The Sinocyclocheilus cavefish genome provides insights into cave adaptation
- Junxing Yang†1Email author,
- Xiaoli Chen†2,
- Jie Bai†2, 3, 4,
- Dongming Fang†2, 6,
- Ying Qiu†2, 3, 5,
- Wansheng Jiang†1,
- Hui Yuan2,
- Chao Bian2, 3,
- Jiang Lu2, 7,
- Shiyang He2, 7,
- Xiaofu Pan1,
- Yaolei Zhang2, 8,
- Xiaoai Wang1,
- Xinxin You2, 3,
- Yongsi Wang2,
- Ying Sun2, 5,
- Danqing Mao2,
- Yong Liu2,
- Guangyi Fan2,
- He Zhang2,
- Xiaoyong Chen1,
- Xinhui Zhang2, 3,
- Lanping Zheng1,
- Jintu Wang2,
- Le Cheng5, 9,
- Jieming Chen2, 3,
- Zhiqiang Ruan2, 3,
- Jia Li2, 3, 7,
- Hui Yu2, 3, 7,
- Chao Peng2, 3,
- Xingyu Ma10, 11,
- Junmin Xu10, 11,
- You He12,
- Zhengfeng Xu13,
- Pao Xu14,
- Jian Wang2, 15,
- Huanming Yang2, 15,
- Jun Wang2, 16,
- Tony Whitten4Email author,
- Xun Xu2Email author and
- Qiong Shi2, 3, 10, 11Email author
© Yang et al. 2016
Received: 8 October 2015
Accepted: 17 December 2015
Published: 4 January 2016
An emerging cavefish model, the cyprinid genus Sinocyclocheilus, is endemic to the massive southwestern karst area adjacent to the Qinghai-Tibetan Plateau of China. In order to understand whether orogeny influenced the evolution of these species, and how genomes change under isolation, especially in subterranean habitats, we performed whole-genome sequencing and comparative analyses of three species in this genus, S. grahami, S. rhinocerous and S. anshuiensis. These species are surface-dwelling, semi-cave-dwelling and cave-restricted, respectively.
The assembled genome sizes of S. grahami, S. rhinocerous and S. anshuiensis are 1.75 Gb, 1.73 Gb and 1.68 Gb, respectively. Divergence time and population history analyses of these species reveal that their speciation and population dynamics are correlated with the different stages of uplifting of the Qinghai-Tibetan Plateau. We carried out comparative analyses of these genomes and found that many genetic changes, such as gene loss (e.g. opsin genes), pseudogenes (e.g. crystallin genes), mutations (e.g. melanogenesis-related genes), deletions (e.g. scale-related genes) and down-regulation (e.g. circadian rhythm pathway genes), are possibly associated with the regressive features (such as eye degeneration, albinism, rudimentary scales and lack of circadian rhythms), and that some gene expansion (e.g. taste-related transcription factor gene) may point to the constructive features (such as enhanced taste buds) which evolved in these cave fishes.
As the first report on cavefish genomes among distinct species in Sinocyclocheilus, our work provides not only insights into genetic mechanisms of cave adaptation, but also represents a fundamental resource for a better understanding of cavefish biology.
KeywordsCavefish Genome Adaptation Evolution Qinghai-Tibetan Plateau Sinocyclocheilus
As one of the most successful vertebrate colonizers in subterranean habitats, cavefishes attract interest because of their unusual regressive features, such as the rudimentary eyes and scales, and loss of pigmentation. As possible compensation, some constructive traits have evolved, such as elongated appendages and non-visual sensory systems [1, 2]. Nevertheless, biologists have long puzzled over these troglomorphic characters , and the study of their relationship to their environment has been largely ignored . Although recent work on a traditional model, Astyanax mexicanus, revealed some important advances , especially in aspects of eye loss  and identifying candidate genes underlying quantitative trait loci (QTL) , there is no whole genomic data available to unravel the evolution and general adaptation to dark subterranean life among other groups of distinct but closely-related cavefishes.
Results and discussion
Genome assembly, assessment and annotation
High-quality genomic DNA was extracted from muscle tissues of the three Sinocyclocheilus species, which were collected from Yunnan (Sg and Sr) and Guangxi (Sa) provinces in China (Additional file 1: Figure S1). A series of sequencing libraries (250 bp to 20 kb) were constructed and applied in a whole-genome shotgun sequencing strategy, and a total of 313.3, 174.0 and 188.2 Gb of raw data were obtained for the Sg, Sr and Sa fishes, respectively (Additional file 2: Table S1). The assembled genome sizes are approximately 1.7 Gb (1.75 Gb for Sg, 1.73 Gb for Sr and 1.68 Gb for Sa), and the calculated contig N50 and scaffold N50 values are 17–29 Kb and 0.9–1.3 Mb, respectively (Fig. 1; Additional file 2: Table S3). The quality of the three genome assemblies was evaluated (Additional file 2: Tables S5 and S9, Additional file 3: Figures S6 and S7), and our assessment confirmed that all were high in quality and could be used for further comparative analyses. In addition, we employed a standard annotation pipeline to predict gene sets, resulting in approximately 40,000 genes in the three fish genomes (42,109 for Sg, 40,333 for Sr and 40,470 for Sa; see more details in Additional file 2: Table S15 and Additional file 4: Figure S14), which were double that of most diploid species (Additional file 4: Figure S13). The further Hox gene distribution analyses in three Sinocyclocheilus species (Additional file 4: Figure S11) and genome alignment between zebrafish and Sg (Additional file 4: Figure S10) provided more evidence to support the tetraploid nature of Sinocyclocheilus.
