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Article

Meta-Transcriptomic Analysis of RNAseq Data Reveals Pacu and Loach Fish with Unusually High Levels of Myoglobin Expression in Skeletal Muscles

by
Rui-Yi Chen
1,2,
Bui Thi Ngoc Hieu
3,4,
Gilbert Audira
3,4,
Bao Lou
5,*,
Ming-Der Lin
6,* and
Chung-Der Hsiao
3,4,7,*
1
Key Lab of Mariculture and Enhancement of Zhejiang Province, Marine Fisheries Research Institute of Zhejiang, Zhoushan 316100, China
2
Marine and Fishery Institute, Zhejiang Ocean University, Zhoushan 316100, China
3
Department of Bioscience Technology, Chung Yuan Christian University, Chung-Li 32023, Taiwan
4
Department of Chemistry, Chung Yuan Christian University, Chung-Li 32023, Taiwan
5
Institute of Hydrobiology, Zhejiang Academy of Agricultural Sciences, Shiqiao Road 198, Hangzhou 310021, China
6
Department of Molecular Biology and Human Genetics, College of Medicine, Tzu Chi University, 701 Zhongyang Rd, Sec. 3, Hualien 97004, Taiwan
7
Center for Nanotechnology, Chung Yuan Christian University, Chung-Li 32023, Taiwan
*
Authors to whom correspondence should be addressed.
Animals 2020, 10(7), 1130; https://doi.org/10.3390/ani10071130
Submission received: 25 May 2020 / Revised: 20 June 2020 / Accepted: 27 June 2020 / Published: 3 July 2020
(This article belongs to the Special Issue Transcriptomics in Autochthonous Breeds or Populations of Livestock and Aquaculture Species)
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Abstract

:

Simple Summary

Oxygen-binding proteins that mediate oxygen-binding for storage and consumption, to reduce energy, are very diverse in fish, depending on their habitats. In the present study, oxygen-binding protein gene expression in the skeletal muscle of 25 diverse fish species was examined by a meta-transcriptomic approach. By using RNAseq data, this is the first study to examine the high level of myoglobin, one of the oxygen-binding proteins, transcripts in pacu and loach fish that might be related to their high tolerance for the oxygen-deficient environment. In addition, this study presents the power of the current method to compare the fish oxygen-binding protein expression and its putative gene expansion event.

Abstract

Oxygen-binding proteins, such as myoglobin, hemoglobin, neuroglobin, and cytoglobin, play a role in oxygen binding and delivery to tissues. In icefish, the loss of myoglobin and hemoglobin genes has been reported to be an adaptive evolution event. This interesting finding prompted us to exam oxygen-binding protein expression in diverse fish species. Taking advantage of substantial RNAseq data deposited in the NCBI (National Center for Biotechnology Information) database, we adopted a meta-transcriptomic approach to explore and compare four oxygen-binding protein gene expression levels in the skeletal muscle of 25 diverse fish species for the first time. RNAseq data were downloaded from the NCBI Sequence Read Archive (SRA) database, and de novo assembly was performed to generate transcript contigs. The genes encoding oxygen-binding proteins were then identified by the BLAST search, and the relative expression level of oxygen-binding protein genes was normalized by the RPKM (Reads per Kilobase Million) method. By performing expression profiling, hierarchy clustering, and principal component analysis, pacu and loach fish were noticed by their high myoglobin expression levels in skeletal muscle tissues among 25 diverse fish species. In conclusion, we demonstrated that meta-transcriptomic analysis of RNAseq data is an informative approach to compare the oxygen-binding protein expression and putative gene expansion event in fish.

