomics 2005    Orthoptera   Rhaphidophoridae Cave camel cricket 2013b Review  Malacostraca   Amphipoda    Gammaridae Spring/cave amphipod 1994 1992    Paramelitidae Subterranean amphipod 2007    Hyalidae Subterranean amphipod 2007   Decapoda    Cambaridae Cave crayfish 2005    Gecarcinucidae Cave crabs 2013   Isopoda    Asellidae Cave isopod 2011  Trilobita   Ptychopariida    Conocoryphidae Blind trilobites 2003 Chordata  Actinopterygii   Characiformes    Characidae Mexican cavefish 2017 (5)c Transcriptomics 2016 (2) 2015 (2) 2014 (2) 2013 (6) Transcriptomics, review 2012 (2)b, d 2011 2009 (3) 2008 (3) 2007 (2) 2006 (2) 2005 2004 2002 1998 (2) 1997 1995 1993 (2) 1998   Cypriniformes    Cyprinidae Omani cavefish 2017 2011 2009 Somalian cavefish 2016 2015 Golden line fish 2016e Genomics 2013 (4)f Transcriptomics    Nemacheilidae Murangi ray-finned fish 2013b Review   Cyprinodontiformes    Poeciliidae Atlantic cave molly 2010 2009 2008 (2) 2007 2006 2001   Percopsiformes    Amblyopsidae Amblyopsid cavefish 2011   Siluriformes    Ictaluridae Blind catfish 1993    Loricariidae Cave armored catfish 2009  Amphibia   Caudata    Proteidae Olm salamander 2013b Review 2001  Aves   Apterygiformes    Apterygidae Kiwi 2007  Mammalia   Afrosoricida   Chrysochloridae Cape golden mole 2014g Post hoc screen   Soricomorpha    Talpidae Star nose-mole 2014g Post hoc screen   Primates    Hominidae Humans 2005   Rodentia    Bathyergidae Naked mole-rat 2014g Post hoc screen 2004    Spalacidae Blind mole-rat 2002 1990 Mollusca  Gastropoda   Vetigastropoda    Solariellidae Marine snails 2016 Classification Common name Year published (number per year) Parallel sequencing Arthropoda  Arachnida   Trombidiformes    Tetranychidae Spider mite 1998  Insecta    Coleoptera     Carabidae Ground beetles 2016     Dytiscidae Diving beetles 2015a Transcriptomics 2005    Orthoptera   Rhaphidophoridae Cave camel cricket 2013b Review  Malacostraca   Amphipoda    Gammaridae Spring/cave amphipod 1994 1992    Paramelitidae Subterranean amphipod 2007    Hyalidae Subterranean amphipod 2007   Decapoda    Cambaridae Cave crayfish 2005    Gecarcinucidae Cave crabs 2013   Isopoda    Asellidae Cave isopod 2011  Trilobita   Ptychopariida    Conocoryphidae Blind trilobites 2003 Chordata  Actinopterygii   Characiformes    Characidae Mexican cavefish 2017 (5)c Transcriptomics 2016 (2) 2015 (2) 2014 (2) 2013 (6) Transcriptomics, review 2012 (2)b, d 2011 2009 (3) 2008 (3) 2007 (2) 2006 (2) 2005 2004 2002 1998 (2) 1997 1995 1993 (2) 1998   Cypriniformes    Cyprinidae Omani cavefish 2017 2011 2009 Somalian cavefish 2016 2015 Golden line fish 2016e Genomics 2013 (4)f Transcriptomics    Nemacheilidae Murangi ray-finned fish 2013b Review   Cyprinodontiformes    Poeciliidae Atlantic cave molly 2010 2009 2008 (2) 2007 2006 2001   Percopsiformes    Amblyopsidae Amblyopsid cavefish 2011   Siluriformes    Ictaluridae Blind catfish 1993    Loricariidae Cave armored catfish 2009  Amphibia   Caudata    Proteidae Olm salamander 2013b Review 2001  Aves   Apterygiformes    Apterygidae Kiwi 2007  Mammalia   Afrosoricida   Chrysochloridae Cape golden mole 2014g Post hoc screen   Soricomorpha    Talpidae Star nose-mole 2014g Post hoc screen   Primates    Hominidae Humans 2005   Rodentia    Bathyergidae Naked mole-rat 2014g Post hoc screen 2004    Spalacidae Blind mole-rat 2002 1990 Mollusca  Gastropoda   Vetigastropoda    Solariellidae Marine snails 2016 Results are systematically categorized by class, order/clade, family, and common name and qualifies whether high-throughput parallel sequencing studies have been initiated, namely: a, Tierney et al. (2015); b, Friedrich (2013); c, Stahl and Gross (2017); d, Gross et al. (2013); e, Yang et al. (2016); f, Meng et al. (2013); g, Emerling and Springer (2014). Source data are provided in Supplementary Table S1. Fig. 2 View largeDownload slide Citations of research on the regressive evolution of eyes. Line-plot of annual citations on publications over the last 100 years derived from a filtered search of the Web of Science database (accessed March 2018), using the terms “regressive evolution” + “eyes.” Fig. 2 View largeDownload slide Citations of research on the regressive evolution of eyes. Line-plot of annual citations on publications over the last 100 years derived from a filtered search of the Web of Science database (accessed March 2018), using the terms “regressive evolution” + “eyes.” Unusual study system In Western Australia, there is evidence that both the geological formation of calcrete deposition and the subsequent biological colonization of the aquifers was climate driven. Post-separation of Australia from remnant Gondwanan landmasses (Antarctica + South America), much of the continent contained expansive rainforests and freshwater lakes (Blewett 2012). As the Australian plate continued to drift northward from Antarctica a series of physical events initiated and intensified the continental aridification that is evident in the present day landscape. First, from the Oligocene to the Miocene (34–5 Mya) the continent began to experience seasonal aridity as it met with bands of subtropical high-pressure systems, in addition to periods of dry cooler climates (Antarctic ice sheets were larger and sea levels lower than present day). The second and more intense phase led to aridification of two-thirds of the continent during the Plio-Pleistocene (3 Mya to present), when ice sheets greatly expanded and forced the migration of the band of high-pressure systems into the center of the continent (Byrne et al. 2008; Fujioka and Chappell 2010). The calcrete aquifer habitats of subterranean beetles are deposited in paleodrainage valleys upstream of salt lakes in arid regions of the Australian Western Plateau. The carbonate depositions of near-surface permeable rock (the calcretes) are relatively thin (10–30 m deep) and were formed in association with groundwater by evaporative processes (Morgan 1993; Humphreys 2006; Humphreys et al. 2009). While the paleodrainage channels are ancient, the calcrete deposition is thought to have begun after the onset of continental aridification (described above) and continues to form in some arid regions with high evaporation. Epigean arthropods are thought to have colonized the aquifers within the last 8–3 million years during transient warm-wet periods with increased and widespread surface water flows (Leys et al. 2003; Humphreys 2012; Sniderman et al. 2016), which led to the repeated colonization of isolated aquifer pockets that now represent biogeographic refugia. In the Yilgarn region of Western Australia, these communities are largely comprised of crustaceans (including Amphipoda, Isopoda, Bathynellacea, Copepoda) and insects (but see the following for a fuller account of taxonomic diversity: Karanovic 2004; Cooper et al. 2007, 2008; Guzik et al. 2008; Juan et al. 2010; Abrams et al. 2012; Humphreys 2012; Karanovic and Cooper 2012). Beetles from the family Dytiscidae are commonly referred to as diving water beetles and are predatory in surface water habitats (Watts 1978; Yee 2014). The Yilgarn species comprise one of the world’s most speciose radiations, with at least 100 known subterranean species from the tribes Bidessini and Hydroporini (Balke et al. 2004). The actual number of species that are yet to be discovered and described is undoubtedly much greater, given that <25% of potential habitat has been sampled to date; the region contains more than 200 isolated calcrete aquifers that range in size from ca. 2–200 km2. The described species have been collected from 46 discrete calcrete aquifers with between one and four endemic species per calcrete and there are approximately 13 cases of sympatric sister species (Leijs et al. 2012). Figure 1 shows an exemplar of a sister species triplet from the Sturt Meadows calcrete (P. macrosturtensis, P. mesosturtensis, P. microsturtensis); such distribution in body size is common across calcretes and may represent ecological partitioning within a common niche consistent with theories of evolutionary self-organization (Vergnon et al. 2013). Figure 3b (Leijs et al. 2012) presents a species level phylogeny of the two dytiscid tribes of interest based on mitochondrial gene fragments. The precise number of subterranean colonization events is unknown, but it is assumed that relatively few surface species repeatedly colonized geographically discrete calcretes on multiple occasions (Leijs et al. 2012). There is a lack of phylogeographic structure across the landscape for most of these beetle species (i.e., no clear geographic pattern to the relationships among the subterranean species), with the exception of the sympatric sister species within calcretes. Hence, the majority of subterranean species evolved independently from widespread surface ancestors, with the Lineage-Through-Time plot (Fig. 3a) suggesting at least 30 ancestral species were most likely present prior to the radiation of the subterranean species (Leijs et al. 2012). Predaceous diving beetles constitute the most specious clade of aquatic beetles (ca. 4800 species globally), with an estimated 600 species in the Australian + Pacific region (Jäch and Balke 2008) that are assumed to have dispersed to Australia from South-East Asia (Balke and Ribera 2004). Among the described Australian taxa ca. 100 species are subterranean (Watts and Humphreys 2009). For global comparisons, less than 1% of Coleopteran fauna are estimated to inhabit subterranean environments (Tierney et al. 2017). Fig. 3 View largeDownload slide Surface and subterranean beetle speciation through time. A lineage through time plot (a) indicates the number of lineage divergence events that derive from a mitochondrial phylogeny (b) of Australian dytiscid beetles. Shaded orange rectangles indicate the estimated time period of most rapid diversification among the stygofauna. Both figures are adapted from Leijs et al. (2012). (a) Plots lineage events among surface water (black lines) and stygobiontic (red lines) beetles. (b) Presents a Bayesian inferred species-level molecular phylogenetic tree with posterior probability node support values (>0.7), that indicates: terminal branches leading to surface water beetles (black branches), stygobiontic beetles from the Yilgarn region (red branches), and stygobiontic beetles from outside of the Yilgarn region (green branches); sympatric sister species endemic to single calcrete aquifers denoted by shaded blue boxes (as exemplified in Fig. 1 species triplet Paroster microsturtensis, P. mesosturtensis, and P. macrosturtensis). Access the electronic PDF version of this article for color figure production. Fig. 3 View largeDownload slide Surface and subterranean beetle speciation through time. A lineage through time plot (a) indicates the number of lineage divergence events that derive from a mitochondrial phylogeny (b) of Australian dytiscid beetles. Shaded orange rectangles indicate the estimated time period of most rapid diversification among the stygofauna. Both figures are adapted from Leijs et al. (2012). (a) Plots lineage events among surface water (black lines) and stygobiontic (red lines) beetles. (b) Presents a Bayesian inferred species-level molecular phylogenetic tree with posterior probability node support values (>0.7), that indicates: terminal branches leading to surface water beetles (black branches), stygobiontic beetles from the Yilgarn region (red branches), and stygobiontic beetles from outside of the Yilgarn region (green branches); sympatric sister species endemic to single calcrete aquifers denoted by shaded blue boxes (as exemplified in Fig. 1 species triplet Paroster microsturtensis, P. mesosturtensis, and P. macrosturtensis). Access the electronic PDF version of this article for color figure production. Like most obligate cave dwelling arthropods these stygobiontic beetles exhibit convergent morphological phenotypes, namely: an absence of cuticle melanization and the reduction or complete loss of wings and eyes (Tierney et al. 2017). Such repetition of trait loss represents a massively parallel system that, from a quantitative evolutionary comparative perspective (Felsenstein 1985; Harvey and Pagel 1991), presents an ideal opportunity to examine the long-term consequences to the genome that result from regressive evolution. The search for genetic signatures of regression The most attractive aspect of this massively parallel evolutionary complex of beetles lies in its potential to understand regressive evolution from a genomic perspective. Although a wide range of cave animals exhibit very similar morphological convergence of traits, they generally arise from very distant phylogenetic lineages and developmental pathways that may confound a similar kind of broad scale comparison at the genomic level. In contrast, the stygobiontic bidessine and hydroporine dytiscid beetle species from the Yilgarn aquifers exhibit very similar phylogeographic histories and are descended from only a few geographically widespread ancestral epigean species (Cooper et al. 2002; Leys et al. 2003; Watts and Humphreys 2004, 2006, 2009; Leijs et al. 2012). An additional, and important, aspect of Australian dytiscid beetle natural history that relates to the genetics of regression is their age of origin and diversification. Based on mitochondrial rates of evolution (Leijs et al. 2012), subterranean lineages are estimated to have initially diverged from surface ancestors in the middle Miocene (∼13 Mya) with the majority of speciation events occurring through the late Miocene, Pliocene, and Pleistocene; however, we are unable to confidently predict the exact point along a phylogenetic branch that a particular taxon evolved underground. With this caveat in mind, the most rapid period of speciation (∼8–3 Mya) can be visualized as a lineage through time plot based on uncalibrated molecular clock rates (shaded rectangle Fig. 3a,b). This contrasts to many other cave study systems that have only diverged from surface lineages relatively recently and raises the question of how much geological time is required for genetic signatures of regressive loss to arise or be overwritten (Tierney et al. 2017). For example, research on visual photoreceptor genes of different cavefish species (Niemiller et al. 2013) found evidence that corroborated both indirect natural selection (pleiotropy) and neutral evolution (pseudogene) theories. Non-adaptive evolutionary processes require sufficient time to accrue random mutations via genetic drift in order to lose function as a result of pseudogene development. Given that this is a random process, a study system such as dytiscid beetles with multiple speciation events over considerable periods of geological time (Fig. 3) would appear to represent a suitable study-target for attempts to capture signals of deleterious mutations that nullify the function of vision related genes. Previous research employing Sanger sequencing has explored rates of evolution for the eye pigment gene cinnabar in surface and subterranean species and found increased rates of evolution among the eyeless lineages and a number of missence mutations (frameshifts and aberrant stop-codons) that are indicative of pseudogene development (Leys et al. 2005). Similar missence mutations have also been identified among opsin photoreceptor genes of Somalian and amblyopsid cave fish (Cavallari et al. 2011; Niemiller et al. 2013). However, a number of studies have identified the existence of seemingly functional visual opsin genes among cave crustaceans and fish with degenerate eyes (Langecker et al. 1993; Crandall and Hillis 1997; Carlini et al. 2013; Niemiller et al. 2013). Genomic advancement Until recently, research projects investigating the regressive loss of vision have utilized standard PCR-amplification and Sanger sequencing technology and, therefore, have been restricted to exploration of one or only a few focal genes within standard funding scheme cycles and budgets (for examples see paragraph above). However, the advent of high-throughput massively parallel sequencing technology alters this research landscape by orders of magnitude because it permits a gene-network approach for understanding functional gene evolution. The combination of technological advances with an increased frequency of co-operative research consortiums and continuing reductions in sequencing costs, both reagents and hardware, means that genomic-empowered projects are now able to be applied to a wide range of non-model organisms. This technological expansion has certainly been applied to the genetics of regression and vision generally. Not surprisingly, research that incorporates high-throughput parallel sequencing technology have only entered the research conversation within the previous 5 years (8.6% of total publications, Table 1 and Supplementary Table S1), however, given the adaptability of broad scale functional genomics to non-model systems we may expect the diversity of taxonomic groups used to study the genetics of regressive eye evolution to noticeably expand over the coming decades. From the invertebrate perspective, important foundational steps were undertaken by Friedrich (2011) and colleagues (Bao and Friedrich 2009; Friedrich et al. 2011) via the extension of an in-depth knowledge gleaned from the model-insect genomes Drosophila melanogaster (fruit fly: Adams et al. 2000) and Tribolium castaneum (red flour beetle: Jackowska et al. 2007; Richards et al. 2008), and subsequent application to the small carrion beetle Ptomophagus hirtus—a flightless troglobiont species with degenerate eyes that is endemic to Mammoth Cave (Kentucky, USA). Friedrich et al. (2011) sequenced the transcriptome of P. hirtus and identified an orthologous set of 20-phototransduction genes, 25-eye pigmentation, and 16-circadian clock genes. The regressed eyes of P. hirtus contain residual lenses and the presence of a seemingly complete set of phototransduction genes instigated ethological assays that indicated negative-phototactic abilities (Friedrich et al. 2011). The Coleopteran species studied thus far appear to possess the same core set of phototransduction genes and, therefore, presumably similar biochemical cascades as in well studied model insect species with compound eyes (e.g., D. melanogaster); light being absorbed in the rhabdomeres of photoreceptor cells by opsin molecules that initiate a neuro-electrical signal (Friedrich et al. 2011; Tierney et al. 2015, 2017). Insects typically possess trichromatic vision with opsin photoreceptor proteins sensitive to long (green) and short (blue, ultraviolet) wavelengths of the light spectrum, as well as extraretinal opsins, which together derive from four rhabdomeric-type and one ciliary-type opsin classes (Briscoe and Chittka 2001; Porter et al. 2012; Henze and Oakley 2015). A variety of beetle taxa have entirely lost one or more visual opsin gene subfamilies: blue-sensitive opsin loss in diving water beetles (Maksimovic et al. 2011; Tierney et al. 2015), red flour beetles (Jackowska et al. 2007), and jewel beetles (Lord et al. 2016); ultraviolet-sensitive loss + blue-sensitive loss in cave dwelling small carrion beetles (Friedrich et al. 2011). Many of these aforementioned beetle species inhabit aphotic or dim-light niches, however, generalities are difficult to draw with regard to convergent opsin-losses linked with transitions in photic environments because there are exceptions to the rule for beetles and other insects (see review by Feuda et al. 2016); in that both surface (diurnal, crepuscular, nocturnal) and subterranean (obligate, facultative) species variously show both losses and gains of opsin gene classes. However as intimated at the beginning of this section (The search for genetic signatures of regression), genotypic trait loss may require extensive and undetermined periods of geological time in order for a relaxation of evolutionary selective pressures to permit neutral evolution processes (missence mutations) to occur, eventually obfuscate gene function and ultimately lead to phenotypic trait loss. Therefore, if the regressive loss of traits is indeed a highly stochastic process, then a lack of broad sweeping general rules across phylogenetically distant lineages may well be expected, and the importance of studying groups that enable robust genome-level comparative assessments among close phylogenetic relatives becomes paramount. Friedrich’s research set an outstanding benchmark that our research group adopted in order to identify candidate vision genes from transcriptome data that were subsequently used to design baits for targeted capture. We applied an in-solution hybrid-capture sequencing method that provisionally followed established methods (Mamanova et al. 2010; Lemmon et al. 2012; Lemmon and Lemmon 2013; Li et al. 2013), and enabled us to customize a targeted set of candidate genes to assess vision loss among the Australian stygobiontic dytiscid beetles. Our initial aim was to qualitatively identify protein coding genes related to vision that were expressed (i.e., transcribed) in surface lineages, but lacked expression in subterranean lineages. Simple presence or absence of expression would then provide grounds for subsequent comparative exploration of genomic DNA to assess whether adaptive (natural selection) or non-adaptive (neutral) evolution has rendered any of these genes non-functional and contributed to the regressive evolution of eyes in stygofauna. A simplified representation of our methodological workflow is provided in Fig. 4; which can broadly be divided into two phases. Phase I involved the sequencing of transcriptomes for five dytiscid beetles (two-surface and three-subterranean species) that were blasted (BLASTx) against a customized set of target candidate orthologs, and then best hits were reciprocally blasted (BLASTn) against the original reads. These results were then subjected to phylogenetic analyses to verify ortholog identification—see Tierney et al. (2015) for a detailed description of Phase I methods applied to a subset of target visual and non-visual opsin (phototransduction) genes. In cases where vision gene transcribed products were identified in surface species, but appeared absent in stygobiontic species, we subsequently carried out BLASTn analyses of the transcriptome assemblies, to determine whether there was evidence for expressed pseudogenes in the stygobiontic beetles that may not have been detected initially using BLASTx. The above approach is not published, but it may identify additional cases of expressed pseudogenes or potential assembly errors leading to frameshift mutations that may alter amino acid sequences. For Phase II, identified orthologs from all five transcriptomes were then used as the blueprint for a custom-set of RNA-baits in order to capture targeted DNA (in-solution) from a wider sampling of beetle species from the Yilgarn region. This specific methodology is referred to as “targeted enrichment” (per Gnirke et al. 2009) and our RNA baits (MYbaits) were designed in conjunction with Arbor Biosciences (formerly MYcroarray). Once captured, the DNA targets are then sequenced on high-throughput sequencing platforms. Phase II is ongoing, and to date we have captured DNA from approximately 40 additional dytiscid species. Fig. 4 View largeDownload slide Genomic workflow. Workflow of Phase I (transcript assembly, orthologous searches based around the Candidate Set of opsin proteins, and molecular evolutionary analyses, including phylogenetic reconstruction) and Phase II (RNA bait design and in-solution sequence capture for targeted high-throughput sequencing). Figure adapted from Tierney et al. (2015). Image credits: Chris Watts; www.cpbr.gov.au; pngpix.com. Fig. 4 View largeDownload slide Genomic workflow. Workflow of Phase I (transcript assembly, orthologous searches based around the Candidate Set of opsin proteins, and molecular evolutionary analyses, including phylogenetic reconstruction) and Phase II (RNA bait design and in-solution sequence capture for targeted high-throughput sequencing). Figure adapted from Tierney et al. (2015). Image credits: Chris Watts; www.cpbr.gov.au; pngpix.com. Expected outcomes At the outset, we stated that our project endeavored to improve the understanding of the genetic mechanisms resulting in regressive eye and vision loss; but what do we expect to find from an enhanced genomic perspective? The excision of individual genes from subterranean species (that are present in surface species) may indicate an adaptive response in the form of genome efficiency, in terms of the evolutionary economy of an organism’s proteome or metabolic load and particularly so in low nutrient environments (Wagner 2005; Bragg and Wagner 2009; Hessen et al. 2010). However, an absence by itself may not be informative with regard to how that genetic information was excised, or why. The maintenance of a full quiver of functional photoreception and eye development genes in an eyeless beetle living in aphotic environment with exceedingly limited outbreeding potential and no physical connection to surface species could imply a variety of processes. First, that there is negligible physiological cost in maintaining a functional visual system when it is not required, which would suggest that direct selection is not operating on the visual system in aphotic habitats—but see Moran et al. (2014, 2015) for arguments in favor of natural selection conserving physiological energy in Mexican cave fish. Second, that the visual system is constrained by developmental ontogeny and is required for alternate multiple functions—such pleiotropic processes would be indicative of indirect natural selection and may involve functions that we are not aware of. An explanatory example is the developmental re-engineering of the Drosophila Bolwig organ, which initially serves as the larval-stage visual system, but ultimately engages in deep brain circadian photo-entrainment in the adult-stage (Buschbeck and Friedrich 2008; Friedrich 2008, 2013b). This is just one example of extra-ocular photoreception function (reviewed by Tierney et al. 2017). Third, several photoreceptor genes may have pleiotropic functions in a variety of other developmental pathways that are unrelated to vision (e.g., Crumbs influences epithelial cell polarity, wing venation, and growth regulation of D. melanogaster; Spannl et al. 2017). In this latter example, the gene encodes multiple unique isoforms due to alternative splicing; the isoform Crumbs_C has a role in prevention of light-dependent retinal degeneration (Spannl et al. 2017). Similarly, the D. melanogaster gene Chaoptin encodes five transcripts and five unique isoforms that are involved in several phenotypes associated with the rhabdomere of photoreceptor cells as well as tergites of the mesothorax (see http://flybase.org/reports/FBgn0267435.html accessed March 2018). Such genes are not solely expressed in the eye and, therefore, should maintain their structural integrity as a result of purifying selection, though it is possible that exons that are specific to eye function may potentially show relaxed selection under the neutral evolution model. Finally, the gene may retain its structural integrity, but never be translated. Alternatively, there may be a complete absence of any selective processes operating on genes that are specific to the visual system given that they are unlikely to serve any selective advantage in an aphotic environment. The lack of purifying selection results in the accumulation of missence mutations (insertion/deletion frame-shifts or aberrant stop codons) that alter the open reading frame and result in improper translation of proteins and potentially loss of gene function. Under neutral evolution scenarios and given enough evolutionary time, genetic drift and the continual accrual of deleterious mutations might reasonably be expected to culminate in the development of functionless genes (pseudogenes) and ultimately regressed phenotypes (reviewed by Jeffery 2009; Wilkens 2010). Cartoon examples of these outcomes of “selection in absentia” are provided in Fig. 5. Fig. 5 View largeDownload slide Missence mutations indicative of neutral evolution. Hypothetical examples of independent or shared indels, frameshifts, and aberrant stop codons in a targeted vision gene. Such missence mutations would alter the open reading frame sequence inherited from ancestral species that inhabit surface water bodies and possesses functional eyes. Image credits: Chris Watts; www.cpbr.gov.au. Fig. 5 View largeDownload slide Missence mutations indicative of neutral evolution. Hypothetical examples of independent or shared indels, frameshifts, and aberrant stop codons in a targeted vision gene. Such missence mutations would alter the open reading frame sequence inherited from ancestral species that inhabit surface water bodies and possesses functional eyes. Image credits: Chris Watts; www.cpbr.gov.au. Summary The development of a comprehensive genomic understanding of the dytiscid beetles of the Yilgarn region of Western Australia should serve as a blueprint for future integrative research. Data sources from a diverse range of components can be then overlain in order to assess extrinsic (light environment) and intrinsic factors (functional gene modifications; behavioral activity patterns; optical, neural, and chemosensory morphology) influencing the regressive loss of vision among animals in order to assess their reciprocal influence on organismal fitness (Tierney et al. 2017). The collection of high-resolution data from each component should provide improved statistical rigor for comparative hypothesis-testing. Indeed, research has recently begun to branch into the photosensitive behavior of eyeless beetle species (Langille et al. 2018) for which the genomics of vision genes are being developed. The benefits that a species rich comparative system provide relate to an enhancement of the comparative method, primarily with regard to statistical power and the ability to self-assess confidence (or doubts) in our findings. Due to their unusual natural history, with multiple independently-evolved stygobionts, these Australian dytiscid species are expected to provide insights on the genetic processes of regressive evolution at a massively parallel scale that is currently unheralded. Acknowledgments Thanks are extended to symposium organizers Megan Porter and Lauren Sumner-Rooney. The symposium was generously sponsored by the Company of Biologists (http://www.biologists.com); the Palaeontological Association (PA-GA201707); the American Microscopical Society; the Crustacean Society; and the SICB divisions DEDB, DEE, DIZ, DNB, and DPCB. We thank Chris Watts for the use of his photograph and two anonymous reviewers for constructive comments on this manuscript. Funding This work was supported by an Australian Entomological Society Research Seeding Grant [to S.M.T.], an Australian Research Council Discovery Grant [DP120102132 to S.J.B.C., W.F.H., and A.D.A], and University of Adelaide research support funds. Supplementary data Supplementary data available at ICB online. References Abrams KM , Guzik MT , Cooper SJB , Humphreys WF , King RA , Cho J-L , Austin AD. 2012 . What lies beneath: molecular phylogenetics and ancestral state reconstruction of the ancient subterranean Australian Parabathynellidae (Syncarida, Crustacea) . Mol Phylogenet Evol 64 : 130 – 44 . 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Ecology, systematics, and the natural history of predaceous diving beetles (Coleoptera: Dytiscidae ). Dordrecht : Springer . Google Scholar CrossRef Search ADS © The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Integrative and Comparative Biology Oxford University Press

Massive Parallel Regression: A Précis of Genetic Mechanisms for Vision Loss in Diving Beetles

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10.1093/icb/icy035
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Abstract

Abstract Two tribes of subterranean dytiscid diving beetles independently colonized groundwater systems of the Western Australian arid zone, a habitat transition that was most likely driven by the contraction of surface water bodies following late Neogene aridification of the Australian continent. These “stygofauna” are now trapped within discrete calcrete aquifers that have formed in paleodrainage valleys, resulting in the world’s most diverse radiations of subterranean dytiscid beetles. Approximately 100 species from three genera exhibit partial or fully regressed visual systems and are essentially blind. This unique study system, with multiple independent transitions to subterranean life enables regressive and adaptive evolutionary processes to be studied in parallel at an unheralded comparative scale. Here we provide an overview of the progression of dytiscid beetle research and undertake a literature survey of published research within the field of regressive evolution as it applies to eye loss. We detail our exploration of insect vision genes for signatures of adaptive and neutral evolutionary mechanisms related to eye regression, largely within photoreceptor and eye pigment genes. Our project makes use of transcriptome data from five representative dytiscid beetle species (two surface and three subterranean) in order to design a customized set of RNA baits for use in a hybrid-capture method to target a pool of vision genes sequenced using high-throughput Illumina platforms. This methodological design permits the assessment of modifications in the genomic sequence of beetle vision genes at a much broader scale than Sanger sequencing, enabling a higher number of both target species and genes to be simultaneously assessed relative to research time-investments. Based on our literature search criteria of the research field (“regressive evolution” + “eyes”), 81 papers have been published since the late 1980s accruing an h-index of 27 and a mean citation rate of 24.57. Collective annual citations for this field of research have surged over the past 5 years, an indication that broader scientific community interest is gaining momentum. The majority of publications (75%) have focused on the chordate clade Actinopterygii. Historically, research on variant subterranean taxa has faced difficulties inferring the evolutionary mechanisms of eye regression (and vision loss) using molecular approaches because only a handful of target genes could be feasibly addressed within grant funding cycles. From a comparative phylogenetic perspective, next-generation sequencing approaches applied to stygobiontic dytiscid beetles hold the potential to greatly improve our understanding of the genetic mechanisms underlying regressive evolution generally. Introduction Evolution is often perceived as a process of progressive refinement or improvement, which may explain why the regressive loss of functional phenotypic traits persists as one of evolutionary biology’s most notably anomalies. The evolutionary loss of vision is particularly intriguing because the Paleozoic origin of eyes is posited to have had a catalytic evolutionary impact leading to the explosion of animal diversity in the Cambrian (Parker 1998, 2011). Understanding the fitness advantages of the reduction and loss of eyes in aphotic (lightless) environments, where vision appears to serve no selective advantage, makes intuitive theoretical sense. Yet the establishment of a unilateral empirically supported Neo-Darwinian mechanistic explanation for regressive evolution remains elusive and continues to generate vigorous debate. Stygofauna are cave-dwelling animals that are dark-adapted and live in groundwater—the prefix “stygo” derives from the Greek mythological underworld river Styx. Courtesy of their natural history, a complex of stygobiontic dytiscid water beetles may provide unique opportunities to help solve one of evolutionary biology’s greatest riddles—the long-term consequences to the genome that result from regressive evolution. The subterranean diving beetles of the Australian arid zone represent an unusual group of organisms for understanding the proximate factors of regressive evolution, because their natural history is notably different to the majority of animal systems that have been used to explore the loss of eyes and vision generally. Their evolutionary history involved recurrent independent colonizations of disjunct groundwater habitats by a relatively small number of geographically widespread species inhabiting either bodies of surface-water or interstitial niches at the groundwater/surface-water interface (Leys et al 2003; Leijs et al 2012; Watts et al. 2016). From a comparative evolutionary perspective, these repeated entries into a novel niche collectively provide a large number of independent contrasts between photic and aphotic lineages with inherent statistical power. There are numerous cases of sympatric sister species that potentially evolved from a stygobiontic common ancestor within the calcrete aquifer, allowing an assessment of genomic changes (shared among the sister taxa) in the very early phase of colonization of, and evolution within, the calcretes. The recent application of high-throughput sequence tools, combined with the relatively detailed understanding of the physiology and evolutionary development of eyes and their genetic underpinnings, therefore permits a rigorous and integrative approach to one of the enduring quandaries in evolutionary biology (Dobzhansky 1970; Culver and Wilkens 2000; Porter and Crandall 2003; Jeffery 2009; Romero 2009; Wilkens 2010). Many of the vanguard of this new phase of technologically empowered research are represented in the current issue of this publication (W. R. Jeffery; J. L. Pérez-Moreno; M. L. Porter; M. Protas; A. S. Riviera; D. B. Stern and K. A. Crandall; L. H. Sumner-Rooney), and in particular Friedrich (2013a) whom opined that we have now entered the era of Speleogenomics (derived from the Greek “spēlaion” for cave). Current research on Australian dytiscid beetles (Coleoptera: Dytiscidae: Bidessini, Hydroporini) is concerned with the genomic-level interrogation of a broad swathe of genes related to invertebrate phototransduction (Tierney et al. 2012, 2015, 2017). The specific objective is to make use of the aforementioned natural experiment by comparing the molecular structure and expression patterns of focal genes among phylogenetically related surface and subterranean species. Namely, have these genes accumulated mutations that would lead to a loss of function in the translated proteins (i.e., major deletions, frameshift mutations, stop codons, or elevated rates of amino acid substitutions) or, in the extreme case, completely excised the functional vision genes present in their closest surface relatives? Our core interest is whether any identified differences can meaningfully inform our understanding of the mechanistic process of regression from Neo-Darwinian perspectives of direct natural selection, indirect pleiotropic selection, or an absence of selection (neutral theory); and if neutral processes are at play, how many genes can actually evolve by neutral processes, when they may have other pleiotropic functions not related to vision. A further goal is to make inroads toward a truly integrative understanding of organismal biology and evolutionary fitness (reviewed by Tierney et al. 2017). That is, can the change in light environment experienced by an organism be interconnected with structural (both genetic and phenotypic) and behavioral variation when contrasted with closely related organisms obligatorily inhabiting discretely different photic niches—ideally, bright daylight versus a complete absence of light, or gradations thereof. Evolutionary transitions in light environment Speciation is often driven by a change in the physical environment leading to the creation of a novel habitat that is colonized by organisms, which subsequently adapt to and diversify within their new surrounds, as exemplified by adaptive radiations (e.g., Seehausen et al. 2008). The regressive evolution of eyes and eventual loss of vision is predominantly driven by a transition in photic environment, moving from a brightly lit to dim-light to completely aphotic environments. Regressive evolution is typically associated with shallow subterranean (<10 m) and cave dwelling organisms, and the field of biospeleology (White and Culver 2012; Culver and Pipan 2014). Cave biologists often delineate these variant light environments into discrete photic zones, beginning at the cave “entrance zone” through a series of transitional and increasingly dimmer light zones and culminating in the “dark zone,” the deep regions of a cave wherein there is a complete absence of light in addition to relatively constant temperature and humidity levels that are less affected by surface climate variation (e.g., Howarth 1980). Similar parallels can be drawn with transitional light environments at different depths of the water column (e.g., disphotic zone receives light that is insufficient for plants to photosynthesize), as well as transitions from diurnal to nocturnal behavioral activity (Tierney et al. 2017). It is important to note that the Australian calcrete aquifers occupied by dytiscid beetles are currently isolated from the surface (no cave entrances and no surface connectivity post-colonization) and are therefore aphotic both above and below the cave water column (Humphreys 2006, 2008). These limestone depositions (explained in greater detail below—Unusual Study System section) are relatively shallow (up to 10 m below the surface) compared with most other cave systems. It is plausible that individual calcretes may be subject to surface cracking which would then subject them to light environment categorization akin to Howarth’s (1980) zonations. In the majority of cases the stygobiontic beetles are assumed to have evolved in complete darkness, however, it is possible that the beetles may have evolved initially in interstitial environments (e.g., gravels in ephemeral river or creek systems), as evident for several other dytiscid species in Australia (e.g., Watts et al. 2016). The finding of negative-phototactic behavior in the stygobiontic species Paroster macrosturtensis (Langille et al. 2018; Fig. 1) may be representative of a behavior that has been retained by chance from an ancestral interstitial species. Fig. 1 View largeDownload slide Subterranean beetle sister species triplet. Exemplar of a recurrent diversification pattern wherein multiple stygobiontic species, most commonly triplets, are restricted within isolated calcrete aquifers situated in ancient paleodrainage valleys of the western Australian arid zone. Paroster Sharp (Dytiscidae: Hydroporini) species nomens from left to right: P. macrosturtensis, P. mesosturtensis, and P. microsturtensis (Watts and Humphreys 2006, 2009; Leys and Watts 2008). Photo credit: Chris Watts and Howard Hamon, South Australian Museum. Fig. 1 View largeDownload slide Subterranean beetle sister species triplet. Exemplar of a recurrent diversification pattern wherein multiple stygobiontic species, most commonly triplets, are restricted within isolated calcrete aquifers situated in ancient paleodrainage valleys of the western Australian arid zone. Paroster Sharp (Dytiscidae: Hydroporini) species nomens from left to right: P. macrosturtensis, P. mesosturtensis, and P. microsturtensis (Watts and Humphreys 2006, 2009; Leys and Watts 2008). Photo credit: Chris Watts and Howard Hamon, South Australian Museum. Movile cave in Romania is the only other comparable cave system under study, with regard to the nature of discrete pockets of calcrete that contain groundwater and lack surface connections. These systems differ from the Australian calcretes, in that they are outlets for hydrothermal fluids that react with cave substrates to produce nutrients incorporated by chemolithotrophic bacteria—which in turn supply a primary nutrient source for the resident cave invertebrates (Kumaresan et al. 2014). Taxonomic groups used for the study of regressive evolution We undertook a survey of the primary literature for animal study systems that have been used to explore the regressive evolution of eyes. We searched the electronic database Web of Science v5.28 Core Collection (Clarivate Analytics—accessed March 2018) using the Basic Search option with the Topic term: “regressive evolution.” We then restricted output to Articles, Proceedings Papers, and Meeting Abstracts published over the last 100 years (1919–2018), excluded physical and social science categories, and refined the remaining publications for the term “eyes.” Our search returned 81 publications that have been cited 1990 times (mean = 24.57 ± s.e. 3.01; absolute maximum citation = 122; research field citation h-index = 27). Collective annual citations of the field remained below 50 per year until 2006, but then increase considerably peaking at more than 300 per annum in 2016 (Fig. 2; Supplementary Table S1), suggesting that neo-Darwinian interest in the field is gaining momentum. Citations derive from the following scientific fields: Evolutionary Biology (38.3%), Genetics Heredity (25.9%), Ecology (21%), Multidisciplinary Sciences (17.2%), Zoology (17.2%), Developmental Biology (16%), and Biochemistry Molecular Biology (12.3%); which constitute Web of Science Categories with at least 10 entries. The majority of publications arose from research laboratories in the Americas (United States of America 55.6%, Mexico 4.9%, Canada 3.9%), Europe (Germany 25.9%, England 8.6%, France 4.9%, Austria 3.7%, Switzerland 3.7%), Australia (4.9%), and People's Republic of China (3.7%). Table 1 summarizes publications by taxonomic classification (class, order, family, and common name) for taxa listed in titles or abstracts of the 81 surveyed publications. The table indicates whether high-throughput sequencing techniques have been applied to these study systems; we also listed cases where parallel sequencing results were screened post hoc, or the potential of genomic application has been reviewed (all respective studies are cited in the legend of Table 1). Under our search filters, publications arose in 1988 and are predominantly focused on chordates (Actinopterygii comprise 75% of all publications), and aside from work on spring- and cave-dwelling amphipods, it is not until about 2000 that invertebrate studies begin to appear in the literature (Table 1 and Supplementary Table S1). We should note that known studies on fruit fly and cholevid carrion beetles did not appear in our refined publication list and two papers that were included (on acari and hominids) do not appear to relate specifically to eye regression per se. Table 1. Taxa used to investigate regression of animal eyes over the last 100 years Classification Common name Year published (number per year) Parallel sequencing Arthropoda  Arachnida   Trombidiformes    Tetranychidae Spider mite 1998  Insecta    Coleoptera     Carabidae Ground beetles 2016     Dytiscidae Diving beetles 2015a Transcriptomics 2005    Orthoptera   Rhaphidophoridae Cave camel cricket 2013b Review  Malacostraca   Amphipoda    Gammaridae Spring/cave amphipod 1994 1992    Paramelitidae Subterranean amphipod 2007    Hyalidae Subterranean amphipod 2007   Decapoda    Cambaridae Cave crayfish 2005    Gecarcinucidae Cave crabs 2013   Isopoda    Asellidae Cave isopod 2011  Trilobita   Ptychopariida    Conocoryphidae Blind trilobites 2003 Chordata  Actinopterygii   Characiformes    Characidae Mexican cavefish 2017 (5)c Transcriptomics 2016 (2) 2015 (2) 2014 (2) 2013 (6) Transcriptomics, review 2012 (2)b, d 2011 2009 (3) 2008 (3) 2007 (2) 2006 (2) 2005 2004 2002 1998 (2) 1997 1995 1993 (2) 1998   Cypriniformes    Cyprinidae Omani cavefish 2017 2011 2009 Somalian cavefish 2016 2015 Golden line fish 2016e Genomics 2013 (4)f Transcriptomics    Nemacheilidae Murangi ray-finned fish 2013b Review   Cyprinodontiformes    Poeciliidae Atlantic cave molly 2010 2009 2008 (2) 2007 2006 2001   Percopsiformes    Amblyopsidae Amblyopsid cavefish 2011   Siluriformes    Ictaluridae Blind catfish 1993    Loricariidae Cave armored catfish 2009  Amphibia   Caudata    Proteidae Olm salamander 2013b Review 2001  Aves   Apterygiformes    Apterygidae Kiwi 2007  Mammalia   Afrosoricida   Chrysochloridae Cape golden mole 2014g Post hoc screen   Soricomorpha    Talpidae Star nose-mole 2014g Post hoc screen   Primates    Hominidae Humans 2005   Rodentia    Bathyergidae Naked mole-rat 2014g Post hoc screen 2004    Spalacidae Blind mole-rat 2002 1990 Mollusca  Gastropoda   Vetigastropoda    Solariellidae Marine snails 2016 Classification Common name Year published (number per year) Parallel sequencing Arthropoda  Arachnida   Trombidiformes    Tetranychidae Spider mite 1998  Insecta    Coleoptera     Carabidae Ground beetles 2016     Dytiscidae Diving beetles 2015a Transcriptomics 2005    Orthoptera   Rhaphidophoridae Cave camel cricket 2013b Review  Malacostraca   Amphipoda    Gammaridae Spring/cave amphipod 1994 1992    Paramelitidae Subterranean amphipod 2007    Hyalidae Subterranean amphipod 2007   Decapoda    Cambaridae Cave crayfish 2005    Gecarcinucidae Cave crabs 2013   Isopoda    Asellidae Cave isopod 2011  Trilobita   Ptychopariida    Conocoryphidae Blind trilobites 2003 Chordata  Actinopterygii   Characiformes    Characidae Mexican cavefish 2017 (5)c Transcriptomics 2016 (2) 2015 (2) 2014 (2) 2013 (6) Transcriptomics, review 2012 (2)b, d 2011 2009 (3) 2008 (3) 2007 (2) 2006 (2) 2005 2004 2002 1998 (2) 1997 1995 1993 (2) 1998   Cypriniformes    Cyprinidae Omani cavefish 2017 2011 2009 Somalian cavefish 2016 2015 Golden line fish 2016e Genomics 2013 (4)f Transcriptomics    Nemacheilidae Murangi ray-finned fish 2013b Review   Cyprinodontiformes    Poeciliidae Atlantic cave molly 2010 2009 2008 (2) 2007 2006 2001   Percopsiformes    Amblyopsidae Amblyopsid cavefish 2011   Siluriformes    Ictaluridae Blind catfish 1993    Loricariidae Cave armored catfish 2009  Amphibia   Caudata    Proteidae Olm salamander 2013b Review 2001  Aves   Apterygiformes    Apterygidae Kiwi 2007  Mammalia   Afrosoricida   Chrysochloridae Cape golden mole 2014g Post hoc screen   Soricomorpha    Talpidae Star nose-mole 2014g Post hoc screen   Primates    Hominidae Humans 2005   Rodentia    Bathyergidae Naked mole-rat 2014g Post hoc screen 2004    Spalacidae Blind mole-rat 2002 1990 Mollusca  Gastropoda   Vetigastropoda    Solariellidae Marine snails 2016 Results are systematically categorized by class, order/clade, family, and common name and qualifies whether high-throughput parallel sequencing studies have been initiated, namely: a, Tierney et al. (2015); b, Friedrich (2013); c, Stahl and Gross (2017); d, Gross et al. (2013); e, Yang et al. (2016); f, Meng et al. (2013); g, Emerling and Springer (2014). Source data are provided in Supplementary Table S1. Table 1. Taxa used to investigate regression of animal eyes over the last 100 years Classification Common name Year published (number per year) Parallel sequencing Arthropoda  Arachnida   Trombidiformes    Tetranychidae Spider mite 1998  Insecta    Coleoptera     Carabidae Ground beetles 2016     Dytiscidae Diving beetles 2015a Transcriptomics 2005    Orthoptera   Rhaphidophoridae Cave camel cricket 2013b Review  Malacostraca   Amphipoda    Gammaridae Spring/cave amphipod 1994 1992    Paramelitidae Subterranean amphipod 2007    Hyalidae Subterranean amphipod 2007   Decapoda    Cambaridae Cave crayfish 2005    Gecarcinucidae Cave crabs 2013   Isopoda    Asellidae Cave isopod 2011  Trilobita   Ptychopariida    Conocoryphidae Blind trilobites 2003 Chordata  Actinopterygii   Characiformes    Characidae Mexican cavefish 2017 (5)c Transcriptomics 2016 (2) 2015 (2) 2014 (2) 2013 (6) Transcriptomics, review 2012 (2)b, d 2011 2009 (3) 2008 (3) 2007 (2) 2006 (2) 2005 2004 2002 1998 (2) 1997 1995 1993 (2) 1998   Cypriniformes    Cyprinidae Omani cavefish 2017 2011 2009 Somalian cavefish 2016 2015 Golden line fish 2016e Genomics 2013 (4)f Transcriptomics    Nemacheilidae Murangi ray-finned fish 2013b Review   Cyprinodontiformes    Poeciliidae Atlantic cave molly 2010 2009 2008 (2) 2007 2006 2001   Percopsiformes    Amblyopsidae Amblyopsid cavefish 2011   Siluriformes    Ictaluridae Blind catfish 1993    Loricariidae Cave armored catfish 2009  Amphibia   Caudata    Proteidae Olm salamander 2013b Review 2001  Aves   Apterygiformes    Apterygidae Kiwi 2007  Mammalia   Afrosoricida   Chrysochloridae Cape golden mole 2014g Post hoc screen   Soricomorpha    Talpidae Star nose-mole 2014g Post hoc screen   Primates    Hominidae Humans 2005   Rodentia    Bathyergidae Naked mole-rat 2014g Post hoc screen 2004    Spalacidae Blind mole-rat 2002 1990 Mollusca  Gastropoda   Vetigastropoda    Solariellidae Marine snails 2016 Classification Common name Year published (number per year) Parallel sequencing Arthropoda  Arachnida   Trombidiformes    Tetranychidae Spider mite 1998  Insecta    Coleoptera     Carabidae Ground beetles 2016     Dytiscidae Diving beetles 2015a Transcriptomics 2005    Orthoptera   Rhaphidophoridae Cave camel cricket 2013b Review  Malacostraca   Amphipoda    Gammaridae Spring/cave amphipod 1994 1992    Paramelitidae Subterranean amphipod 2007    Hyalidae Subterranean amphipod 2007   Decapoda    Cambaridae Cave crayfish 2005    Gecarcinucidae Cave crabs 2013   Isopoda    Asellidae Cave isopod 2011  Trilobita   Ptychopariida    Conocoryphidae Blind trilobites 2003 Chordata  Actinopterygii   Characiformes    Characidae Mexican cavefish 2017 (5)c Transcriptomics 2016 (2) 2015 (2) 2014 (2) 2013 (6) Transcriptomics, review 2012 (2)b, d 2011 2009 (3) 2008 (3) 2007 (2) 2006 (2) 2005 2004 2002 1998 (2) 1997 1995 1993 (2) 1998   Cypriniformes    Cyprinidae Omani cavefish 2017 2011 2009 Somalian cavefish 2016 2015 Golden line fish 2016e Genomics 2013 (4)f Transcriptomics    Nemacheilidae Murangi ray-finned fish 2013b Review   Cyprinodontiformes    Poeciliidae Atlantic cave molly 2010 2009 2008 (2) 2007 2006 2001   Percopsiformes    Amblyopsidae Amblyopsid cavefish 2011   Siluriformes    Ictaluridae Blind catfish 1993    Loricariidae Cave armored catfish 2009  Amphibia   Caudata    Proteidae Olm salamander 2013b Review 2001  Aves   Apterygiformes    Apterygidae Kiwi 2007  Mammalia   Afrosoricida   Chrysochloridae Cape golden mole 2014g Post hoc screen   Soricomorpha    Talpidae Star nose-mole 2014g Post hoc screen   Primates    Hominidae Humans 2005   Rodentia    Bathyergidae Naked mole-rat 2014g Post hoc screen 2004    Spalacidae Blind mole-rat 2002 1990 Mollusca  Gastropoda   Vetigastropoda    Solariellidae Marine snails 2016 Results are systematically categorized by class, order/clade, family, and common name and qualifies whether high-throughput parallel sequencing studies have been initiated, namely: a, Tierney et al. (2015); b, Friedrich (2013); c, Stahl and Gross (2017); d, Gross et al. (2013); e, Yang et al. (2016); f, Meng et al. (2013); g, Emerling and Springer (2014). Source data are provided in Supplementary Table S1. Fig. 2 View largeDownload slide Citations of research on the regressive evolution of eyes. Line-plot of annual citations on publications over the last 100 years derived from a filtered search of the Web of Science database (accessed March 2018), using the terms “regressive evolution” + “eyes.” Fig. 2 View largeDownload slide Citations of research on the regressive evolution of eyes. Line-plot of annual citations on publications over the last 100 years derived from a filtered search of the Web of Science database (accessed March 2018), using the terms “regressive evolution” + “eyes.” Unusual study system In Western Australia, there is evidence that both the geological formation of calcrete deposition and the subsequent biological colonization of the aquifers was climate driven. Post-separation of Australia from remnant Gondwanan landmasses (Antarctica + South America), much of the continent contained expansive rainforests and freshwater lakes (Blewett 2012). As the Australian plate continued to drift northward from Antarctica a series of physical events initiated and intensified the continental aridification that is evident in the present day landscape. First, from the Oligocene to the Miocene (34–5 Mya) the continent began to experience seasonal aridity as it met with bands of subtropical high-pressure systems, in addition to periods of dry cooler climates (Antarctic ice sheets were larger and sea levels lower than present day). The second and more intense phase led to aridification of two-thirds of the continent during the Plio-Pleistocene (3 Mya to present), when ice sheets greatly expanded and forced the migration of the band of high-pressure systems into the center of the continent (Byrne et al. 2008; Fujioka and Chappell 2010). The calcrete aquifer habitats of subterranean beetles are deposited in paleodrainage valleys upstream of salt lakes in arid regions of the Australian Western Plateau. The carbonate depositions of near-surface permeable rock (the calcretes) are relatively thin (10–30 m deep) and were formed in association with groundwater by evaporative processes (Morgan 1993; Humphreys 2006; Humphreys et al. 2009). While the paleodrainage channels are ancient, the calcrete deposition is thought to have begun after the onset of continental aridification (described above) and continues to form in some arid regions with high evaporation. Epigean arthropods are thought to have colonized the aquifers within the last 8–3 million years during transient warm-wet periods with increased and widespread surface water flows (Leys et al. 2003; Humphreys 2012; Sniderman et al. 2016), which led to the repeated colonization of isolated aquifer pockets that now represent biogeographic refugia. In the Yilgarn region of Western Australia, these communities are largely comprised of crustaceans (including Amphipoda, Isopoda, Bathynellacea, Copepoda) and insects (but see the following for a fuller account of taxonomic diversity: Karanovic 2004; Cooper et al. 2007, 2008; Guzik et al. 2008; Juan et al. 2010; Abrams et al. 2012; Humphreys 2012; Karanovic and Cooper 2012). Beetles from the family Dytiscidae are commonly referred to as diving water beetles and are predatory in surface water habitats (Watts 1978; Yee 2014). The Yilgarn species comprise one of the world’s most speciose radiations, with at least 100 known subterranean species from the tribes Bidessini and Hydroporini (Balke et al. 2004). The actual number of species that are yet to be discovered and described is undoubtedly much greater, given that <25% of potential habitat has been sampled to date; the region contains more than 200 isolated calcrete aquifers that range in size from ca. 2–200 km2. The described species have been collected from 46 discrete calcrete aquifers with between one and four endemic species per calcrete and there are approximately 13 cases of sympatric sister species (Leijs et al. 2012). Figure 1 shows an exemplar of a sister species triplet from the Sturt Meadows calcrete (P. macrosturtensis, P. mesosturtensis, P. microsturtensis); such distribution in body size is common across calcretes and may represent ecological partitioning within a common niche consistent with theories of evolutionary self-organization (Vergnon et al. 2013). Figure 3b (Leijs et al. 2012) presents a species level phylogeny of the two dytiscid tribes of interest based on mitochondrial gene fragments. The precise number of subterranean colonization events is unknown, but it is assumed that relatively few surface species repeatedly colonized geographically discrete calcretes on multiple occasions (Leijs et al. 2012). There is a lack of phylogeographic structure across the landscape for most of these beetle species (i.e., no clear geographic pattern to the relationships among the subterranean species), with the exception of the sympatric sister species within calcretes. Hence, the majority of subterranean species evolved independently from widespread surface ancestors, with the Lineage-Through-Time plot (Fig. 3a) suggesting at least 30 ancestral species were most likely present prior to the radiation of the subterranean species (Leijs et al. 2012). Predaceous diving beetles constitute the most specious clade of aquatic beetles (ca. 4800 species globally), with an estimated 600 species in the Australian + Pacific region (Jäch and Balke 2008) that are assumed to have dispersed to Australia from South-East Asia (Balke and Ribera 2004). Among the described Australian taxa ca. 100 species are subterranean (Watts and Humphreys 2009). For global comparisons, less than 1% of Coleopteran fauna are estimated to inhabit subterranean environments (Tierney et al. 2017). Fig. 3 View largeDownload slide Surface and subterranean beetle speciation through time. A lineage through time plot (a) indicates the number of lineage divergence events that derive from a mitochondrial phylogeny (b) of Australian dytiscid beetles. Shaded orange rectangles indicate the estimated time period of most rapid diversification among the stygofauna. Both figures are adapted from Leijs et al. (2012). (a) Plots lineage events among surface water (black lines) and stygobiontic (red lines) beetles. (b) Presents a Bayesian inferred species-level molecular phylogenetic tree with posterior probability node support values (>0.7), that indicates: terminal branches leading to surface water beetles (black branches), stygobiontic beetles from the Yilgarn region (red branches), and stygobiontic beetles from outside of the Yilgarn region (green branches); sympatric sister species endemic to single calcrete aquifers denoted by shaded blue boxes (as exemplified in Fig. 1 species triplet Paroster microsturtensis, P. mesosturtensis, and P. macrosturtensis). Access the electronic PDF version of this article for color figure production. Fig. 3 View largeDownload slide Surface and subterranean beetle speciation through time. A lineage through time plot (a) indicates the number of lineage divergence events that derive from a mitochondrial phylogeny (b) of Australian dytiscid beetles. Shaded orange rectangles indicate the estimated time period of most rapid diversification among the stygofauna. Both figures are adapted from Leijs et al. (2012). (a) Plots lineage events among surface water (black lines) and stygobiontic (red lines) beetles. (b) Presents a Bayesian inferred species-level molecular phylogenetic tree with posterior probability node support values (>0.7), that indicates: terminal branches leading to surface water beetles (black branches), stygobiontic beetles from the Yilgarn region (red branches), and stygobiontic beetles from outside of the Yilgarn region (green branches); sympatric sister species endemic to single calcrete aquifers denoted by shaded blue boxes (as exemplified in Fig. 1 species triplet Paroster microsturtensis, P. mesosturtensis, and P. macrosturtensis). Access the electronic PDF version of this article for color figure production. Like most obligate cave dwelling arthropods these stygobiontic beetles exhibit convergent morphological phenotypes, namely: an absence of cuticle melanization and the reduction or complete loss of wings and eyes (Tierney et al. 2017). Such repetition of trait loss represents a massively parallel system that, from a quantitative evolutionary comparative perspective (Felsenstein 1985; Harvey and Pagel 1991), presents an ideal opportunity to examine the long-term consequences to the genome that result from regressive evolution. The search for genetic signatures of regression The most attractive aspect of this massively parallel evolutionary complex of beetles lies in its potential to understand regressive evolution from a genomic perspective. Although a wide range of cave animals exhibit very similar morphological convergence of traits, they generally arise from very distant phylogenetic lineages and developmental pathways that may confound a similar kind of broad scale comparison at the genomic level. In contrast, the stygobiontic bidessine and hydroporine dytiscid beetle species from the Yilgarn aquifers exhibit very similar phylogeographic histories and are descended from only a few geographically widespread ancestral epigean species (Cooper et al. 2002; Leys et al. 2003; Watts and Humphreys 2004, 2006, 2009; Leijs et al. 2012). An additional, and important, aspect of Australian dytiscid beetle natural history that relates to the genetics of regression is their age of origin and diversification. Based on mitochondrial rates of evolution (Leijs et al. 2012), subterranean lineages are estimated to have initially diverged from surface ancestors in the middle Miocene (∼13 Mya) with the majority of speciation events occurring through the late Miocene, Pliocene, and Pleistocene; however, we are unable to confidently predict the exact point along a phylogenetic branch that a particular taxon evolved underground. With this caveat in mind, the most rapid period of speciation (∼8–3 Mya) can be visualized as a lineage through time plot based on uncalibrated molecular clock rates (shaded rectangle Fig. 3a,b). This contrasts to many other cave study systems that have only diverged from surface lineages relatively recently and raises the question of how much geological time is required for genetic signatures of regressive loss to arise or be overwritten (Tierney et al. 2017). For example, research on visual photoreceptor genes of different cavefish species (Niemiller et al. 2013) found evidence that corroborated both indirect natural selection (pleiotropy) and neutral evolution (pseudogene) theories. Non-adaptive evolutionary processes require sufficient time to accrue random mutations via genetic drift in order to lose function as a result of pseudogene development. Given that this is a random process, a study system such as dytiscid beetles with multiple speciation events over considerable periods of geological time (Fig. 3) would appear to represent a suitable study-target for attempts to capture signals of deleterious mutations that nullify the function of vision related genes. Previous research employing Sanger sequencing has explored rates of evolution for the eye pigment gene cinnabar in surface and subterranean species and found increased rates of evolution among the eyeless lineages and a number of missence mutations (frameshifts and aberrant stop-codons) that are indicative of pseudogene development (Leys et al. 2005). Similar missence mutations have also been identified among opsin photoreceptor genes of Somalian and amblyopsid cave fish (Cavallari et al. 2011; Niemiller et al. 2013). However, a number of studies have identified the existence of seemingly functional visual opsin genes among cave crustaceans and fish with degenerate eyes (Langecker et al. 1993; Crandall and Hillis 1997; Carlini et al. 2013; Niemiller et al. 2013). Genomic advancement Until recently, research projects investigating the regressive loss of vision have utilized standard PCR-amplification and Sanger sequencing technology and, therefore, have been restricted to exploration of one or only a few focal genes within standard funding scheme cycles and budgets (for examples see paragraph above). However, the advent of high-throughput massively parallel sequencing technology alters this research landscape by orders of magnitude because it permits a gene-network approach for understanding functional gene evolution. The combination of technological advances with an increased frequency of co-operative research consortiums and continuing reductions in sequencing costs, both reagents and hardware, means that genomic-empowered projects are now able to be applied to a wide range of non-model organisms. This technological expansion has certainly been applied to the genetics of regression and vision generally. Not surprisingly, research that incorporates high-throughput parallel sequencing technology have only entered the research conversation within the previous 5 years (8.6% of total publications, Table 1 and Supplementary Table S1), however, given the adaptability of broad scale functional genomics to non-model systems we may expect the diversity of taxonomic groups used to study the genetics of regressive eye evolution to noticeably expand over the coming decades. From the invertebrate perspective, important foundational steps were undertaken by Friedrich (2011) and colleagues (Bao and Friedrich 2009; Friedrich et al. 2011) via the extension of an in-depth knowledge gleaned from the model-insect genomes Drosophila melanogaster (fruit fly: Adams et al. 2000) and Tribolium castaneum (red flour beetle: Jackowska et al. 2007; Richards et al. 2008), and subsequent application to the small carrion beetle Ptomophagus hirtus—a flightless troglobiont species with degenerate eyes that is endemic to Mammoth Cave (Kentucky, USA). Friedrich et al. (2011) sequenced the transcriptome of P. hirtus and identified an orthologous set of 20-phototransduction genes, 25-eye pigmentation, and 16-circadian clock genes. The regressed eyes of P. hirtus contain residual lenses and the presence of a seemingly complete set of phototransduction genes instigated ethological assays that indicated negative-phototactic abilities (Friedrich et al. 2011). The Coleopteran species studied thus far appear to possess the same core set of phototransduction genes and, therefore, presumably similar biochemical cascades as in well studied model insect species with compound eyes (e.g., D. melanogaster); light being absorbed in the rhabdomeres of photoreceptor cells by opsin molecules that initiate a neuro-electrical signal (Friedrich et al. 2011; Tierney et al. 2015, 2017). Insects typically possess trichromatic vision with opsin photoreceptor proteins sensitive to long (green) and short (blue, ultraviolet) wavelengths of the light spectrum, as well as extraretinal opsins, which together derive from four rhabdomeric-type and one ciliary-type opsin classes (Briscoe and Chittka 2001; Porter et al. 2012; Henze and Oakley 2015). A variety of beetle taxa have entirely lost one or more visual opsin gene subfamilies: blue-sensitive opsin loss in diving water beetles (Maksimovic et al. 2011; Tierney et al. 2015), red flour beetles (Jackowska et al. 2007), and jewel beetles (Lord et al. 2016); ultraviolet-sensitive loss + blue-sensitive loss in cave dwelling small carrion beetles (Friedrich et al. 2011). Many of these aforementioned beetle species inhabit aphotic or dim-light niches, however, generalities are difficult to draw with regard to convergent opsin-losses linked with transitions in photic environments because there are exceptions to the rule for beetles and other insects (see review by Feuda et al. 2016); in that both surface (diurnal, crepuscular, nocturnal) and subterranean (obligate, facultative) species variously show both losses and gains of opsin gene classes. However as intimated at the beginning of this section (The search for genetic signatures of regression), genotypic trait loss may require extensive and undetermined periods of geological time in order for a relaxation of evolutionary selective pressures to permit neutral evolution processes (missence mutations) to occur, eventually obfuscate gene function and ultimately lead to phenotypic trait loss. Therefore, if the regressive loss of traits is indeed a highly stochastic process, then a lack of broad sweeping general rules across phylogenetically distant lineages may well be expected, and the importance of studying groups that enable robust genome-level comparative assessments among close phylogenetic relatives becomes paramount. Friedrich’s research set an outstanding benchmark that our research group adopted in order to identify candidate vision genes from transcriptome data that were subsequently used to design baits for targeted capture. We applied an in-solution hybrid-capture sequencing method that provisionally followed established methods (Mamanova et al. 2010; Lemmon et al. 2012; Lemmon and Lemmon 2013; Li et al. 2013), and enabled us to customize a targeted set of candidate genes to assess vision loss among the Australian stygobiontic dytiscid beetles. Our initial aim was to qualitatively identify protein coding genes related to vision that were expressed (i.e., transcribed) in surface lineages, but lacked expression in subterranean lineages. Simple presence or absence of expression would then provide grounds for subsequent comparative exploration of genomic DNA to assess whether adaptive (natural selection) or non-adaptive (neutral) evolution has rendered any of these genes non-functional and contributed to the regressive evolution of eyes in stygofauna. A simplified representation of our methodological workflow is provided in Fig. 4; which can broadly be divided into two phases. Phase I involved the sequencing of transcriptomes for five dytiscid beetles (two-surface and three-subterranean species) that were blasted (BLASTx) against a customized set of target candidate orthologs, and then best hits were reciprocally blasted (BLASTn) against the original reads. These results were then subjected to phylogenetic analyses to verify ortholog identification—see Tierney et al. (2015) for a detailed description of Phase I methods applied to a subset of target visual and non-visual opsin (phototransduction) genes. In cases where vision gene transcribed products were identified in surface species, but appeared absent in stygobiontic species, we subsequently carried out BLASTn analyses of the transcriptome assemblies, to determine whether there was evidence for expressed pseudogenes in the stygobiontic beetles that may not have been detected initially using BLASTx. The above approach is not published, but it may identify additional cases of expressed pseudogenes or potential assembly errors leading to frameshift mutations that may alter amino acid sequences. For Phase II, identified orthologs from all five transcriptomes were then used as the blueprint for a custom-set of RNA-baits in order to capture targeted DNA (in-solution) from a wider sampling of beetle species from the Yilgarn region. This specific methodology is referred to as “targeted enrichment” (per Gnirke et al. 2009) and our RNA baits (MYbaits) were designed in conjunction with Arbor Biosciences (formerly MYcroarray). Once captured, the DNA targets are then sequenced on high-throughput sequencing platforms. Phase II is ongoing, and to date we have captured DNA from approximately 40 additional dytiscid species. Fig. 4 View largeDownload slide Genomic workflow. Workflow of Phase I (transcript assembly, orthologous searches based around the Candidate Set of opsin proteins, and molecular evolutionary analyses, including phylogenetic reconstruction) and Phase II (RNA bait design and in-solution sequence capture for targeted high-throughput sequencing). Figure adapted from Tierney et al. (2015). Image credits: Chris Watts; www.cpbr.gov.au; pngpix.com. Fig. 4 View largeDownload slide Genomic workflow. Workflow of Phase I (transcript assembly, orthologous searches based around the Candidate Set of opsin proteins, and molecular evolutionary analyses, including phylogenetic reconstruction) and Phase II (RNA bait design and in-solution sequence capture for targeted high-throughput sequencing). Figure adapted from Tierney et al. (2015). Image credits: Chris Watts; www.cpbr.gov.au; pngpix.com. Expected outcomes At the outset, we stated that our project endeavored to improve the understanding of the genetic mechanisms resulting in regressive eye and vision loss; but what do we expect to find from an enhanced genomic perspective? The excision of individual genes from subterranean species (that are present in surface species) may indicate an adaptive response in the form of genome efficiency, in terms of the evolutionary economy of an organism’s proteome or metabolic load and particularly so in low nutrient environments (Wagner 2005; Bragg and Wagner 2009; Hessen et al. 2010). However, an absence by itself may not be informative with regard to how that genetic information was excised, or why. The maintenance of a full quiver of functional photoreception and eye development genes in an eyeless beetle living in aphotic environment with exceedingly limited outbreeding potential and no physical connection to surface species could imply a variety of processes. First, that there is negligible physiological cost in maintaining a functional visual system when it is not required, which would suggest that direct selection is not operating on the visual system in aphotic habitats—but see Moran et al. (2014, 2015) for arguments in favor of natural selection conserving physiological energy in Mexican cave fish. Second, that the visual system is constrained by developmental ontogeny and is required for alternate multiple functions—such pleiotropic processes would be indicative of indirect natural selection and may involve functions that we are not aware of. An explanatory example is the developmental re-engineering of the Drosophila Bolwig organ, which initially serves as the larval-stage visual system, but ultimately engages in deep brain circadian photo-entrainment in the adult-stage (Buschbeck and Friedrich 2008; Friedrich 2008, 2013b). This is just one example of extra-ocular photoreception function (reviewed by Tierney et al. 2017). Third, several photoreceptor genes may have pleiotropic functions in a variety of other developmental pathways that are unrelated to vision (e.g., Crumbs influences epithelial cell polarity, wing venation, and growth regulation of D. melanogaster; Spannl et al. 2017). In this latter example, the gene encodes multiple unique isoforms due to alternative splicing; the isoform Crumbs_C has a role in prevention of light-dependent retinal degeneration (Spannl et al. 2017). Similarly, the D. melanogaster gene Chaoptin encodes five transcripts and five unique isoforms that are involved in several phenotypes associated with the rhabdomere of photoreceptor cells as well as tergites of the mesothorax (see http://flybase.org/reports/FBgn0267435.html accessed March 2018). Such genes are not solely expressed in the eye and, therefore, should maintain their structural integrity as a result of purifying selection, though it is possible that exons that are specific to eye function may potentially show relaxed selection under the neutral evolution model. Finally, the gene may retain its structural integrity, but never be translated. Alternatively, there may be a complete absence of any selective processes operating on genes that are specific to the visual system given that they are unlikely to serve any selective advantage in an aphotic environment. The lack of purifying selection results in the accumulation of missence mutations (insertion/deletion frame-shifts or aberrant stop codons) that alter the open reading frame and result in improper translation of proteins and potentially loss of gene function. Under neutral evolution scenarios and given enough evolutionary time, genetic drift and the continual accrual of deleterious mutations might reasonably be expected to culminate in the development of functionless genes (pseudogenes) and ultimately regressed phenotypes (reviewed by Jeffery 2009; Wilkens 2010). Cartoon examples of these outcomes of “selection in absentia” are provided in Fig. 5. Fig. 5 View largeDownload slide Missence mutations indicative of neutral evolution. Hypothetical examples of independent or shared indels, frameshifts, and aberrant stop codons in a targeted vision gene. Such missence mutations would alter the open reading frame sequence inherited from ancestral species that inhabit surface water bodies and possesses functional eyes. Image credits: Chris Watts; www.cpbr.gov.au. Fig. 5 View largeDownload slide Missence mutations indicative of neutral evolution. Hypothetical examples of independent or shared indels, frameshifts, and aberrant stop codons in a targeted vision gene. Such missence mutations would alter the open reading frame sequence inherited from ancestral species that inhabit surface water bodies and possesses functional eyes. Image credits: Chris Watts; www.cpbr.gov.au. Summary The development of a comprehensive genomic understanding of the dytiscid beetles of the Yilgarn region of Western Australia should serve as a blueprint for future integrative research. Data sources from a diverse range of components can be then overlain in order to assess extrinsic (light environment) and intrinsic factors (functional gene modifications; behavioral activity patterns; optical, neural, and chemosensory morphology) influencing the regressive loss of vision among animals in order to assess their reciprocal influence on organismal fitness (Tierney et al. 2017). The collection of high-resolution data from each component should provide improved statistical rigor for comparative hypothesis-testing. Indeed, research has recently begun to branch into the photosensitive behavior of eyeless beetle species (Langille et al. 2018) for which the genomics of vision genes are being developed. The benefits that a species rich comparative system provide relate to an enhancement of the comparative method, primarily with regard to statistical power and the ability to self-assess confidence (or doubts) in our findings. Due to their unusual natural history, with multiple independently-evolved stygobionts, these Australian dytiscid species are expected to provide insights on the genetic processes of regressive evolution at a massively parallel scale that is currently unheralded. Acknowledgments Thanks are extended to symposium organizers Megan Porter and Lauren Sumner-Rooney. The symposium was generously sponsored by the Company of Biologists (http://www.biologists.com); the Palaeontological Association (PA-GA201707); the American Microscopical Society; the Crustacean Society; and the SICB divisions DEDB, DEE, DIZ, DNB, and DPCB. We thank Chris Watts for the use of his photograph and two anonymous reviewers for constructive comments on this manuscript. Funding This work was supported by an Australian Entomological Society Research Seeding Grant [to S.M.T.], an Australian Research Council Discovery Grant [DP120102132 to S.J.B.C., W.F.H., and A.D.A], and University of Adelaide research support funds. Supplementary data Supplementary data available at ICB online. References Abrams KM , Guzik MT , Cooper SJB , Humphreys WF , King RA , Cho J-L , Austin AD. 2012 . What lies beneath: molecular phylogenetics and ancestral state reconstruction of the ancient subterranean Australian Parabathynellidae (Syncarida, Crustacea) . Mol Phylogenet Evol 64 : 130 – 44 . 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Integrative and Comparative BiologyOxford University Press

Published: Jun 7, 2018

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