Phylogenetic relationships and divergence time
A reconstruction of the population demography of the three Sinocyclocheilus species has revealed a similar start but a subsequent divergent trend from 104 to 107 years ago (Fig. 2b). It seems that the population demography has a greater correlation with the uplifting of the Qinghai-Tibet Plateau than other significant environmental events, such as the Eurasian ice volume or the atmospheric surface air temperature. In a relatively short period of time (from 3.0 to 0.5 Ma), all three species underwent two rounds of population decline, which occurred following two intense uplift phases in the third tectonic uplift of the Qinghai-Tibet Plateau [17, 18]. These two phases of movements at Qingzang (3.6–1.7 Ma) and Kunhuang (1.1–0.6 Ma) uplifted the Plateau from an average of <1,000 m up to 4,000 m, followed by the intensification of the Asian monsoon and increased precipitation , in addition to the large-scale development of glaciers . The patterns of coincident population declines in the three species are believed to be a response of a common background following the intense uplift of the Plateau that may have been unfavorable to them (although it is still not clear which kind of environmental changes contributed the most). However, two events of unusual population expansion were also detected after these events. One was recognized in Sr during the interglacial period (0.5–0.15 Ma), a period during which Sg and Sa kept their low populations, which hints at the presence of extensive subterranean water systems in the Sr-native Luoping Basin at this time. Another was observed for Sg from 0.023 Ma when its main distribution area, the paleo-lake Dianchi, was coincidentally documented from geological sediments to have been some three times larger than at present . Range expansion along new river channels might accompany Plateau uplift, thereby providing some fish the opportunity to increase their population sizes as reported in the typical Plateau schizothoracine fish Schizopygopsis pylzovi  and Gymnocypris chilianensis .
Variations of eye structures and related genetic and expression responses
By screening crystallin genes in the three Sinocyclocheilus genomes, we found that copy numbers of most genes were lower than those of the diploid zebrafish (Additional file 2: Table S26 and Additional file 6: Figure S28). Transcriptomic data further demonstrated that the expression levels of most crystallin genes were maintained at high levels in Sg, but were not expressed in Sa (Additional file 2: Table S27). We also observed that several crystallin genes in Sa (such as Cryball1, Crygm2d12 and Crygm7) have evolved into pseudogenes due to existing premature stop codons (Additional file 2: Table S25E). Previous studies in Astyanax found that the expression of crystallin genes were down-regulated in the development of cavefish lens , suggesting that the lens plays a critical role in promoting cell survival in the development of eyes . In particular, β- and γ-crystallins play a pivotal role in retinal tissue remodeling and repair, and also strongly enhance axon regeneration of retinal ganglion cells . Hence, the lack, or down-regulation, of crystallin gene expression in Sa supports its phenotype of a visual system in which both the lens and retina have degenerated. Interestingly, we also found that Sa has two copies of Hsp90α1.1 and Hsp90a1.2 (heat shock protein 90α) genes, while both Sg and Sr have only one. Meanwhile, the expression levels of Hsp90α in Sa eyes were much higher than those in Sg and Sr (Additional file 2: Table S27). These observations provide further evidence to support a novel role of Hsp90α in lens apoptosis and eye degeneration of cavefishes .
Different mechanisms of albinism compared with Astyanax
In order to check the mechanisms of loss of pigmentation in Sa skin, we compared melanogenesis-related genes in the three Sinocyclocheilus genomes. In Astyanax, the albinism of some cave populations is caused by the deletions of Oca2 gene exon regions, which disturbs the upstream steps of the melanin synthesis pathway . Although similar deletions of Oca2 genes were not found in either of the two copies in Sa (Additional file 6: Figure S21), nor were any identical mutations specifically present in Sa and Astyanax cave populations, some other new mutations were identified (Additional file 6: Figure S21), and the transcriptome analysis performed on the skin of Sg, Sr and Sa indicated that the expression of Oca2 gene in Sa was the lowest (Additional file 2: Table S20). In the melanin synthesis pathway, several enzymes work downstream, such as Tyr (tyrosinase), a key rate-limiting enzyme, and Tyrp1 (tyrosinase-related protein 1) . More interestingly, we found that Tyr has an amino acid mutation (G420R) in Sa (Additional file 6: Figure S18), which was identical to that identified in Caucasian human patients (G419R , http://www.ifpcs.org/albinism/oca1mut.html) [33, 34]. Meanwhile, the expression levels of Sa genes in the melanogenesis pathway in the skin transcriptomes were the lowest, especially Tyr and Tyrp1, with significantly lower expression levels in Sa compared with Sg (Additional file 2: Table S20). It seems that similar phenotypes in Sinocyclocheilus cavefish might evolve by different mechanisms from Astyanax. Furthermore, we found that the Mpv17 protein in Sa had a deletion in the signal region compared with zebrafish, Sg and Sr (Additional file 6: Figure S22), and the expression level of Mpv17 in Sa is the lowest (Additional file 2: Table S20). A previous study shows that the deletion in Mpv17 can cause the tra mutant phenotype in zebrafish, and cause a loss (or strong reduction) of iridophores throughout larval and adult stages . This study also pointed out that differentiated iridophores were required for the accumulation and maintenance of melanophores during pigment pattern formation , and a parallel study showed that the interaction between iridophores and other chromatophores is critical in the stripe formation of zebrafish . Thus we infer that the deletion of Mpv17 might cause the loss of iridophores, which affected the formation of melanophores, and consequently played a role in the albinism of Sa.
Gene mutation and loss in scale degeneration
A previous study has indicated that mutations in the ectodysplasin-A receptor (Edar) encoding locus can lead to complete scale loss in fish such as medaka . For this reason, two copies of Edar gene (named as Edar1 and Edar2, respectively) in the three Sinocyclocheilus genomes were identified and checked. Interestingly, one of the proteins, Edar1, has deletions in the signal peptide and partial extracellular regions in all three Sinocyclocheilus species, which may lead to functional changes or loss in this copy (Additional file 6: Figure S20). For the other protein copy, Edar2, only Sa has the signal peptide region and partial extracellular regions totally deleted when compared with Sg and Sr (Additional file 6: Figure S20). This deletion in Sa may lead to a functional disorder in guiding the Edar protein transfer across the membrane, thus generating fewer scales at the skin surface of Sa (Additional file 7: Figure S29). Coincidentally, two important genes, Lamb3 and Col7a, were also lost from the Sa genome, which may cause a defect in the anchoring between the epidermis and dermis, resulting in friction and skin fragility [38, 39] in the scale covering.
Possible hearing loss in Sa
Different immune responses to specific habitats
The immune activities of Sa may be lower than its epigean counterparts because it probably lives in a less diverse microbial environment. The fact that Sa is more susceptible to disease in captivity might support this inference (unpublished data). We found relatively fewer copies of immune genes in Sa when compared with those in Sg and Sr (Additional file 2: Table S22). However, one important innate immune group, the Tlr (toll-like receptor) gene family, showed some degree of expansion in Sa (Additional file 2: Table S23), through the duplication of Tlr8 and Tlr18 in the Sa genome. This suggests that these three species may have evolved differential immune activities for innate immunity and adaptive immunity according to their different habitats. Interestingly, the semi-cave-dwelling Sr had substantially more copy numbers of immune genes than Sg and Sa (Additional file 2: Table S22), which may be a result of an adaptation to heterogeneous elements between epigean and hypogean habitats, as found in the amphibious mudskippers .
Lack of diurnal rhythms
Previous research reported that some cavefishes lack diurnal rhythms when living in perpetual darkness . For example, cave populations of A. mexicanus have a phenotype of reduced sleep in comparison to their surface relatives . We found that both the two copies of Skp1 in Sa had deletions in the N-terminal end of its protein (Additional file 6: Figure S24). Since Skp1 is one of the components of the Skp1-Cul1-Fbxl3 (SCF) protein complex, and the SCF complex is most relevant in the mammalian clock mechanism , the deletions in Skp1 might lead to some dysfunction in SCF, which suggests weaker light rhythms in Sa. Meanwhile, the transcriptomic analysis of the eye demonstrated that expression levels of the rhythm pathway genes decrease in the order Sg > Sr > Sa (Additional file 2: Table S28 and Additional file 6: Figure S26).
Low fecundity in Sa
Although low fecundity is often assumed to be normal in cave species , there is little empirical evidence, and the different fecundity levels between surface and cave forms sometimes seem to be habitat plastic (e.g. ). We know of no study on the fecundity of the cave-dwelling Sinocyclocheilus species. Our analysis of the absolute fecundity (number of mature eggs) of Sg and Sa (2,402.9 ± 881.9 in Sg  vs. 143 ± 116 in Sa (count from four specimens with mature eggs in this study)) indicated that the fecundity in cave Sinocyclocheilus species is much less than surface congeners. Interestingly, one related gene, Creb3l4, was found to have been lost in the Sa genome. It has been reported that Creb3l4 can regulate the expression of genes required for germ cell survival, although it is insufficient to disrupt the normal fertility in mice .
Enhancement of taste
Taste buds are enhanced in some cavefishes, such as Astyanax . We applied the taste-related gene sequences of zebrafish to BLAST to the three Sinocyclocheilus genomes, and unexpectedly found that one taste receptor gene, the Tast1r2-1, was significantly expanded (almost fourfold) and one important transcription factor, the Prox1 gene, had threefold copies in these three species compared with zebrafish (Additional file 8: Table S29). However, if these expansions were correlated to the overall enhancement of taste in the three Sinocyclocheilus species (benthic and cave-preferred) we still need further testing. Some taste receptor genes, such as Tas1r1 and Tas2r200-2, were specifically duplicated in the Sa genome (vs. Sg and Sr) (Additional file 8: Table S29), which suggests a further improvement in the sense of taste in the cave-restricted Sa. A preliminary study of the distribution of taste buds within the jaws of these three species also indicated that their numbers increase in a sequence from Sg < Sr < Sa (Additional file 7: Figure S32).
In the history of cave biology research, people have often been confused by the plethora of views and terms, such as disuse, preadaptation, opportunism, compensation, regressive evolution, etc. Adaptations to cave living are complicated because there is no morphological ‘archetype’ for cave animals, and the characters show a highly diverse mix . There is still a long way to go before this work can be applied to general evolutionary theory. As the first report on cavefish genomes among distinct species in Sinocyclocheilus, our work provides not only insights into genetic mechanisms of cave adaptation, but is also a fundamental resource for better understanding of cavefish biology.
Genome sequencing and assembly
Three female adult Sinocyclocheilus fishes, collected from Yunnan province (Sg and Sr) and Guangxi province (Sa) of China, were used for sequencing. The research protocol and treatment of experimental fishes have been reviewed and approved by the internal review board of the Kunming Institute of Zoology, Chinese Academy of Sciences (approval ID: SYDW-2014020). High-quality genomic DNA was extracted from muscle tissues using Puregene Tissue Core Kit A (Qiagen, MD, USA) for construction of libraries with different inserted sizes (250 bp to 20 kb) (Additional file 2: Table S1). In total, 25 paired-end libraries (11 for Sg, 7 for Sr and 7 for Sa, respectively) were generated with the Illumina standard operating procedure. HiSeq 2000 shotgun sequencing and assembling by SOAPdenovo assembler were performed as previously reported . Artificial and low-quality reads were filtered first and then sequencing errors with 17-mer frequency lower than four were collected using a method described in a previous study . Next, 88.05-, 48.31- and 60.54-fold coverage of Sinocyclocheilus genomes were used for assembly (Additional file 2: Table S2). In addition, we estimated genome sizes of the three Sinocyclocheilus fishes using the 17-mer depth frequency distribution method: G (Genome size) = K-mer_num/Peak_depth. The estimated genome sizes are 1.79, 1.89 and 1.81 Gb, respectively (Additional file 2: Table S4). Subsequently, the filtered reads were assembled into contigs and scaffolds with SOAPdenovo  and gaps were fulfilled with GapCloser . Finally, a primary assessment was performed on the genome assemblies (Additional file 9: Note S1).
We performed homology-based predictions by running RepeatMasker (version 3.3.0)  against the RepBase , and identified repeat sequences at DNA and protein levels using TE library (version 16.10) and RepeatProteinMask. We searched the de novo prediction build repeat library using RepeatModeler (version 1.0.5) and generated TE results with classification information for each repeat family by running RepeatMasker on the genome sequences subsequently. Tandem repeats were also searched using Tandem Repeats Finder (version 4.04) . The protein coding genes were obtained using a combination of the de novo method, homology-based gene prediction and RNA-Seq data (Additional file 9: Note S2). All predicted gene evidence was integrated by GLEAN  to get non-redundant data .
RNA was isolated for sequencing from four tissues (eye, skin, liver and ovary) of Sg, Sr and Sa, respectively. We applied an in-house C++ program to filter raw reads and then obtain high-quality reads (Additional file 9: Note S3). All of the clean RNA-Seq reads were mapped onto the corresponding reference genomes (Sg, Sr and Sa) using TopHat (version 2.0.4) . According to the mapped results, transcripts were constructed using Cufflinks (version 2.0.0) . The de novo transcriptomes of the four tissues were assembled by Trinity with filtered reads from each tissue separately into contigs and scaffolds. Trinity contains Inchworm, Chrysalis and Butterfly, which were employed sequentially to process large volumes of RNA-Seq reads.
(1) Gene family cluster: we defined gene families using TreeFam (http://www.treefam.org) among the three Sinocyclocheilus fishes (Sg, Sr and Sa) and seven other vertebrates, including fugu (Takifugu rubripes), green spotted puffer (Tetraodon nigroviridis), three-spined stickleback (Gasterosteus aculeatus), Atlantic cod (Gadus morhua), medaka (Oryzias latipes), zebrafish (Danio rerio) and human (Homo sapiens). A total of 17,883 gene families and 210 single-copy gene families were identified. The numbers of orthologous genes across the ten species were counted (Additional file 2: Table S19 and Additional file 4: Figure S13) and plotted in a Venn diagram (Additional file 4: Figure S14). (2) Phylogenetic analysis: phylogenetic relationships were established using 3,181 single-copy orthologous genes shared among nine teleost fish genomes (Additional file 5: Figure S15) using maximum likelihood (ML) method in PhyML [66, 67] and Bayesian inference method in MrBayes . An additional dataset of six mitochondrial gene sequences were also used to reconstruct the phylogenetic trees (Additional file 5: Figure S16). (3) Divergence time estimation: the divergence times were estimated using the mcmctree  in PAML  and recalculated using the multidivtime [71, 72] program, and all were calibrated by five fossil records  (Additional file 5: Figure S17 and Additional file 9: Note S4). (4) Demographic history: the distribution of time to TMRCA (the most recent common ancestor) between two alleles in an individual can be related to the history of population size fluctuation. The population size histories of Sg, Sr and Sa were inferred using the pairwise sequentially Markovian coalescent (PSMC) model  on heterozygous sites with the generation time (g = 1 year) (according to artificial breeding of Sg) and the mutation rate (m = 3.51 × 10−9 per year per nucleotide) . Reconstructed population history was plotted for Sg, Sr and Sa separately using gnuplot (version 4.4) . In addition, we obtained the atmospheric surface air temperature (°C) and Eurasian ice volume (m sea level equivalent) data for the past 3 million years from the NCEI (http://www.ncdc.noaa.gov/). (5) Gene family contraction and expansion: we performed Sinocyclocheilus lineage-specific expansion and contraction analysis using the CAFE program . Based on random birth and death model , a global parameter λ was estimated using maximum likelihood. Comparing each branch and their ancestor branch, we calculated a conditional P value and marked families with a P value of less than 0.05 as a significant change , which means it underwent contraction or expansion during evolution. These families were then subjected to GO/KEGG/IPR enrichment analyses along each Sinocyclocheilus lineage, respectively (Additional file 2: Table S25). More details are shown in Additional file 8: Table S29. (6) Genes with accelerated evolutionary rate: positive Darwinian selection at the DNA sequence level has been tested by estimating the ratio (ω) of nonsynonymous nucleotide substitutions (dN) to synonymous nucleotide substitutions (dS) between ortholog genes . A branch-site model was used to search for the positive selection genes (PSG) . After obtaining the Sinocyclocheilus PSG list (Additional file 10: Table S30), we converted it to the corresponding human orthologs as the input against a background of human genes  using the DAVID Functional Annotation  tool. (7) Evolution of Hox clusters: to define Hox genes in the three Sinocyclocheilus genomes, the Hox genes of zebrafish were downloaded from the ensemble as cross-references. The Hox gene numbers (Additional file 2: Table S18) and the order along the scaffolds (Additional file 4: Figure S11) in Sinocyclocheilus indicated that these fishes are indeed tetraploids when compared to diploid zebrafish. (8) Loss of Sa-specific gene families: in order to identify Sa-specific gene family loss, we extracted gene families that have no member in Sa while more than zero in the other nine species. The lost gene family list is included in Additional file 2: Table S24.
(1) Paraffin sections of the eyes of three Sinocyclocheilus species: histological studies on eyes were performed from paraffin sections and hematoxylin and eosin (H&E) staining. (2) Immunocytochemistry of taste buds: this analysis focused on distributions of taste buds on upper and lower jaws, using a primary antibody (rabbit against calretinin, labeling entire receptor cells within taste buds) according to a standard protocol (Additional file 9: Note S5). (3) Anatomy of gas bladder, absolute fecundity and other measurements: all samples for anatomy and measurements were from specimens immersed in 90 % ethanol. (4) Synchrotron X-ray microtomography of the saccular otolith: this experiment was performed at BL13W1 beamline at the Shanghai Synchrotron Radiation Facility (Shanghai, China); the slices were reconstructed using FBP algorithm, and 3D renderings were created and manipulated in VGStudio 2.1 software.
The Whole Genome Shotgun projects have been deposited at GenBank under accession numbers LCYQ00000000 (Sg), LAVF00000000 (Sr) and LAVE00000000 (Sa), which are the same versions described in this paper. The RNA-Seq data from four tissues (eye, skin, liver and ovary) have been deposited at GenBank under accession numbers SRS1179797–SRS1179800 (Sg), SRS1179996–SRS1179999 (Sr) and SRS1180000–SRS1180003 (Sa).
We thank Richard Winterbottom (Royal Ontario Museum, Toronto, ON, Canada) for reviewing and revising the writing of this paper; and we also acknowledge two anonymous reviewers for providing many excellent suggestions for improving this work. We acknowledge financial support from the joint project by the Yunnan Provincial Science and Technology Department and Yunnan Provincial Environmental Protection Department (Ottelia & Golden-line barbel Project 2012CA014) and the grant for the Lake Dianchi Freshwater Biodiversity Restoration Project (World Bank: GEF TF051795) to Junxing Yang; the Shenzhen Key Lab of Marine Genomics (CXB201108250095A), the Guangdong Provincial Key Lab of Molecular Breeding in Marine Economic Animals (2013B090800017) and the China 863 Project (2012AA10A407-2) to Qiong Shi; and the Yunnan Special Program for BGI-Yunnan (2013DA008) and the Cultivation of Backup Young and Middle-aged Academic Technology Leaders in Yunnan Province (2014HB053) to Le Cheng.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Jeffery WR. Cavefish as a model system in evolutionary developmental biology. Dev Biol. 2001;231(1):1–12.View ArticlePubMedGoogle Scholar
- Soares D, Niemiller ML. Sensory adaptations of fishes to subterranean environments. Bioscience. 2013;63(4):274–83.View ArticleGoogle Scholar
- Jeffery WR. Regressive evolution in Astyanax cavefish. Ann Rev Gene. 2009;43:25–47.View ArticleGoogle Scholar
- Romero A. Cave biology, life in darkness. New York: Cambridge University Press; 2009.View ArticleGoogle Scholar
- Rohner N, Jarosz DF, Kowalko JE, Yoshizawa M, Jeffery WR, Borowsky RL, et al. Cryptic variation in morphological evolution: HSP90 as a capacitor for loss of eyes in cavefish. Science. 2013;342(6164):1372–5.View ArticlePubMedPubMed CentralGoogle Scholar
- McGaugh SE, Gross JB, Aken B, Blin M, Borowsky R, Chalopin D, et al. The cavefish genome reveals candidate genes for eye loss. Nat Commun. 2014;5:5307.View ArticlePubMedPubMed CentralGoogle Scholar
- Shu S, Jiang W, Whitten T, Yang J, Chen X. Drought and China’s cave species. Science. 2013;340:272.View ArticlePubMedGoogle Scholar
- Wang D, Chen Y. The origin and adaptive evolution of the genus Sinocyclocheilus. Acta Hydrobiol Sinica. 2000;24(6):630–4.Google Scholar
- Che J, Zhou WW, Hu JS, Yan F, Papenfuss TJ, Wake DB, et al. Spiny frogs (Paini) illuminate the history of the Himalayan region and Southeast Asia. Proc Natl Acad Sci U S A. 2010;107(31):13765.View ArticlePubMedPubMed CentralGoogle Scholar
- Harrison T, Copeland P, Kidd W, Yin A. Raising Tibet. Science. 1992;255(5052):1663–70.View ArticlePubMedGoogle Scholar
- Zhisheng A, Kutzbach JE, Prell WL, Porter SC. Evolution of Asian monsoons and phased uplift of the Himalaya–Tibetan plateau since Late Miocene times. Nature. 2001;411(6833):62–6.View ArticlePubMedGoogle Scholar
- Clark M, Schoenbohm L, Royden L, Whipple K, Burchfiel B, Zhang X, et al. Surface uplift, tectonics, and erosion of eastern Tibet from large-scale drainage patterns. Tectonics. 2004;23(1):1006–29.View ArticleGoogle Scholar
- He DK, Chen YF. Biogeography and molecular phylogeny of the genus Schizothorax (Teleostei: Cyprinidae) in China inferred from cytochrome b sequences. J Biogeogr. 2006;33(8):1448–60.View ArticleGoogle Scholar
- Xiao H, Chen S, Liu Z, Zhang R, Li W, Zan R, et al. Molecular phylogeny of Sinocyclocheilus (Cypriniformes: Cyprinidae) inferred from mitochondrial DNA sequences. Mol Phylogenet Evol. 2005;36(1):67–77.View ArticlePubMedGoogle Scholar
- Zhao Y, Zhang C. Endemic fishes of Sinocyclocheilus (Cypriniformes: Cyprinidae) in China-species diversity, cave adaptation, systematics and zoogeography. Beijing: Science Press; 2009.Google Scholar
- Pasco-Viel E, Yang L, Veran M, Balter V, Mayden RL, Laudet V, et al. Stability versus diversity of the dentition during evolutionary radiation in cyprinine fish. Proc Biol Sci. 2014;281(1780):20132688.View ArticlePubMedPubMed CentralGoogle Scholar
- Shi Y, Li J, Li B, Yao T, Wang S, Li S, et al. Uplift of the Qinghai-Xizang (Tibetan) plateau and east Asia environmental change during late Cenozoic. Acta Geogr Sin. 1999;54(1):10–20.Google Scholar
- Li J, Fang X. Uplift of the Tibetan Plateau and environmental changes. Chinese Sci Bull. 1999;44(23):2117–24.View ArticleGoogle Scholar
- Zhu H, Chen Y, Pu P, Wang S, Zhuang D. Environments and sedimentation of fault lakes, Yunnan province. Beijing: Science Press; 1989.Google Scholar
- Qi D, Guo S, Zhao X, Yang J, TANG W. Genetic diversity and historical population structure of Schizopygopsis pylzovi (Teleostei: Cyprinidae) in the Qinghai-Tibetan Plateau. Freshwater Biol. 2007;52(6):1090–104.View ArticleGoogle Scholar
- Zhao K, Duan Z, Peng Z, Gan X, Zhang R, He S, et al. Phylogeography of the endemic Gymnocypris chilianensis (Cyprinidae): sequential westward colonization followed by allopatric evolution in response to cyclical Pleistocene glaciations on the Tibetan Plateau. Mol Phylogenet Evol. 2011;59(2):303–10.View ArticlePubMedGoogle Scholar
- Langecker TG, Neumann B, Hausberg C, Parzefall J. Evolution of the optical releasers for aggressive behavior in cave-dwelling Astyanax fasciatus (Teleostei, Characidae). Behav Processes. 1995;34(2):161–7.View ArticlePubMedGoogle Scholar
- Tobler M, Coleman SW, Perkins BD, Rosenthal GG. Reduced opsin gene expression in a cave-dwelling fish. Biol Lett. 2010;6(1):98–101.View ArticlePubMedPubMed CentralGoogle Scholar
- Strickler AG, Jeffery WR. Differentially expressed genes identified by cross-species microarray in the blind cavefish Astyanax. Integr Zool. 2009;4(1):99–109.View ArticlePubMedPubMed CentralGoogle Scholar
- Meng F, Zhao Y, Postlethwait JH, Zhang C. Differentially-expressed genes identified in cavefish endemic to China. Curr Zool. 2013;59(2):170–4.PubMedPubMed CentralGoogle Scholar
- Meng F, Braasch I, Phillips JB, Lin X, Titus T, Zhang C, et al. Evolution of the eye transcriptome under constant darkness in Sinocyclocheilus cavefish. Mol Bio Evol. 2013;30(7):1527–43.View ArticleGoogle Scholar
- Strickler AG, Byerly MS, Jeffery WR. Lens gene expression analysis reveals downregulation of the anti-apoptotic chaperone αA-crystallin during cavefish eye degeneration. Dev Genes Evol. 2007;217(11–12):771–82.View ArticlePubMedGoogle Scholar
- Strickler AG, Yamamoto Y, Jeffery WR. The lens controls cell survival in the retina: evidence from the blind cavefish Astyanax. Dev Biol. 2007;311(2):512–23.View ArticlePubMedPubMed CentralGoogle Scholar
- Thanos S, Bohm MR, Meyer Zu Horste M, Prokosch-Willing V, Hennig M, Bauer D, et al. Role of crystallins in ocular neuroprotection and axonal regeneration. Prog Retin Eye Res. 2014;42C:145–61.View ArticleGoogle Scholar
- Hooven TA, Yamamoto Y, Jeffery WR. Blind cavefish and heat shock protein chaperones: a novel role for hsp90alpha in lens apoptosis. Int J Dev Biol. 2004;48(8–9):731–8.View ArticlePubMedGoogle Scholar
- Protas ME, Hersey C, Kochanek D, Zhou Y, Wilkens H, Jeffery WR, et al. Genetic analysis of cavefish reveals molecular convergence in the evolution of albinism. Nat Genet. 2005;38(1):107–11.View ArticlePubMedGoogle Scholar
- Bilandžija H, Ma L, Parkhurst A, Jeffery WR. A potential benefit of albinism in Astyanax cavefish: downregulation of the oca2 gene increases tyrosine and catecholamine levels as an alternative to melanin synthesis. PLoS One. 2013;8(11):e80823.View ArticlePubMedPubMed CentralGoogle Scholar
- King RA, Mentink MM, Oetting WS. Non-random distribution of missense mutations within the human tyrosinase gene in type I (tyrosinase-related) oculocutaneous albinism. Mol Biol Med. 1991;8(1):19–29.PubMedGoogle Scholar
- Hutton SM, Spritz RA. Comprehensive analysis of oculocutaneous albinism among non-Hispanic caucasians shows that OCA1 is the most prevalent OCA type. J Invest Dermatol. 2008;128(10):2442–50.View ArticlePubMedPubMed CentralGoogle Scholar
- Krauss J, Astrinides P, Frohnhöfer HG, Walderich B, Nüsslein-Volhard C. Transparent, a gene affecting stripe formation in Zebrafish, encodes the mitochondrial protein Mpv17 that is required for iridophore survival. Biol Open. 2013;2:703–10.View ArticlePubMedPubMed CentralGoogle Scholar
- Frohnhöfer HG, Krauss J, Maischein HM, Nüsslein-Volhard C. Iridophores and their interactions with other chromatophores are required for stripe formation in zebrafish. Development. 2013;140(14):2997–3007.View ArticlePubMedPubMed CentralGoogle Scholar
- Kondo S, Kuwahara Y, Kondo M, Naruse K, Mitani H, Wakamatsu Y, et al. The medaka rs-3 locus required for scale development encodes ectodysplasin-A receptor. Curr Biol. 2001;11(15):1202–6.View ArticlePubMedGoogle Scholar
- Pulkkinen L, Gerecke D, Christiano A, Wagman D, Burgeson R, Uitto J. Cloning of the beta 3 chain gene (LAMB3) of human laminin 5, a candidate gene in junctional epidermolysis bullosa. Genomics. 1995;25(1):192–8.View ArticlePubMedGoogle Scholar
- Mecklenbeck S, Hammami-Hauasli N, Höpfner B, Schumann H, Kramer A, Küster W, et al. Clustering of COL7A1 mutations in exon 73: implications for mutation analysis in dystrophic epidermolysis bullosa. J Invest Dermatol. 1999;112(3):398–400.View ArticlePubMedGoogle Scholar
- Muller M, Smolders JW, Meyer zum Gottesberge AM, Reuter A, Zwacka RM, Weiher H, et al. Loss of auditory function in transgenic Mpv17-deficient mice. Hear Res. 1997;114(1–2):259–63.View ArticlePubMedGoogle Scholar
- Dreyer B, Tranebjaerg L, Rosenberg T, Weston MD, Kimberling WJ, Nilssen O. Identification of novel USH2A mutations: implications for the structure of USH2A protein. Eur J Hum Genet. 2000;8(7):500–6.View ArticlePubMedGoogle Scholar
- Baux D, Larrieu L, Blanchet C, Hamel C, Ben Salah S, Vielle A, et al. Molecular and in silico analyses of the full-length isoform of usherin identify new pathogenic alleles in Usher type II patients. Hum Mutat. 2007;28(8):781–9.View ArticlePubMedGoogle Scholar
- Garcia-Garcia G, Aparisi MJ, Jaijo T, Rodrigo R, Leon AM, Avila-Fernandez A, et al. Mutational screening of the USH2A gene in Spanish USH patients reveals 23 novel pathogenic mutations. Orphanet J Rare Dis. 2011;6:65.View ArticlePubMedPubMed CentralGoogle Scholar
- Van WE, Pennings R, te Brinke H, Claassen A, Yntema H, Hoefsloot L, et al. Identification of 51 novel exons of the Usher syndrome type 2A (USH2A) gene that encode multiple conserved functional domains and that are mutated in patients with Usher syndrome type II. Am J Hum Genet. 2004;74(4):738–44.View ArticleGoogle Scholar
- Bhattacharya G, Kalluri R, Orten D, Kimberling W, Cosgrove D. A domain-specific usherin/collagen IV interaction may be required for stable integration into the basement membrane superstructure. J Cell Sci. 2004;15(117):233–42.View ArticleGoogle Scholar
- Niemiller ML, Higgs DM, Soares D. Evidence for hearing loss in amblyopsid cavefishes. Bio Lett. 2013;9(3):20130104.View ArticleGoogle Scholar
- Yoshizawa M, Gorički Š, Soares D, Jeffery WR. Evolution of a behavioral shift mediated by superficial neuromasts helps cavefish find food in darkness. Curr Biol. 2010;20(18):1631–6.View ArticlePubMedPubMed CentralGoogle Scholar
- You X, Bian C, Zan Q, Xu X, Liu X, Chen J, et al. Mudskipper genomes provide insights into the terrestrial adaptation of amphibious fishes. Nat Commun. 2014;5(5594):1–8.Google Scholar
- Cavallari N, Frigato E, Vallone D, Frohlich N, Lopez-Olmeda JF, Foa A, et al. A blind circadian clock in cavefish reveals that opsins mediate peripheral clock photoreception. PLoS Bio. 2011;9(9):e1001142.View ArticleGoogle Scholar
- Duboue ER, Keene AC, Borowsky RL. Evolutionary convergence on sleep loss in cavefish populations. Curr Biol. 2011;21(8):671–6.View ArticlePubMedGoogle Scholar
- Lowrey PL, Takahashi JS. Genetics of circadian rhythms in mammalian model organisms. Adv Genet. 2011;74:175–230.View ArticlePubMedPubMed CentralGoogle Scholar
- Riesch R, Tobler M, Plath M, Schlupp I. Offspring number in a livebearing fish (Poecilia mexicana, Poeciliidae): reduced fecundity and reduced plasticity in a population of cave mollies. Environ Biol Fish. 2009;84(1):89–94.View ArticleGoogle Scholar
- Pan X, Yang J, Chen X, Li Z. Broodstocks management, fecundity and the relationship between egg size and embryo survival ability of Sinocyclocheilus grahami. Zoological Res. 2011;32(2):196–203.Google Scholar
- Adham IM, Eck TJ, Mierau K, Müller N, Sallam MA, Paprotta I, et al. Reduction of spermatogenesis but not fertility in Creb3l4-deficient mice. Mol Cell Biol. 2005;25(17):7657–64.View ArticlePubMedPubMed CentralGoogle Scholar
- Yamamoto Y, Byerly MS, Jackman WR, Jeffery WR. Pleiotropic functions of embryonic sonic hedgehog expression link jaw and taste bud amplification with eye loss during cavefish evolution. Dev Biol. 2009;330(1):200–11.View ArticlePubMedPubMed CentralGoogle Scholar
- Luo R, Liu B, Xie Y, Li Z, Huang W, Yuan J, et al. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Gigascience. 2012;1(1):18.View ArticlePubMedPubMed CentralGoogle Scholar
- Li R, Fan W, Tian G, Zhu H, He L, Cai J, et al. The sequence and de novo assembly of the giant panda genome. Nature. 2010;463(7279):311–7.View ArticlePubMedPubMed CentralGoogle Scholar
- Li R, Yu C, Li Y, Lam TW, Yiu SM, Kristiansen K, et al. SOAP2: An improved ultrafast tool for short read alignment. Bioinformatics. 2009;25(15):1966–7.View ArticlePubMedGoogle Scholar
- Tarailo-Graovac M, Chen N. Using RepeatMasker to identify repetitive elements in genomic sequences. Curr Protoc Bioinformatics. 2009;Chapter 4:Unit 4.10. doi:10.1002/0471250953.bi0410s25.PubMedGoogle Scholar
- Jurka J, Kapitonov VV, Pavlicek A, Klonowski P, Kohany O, Walichiewicz J. Repbase Update, a database of eukaryotic repetitive elements. Cytogenet Genome Res. 2005;110(1–4):462–7.View ArticlePubMedGoogle Scholar
- Benson G. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 1999;27(2):573–80.View ArticlePubMedPubMed CentralGoogle Scholar
- Elsik CG, Mackey AJ, Reese JT, Milshina NV, Roos DS, Weinstock GM. Creating a honey bee consensus gene set. Genome Biol. 2007;8(1):R13.View ArticlePubMedPubMed CentralGoogle Scholar
- Cho YS, Hu L, Hou H, Lee H, Xu J, Kwon S, et al. The tiger genome and comparative analysis with lion and snow leopard genomes. Nat Commun. 2013;4:2433.PubMedPubMed CentralGoogle Scholar
- Trapnell C, Pachter L, Salzberg SL. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics. 2009;25(9):1105–11.View ArticlePubMedPubMed CentralGoogle Scholar
- Trapnell C, Hendrickson DG, Sauvageau M, Goff L, Rinn JL, Pachter L. Differential analysis of gene regulation at transcript resolution with RNA-seq. Nat Biotechnol. 2013;31(1):46–53.View ArticlePubMedGoogle Scholar
- Guindon S, Dufayard JF, Lefort V, Anisimova M, Hordijk W, Gascuel O. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst Biol. 2010;59(3):307–21.View ArticlePubMedGoogle Scholar
- Guindon S, Delsuc F, Dufayard JF, Gascuel O. Estimating maximum likelihood phylogenies with PhyML. Methods Mol Biol. 2009;537:113–37.View ArticlePubMedGoogle Scholar
- Huelsenbeck JP, Ronquist F. MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics. 2001;17(8):754–5.View ArticlePubMedGoogle Scholar
- Yang Z. PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol. 2007;24(8):1586–91.View ArticlePubMedGoogle Scholar
- Yang Z. PAML: a program package for phylogenetic analysis by maximum likelihood. Comput Appl Biosci. 1997;13(5):555–6.PubMedGoogle Scholar
- Wikstrom N, Savolainen V, Chase MW. Evolution of the angiosperms: calibrating the family tree. Proc Biol Sci. 2001;268(1482):2211–20.View ArticlePubMedPubMed CentralGoogle Scholar
- Wang ZQ. A new Permian gnetalean cone as fossil evidence for supporting current molecular phylogeny. Ann Bot. 2004;94(2):281–8.View ArticlePubMedPubMed CentralGoogle Scholar
- Benton MJ, Donoghue PC. Paleontological evidence to date the tree of life. Mol Bio Evol. 2007;24(1):26–53.View ArticleGoogle Scholar
- Li H, Durbin R. Inference of human population history from individual whole-genome sequences. Nature. 2011;475(7357):493–6.View ArticlePubMedPubMed CentralGoogle Scholar
- Graur D, Li WH. Fundamentals of molecular evolution. Sunderland: Sinauer Associates; 2000.Google Scholar
- Philipp JK. Gnuplot in action: understanding data with graphs. New York: Manning Publications; 2009.Google Scholar
- De Bie T, Cristianini N, Demuth JP, Hahn MW. CAFE: a computational tool for the study of gene family evolution. Bioinformatics. 2006;22(10):1269–71.View ArticlePubMedGoogle Scholar
- Hahn MW, De Bie T, Stajich JE, Nguyen C, Cristianini N. Estimating the tempo and mode of gene family evolution from comparative genomic data. Genome Res. 2005;15(8):1153–60.View ArticlePubMedPubMed CentralGoogle Scholar
- Demuth JP, De Bie T, Stajich JE, Cristianini N, Hahn MW. The evolution of mammalian gene families. PLoS One. 2006;1:e85.View ArticlePubMedPubMed CentralGoogle Scholar
- Sun YB, Zhou WP, Liu HQ, Irwin DM, Shen YY, Zhang YP. Genome-wide scans for candidate genes involved in the aquatic adaptation of dolphins. Genome Biol Evol. 2013;5(1):130–9.View ArticlePubMedPubMed CentralGoogle Scholar
- Zhang J, Nielsen R, Yang Z. Evaluation of an improved branch-site likelihood method for detecting positive selection at the molecular level. Mol Biol Evol. 2005;22(12):2472–9.View ArticlePubMedGoogle Scholar
- da Huang W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4(1):44–57.View ArticleGoogle Scholar