1. Introduction

Oxygen homeostasis is an essential mechanism in living organisms that is regulated by four major oxygen-binding proteins, namely hemoglobin, myoglobin, cytoglobin, and neuroglobin [1]. The primary classification of these four oxygen-binding proteins is based on their tissue distribution and oxygen-binding affinity. The major role of these oxygen-binding proteins is on mediating oxygen-binding for storage and consumption, to reduce energy by respiratory progress. Hemoglobin is a tetramer comprising two α and two β globin chains (α2β2), one molecule of heme, and ferric ions. Hemoglobin is essential for aerobic-respiratory fishes, whose living habitats are highly abundant in oxygen [2,3,4]. Myoglobin is a monomer and predominantly expressed in skeletal and cardiac muscles, and it is an essential intermediary factor to mediate an oxygen delivery from blood to muscle tissues [5,6]. Cytoglobin is a hemoprotein expressed in response to oxidative stress in a variety of tissues. It facilitates the diffusion of oxygen through tissues and helps intracellular oxygen transport [7,8]. The neuroglobin is a monomeric globin with a higher oxygen affinity than hemoglobin. It has been reported that neuroglobin plays a protective role against nitric oxide toxicity in the nervous system [9,10].
Fish are the most widespread and divergent vertebrates that adopted to diverse habitats with different salinity (freshwater, brackish water, or seawater), distinct dissolved oxygen, alkalinity, and temperatures. Some freshwater species, such as crucian carp (Carassius carassius) can survive in extremely oxygen-deficient conditions by relying more on subtle neuromodulatory mechanisms, such as ethanol production as their metabolic end-product, caused by duplicated pyruvate dehydrogenase genes, for anoxic metabolic depression [11,12]. In addition, another freshwater species, the pacu fish (Piaractus mesopotamicus), which has a high economic value in South America, utilizes aquatic surface respiration (ASR) in order to survive in this condition [13]. Moreover, this species can also survive in conditions with less than 9 mm Hg oxygen concentrations under the intensive aquaculture conditions in fishponds. There is increasing attention being given to the pacu fish, particularly from researchers from Brazil; this interest enhances the farming of this species. Accordingly, some studies on the reproduction [14], feeding, and nutrition [15,16,17] of pacu fish have been carried out [18]. Several fish species have been evolved in dealing with hypoxia or even anoxia conditions, such as pond loach (Misgurnus anguillicaudatus), by aquatic surface respiration [19], and Siamese fighting fish (Betta splendens), by labyrinth organ respiration [20]. Instead of the tolerance of hypoxia conditions, the Atlantic cod (Gadus morhua L.) displays avoidance behavior from the hypoxia environment, by enhancing oxygen sensing [21].
Gene expression profiling based on the difference in expression levels, such as microarray, which detects the upregulation or downregulation of target genes in certain physiological or pathological conditions in fish, is widely used in the study of biological processes [22,23,24]. However, one major disadvantage of such a microarray-based transcript detection method lies in its limitation on detecting transcripts with low expression levels. In addition, due to the limitation of the probe density in a single chip, the gene of interest could be missed if the corresponding probe does not exist on the chip. Compared to the microarray-based method, RNAseq deep sequencing provides a complete transcript content and thus can quantify gene expression according to a given reference genome. Therefore, the next-generation sequencing techniques for RNAseq have become an alternative or even better tool to the researches in the field of transcriptomic analysis due to its high-throughput, unbiased, and relatively cost-effective nature. Taken together, by taking advantage of the abundant RNAseq entries in the NCBI (National Center for Biotechnology Information) Sequence Read Archive (SRA) database, we applied a meta-transcriptomics approach to explore the expression profiling of four oxygen-binding protein genes in skeletal muscle from 25 diverse fish species.

2. Materials and Methods

2.1. RNA Extraction

The muscle tissues dissected from wild juvenile Bombay duck (body length around 2 cm) and beltfish (Trichiurus lepturus) were immediately stored in RNAlater (Qiagen, Hilden, Germany) and then stored at −80 °C, prior to RNA extraction. Total RNAs were extracted by using the TRIZOL Kit (Invitrogen, Carlsbad, CA, USA), following the manufacturer’s instructions. Total RNA samples were then digested by DNase I (Thermo Scientific, Waltham, MA, USA), to remove potential genomic DNA contamination. Integrity and size distribution were checked with a Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA, USA) (with ethics document approval ID CYCU104024).

2.2. RNA Isolation, Library Construction, and Illumina Sequencing

Initially, about 2.5 µg of starting total RNAs was used to synthesize the cDNA libraries, by following the standard protocols of the Illumina TruSeq RNA Sample Preparation Kit (Illumina, San Diego, CA, USA). The final library had an insert size of about 200–300 bp. After qPCR quantitation and dilution (by using KAPA SYBR FAST Master Mix), the sequencing library was sequenced on an Illumina NextSeq500 platform with 150 bp paired-end reads. Adaptor sequences were trimmed, and reads with low quality were further removed by cutadapt software [25]. After the removal of ambiguous nucleotides, duplicates, and low-quality sequences (Phred quality scores < 20), cleaned reads were obtained and deposited in the NCBI SRA database (Table 1).

2.3. De Novo Assembly of RNAseq

Other fish muscles’ raw next-generation sequencing (NGS) reads were downloaded from the file transfer protocol (FTP) site of Sequence Read Archive (SRA) in the DNA Data Bank of Japan (DDBJ) database (http://trace.ddbj.nig.ac.jp/dra/index_e.html) by FileZilla software (https://filezilla-project.org/) and then converted into fastq format by using NCBI sratoolkit (http://www.ncbi.nlm.nih.gov/Traces/sra/?view=software). The raw NGS reads of muscle from each fish species were de novo assembled into contigs by CLCBio software (http://www.clcbio.com/) with default parameter settings (k-mer = 23 and bubble size = 50). The number and quality (N50) of assembled contigs for all analyzed fish species are summarized in Table 1.

2.4. Identification of Oxygen-Binding Proteins in Muscle Transcriptome

The assembled contigs were later exported from CLCBio software and imported into Geneious software, to perform in-house basic local alignment search tool (BLAST), to find regions of local similarity between sequences. We used tBLASTN, a mode operation for BLAST that aligns protein sequences to a nucleotide database translated in all six frames, to search the potential contigs coding for either myoglobin, hemoglobin, cytoglobin, or neuroglobin with an e-value cutoff setting at 1 × 10−5. The potential contig was later BLASTX against the reference sequence (Refseq) database, a comprehensive, integrated, non-redundant, well-annotated set of reference sequences, including genomic, transcript, and protein, to validate the gene annotation with an e-value cutoff of 1 × 10−5. For gene expression calculation, the raw reads were mapped to the assembled contigs by CLCBio software, and the relative expressional level was calculated as RPKM (Reads per Kilobase Million). The number and quality (N50) of the oxygen-binding-related proteins of 25 analyzed fish species were summarized in Table 1.

2.5. PCA, Heatmap, and Clustering Analysis

In order to compare the relative gene expression patterns of four oxygen-binding proteins in muscle tissues among 25 different fish species, PCA was performed, and heatmap clusters were generated. The relative contig number and RPKM values for each oxygen-binding protein were input into and saved as an Excel file (.xlsx), by using Microsoft Excel, and the Excel file was converted to a comma-separated values-type file (.csv) to be readable by R software. PCA, heatmap, and clustering analysis were carried out by R software (https://www.r-project.org/). In addition, mean centering was carried out, since each variable was treated equally, in the sense that larger relative changes in response will receive the most weighting. In the PCA, variable group classification was determined by using the k-means clustering algorithm, and then the clusters returned by the k-means algorithm were used to color variables [26].

3. Results and Discussion

3.1. Meta-Transcriptomic Analysis of Oxygen-Binding Protein Expression

Fish can survive in a diverse range of water oxygen levels. By radiation adaptation, the expression of hemoglobin and myoglobin genes is absent in some Antarctic icefishes [29,30]. This interesting phenomenon led us to ask whether the expression levels of oxygen-binding protein genes display a unique pattern among various fish species that live in a diverse habitat with different water oxygen levels. To answer this question, we used a bioinformatics approach to compare the relative expression levels of two major oxygen-binding protein genes, hemoglobin and myoglobin, in the skeletal muscle of fish. In addition, other two oxygen-binding protein genes, cytoglobin and neuroglobin were also analyzed, in order to serve as control groups. Taking the advantage of the rich information in the Sequence Read Archive (SRA) database, we sequenced or collected muscle RNAseq data from 25 fish species, to perform comparative studies systematically (species names are listed in Table 1). We used CLCBio software to assemble raw RNAseq reads into contigs by using the default setting (analysis pipeline is summarized in Figure 1). The detailed information for fish species, raw data size, sequencing method, assembly contig number, and assembly quality (N50) were summarized in Table 1. The size of raw SRA data for different fish species ranged from 1.9 to 8.1 Gb. The size of the assembled contig number for different fish species ranged from 21,259 to 136,066, with N50 ranging from 338 to 972. The oxygen-binding protein homologs of hemoglobin, myoglobin, cytoglobin, and neuroglobin were identified by using BLAST search, and the relative number of assembled contigs matched with oxygen-binding proteins for different fish species is summarized in Appendix A, Table A1. In RNAseq datasets of fish skeletal muscle, based on relative gene expression level, we found the predominant oxygen-binding proteins expressed are hemoglobin and myoglobin. On the contrary, the number of annotated contigs encoding cytoglobin or neuroglobin is very low or even absent in most fish species (Appendix A, Table A1). Among 25 fish species analyzed, we found the pacu fish (Piaractus mesopotamicus) displays a unique oxygen-binding protein expression due to its outstanding high number for assembled contigs annotated as either hemoglobin (65 transcripts) and myoglobin (31 transcripts) (Appendix A, Table A1). By contrast, the contig numbers of hemoglobin and myoglobin in other fish species are usually less than 16 and 6, respectively (Appendix A, Table A1).

3.2. Comparison of the Expression Levels of Oxygen-Binding Protein Genes among Fish Species

Next, we performed gene mapping to compare the relative expression level of hemoglobin and myoglobin in skeletal muscle tissues among diverse fish species. The relative expression level of oxygen-binding protein homologs was calculated and presented as RPKM (Reads per Kilobase Million) for expressional normalization [31]. As a result, we identified that the pacu fish has a high myoglobin expression level of 1327.8, based on RPKM (Figure 2A, Appendix A, Table A2). Although the number of contigs annotated as hemoglobin is high in pacu fish, their relative expression level is low (Figure 2B). Another interesting species is the loach fish (Paramisgurnus dabryanus), showing one myoglobin-associated contig, but with an extremely high RPKM expression level, at 3136.4 (Figure 2A, Appendix A, Table A2). Based on hemoglobin transcript abundance, we found the Blunt snout bream (Megalobrama amblycephala), an oxygen-sensitive fish species, displays a relatively high hemoglobin expression level in the skeletal muscle (Figure 2B). The other two oxygen-binding protein genes, cytoglobin and neuroglobin can be considered as low-expressed genes in skeletal muscle since their RPKM level is less than 2.5 in all fish species examined. The phylogenetic tree based on complete mitochondrial DNA sequences from these fish species can be found in Figure 2C.

3.3. PCA and Hierarchical Clustering Analyses of the Oxygen-Binding Protein Genes Expression among Fish Species

Next, we performed principal component analysis (PCA) and hierarchical clustering, to reduce the data dimension and complexity, and to generate a heatmap for inter-species comparison. PCA is a mathematical method able to reduce data dimension and complexity. From the PCA analysis, all of the 25 fishes were grouped into four major clusters, based on their gene expression patterns for hemoglobin, myoglobin, cytoglobin, and neuroglobin, with the first cluster (red color) as the biggest cluster among all the clusters (Figure 3B). The majority of the fishes, including zebrafish and medaka fish, were grouped in the first cluster (red color) (Figure 3B), which has higher hemoglobin expression than the fish species in other clusters (Figure 3A). Four fishes, namely Amia calva, Pangasianodon hypophtaimus, Parmisgurpus dabryanus, and Piaractus mesopotamicus, were grouped into the second cluster (blue color). Based on the heatmap results, it can be concluded that this grouping is reasonable because these fishes have unique and similar patterns regarding their myoglobin expression level, which is quite high compared to the rest of the fishes (Figure 3A). The third cluster (pink color) consists of two species, Gnathonemus petersii and Callorhinchus milii. This categorization is plausible since both of the fishes showed a high level of cytoglobin expression in the skeletal muscle, while this phenomenon was not observed in other fishes (Figure 3A). Furthermore, the fourth cluster (green color) consists of Apteronotus albifrons, Coregonus lavaretus, and Osteglossum bicirrhosum, showing a high-level expression of both myoglobin and hemoglobin in their skeletal muscle (Figure 3A). