Severe inbreeding and gene loss in the historical and extant population of the critically endangered Devils Hole pupfish

Severe inbreeding and gene loss in the historical and extant population of the critically endangered Devils Hole pupfish | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Severe inbreeding and gene loss in the historical and extant population of the critically endangered Devils Hole pupfish View ORCID Profile David Tian , Bruce J. Turner , View ORCID Profile Christopher H. Martin doi: https://doi.org/10.1101/2021.08.13.456274 David Tian 1 Department of Integrative Biology and Museum of Vertebrate Zoology, University of California , Berkeley, Berkeley, CA 94720 USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for David Tian Bruce J. Turner 2 Department of Biological Sciences , Virginia Tech, Blacksburg, VA 24061 USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Christopher H. Martin 1 Department of Integrative Biology and Museum of Vertebrate Zoology, University of California , Berkeley, Berkeley, CA 94720 USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Christopher H. Martin For correspondence: chmartin{at}berkeley.edu Abstract Full Text Info/History Metrics Preview PDF Abstract Small populations with limited geographic distributions are predicted to be threatened by inbreeding and lack of genetic diversity, both of which may negatively impact fitness and exacerbate population decline. One of the most extreme natural examples is the Devils Hole pupfish ( Cyprinodon diabolis ), an iconic and critically endangered species with the smallest known habitat range of any vertebrate. This imperiled species has experienced severe declines in population size over the last thirty years and suffered major, repeated bottlenecks in 2007 and 2013, when the population sunk to 38 and 35 individuals, respectively. Here we sequenced contemporary and historical genomes of Devils Hole and neighboring Death Valley and Ash Meadows desert pupfishes to examine the genomic consequences of small population size. We found extreme inbreeding ( F ROH = 0.71 - 0.82) and increased genetic load in the Devils Hole pupfish. We also document unique fixed loss-of-function (LOF) alleles and deletions in genes associated with sperm motility, stress, and hypoxia within the extant Devils Hole pupfish population that likely reduce fitness. Comparisons between contemporary samples (2008 – 2012) and a genome sequenced from a 1980 formalin-fixed museum specimen suggest that inbreeding has increased 6% as the population has declined, but that many putatively deleterious variants have been segregating in the population since at least 1980. This includes a fixed early stop codon in cfap43 ( n = 8/8 samples), which is associated with sperm flagellum defects and causes infertility in humans and mice. Out of ninety-four unique deletions, fifteen were detected within 2 kb of annotated genes. Five have roles in physiological responses to hypoxia and mitochondrial activity, such as redd1 ( n = 7/7 samples), suggesting impaired hypoxia tolerance in this species despite the low oxygen concentrations of Devils Hole. We thus document one of the most extreme inbreeding events in a natural population and a set of candidate deleterious variants to inform management and potential genetic rescue in this conservation icon. Introduction Due to the declining population sizes of many species and increasing isolation due to anthropogenic habitat fragmentation and climate change, understanding the extent and nature of genetic threats in small populations is essential for predicting and increasing population persistence and resiliency ( Frankham 1995 ). Small and isolated populations are predicted to suffer from inbreeding depression, a reduction in fitness caused by the increased homozygosity of deleterious recessive alleles or overdominant loci ( Charlesworth and Charlesworth 1999 ; Charlesworth and Willis 2009 ). Prolonged population decline can result in increased long-term extinction risk due to stochastic demographic events ( Melbourne and Hastings 2008 ), reduced genetic variation for adaptation ( Kohn et al . 2006 ), and decreased efficacy of purifying selection to overpower drift and purge deleterious variants ( Kimura 1957 ) (reviewed by ( Frankham 1995 )). Many examples of reduced genetic diversity and inbreeding depression have been documented in the wild such as Florida panthers ( Puma concolor ) ( Johnson et al . 2010 ), Isle Royale wolves ( Canis lupus ) ( Robinson et al . 2019 ), and mountain gorillas ( Gorilla beringei ) ( Xue et al . 2015 ). Inbreeding associated population decline has been identified in the context of ancient bottlenecks ( Palkopoulou et al . 2015 ; Rogers and Slatkin 2017 ) and on recent timescales ( Robinson et al . 2019 , 2021 ). Nevertheless, identifying inbreeding depression and its genetic basis in wild populations remains challenging due to small sample sizes and a lack of genomic resources. Recent studies of mountain gorillas ( van der Valk et al . 2019 ) and Przewalski’s horses (Der Sarkissian et al . 2015) have also successfully leveraged museum specimens to measure temporal changes in inbreeding and genomic erosion. This is a powerful emerging approach because genomes from pre-decline museum specimens can serve as a baseline for estimating recent changes in inbreeding and genetic load ( Bi et al . 2013 ; Díez-Del-Molino et al . 2018 ) and ultimately assist in restoring genetic diversity to a population ( Bell et al . 2019 ). Traditionally, conservation genetics has relied on neutral molecular markers to measure genetic variation in wild populations as a way of assessing population health and extinction risk, due to positive correlations between heterozygosity and fitness ( Hansson and Westerberg 2002 ). Maintaining genome-wide genetic variation is crucial to preserving adaptive potential and preventing inbreeding depression in populations of conservation interest ( Kardos et al . 2021 ). However, several recent studies have suggested that genetic variation summary statistics do not necessarily accurately reflect population size or extinction risk and that we should also leverage genomics to assess functional genetic diversity and genetic load ( Díez-Del-Molino et al . 2018 ; Teixeira and Huber 2021 ). Genomics also allows for more accurate measurements of individual inbreeding relative to pedigree approaches and the opportunity to infer the genetic basis of inbreeding depression ( Kardos et al . 2016 ). Thus, a comprehensive understanding of the population and evolutionary dynamics of small population sizes in the wild from a genomic perspective is key to understanding the future of endangered populations and informing conservation management. Here we leverage the unique evolutionary and demographic history of the Devils Hole pupfish ( C. diabolis ) to investigate how isolation and recent population decline have shaped inbreeding depression and genetic load. While many desert pupfishes are generally isolated with low population sizes, none are as extreme as C. diabolis. The habitat of C. diabolis is widely believed to be the smallest in the world for a vertebrate (3.5m x 22m) ( Deacon et al . 1995 ) and the population has steadily declined since the late 1990s before reaching lows of 38 and 35 individuals in the spring of 2007 and 2013, respectively. Population viability analysis models in 2014 suggested that the median time to extinction is 26 years ( Beissinger 2014 ). Although this species was previously believed to be isolated in Devils Hole for 10,000 – 20,000 years ( Miller 1981 ), more recent genome-wide estimates suggest that Devils Hole may have been colonized most recently approximately 1-2 thousand years ago and suggest that gene flow among these desert oases is surprisingly common ( Martin et al . 2016 ; Martin et al . 2017 ; Martin and Höhna 2018 ; Martin and Turner 2018 ). Furthermore, extremophile conditions include a nearly constant temperature of 34°C ( Miller 1948 ; James 1969 ), no direct sunlight during the winter ( Riggs and Deacon 2002 ) which limits primary production and nutrient availability ( Wilson et al . 2001 ), and low dissolved oxygen levels near lethal limits for most fishes (2 – 3 ppm) (Gustafson, E.S. and Deacon, J.E. 1997; Riggs and Deacon 2002 ; Sackett et al . 2018 ). The continued persistence of C. diabolis in the hottest desert on earth in one of the most inhospitable habitats for fishes is nearly inconceivable. Despite being one of the world’s most vulnerable species, genetic analyses have so far been limited to mitochondrial ( Echelle and Dowling 1992 ), allozyme ( Echelle and Echelle 1993 ), retrotransposon ( Duvernell and Turner 1999 ), and RADseq ( Martin et al . 2016 ; Martin and Höhna 2018 ) approaches. Here we used resequenced whole genomes of C. diabolis and several closely related Cyprinodon desert pupfishes to investigate how isolation and small population size influence inbreeding and genetic load on a genome-wide scale and across time in this iconic symbol of conservation. Results Geography and population structure Principal components, admixture analyses, and genome-wide mean F st estimates ( C. diabolis / C. nevadensis and C. salinus = 0.31) indicate the presence of population structure among Death Valley desert pupfishes, corroborating previous results ( Martin et al . 2016 ) ( Fig. 1 ). Differences in individual inbreeding both between and within species also provide evidence for population structure. The C. diabolis population is highly inbred while C. nevadensis and C. salinus populations generally exhibited low to intermediate levels of inbreeding, measured by the cumulative fraction of the genome made up of runs of homozygosity (ROHs) ( Fig. 2A ). ROHs made up less than 10% of the genome in our C. nevadensis amargosae and C. nevadensis nevadensis samples, both relatively undisturbed natural spring populations. C. nevadensis shoshone and C. nevadensis pectoralis tended to have a higher F ROH than other C. nevadensis species, consistent with previous surveys that called to attention their small population size and need for protection ( Miller 1969 ) and the intensive management histories of these desert spring populations. Within a species, individuals from different spring populations often revealed contrasting levels of inbreeding, such as between the Indian Spring and School Spring populations of C. nevadensis pectoralis , indicating that isolation is strong between different springs with different management histories. Download figure Open in new tab Figure 1. Geography and genetic structure of desert pupfishes A) Photo of male C. diabolis individual by Olin Feuerbacher. B). Principle component analysis of desert pupfishes revealing genetic population structure. C) Map of Death Valley NP and Ash Meadows NWR sampling locations. Colors in PCA designate individuals from different species. D) Ancestry proportions across individuals in Death Valley NP, Ash Meadows NWR, and outgroup desert pupfishes estimated from a LD-pruned SNP dataset in ADMIXTURE with k = 4. Download figure Open in new tab Figure 2. Extreme inbreeding in the Devils Hole pupfish A) F ROH measured as the cumulative fraction of the genome made up of runs of homozygosity (ROHs) at least 100 kb long. F ROH was calculated for all Death Valley pupfish individuals with at least 8X coverage. B) Biannual census counts of C. diabolis population size over time. Bottlenecks in 2007 and 2013 reduced the population size down to low as 38 and 35 individuals, respectively. C) Distribution of ROH lengths across C. diabolis samples from different time points. Greater values of F ROH among recent C. diabolis samples relative to 1980 can be primarily attributed to large ROHs (4 – 10 Mb) that are predicted to have arisen recently due to inbreeding within the last 1-3 generations, corresponding with the 2007 bottleneck. Severe inbreeding in Devils Hole pupfish Strikingly, more than 70% of the C. diabolis genome consists of runs of homozygosity (ROHs), which is indicative of extreme inbreeding. Inbreeding can be identified and quantified through ROHs, which are long contiguous tracts of identical haplotypes inherited from a common ancestor ( Kardos et al . 2016 ). For context, this level of inbreeding is far greater than other documented studies of notable, endangered species such as the Isle Royale wolves ( Robinson et al . 2019 ) (< 50%), mountain gorillas (<40%) ( van der Valk et al . 2019 ), and extant tigers (<50%) ( Armstrong et al . 2021 ), with the exception of one population of lions from the Kathiawar Peninsula of India (90%) that had a population as low as 20 individuals in the early 20 th century ( de Manuel et al . 2020 ). The inbreeding observed within our 2008 - 2011 C. diabolis samples is ∼ 6% more severe than in our 1980 C. diabolis sample, which is consistent with the documented population decline that began in the mid 1990s and bottlenecks in 2007 and 2013 when the population size plummeted to 38 and 35, respectively ( Beissinger 2014 ). While shorter ROHs indicate mating between distant relatives or longer-scale historical processes, long ROHs are indicative of recent inbreeding. We can estimate the mean number of generations back to the common ancestor of these homologous sequences based on the expectation that recombination breaks down long ROHs over time ( Thompson 2013 ). We focused our attention on longer ROHs for which we have more confidence in timing and investigated long ROHs that are present in our 2008 – 2011 samples but not our 1980 sample. These long ROHs ranged from 4 – 10 Mb and are estimated to have originated only a few generations prior, suggesting that while the population began to decline a decade earlier, much of the additional inbreeding occurred more recently, due to the 2007 bottleneck. Our results illustrate that extreme isolation and prolonged small population size have driven C. diabolis to become one of the most inbred wild populations surviving today. Recent population bottlenecks increased F ROH , but it was already extremely inbred prior to the recent population decline in the 1990s. Highest genetic load in Devils Hole pupfish To measure genetic load, we used three summary statistics: the number of variants, derived alleles, and derived homozygous genotypes per individual, per site ( Figure 3 ). We measured these statistics for synonymous, non-synonymous, and loss-of-function (LOF) mutations. C. diabolis had significantly more non-synonymous derived alleles ( P = 0.0423) and derived homozygous genotypes than our Cyprinodon desert outgroups ( P = 0.0258, Tukey’s HSD tests). Furthermore, C. diabolis had significantly more LOF variants than Cyprinodon desert outgroups ( P = 0.0010, Tukey’s HSD test) and Cyprinodon diabolis, nevadensis , and salinus all had more LOF derived alleles than outgroups ( P = 8.36 x 10 -5 ; P = 0.0012; and P = 0.0229; Tukey’s HSD test, respectively). We found a similar pattern for LOF homozygous derived genotypes, although in this case C. diabolis also had significantly more LOF homozygous derived genotypes than C. nevadensis ( P = 0.0036, Tukey’s HSD test). Download figure Open in new tab Figure 3. Genetic load across Cyprinodon species The number of synonymous, non-synonyomous, and loss-of-function mutations per site, per individual. Genetic load was measured in terms of three proxies: number of variants, number of derived alleles, and number of derived homozygous genotypes. The number of derived alleles per individual can be used to quantify load under an additive model while the number of derived homozygous genotypes can be used to quantify load under a recessive model. Results were scaled by the number of genotyped sites per individual to account for varying coverage. Loss-of-function mutations are those that encode a premature stop codon. Letters indicate which pairwise comparisons using a Tukey’s HSD test were significant. Fixed loss-of-function variants unique to Devils Hole We searched for specific genetic variants that are predicted to be deleterious, may explain C. diabolis population decline, and can serve as a list of candidate deleterious variants to screen for potential genetic rescue ( Table S1 ). We focused our attention on LOF SNPs and deletions unique to C. diabolis , which are expected to be deleterious and likely pose a threat by disrupting gene function. View this table: View inline View popup Table 1: Unique deletions in C. diabolis tend to be involved in hypoxia Frequencies are based on samples for which there is enough coverage to determine whether the deletion is present or absent. Highlighted genes have functions related to hypoxia and mitochondrial stress. See extended data for details on intermediate scenarios where random spurious reads span the deletion or there is not enough coverage to make a definitive call of deletion presence or absence. We found 16 predicted LOF SNPs that were primarily premature stop codons, including several within genes that potentially reduce fecundity and resistance to disease and stress ( Table S1 ). These included ora1 , a zebrafish olfactory receptor which is predicted to be a reproductive pheromone because it induces increased oviposition frequency ( Behrens et al . 2014 ) and trim25 , an ubiquitin ligase that promotes innate immune function in zebrafish ( Jin et al . 2019 ). We also found a gained premature stop codon in cfap43 , a protein involved in the conserved structure and function of the sperm flagellum axoneme and implicated in the multiple morphological abnormalities of the flagella (MMAF) infertility phenotype ( Tang et al . 2017 ; Coutton et al . 2018 ). In nine men with MMAF that had homozygous mutations in cfap43 , five had gained a premature stop codon ( Coutton et al . 2018 ). Intriguingly, reduced sperm motility and abnormal sperm morphology is also an inbreeding phenotype found in Florida panthers ( Johnson et al . 2010 ), East African and Indian lions ( Wildt et al . 1987b ), wild and captive bred cheetahs ( Wildt et al . 1983 , 1987a ) and Dryas monkeys ( van der Valk et al . 2020 ), which have a homozygous LOF mutation in sept12 that causes a defective sperm annulus ( Kuo et al . 2012 ). We also searched for variants that may be responsible for recent increased inbreeding depression post 1980 by identifying variants that were heterozygous in our 1980 sample but were homozygous derived in our more recent samples after 2008 (Table S2). We focused our attention on LOF and non-synonymous variants. We found a premature stop codon in dhx57 , a putative ATP dependent RNA helicase (UniProt 2008), and non-synonymous mutations in arhgap18 , a GTPase-activating protein that modulates cell signaling ( Maeda et al . 2011 ), and galnt3 , a GalNAc transferase implicated in abnormal calcium phosphate deposits in various tissues ( Sun et al . 2016 ). Moreover, we found two non-synonymous mutations that both occurred in itprid2 , which encodes a protein that serves as a sperm surface antigen involved in cleavage of the fertilized oocyte ( Javed and Naz 1992 ). Fixed deletions unique to Devils Hole We searched for unique homozygous deletions in the C. diabolis genome that may negatively impact fitness. We identified 94 deletions unique to C. diabolis and focused our attention on the 15 deletions within 2 kb of any annotated gene. Surprisingly, 5 of the 15 deletions were involved in responses to hypoxia, mitochondrial activity, and oxidative stress (Fig. 4). Hypoxia leads to a wide suite of adaptive cellular responses that include angiogenesis and erythropoiesis, shifts to anaerobic metabolism, inhibition of translation, degradation of misfolded proteins, and regulation of nutrient use and cell fate ( Lee et al . 2020 ). We found an 81 bp deletion in the promoter of redd1 , which is activated by HIF1 ( DeYoung et al . 2008 ). This deletion knocks out the TATA box and a HRE recognition site where HIF1 is predicted to bind. During hypoxia, redd1 inhibits mTORC1 ( Brugarolas et al . 2004 ; DeYoung et al . 2008 ) through the TSC1/TSC2 tumor suppressor complex to conserve energy and prevent the accumulation of misfolded proteins. Intriguingly, upregulation of a homolog of REDD1 ( ddit4L / redd2 ) has been implicated in adaptation to hypoxia in shortfin mollies ( Poecilia mexicana ) from H 2 S rich springs ( Barts 2020 ) and high-altitude deer mice ( Peromyscus maniculatus ) (Rochette 2021 pers. comm.). Further evidence that C. diabolis is unable to properly inhibit protein translation through mTOR comes in the form of a fixed SNP that leads to an early stop codon in tbc1d7 , a third core subunit of the TSC1/TSC2 complex whose knockdown leads to decreased association between TSC1 and TSC2 and thus increased mTORC1 signaling ( Dibble et al . 2012 ). Several deletions also likely result in either no protein transcribed or truncated non-functional proteins. Apeh , an enzyme acylpeptide hydrolase which destroys oxidatively damaged proteins, contains a fixed 837 bp deletion of exon 13 ( Gogliettino et al . 2014 ; Riccio et al . 2015 ). Trim39 , which in humans has been shown to regulate cell cycle progression and DNA damage responses, contains a fixed deletion of the last 254 bp of the last exon ( Zhang et al . 2012b ; a). However, trim39 has undergone multiple rounds of duplications in several teleost lineages; in zebrafish it is known as bloodthirsty ( bty ) and is involved in erythropoiesis ( Yergeau et al . 2005 ; van der Aa et al . 2009 ). There is also a 283 bp deletion containing the start codon for slc25a42 , a mitochondrial transporter of coenzyme A ( Fiermonte et al . 2009 ; Zallot et al . 2013 ). Mutations in slc25a42 have been associated with mitochondrial myopathy and lactic acidosis in humans ( Shamseldin et al . 2016 ; Iuso et al . 2019 ). slc25a42 knockdowns in zebrafish cause severe muscle abnormalities that include dorsal curvature, bent tails, and early motor defects ( Shamseldin et al . 2016 ). Discussion We document extreme inbreeding in the critically endangered Devils Hole pupfish and identify a set of candidate deleterious structural and SNP variants to inform future genetic restoration. We show that C. diabolis is highly inbred, more so than all other Death Valley and Ash Meadows desert pupfishes and nearly all other known examples of inbreeding in the wild. By sequencing a historical museum specimen, we found that inbreeding has recently increased 6% from 1980 levels as the population has declined due to the presence of large (4 – 10 Mb) ROHs. Longer ROHs tend to have higher densities of deleterious alleles and larger fitness effects ( Stoffel et al . 2021a ). Although we were unable to directly measure fitness, the increase in inbreeding of 6% from 1980 to 2008 – 2012 likely resulted in a substantial reduction in fitness. Indeed, previous studies have suggested that increases in F ROH have strong negative effects on fitness; in Soay sheep an increase in F ROH by 10% resulted in a 60% decline in fitness ( Stoffel et al . 2021b ) while in helmeted honeyeaters, a 9% increase in homozygosity reduced lifetime reproductive success by 87-90% ( Harrisson et al . 2019 ). The already substantial amount of inbreeding seen as early as 1980 suggests that C. diabolis has likely frequently experienced population bottlenecks in the past prior to their recent population decline and bottlenecks. We know of at least one period of population decline that occurred in the late 1960s to early 1970s when increased groundwater extraction in Ash Meadows reduced water levels and jeopardized a shallow shelf in Devils Hole necessary for feeding and spawning ( Deacon et al . 1995 ), leading to a landmark U.S. Supreme Court case over water rights ( Cappaert v. United States 1976). While additional inbreeding has likely contributed to lower fitness and population decline, it is also important to note that population decline was amplified in 2004 by extreme rain that scoured the shallow spawning shelf in Devils Hole and resulted in the accidental trapping deaths of at least 72 individuals due to a flash flood ( Beissinger 2014 ; Echelle and Echelle 2020 ). The lek-breeding system of Cyprinodon pupfishes also likely produces substantial reproductive skew every generation ( Arnold 1972 ; Kodric-Brown 1977 ). C. diabolis harbors higher genetic load than other desert pupfishes for nearly all classes of variation. However, load was generally not significantly different among Cyprinodon diabolis / nevadensis / salinus with the exception of the number of homozygous derived LOF genotypes, for which C. diabolis had significantly more than C. nevadensis. This implies that C. diabolis has a substantial genetic load especially if the LOF variants are recessive and strongly deleterious, and that extinction risk likely remains high ( Kyriazis et al . 2021 ). The number of homozygous derived genotypes for LOF variants quantifies load under a recessive model ( Henn et al . 2015 , 2016 ), which is appropriate given that selection and dominance coefficients are generally inversely related ( Simmons and Crow 1977 ; Agrawal and Whitlock 2012 ). Our evidence of higher genetic load in C. diabolis supports previous hypotheses of high load in this species due to its isolation and small population size, short generation time ( Chernoff 1985 ; Deacon et al . 1995 ), and the observation that a refuge population of C. diabolis that was invaded by a few C. nevadensis individuals experienced rapid shifts in the gene pool to C. nevadensis alleles, leading to speculations of mutational meltdown ( Lynch et al . 1995 ; Martin et al . 2012 ). Although recent studies have suggested that small populations generally have lower load ( Xue et al . 2015 ; Robinson et al . 2018 ; Grossen et al . 2020 ), purging is expected to occur over long evolutionary timeframes and thus populations that have experienced recent severe population contraction are likely to have relatively high genetic load as deleterious variants reach fixation before purging removes them, particularly if prior population sizes were much larger ( van der Valk et al . 2021 ). Degradation of hypoxia and reproductive pathways in C. diabolis We found deleterious variants associated with reproduction and hypoxia and mitochondria stress genes. In particular, we found LOF and non-synonymous SNPs associated with sperm morphology and function ( cfap43, itprid2 ). Deletions have thus far been rarely studied or quantified in conservation genetics. However, analysis of woolly mammoth genomes from different time points found that a sample dated close to the time of extinction had accumulated more homozygous deletions ( Rogers and Slatkin 2017 ), suggesting that they may be an understudied genetic threat to endangered populations ( Díez-Del-Molino et al . 2018 ). We found that unique, fixed deletions in C. diabolis tended to be associated with hypoxia and mitochondrial stress, a known environmental stressor in the system. Our results suggests that C. diabolis is poorly equipped to physiologically deal with the stress of low dissolved oxygen in Devils Hole and that putatively deleterious mutations in key genes likely hamper reproduction and population growth. Inbreeding depression often influences phenotypes such as survival, reproduction, and resistance to disease and environmental stress ( Keller and Waller 2002 ); previous studies noted that C. diabolis has low fecundity ( James 1969 ; Liu, R.K. 1969), low egg viability and juvenile survivorship ( Deacon et al . 1995 ), and lays more eggs at lower temperatures (28 °C) compared to the higher constant temperature of 33 °C in Devils Hole ( Burg et al . 2019 ). These results highlight the importance of investigating deletions and structural variants to more comprehensively understand deleterious variation in endangered populations. Adaptation to the Devils Hole environment? However, we cannot rule out that some of these fixed variants are potentially the result of local adaptation, as it is extremely difficult to distinguish between selection and strong genetic drift in small populations because both processes leave similar signatures in allele frequencies ( Leigh et al . 2021 ). One possibility is that repeated adaptations have accumulated in hypoxia pathways for the unique selective environment of Devils Hole relative to all other springs. However, we think it more likely that after the first LOF deletion disabled the entire pathway, additional LOF mutations accumulated without functional effects in a neutral manner. Future transcriptomic work will improve our understanding of how functional hypoxia pathways are in C. diabolis . Did mutational meltdown cause the recent population decline? The DHP population began to decline in the 1990s from historical populations sizes of 200 – 500 individuals to population sizes of less than 100 each year for still unknown reasons. One possible explanation is that changes in environmental conditions, such as reduced nutrient inputs due to the elimination of wild sheep grazing around Devils Hole after the installation of razor wire fencing around the perimeter. Historical accounts of Devils Hole report thick mats of green macroalgae possibly due to ample manure, rather than the current ecosystem dominated by less-nutritious cyanobacterial mats and possibly decreased dissolved oxygen levels ( Madinger et al . 2016 ). Alternatively, previous genetic analyses have speculated that the population has a high genetic load that has led to “mutational meltdown” based on dramatic shifts towards C. nevadensis ancestry in a C. diabolis x C. nevadensis hybrid refuge population ( Martin et al . 2012 ). Our historical and modern analyses suggest that severe inbreeding existed before population decline in the 1990s, but that inbreeding and its negative impacts on the population’s fitness has likely been exacerbated due to recent population declines. Conclusion Our study adds to a growing number of studies of inbreeding in wild populations in which deleterious mutations have been predicted from sequencing data ( Robinson et al . 2019 ; Grossen et al . 2020 ). These studies also indicate that inbreeding depression is stronger in the wild than previously thought. The demographic history and genome-wide measures of genetic load and deleterious variation in the Devils Hole pupfish suggest that the population remains in danger. Our estimates of effective population sizes based on the harmonic mean of biannual census data (Ne Spring = 122, Ne Fall = 209) suggest that C. diabolis has an effective size far below suggested minimums for the maintenance of sufficient genetic variation for adaptive capacity ( Franklin 1980 ; Reed et al . 2003 ; Traill et al . 2007 ). Further genomic sampling in the future will better inform our understanding of the mutation load and the genetic basis of inbreeding depression in this iconic conservation symbol. Methods Samples and sequencing We sequenced 44 whole genomes that encompass C. diabolis , and many of the C. nevadensis and C. salinus Death Valley pupfishes spanning multiple independent springs, along with several further removed outgroups from various areas of California, Arizona, and Mexico. Of the 23 C. diabolis genomes, 8 were from historical museum samples, spanning 1937 – 1980 while the rest were collected between 2008 - 2012. Given the critically endangered status of C. diabolis , NPS and USFWS staff collected dead specimens found during routine checks in this period. C. nevadensis, C. salinus, and outgroup samples were collected in the early 1990s ( Duvernell and Turner 1998 ). Samples were sequenced to 10x coverage on 150 PE runs using an Illumina Novaseq. Historical and several degraded C. diabolis tissues were prepared using Swi ftprep library kits. For sampling dates, see extended data. Alignment and filtering Raw reads were mapped from 44 individuals to the Cyprinodon brontotheroides reference genome (v 1.0; total sequence length = 1,162,855,435 bp; scaffold N50 = 32 Mbp) with bwa-mem (v 0.7.12; ( Li 2013 )). Duplicate reads were identified using MarkDuplicates and BAM indices were created using BuildBamIndex in the Picard software package (( http://picard.sourceforge.net ; v 2.0.1). We followed the best practices guide recommended in the Genome Analysis Toolkit (v 3.5; ( DePristo et al . 2011 )) to call and refine our single nucleotide polymorphism (SNP) variant dataset using the program HaplotypeCaller. SNPs were filtered based on the recommended hard filter criteria (i.e. QD 60; MQ<40; MQRankSum < - 12.5; ReadPosRankSum < −8 because we lacked high-quality known variants. Variants in poorly mapped regions were removed with a mask file generated from the program SNPable (( Li 2009 ); k-mer length =50, and ‘stringency’=0.5). Variants were then filtered by minimum (3) and maximum (315) depth based on recommendations ( Li 2014 ). Variants were additionally filtered to remove SNPs with a minor allele frequency below 0.05, genotype quality below 20, or containing more than 50% missing data across all individuals at the site using bcftools (v 1.6; ( Li 2011 )) and vcftools (v.0.1.15; ( Danecek et al . 2011 )). Our flexible threshold of 50% missing data was necessary given the degraded nature of several samples. Our final dataset contained 6,295,414 SNPs. Population structure We pruned SNPs in strong linkage disequilibrium using the LD pruning function (--indep-pairwise 50 5 0.5) in PLINK (v 1.9; ( Purcell et al . 2007 )) leaving 1.6 million variants. We then characterized population structure with two approaches. First, we used PLINK to conduct principal component analysis. Second, we used ADMIXTURE (v.1.3.0; ( Alexander et al . 2009 )) to assign individuals to variable numbers of population clusters (K = 1-20). We used the subset parameter in PLINK to randomly select 100,000 SNPs for analysis. F st between C. diabolis / C. nevadensis and C. salinus was calculated genome-wide per variant site on the 6.3 million variant dataset using the weir-fst-pop function in vcftools (v.0.1.15; ( Danecek et al . 2011 )). Several samples were excluded from downstream analyses due to a low percentage of reads mapping to the reference genome and properly paired reads, presumably due to degradation. These include 7 out of 8 historical samples sequenced with the exception of one high quality sample (DHP1980-5). Several contemporary samples (DHP54904, DHP54908, DHP54910, DHP54914) were also excluded due to low quality. DHP54909 was excluded because it did not cluster with the remaining nine C. diabolis samples after observing the PCA. DHP54908, DHP54909, and DHP54910 were all collected during the summer of 2009 which may have led to degradation due to the summer heat in Death Valley. The genotypes of unique fixed deleterious variants and deletions were typically invariant or missing in degraded samples. Missing deletions and invariant sites among these samples may be due to degraded samples being more susceptible to contamination by environmental pupfish DNA during the amplification step of sequencing. For DHP54920, a duplicate genome was sequenced, and we only included DHP54920_N2 (higher coverage) in these analyses. We removed DHP54911 due to too much missing data (> 89%). Out of 8 historical museum samples only one sample from 1980 (DHP1980-5) was successfully sequenced. While reads were obtained from the remaining historical samples, these samples had a low percentage of reads mapping and properly paired reads and tended to be low coverage. This 1980 sample clusters with our high quality 2008 – 2012 samples. Population size Census data for 1972 – Spring 2013 was acquired from Beissinger 2014 . Data for subsequent counts was based on released NPS news reports. Variance effective population size was calculated as the harmonic mean of spring (Ne Spring ) and fall (Ne Fall ) population counts over time. Runs of homozygosity Runs of homozygosity (ROHs) were identified using the BCFtools/ROH command, which uses a hidden Markov model to identify autozygous portions of the genome from genetic variation data ( Narasimhan et al . 2016 ). For each species within the Death Valley species complex, we analyzed samples with at least 8X coverage. Samples were run individually and allele frequency was estimated from the AC and AN values within the INFO field of the VCF file. To calculate the cumulative fraction of the genome consisting of ROHs, the identified ROHs were sorted, summed, and divided by the total size of the genome (1,162,855,435 bp). ROHs with a size below 100 kb or a quality score below 50 were filtered out. We calculated the proportion of the genome that was made up of ROHs at least 100 kb long ( F ROH ) for Death Valley samples with at least 8X coverage. Timing of inbreeding We estimated the mean number of generations back to the common ancestor of homologous sequences with the following equation: g = 100 / 2*ROH length (cM), where g is the number of generations ( Thompson 2013 ). Here we assume an average recombination rate across the genome of ∼ 4.6 cM/Mb based on an estimated genetic map length of 5330 cM ( St. John et al . 2021 ) and genome length of 1.16 Gb in C. brontotheroides ( Richards et al . 2021 ). Measuring genetic load We categorized mutations in coding regions with regards to their effect on the amino acid sequence and whether the alleles were ancestral or derived with respect to the C. brontotheroides genome as the reference outgroup. We used Snpeff ( Cingolani et al . 2012 ) to identify variants as either loss-of-function (LOF) or non-synonymous (NSYN) to measure genetic load. LOF variants were conservatively defined as SNPs that resulted in a premature stop codon following ( Robinson et al . 2016 , 2018 ), which are expected to be less prone to misannotation ( de Valles-Ibáñez et al . 2016 ). We did not consider splice variants due to possible transcript differences across Cyprinodon species. We also did not include stop loss nor start loss variants in our measurements of load as stop loss variants are expected to have less important phenotypic effects ( Richards et al . 2015 ) and start loss variants are difficult to assess due to potential alternative translational initiation at other start sites. Genetic load was measured in terms of three proxies: number of variants, number of derived alleles, and number of derived homozygous genotypes. The number of derived alleles per individual can be used to quantify load under an additive model while the number of derived homozygous genotypes can be used to quantify load under a recessive model. Results were scaled by the number of genotyped sites per individual to account for varying coverage. We assessed whether differences in measures of genetic load among the four species groups were significant using an ANOVA in R and used pairwise Tukey’s HSD tests in R to test whether inter-species measurements of load differed. Unique deleterious variants We used the following criteria to identify unique putatively deleterious variants: (i) homozygous, (ii) predicted to be loss-of-function or deleterious based on a Snpeff predicted impact of “HIGH” ( Cingolani et al . 2012 ) (start codon loss, stop codon gain, stop codon loss, splice acceptor site variant, splice donor site variant) and (iii) present in at least our five higher quality C. diabolis samples (including our 1980 sample) and absent in all other non- C. diabolis samples in our dataset. To find unique variants that may be responsible for increased inbreeding depression post 1980, we also identified loss-of-function and non-synonymous variants that were invariant in C. nevadensis , C. salinus , and outgroups, but heterozygous in DHP1980-5 and homozygous derived in at least the higher quality more recent 2008-2012 C. diabolis samples. Unique deletions We identified structural variation in the form of deletions that were unique to C. diabolis using DELLY (v0.8.3) ( Rausch et al . 2012 ) following similar criteria as above (i and iii). We searched for deletions that were present in DHP1980-5, DHP54903, DHP54913, DHP54917, or DIAB54919, and not present in non- C. diabolis samples. Deletions that were exceptionally large and presumably artifacts were checked for accuracy in IGV and subsequently removed. We focused our attention on deletions within 2 kb of an annotated gene, based on annotations of the C. brontotheroides genome ( Richards et al . 2021 ). Deletions were confirmed to be unique to C. diabolis by aligning bam files spanning the deletion in both C. diabolis and non- C. diabolis samples and confirming presence or absence, respectively. We analyzed whether deletions spanned exons, introns, or regulatory regions by blasting deleted sequences against the C_variegatus-1.0 (GCF_000732505.1) assembly on Ensembl (release 102; ( Howe et al . 2021 )). Author Contributions DT wrote the manuscript and conducted all analyses. BJT and CHM collected the samples. DT and CHM contributed to the development of ideas presented in the study and revised the manuscript. All authors edited and approved the manuscript. Competing interests The authors declare no competing interests. Data and materials availability Genomic sequence data will be archived at NCBI. Additional data will be deposited on the Dryad Digital Repository. All scripts are available on Github ( https://github.com/tiandavid/ ). Supplemental Figures and Tables View this table: View inline View popup Table S1. Unique, loss-of-function and deleterious variants in C. diabolis Loss-of-function variants that are invariant (0/0 or ./.) in C. nevadensis , C. salinus , and outgroups, but variant in at least higher quality C. diabolis samples. The frequencies of variants among C. diabolis individuals with genotype information at the given site are shown. DHX57 is heterozygous in our 1980 sample. See extended data for more information on the specific genotypes of individuals. View this table: View inline View popup Table S2. Unique, putative variants associated with inbreeding depression in C. diabolis Loss-of-function and non-synonymous variants that are invariant (0/0 or ./.) in C. nevadensis , C. salinus , and outgroups, but heterozygous (0/1) in DHP1980-5 and homozygous derived (1/1) in at least the higher quality more recent 2008-2012 C. diabolis samples. The frequencies of variants among C. diabolis individuals with genotype information at the given site are shown. Note that there are two separate non-synonymous variants present in itprid2 . See extended data for more information on the specific genotypes of individuals. Acknowledgements We thank members of the Martin lab for valuable comments and discussions; Olin Feuerbacher for providing a photo of C. diabolis ; T. Echelle for providing specimens of C. n. pectoralis from Indian Spring; Lee Simons, U.S. Fish and Wildlife Service, and National Park Service for C. diabolis samples and permits; and the University of California, Berkeley for computational resources. This work was funded by the U.S. Fish and Wildlife Service, National Park Service, National Science Foundation DEB CAREER grant #1749764, National Institutes of Health grant 5R01DE027052-02, and the University of California, Berkeley to CHM. DT was supported by a National Science Foundation Graduate Research Fellowship (DGE 1752814). References 1. ↵ van der Aa L. M. , J.-P. Levraud , M. Yahmi , E. Lauret , V. Briolat , et al. , 2009 A large new subset of TRIM genes highly diversified by duplication and positive selection in teleost fish . BMC Biol 7 : 7 . https://doi.org/10.1186/1741-7007-7-7 OpenUrl CrossRef PubMed 2. ↵ Agrawal A. F. , and M. C. Whitlock , 2012 Mutation Load: The Fitness of Individuals in Populations Where Deleterious Alleles Are Abundant . Annual Review of Ecology, Evolution, and Systematics 43 : 115 – 135 . https://doi.org/10.1146/annurev-ecolsys-110411-160257 OpenUrl 3. ↵ Alexander D. H. , J. Novembre , and K. Lange , 2009 Fast model-based estimation of ancestry in unrelated individuals . Genome Res 19 : 1655 – 1664 . https://doi.org/10.1101/gr.094052.109 OpenUrl Abstract / FREE Full Text 4. ↵ Anthony A. Echelle and Alice F. Echelle , 2020 Cyprinodontidae: Pupfishes, in Freshwater Fishes of North America Characidae to Poeciliidae , Johns Hopkins University Press . 5. ↵ Armstrong E. E. , A. Khan , R. W. Taylor , A. Gouy , G. Greenbaum , et al. , 2021 Recent Evolutionary History of Tigers Highlights Contrasting Roles of Genetic Drift and Selection . Molecular Biology and Evolution 38 : 2366 – 2379 . https://doi.org/10.1093/molbev/msab032 OpenUrl 6. ↵ Barts , N. , 2020 Comparative physiology and the predictability of evolution in extreme environments 7. ↵ Behrens M. , O. Frank , H. Rawel , G. Ahuja , C. Potting , et al. , 2014 ORA1, a zebrafish olfactory receptor ancestral to all mammalian V1R genes, recognizes 4-hydroxyphenylacetic acid, a putative reproductive pheromone . J Biol Chem 289 : 19778 – 19788 . https://doi.org/10.1074/jbc.M114.573162 OpenUrl Abstract / FREE Full Text 8. ↵ Beissinger S. R. , 2014 Digging the pupfish out of its hole: risk analyses to guide harvest of Devils Hole pupfish for captive breeding . PeerJ 2 . https://doi.org/10.7717/peerj.549 9. ↵ Bell D. A. , Z. L. Robinson , W. C. Funk , S. W. Fitzpatrick , F. W. Allendorf , et al. , 2019 The Exciting Potential and Remaining Uncertainties of Genetic Rescue . Trends in Ecology & Evolution 34 : 1070 – 1079 . https://doi.org/10.1016/j.tree.2019.06.006 OpenUrl 10. ↵ Bi K. , T. Linderoth , D. Vanderpool , J. M. Good , R. Nielsen , et al. , 2013 Unlocking the vault: next-generation museum population genomics . Molecular Ecology 22 : 6018 – 6032 . https://doi.org/10.1111/mec.12516 OpenUrl CrossRef Web of Science 11. ↵ Brugarolas J. , K. Lei , R. L. Hurley , B. D. Manning , J. H. Reiling , et al. , 2004 Regulation of mTOR function in response to hypoxia by REDD1 and the TSC1/TSC2 tumor suppressor complex . Genes Dev 18 : 2893 – 2904 . https://doi.org/10.1101/gad.1256804 OpenUrl Abstract / FREE Full Text 12. ↵ Burg G. C. , J. Johnson , S. Spataro , A. O’Keefe , N. Urbina , et al. , 2019 Care and propagation of captive pupfish from the genus Cyprinodon: insight into conservation . Environ Biol Fish 102 : 1015 – 1024 . https://doi.org/10.1007/s10641-019-00887-2 OpenUrl 13. Cappaert v. United States , 1976 14. ↵ Charlesworth B. , and D. Charlesworth , 1999 The genetic basis of inbreeding depression . Genet Res 74 : 329 – 340 . https://doi.org/10.1017/s0016672399004152 OpenUrl CrossRef PubMed Web of Science 15. ↵ Charlesworth D. , and J. H. Willis , 2009 The genetics of inbreeding depression . Nat Rev Genet 10 : 783 – 796 . https://doi.org/10.1038/nrg2664 OpenUrl CrossRef PubMed Web of Science 16. ↵ Chernoff B ., 1985 Population dynamics of the Devils Hole pupfish . Environ Biol Fish 13 : 139 – 147 . https://doi.org/10.1007/BF00002582 OpenUrl 17. ↵ Cingolani P. , A. Platts , L. L. Wang , M. Coon , T. Nguyen , et al. , 2012 A program for annotating and predicting the effects of single nucleotide polymorphisms , SnpEff. Fly (Austin ) 6 : 80 – 92 . https://doi.org/10.4161/fly.19695 OpenUrl 18. ↵ Coutton C. , A. S. Vargas , A. Amiri-Yekta , Z.-E. Kherraf , S. F. Ben Mustapha , et al. , 2018 Mutations in CFAP43 and CFAP44 cause male infertility and flagellum defects in Trypanosoma and human . Nat Commun 9 : 686 . https://doi.org/10.1038/s41467-017-02792-7 OpenUrl CrossRef PubMed 19. ↵ Danecek P. , A. Auton , G. Abecasis , C. A. Albers , E. Banks , et al. , 2011 The variant call format and VCFtools . Bioinformatics 27 : 2156 – 2158 . https://doi.org/10.1093/bioinformatics/btr330 OpenUrl CrossRef PubMed Web of Science 20. ↵ Deacon J. E. , F. R. Taylor , and J. W. Pedretti , 1995 Egg viability and ecology of Devils Hole pupfish: Insights from captive propagation . The Southwestern Naturalist 40 : 216 – 223 . OpenUrl 21. ↵ DePristo M. A. , E. Banks , R. Poplin , K. V. Garimella , J. R. Maguire , et al. , 2011 A framework for variation discovery and genotyping using next-generation DNA sequencing data . Nat Genet 43 : 491 – 498 . https://doi.org/10.1038/ng.806 OpenUrl CrossRef PubMed Web of Science 22. Der Sarkissian C. , L. Ermini , M. Schubert , M. A. Yang , P. Librado , et al. , 2015 Evolutionary Genomics and Conservation of the Endangered Przewalski’s Horse . Curr Biol 25 : 2577 – 2583 . https://doi.org/10.1016/j.cub.2015.08.032 OpenUrl CrossRef PubMed 23. ↵ DeYoung M. P. , P. Horak , A. Sofer , D. Sgroi , and L. W. Ellisen , 2008 Hypoxia regulates TSC1/2-mTOR signaling and tumor suppression through REDD1-mediated 14-3-3 shuttling . Genes Dev 22 : 239 – 251 . https://doi.org/10.1101/gad.1617608 OpenUrl Abstract / FREE Full Text 24. ↵ Dibble C. C. , W. Elis , S. Menon , W. Qin , J. Klekota , et al. , 2012 TBC1D7 is a third subunit of the TSC1-TSC2 complex upstream of mTORC1 . Mol Cell 47 : 535 – 546 . https://doi.org/10.1016/j.molcel.2012.06.009 OpenUrl CrossRef PubMed Web of Science 25. ↵ Díez-Del-Molino D. , F. Sánchez-Barreiro , I. Barnes , M. T. P. Gilbert , and L. Dalén , 2018 Quantifying Temporal Genomic Erosion in Endangered Species . Trends Ecol Evol 33 : 176 – 185 . https://doi.org/10.1016/j.tree.2017.12.002 OpenUrl CrossRef PubMed 26. ↵ Duvernell D. D. , and B. J. Turner , 1998 Evolutionary genetics of Death Valley pupfish populations: mitochondrial DNA sequence variation and population structure . Molecular Ecology 7 : 279 – 288 . https://doi.org/10.1046/j.1365-294X.1998.00347.x OpenUrl CrossRef Web of Science 27. ↵ Duvernell D. D. , and B. J. Turner , 1999 Variation and Divergence of Death Valley Pupfish Populations at Retrotransposon-Defined Loci . Molecular Biology and Evolution 16 : 363 – 371 . https://doi.org/10.1093/oxfordjournals.molbev.a026117 OpenUrl CrossRef Web of Science 28. ↵ Echelle A. A. , and T. E. Dowling , 1992 MITOCHONDRIAL DNA VARIATION AND EVOLUTION OF THE DEATH VALLEY PUPFISHES (CYPRINODON , CYPRINODONTIDAE). Evolution 46 : 193 – 206 . https://doi.org/10.1111/j.1558-5646.1992.tb01994.x OpenUrl 29. ↵ Echelle A. A. , and A. F. Echelle , 1993 Allozyme Perspective on Mitochondrial DNA Variation and Evolution of the Death Valley Pupfishes (Cyprinodontidae: Cyprinodon) . Copeia 1993 : 275 – 287 . https://doi.org/10.2307/1447128 OpenUrl CrossRef 30. ↵ E.T. Arnold , 1972 Behavioral Ecology of two pupfishes (Cyprinodontidae, Genus Cyprinodon) from northern Mexico . 31. ↵ Fiermonte G. , E. Paradies , S. Todisco , C. M. T. Marobbio , and F. Palmieri , 2009 A novel member of solute carrier family 25 (SLC25A42) is a transporter of coenzyme A and adenosine 3’,5’-diphosphate in human mitochondria . J Biol Chem 284 : 18152 – 18159 . https://doi.org/10.1074/jbc.M109.014118 OpenUrl Abstract / FREE Full Text 32. ↵ Frankham R ., 1995 Conservation Genetics . Annual Review of Genetics 29 : 305 – 327 . https://doi.org/10.1146/annurev.ge.29.120195.001513 OpenUrl CrossRef PubMed Web of Science 33. ↵ Franklin I. R ., 1980 Evolutionary change in small populations., pp. 135 – 150 in Conservation Biology: an Evolutionary–Ecological Perspective, Sunderland, Massachusetts, Sinauer Associates , U.S.A . 34. ↵ Gogliettino M. , A. Riccio , M. Balestrieri , E. Cocca , A. Facchiano , et al. , 2014 A novel class of bifunctional acylpeptide hydrolases--potential role in the antioxidant defense systems of the Antarctic fish Trematomus bernacchii . FEBS J 281 : 401 – 415 . https://doi.org/10.1111/febs.12610 OpenUrl CrossRef 35. ↵ Grossen C. , F. Guillaume , L. F. Keller , and D. Croll , 2020 Purging of highly deleterious mutations through severe bottlenecks in Alpine ibex . Nature Communications 11 : 1001 . https://doi.org/10.1038/s41467-020-14803-1 OpenUrl 36. Gustafson , E.S. and Deacon , J.E. , 1997 Distribution of larval Devils Hole pupfish, Cyprinodon diabolis Wales, in relation to dissolved oxygen concentration in Devil’s Hole. Report to the National Park Service, Death Valley National Park . 37. ↵ Hansson B. , and L. Westerberg , 2002 On the correlation between heterozygosity and fitness in natural populations . Mol Ecol 11 : 2467 – 2474 . https://doi.org/10.1046/j.1365-294x.2002.01644.x OpenUrl CrossRef PubMed Web of Science 38. ↵ Harrisson K. A. , M. J. L. Magrath , J. D. L. Yen , A. Pavlova , N. Murray , et al. , 2019 Lifetime Fitness Costs of Inbreeding and Being Inbred in a Critically Endangered Bird . Current Biology 29 : 2711 – 2717 .e4. https://doi.org/10.1016/j.cub.2019.06.064 OpenUrl CrossRef 39. ↵ Henn B. M. , L. R. Botigué , C. D. Bustamante , A. G. Clark , and S. Gravel , 2015 Estimating the mutation load in human genomes . Nat Rev Genet 16 : 333 – 343 . https://doi.org/10.1038/nrg3931 OpenUrl CrossRef PubMed 40. ↵ Henn B. M. , L. R. Botigué , S. Peischl , I. Dupanloup , M. Lipatov , et al. , 2016 Distance from sub-Saharan Africa predicts mutational load in diverse human genomes . Proc Natl Acad Sci U S A 113 : E440 – 449 . https://doi.org/10.1073/pnas.1510805112 OpenUrl Abstract / FREE Full Text 41. ↵ Howe K. L. , P. Achuthan , J. Allen , J. Allen , J. Alvarez-Jarreta , et al. , 2021 Ensembl 2021 . Nucleic Acids Research 49 : D884 – D891 . https://doi.org/10.1093/nar/gkaa942 OpenUrl 42. ↵ Iuso A. , B. Alhaddad , C. Weigel , U. Kotzaeridou , E. Mastantuono , et al. , 2019 A Homozygous Splice Site Mutation in SLC25A42, Encoding the Mitochondrial Transporter of Coenzyme A, Causes Metabolic Crises and Epileptic Encephalopathy . JIMD Rep 44 : 1 – 7 . https://doi.org/10.1007/8904_2018_115 OpenUrl 43. ↵ James C. J. , 1969 Aspects of the Ecology of the Devil’s Hole Pupfish (Cyprinodon Diabolis) Wales. University of Nevada, Las Vegas . 44. ↵ Javed A. A. , and R. K. Naz , 1992 Human cleavage signal-1 protein; cDNA cloning, transcription and immunological analysis . Gene 112 : 205 – 211 . https://doi.org/10.1016/0378-1119(92)90377-2 OpenUrl CrossRef PubMed Web of Science 45. ↵ Jin Y. , K. Jia , W. Zhang , Y. Xiang , P. Jia , et al. , 2019 Zebrafish TRIM25 Promotes Innate Immune Response to RGNNV Infection by Targeting 2CARD and RD Regions of RIG-I for K63-Linked Ubiquitination . Front Immunol 10 : 2805 . https://doi.org/10.3389/fimmu.2019.02805 OpenUrl 46. ↵ Johnson W. E. , D. P. Onorato , M. E. Roelke , E. D. Land , M. Cunningham , et al. , 2010 Genetic Restoration of the Florida Panther . Science 329 : 1641 – 1645 . https://doi.org/10.1126/science.1192891 OpenUrl Abstract / FREE Full Text 47. ↵ Kardos M. , H. R. Taylor , H. Ellegren , G. Luikart , and F. W. Allendorf , 2016 Genomics advances the study of inbreeding depression in the wild . Evolutionary Applications 9 : 1205 – 1218 . https://doi.org/10.1111/eva.12414 OpenUrl 48. ↵ Kardos M. , E. Armstrong , S. Fitzpatrick , S. Hauser , P. Hedrick , et al. , 2021 The crucial role of genome-wide genetic variation in conservation . 49. ↵ Keller L. F. , and D. M. Waller , 2002 Inbreeding effects in wild populations . Trends in Ecology & Evolution 17 : 230 – 241 . https://doi.org/10.1016/S0169-5347(02)02489-8 OpenUrl 50. ↵ Kimura M ., 1957 Some Problems of Stochastic Processes in Genetics . The Annals of Mathematical Statistics 28 : 882 – 901 . https://doi.org/10.1214/aoms/1177706791 OpenUrl 51. ↵ Kodric-Brown A ., 1977 Reproductive Success and the Evolution of Breeding Territories in Pupfish (Cyprinodon) . Evolution 31 : 750 – 766 . https://doi.org/10.2307/2407437 OpenUrl CrossRef Web of Science 52. ↵ Kohn M. H. , W. J. Murphy , E. A. Ostrander , and R. K. Wayne , 2006 Genomics and conservation genetics . Trends Ecol Evol 21 : 629 – 637 . https://doi.org/10.1016/j.tree.2006.08.001 OpenUrl CrossRef PubMed 53. ↵ Kuo Y.-C. , Y.-H. Lin , H.-I. Chen , Y.-Y. Wang , Y.-W. Chiou , et al. , 2012 SEPT12 mutations cause male infertility with defective sperm annulus . Human Mutation 33 : 710 – 719 . https://doi.org/10.1002/humu.22028 OpenUrl CrossRef PubMed 54. ↵ Kyriazis C. C. , R. K. Wayne , and K. E. Lohmueller , 2021 Strongly deleterious mutations are a primary determinant of extinction risk due to inbreeding depression . Evolution Letters 5 : 33 – 47 . https://doi.org/10.1002/evl3.209 OpenUrl 55. ↵ Lee P. , N. S. Chandel , and M. C. Simon , 2020 Cellular adaptation to hypoxia through hypoxia inducible factors and beyond . Nat Rev Mol Cell Biol 21 : 268 – 283 . https://doi.org/10.1038/s41580-020-0227-y OpenUrl CrossRef 56. ↵ Leigh D. M. , H. E. L. Lischer , F. Guillaume , C. Grossen , and T. Günther , 2021 Disentangling adaptation from drift in bottlenecked and reintroduced populations of Alpine ibex . Molecular Ecology Resources n/a . https://doi.org/10.1111/1755-0998.13442 57. ↵ Li H. , 2009 SNPable Regions 58. ↵ Li H ., 2011 A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data . Bioinformatics 27 : 2987 – 2993 . https://doi.org/10.1093/bioinformatics/btr509 OpenUrl CrossRef PubMed Web of Science 59. ↵ Li H. , 2013 Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM . arXiv:1303.3997 [q-bio]. 60. ↵ Li H ., 2014 Toward better understanding of artifacts in variant calling from high-coverage samples . Bioinformatics 30 : 2843 – 2851 . https://doi.org/10.1093/bioinformatics/btu356 OpenUrl CrossRef PubMed 61. Liu , R.K. , 1969 The Comparative Behavior of Allopatric Species (Teleostei-Cyprinodontidae: Cyprinodon) 62. ↵ Lynch M. , J. Conery , and R. Bürger , 1995 Mutational Meltdowns in Sexual Populations . Evolution 49 : 1067 – 1080 . https://doi.org/10.1111/j.1558-5646.1995.tb04434.x OpenUrl CrossRef Web of Science 63. ↵ Madinger H. L. , K. P. Wilson , J. A. Goldstein , and M. J. Bernot , 2016 Biogeochemistry and Nutrient Limitation of Microbial Biofilms in Devils Hole , Nevada. wnan 76 : 53 – 71 . https://doi.org/10.3398/064.076.0107 OpenUrl 64. ↵ Maeda M. , H. Hasegawa , T. Hyodo , S. Ito , E. Asano , et al. , 2011 ARHGAP18, a GTPase-activating protein for RhoA, controls cell shape, spreading, and motility . Mol Biol Cell 22 : 3840 – 3852 . https://doi.org/10.1091/mbc.E11-04-0364 OpenUrl Abstract / FREE Full Text 65. ↵ de Manuel M. , R. Barnett , M. Sandoval-Velasco , N. Yamaguchi , F. Garrett Vieira , et al. , 2020 The evolutionary history of extinct and living lions . PNAS 117 : 10927 – 10934 . OpenUrl Abstract / FREE Full Text 66. ↵ Martin A. P. , A. A. Echelle , G. Zegers , S. Baker , and C. L. Keeler-Foster , 2012 Dramatic shifts in the gene pool of a managed population of an endangered species may be exacerbated by high genetic load . Conserv Genet 13 : 349 – 358 . https://doi.org/10.1007/s10592-011-0289-7 OpenUrl 67. ↵ Martin C. H. , Crawford Jacob E. , Turner Bruce J. , and Simons Lee H ., 2016 Diabolical survival in Death Valley: recent pupfish colonization, gene flow and genetic assimilation in the smallest species range on earth . Proceedings of the Royal Society B: Biological Sciences 283 : 20152334 . https://doi.org/10.1098/rspb.2015.2334 OpenUrl CrossRef PubMed 68. ↵ Martin C. H. , S. Höhna , J. E. Crawford , B. J. Turner , E. J. Richards , et al. , 2017 The complex effects of demographic history on the estimation of substitution rate: concatenated gene analysis results in no more than twofold overestimation . Proceedings of the Royal Society B: Biological Sciences 284 : 20170537 . https://doi.org/10.1098/rspb.2017.0537 OpenUrl CrossRef PubMed 69. ↵ Martin C. H. , and S. Höhna , 2018 New evidence for the recent divergence of Devil’s Hole pupfish and the plausibility of elevated mutation rates in endangered taxa . Molecular Ecology 27 : 831 – 838 . https://doi.org/10.1111/mec.14404 OpenUrl 70. ↵ Martin C. H. , and B. J. Turner , 2018 Long-distance dispersal over land by fishes: extremely rare ecological events become probable over millennial timescales . Proc Biol Sci 285 : 20172436 . https://doi.org/10.1098/rspb.2017.2436 OpenUrl CrossRef PubMed 71. ↵ Melbourne B. A. , and A. Hastings , 2008 Extinction risk depends strongly on factors contributing to stochasticity . Nature 454 : 100 – 103 . https://doi.org/10.1038/nature06922 OpenUrl CrossRef PubMed Web of Science 72. ↵ Miller R. R. , 1948 The Cyprinodont fishes of the Death Valley system of eastern California and southwestern Nevada. undefined . 73. ↵ Miller R. R ., 1969 CONSERVATION OF FISHES OF THE DEATH VALLEY SYSTEM IN CALIFORNIA AND NEVADA . Conservation of fishes of the Death VallTransactions of the California-Nevada section of the Wildlife Society 107 – 22 . 74. ↵ Miller , Robert R. , 1981 Coevolution of deserts and pupfishes (genus Cyprinodon) in the American Southwest, in Naiman, R. J., and Soltz, D. L., eds, Fishes in North American Deserts . 75. ↵ Narasimhan V. , P. Danecek , A. Scally , Y. Xue , C. Tyler-Smith , et al. , 2016 BCFtools/RoH: a hidden Markov model approach for detecting autozygosity from next-generation sequencing data . Bioinformatics 32 : 1749 – 1751 . https://doi.org/10.1093/bioinformatics/btw044 OpenUrl CrossRef PubMed 76. ↵ Palkopoulou E. , S. Mallick , P. Skoglund , J. Enk , N. Rohland , et al. , 2015 Complete genomes reveal signatures of demographic and genetic declines in the woolly mammoth . Curr Biol 25 : 1395 – 1400 . https://doi.org/10.1016/j.cub.2015.04.007 OpenUrl CrossRef PubMed 77. ↵ Purcell S. , B. Neale , K. Todd-Brown , L. Thomas , M. A. R. Ferreira , et al. , 2007 PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses . Am J Hum Genet 81 : 559 – 575 . OpenUrl CrossRef PubMed 78. ↵ Rausch T. , T. Zichner , A. Schlattl , A. M. Stütz , V. Benes , et al. , 2012 DELLY: structural variant discovery by integrated paired-end and split-read analysis . Bioinformatics 28 : i333 – i339 . https://doi.org/10.1093/bioinformatics/bts378 OpenUrl CrossRef PubMed Web of Science 79. ↵ Reed D. H. , J. J. O’Grady , B. W. Brook , J. D. Ballou , and R. Frankham , 2003 Estimates of minimum viable population sizes for vertebrates and factors influencing those estimates . Biological Conservation 113 : 23 – 34 . https://doi.org/10.1016/S0006-3207(02)00346-4 OpenUrl CrossRef Web of Science 80. ↵ Riccio A. , M. Gogliettino , G. Palmieri , M. Balestrieri , A. Facchiano , et al. , 2015 A New APEH Cluster with Antioxidant Functions in the Antarctic Hemoglobinless Icefish Chionodraco hamatus . PLoS One 10 : e0125594 . https://doi.org/10.1371/journal.pone.0125594 OpenUrl CrossRef PubMed 81. ↵ Richards S. , N. Aziz , S. Bale , D. Bick , S. Das , et al. , 2015 Standards and Guidelines for the Interpretation of Sequence Variants: A Joint Consensus Recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology . Genet Med 17 : 405 – 424 . https://doi.org/10.1038/gim.2015.30 OpenUrl CrossRef PubMed 82. ↵ Richards E. J. , J. A. McGirr , J. R. Wang , M. E. S. John , J. W. Poelstra , et al. , 2021 A vertebrate adaptive radiation is assembled from an ancient and disjunct spatiotemporal landscape . PNAS 118 . https://doi.org/10.1073/pnas.2011811118 83. ↵ Riggs A. C. , and J. E. Deacon , 2002 Connectivity in Desert Aquatic Ecosystems: The Devils Hole Story . 38 . 84. ↵ Robinson J. A. , D. Ortega-Del Vecchyo , Z. Fan , B. Y. Kim , B. M. vonHoldt , et al. , 2016 Genomic Flatlining in the Endangered Island Fox . Current Biology 26 : 1183 – 1189 . https://doi.org/10.1016/j.cub.2016.02.062 OpenUrl CrossRef PubMed 85. ↵ Robinson J. A. , C. Brown , B. Y. Kim , K. E. Lohmueller , and R. K. Wayne , 2018 Purging of Strongly Deleterious Mutations Explains Long-Term Persistence and Absence of Inbreeding Depression in Island Foxes . Current Biology 28 : 3487 – 3494 .e4. https://doi.org/10.1016/j.cub.2018.08.066 OpenUrl 86. ↵ Robinson J. A. , J. Räikkönen , L. M. Vucetich , J. A. Vucetich , R. O. Peterson , et al. , 2019 Genomic signatures of extensive inbreeding in Isle Royale wolves, a population on the threshold of extinction . Science Advances 5 : eaau0757 . https://doi.org/10.1126/sciadv.aau0757 OpenUrl FREE Full Text 87. ↵ Robinson J. A. , R. C. K. Bowie , O. Dudchenko , E. L. Aiden , S. L. Hendrickson , et al. , 2021 Genome-wide diversity in the California condor tracks its prehistoric abundance and decline . Current Biology 0. https://doi.org/10.1016/j.cub.2021.04.035 88. ↵ Rogers R. L. , and M. Slatkin , 2017 Excess of genomic defects in a woolly mammoth on Wrangel island . PLOS Genetics 13 : e1006601 . https://doi.org/10.1371/journal.pgen.1006601 OpenUrl 89. ↵ Sackett J. D. , D. C. Huerta , B. R. Kruger , S. D. Hamilton-Brehm , and D. P. Moser , 2018 A comparative study of prokaryotic diversity and physicochemical characteristics of Devils Hole and the Ash Meadows Fish Conservation Facility, a constructed analog . PLOS ONE 13 : e0194404 . https://doi.org/10.1371/journal.pone.0194404 OpenUrl 90. ↵ Shamseldin H. E. , L. L. Smith , A. Kentab , H. Alkhalidi , B. Summers , et al. , 2016 Mutation of the mitochondrial carrier SLC25A42 causes a novel form of mitochondrial myopathy in humans . Hum Genet 135 : 21 – 30 . https://doi.org/10.1007/s00439-015-1608-8 OpenUrl 91. ↵ Simmons M. J. , and J. F. Crow , 1977 Mutations affecting fitness in drosophila populations . Annu. Rev. Genet . 11 : 49 – 78 . https://doi.org/10.1146/annurev.ge.11.120177.000405 OpenUrl CrossRef PubMed Web of Science 92. ↵ St. John M. E. , J. C. Dunker , E. J. Richards , S. Romero , and C. H. Martin , 2021 Parallel genetic changes underlie integrated craniofacial traits in an adaptive radiation of trophic specialist pupfishes . bioRxiv 2021.07.01.450661. https://doi.org/10.1101/2021.07.01.450661 93. ↵ Stoffel M. A. , S. E. Johnston , J. G. Pilkington , and J. M. Pemberton , 2021a Mutation load decreases with haplotype age in wild Soay sheep . Evolution Letters 5 : 187 – 195 . https://doi.org/10.1002/evl3.229 OpenUrl 94. ↵ Stoffel M. A. , S. E. Johnston , J. G. Pilkington , and J. M. Pemberton , 2021b Genetic architecture and lifetime dynamics of inbreeding depression in a wild mammal . Nat Commun 12 : 2972 . https://doi.org/10.1038/s41467-021-23222-9 OpenUrl 95. ↵ Sun L. , L. Zhao , L. Du , P. Zhang , M. Zhang , et al. , 2016 Identification of two novel mutations in the GALNT3 gene in a Chinese family with hyperphosphatemic familial tumoral calcinosis . Bone Res 4 : 1 – 6 . https://doi.org/10.1038/boneres.2016.38 OpenUrl 96. ↵ Tang S. , X. Wang , W. Li , X. Yang , Z. Li , et al. , 2017 Biallelic Mutations in CFAP43 and CFAP44 Cause Male Infertility with Multiple Morphological Abnormalities of the Sperm Flagella . Am J Hum Genet 100 : 854 – 864 . https://doi.org/10.1016/j.ajhg.2017.04.012 OpenUrl CrossRef PubMed 97. ↵ Teixeira J. C. , and C. D. Huber , 2021 The inflated significance of neutral genetic diversity in conservation genetics . PNAS 118 . https://doi.org/10.1073/pnas.2015096118 98. The Universal Protein Resource (UniProt) , 2008 Nucleic Acids Res 36 : D190 – D195 . https://doi.org/10.1093/nar/gkm895 OpenUrl CrossRef PubMed Web of Science 99. ↵ Thompson E. A ., 2013 Identity by Descent: Variation in Meiosis, Across Genomes, and in Populations . Genetics 194 : 301 – 326 . https://doi.org/10.1534/genetics.112.148825 OpenUrl Abstract / FREE Full Text 100. ↵ Traill L. W. , C. J. A. Bradshaw , and B. W. Brook , 2007 Minimum viable population size: A meta-analysis of 30 years of published estimates . Biological Conservation 139 : 159 – 166 . https://doi.org/10.1016/j.biocon.2007.06.011 OpenUrl CrossRef Web of Science 101. ↵ van der Valk T. , D. Díez-Del-Molino , T. Marques-Bonet , K. Guschanski , and L. Dalén , 2019 Historical Genomes Reveal the Genomic Consequences of Recent Population Decline in Eastern Gorillas . Curr Biol 29 : 165 – 170 .e6. https://doi.org/10.1016/j.cub.2018.11.055 OpenUrl CrossRef 102. ↵ van der Valk T. , C. M. Gonda , H. Silegowa , S. Almanza , I. Sifuentes-Romero , et al. , 2020 The Genome of the Endangered Dryas Monkey Provides New Insights into the Evolutionary History of the Vervets . Molecular Biology and Evolution 37 : 183 – 194 . https://doi.org/10.1093/molbev/msz213 OpenUrl CrossRef 103. ↵ van der Valk T. , M. de Manuel , T. Marques-Bonet , and K. Guschanski , 2021 Estimates of genetic load suggest frequent purging of deleterious alleles in small populations . bioRxiv 696831. https://doi.org/10.1101/696831 104. ↵ de Valles-Ibáñez G. , J. Hernandez-Rodriguez , J. Prado-Martinez , P. Luisi , T. Marquès-Bonet , et al. , 2016 Genetic Load of Loss-of-Function Polymorphic Variants in Great Apes . Genome Biol Evol 8 : 871 – 877 . https://doi.org/10.1093/gbe/evw040 OpenUrl CrossRef PubMed 105. ↵ Wildt D. E. , M. Bush , J. G. Howard , S. J. O’Brien , D. Meltzer , et al. , 1983 Unique Seminal Quality in the South African Cheetah and a Comparative Evaluation in the Domestic Cat . Biology of Reproduction 29 : 1019 – 1025 . https://doi.org/10.1095/biolreprod29.4.1019 OpenUrl CrossRef PubMed Web of Science 106. ↵ Wildt D. E. , S. J. O’Brien , J. G. Howard , T. M. Caro , M. E. Roelke , et al. , 1987a Similarity in Ejaculate-Endocrine Characteristics in Captive Versus Free-Ranging Cheetahs of Two Subspecies1 . Biology of Reproduction 36 : 351 – 360 . https://doi.org/10.1095/biolreprod36.2.351 OpenUrl CrossRef PubMed Web of Science 107. ↵ Wildt D. E. , M. Bush , K. L. Goodrowe , C. Packer , A. E. Pusey , et al. , 1987b Reproductive and genetic consequences of founding isolated lion populations . Nature 329 : 328 – 331 . https://doi.org/10.1038/329328a0 OpenUrl CrossRef Web of Science 108. ↵ Wilson , K.P. , Blinn , D.W. , and Herbst , D.B. , 2001 The Devils Hole Energetics/Community Relationships: Death Valley National Park, California . Two-Year Progress Report to Death Valley National Park 109. ↵ Xue Y. , J. Prado-Martinez , P. H. Sudmant , V. Narasimhan , Q. Ayub , et al. , 2015 Mountain gorilla genomes reveal the impact of long-term population decline and inbreeding . Science 348 : 242 – 245 . https://doi.org/10.1126/science.aaa3952 OpenUrl Abstract / FREE Full Text 110. ↵ Yergeau D. A. , C. N. Cornell , S. K. Parker , Y. Zhou , and H. W. Detrich , 2005 bloodthirsty, an RBCC/TRIM gene required for erythropoiesis in zebrafish . Developmental Biology 283 : 97 – 112 . https://doi.org/10.1016/j.ydbio.2005.04.006 OpenUrl CrossRef PubMed Web of Science 111. ↵ Zallot R. , G. Agrimi , C. Lerma-Ortiz , H. J. Teresinski , O. Frelin , et al. , 2013 Identification of mitochondrial coenzyme a transporters from maize and Arabidopsis . Plant Physiol 162 : 581 – 588 . https://doi.org/10.1104/pp.113.218081 OpenUrl Abstract / FREE Full Text 112. Zhang L. , N.-J. Huang , C. Chen , W. Tang , and S. Kornbluth , 2012a Ubiquitylation of p53 by the APC/C inhibitor Trim39 . Proc Natl Acad Sci U S A 109 : 20931 – 20936 . https://doi.org/10.1073/pnas.1212047110 OpenUrl Abstract / FREE Full Text 113. ↵ Zhang L. , Y. Mei , N. Fu , L. Guan , W. Xie , et al. , 2012b TRIM39 regulates cell cycle progression and DNA damage responses via stabilizing p21 . PNAS 109 : 20937 – 20942 . OpenUrl Abstract / FREE Full Text Back to top Previous Next Posted August 14, 2021. Download PDF Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Severe inbreeding and gene loss in the historical and extant population of the critically endangered Devils Hole pupfish Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Severe inbreeding and gene loss in the historical and extant population of the critically endangered Devils Hole pupfish David Tian , Bruce J. Turner , Christopher H. Martin bioRxiv 2021.08.13.456274; doi: https://doi.org/10.1101/2021.08.13.456274 Share This Article: Copy Citation Tools Severe inbreeding and gene loss in the historical and extant population of the critically endangered Devils Hole pupfish David Tian , Bruce J. Turner , Christopher H. Martin bioRxiv 2021.08.13.456274; doi: https://doi.org/10.1101/2021.08.13.456274 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Evolutionary Biology Subject Areas All Articles Animal Behavior and Cognition (8025) Biochemistry (18803) Bioengineering (14932) Bioinformatics (44519) Biophysics (22647) Cancer Biology (19785) Cell Biology (26960) Clinical Trials (138) Developmental Biology (14000) Ecology (21056) Epidemiology (2067) Evolutionary Biology (25500) Genetics (16189) Genomics (23540) Immunology (18737) Microbiology (42585) Molecular Biology (18115) Neuroscience (93664) Paleontology (701) Pathology (2989) Pharmacology and Toxicology (5106) Physiology (8134) Plant Biology (16034) Scientific Communication and Education (2098) Synthetic Biology (4575) Systems Biology (10258) Zoology (2393) window.__CF$cv$params={r:'a403b592fd0ef4f0',t:'MTc5MDI3MzA0Mg==',u:'01a0d496c39076ceb74f70d8ddc0f3b0',ut:'0uUHYo8_QQ1AsLa48fhflRsWfPbG_F6rMKbkKdPMR4U-1790273045-1.2.1.1-XYPDccBF7HdGffdarXz1F_xbj3wUgnZ1GHL10HFtNKrs9HPUEHrcWBMukbcGeW_oZGBl93HGALIPmieiTsL2VuCbK6SegRs664LmtJboNNI',i:60};(function(){if(!document.body)return;var s=document.createElement('script');s.src='/cdn-cgi/challenge-platform/scripts/precursor/main.js';document.head.appendChild(s);})();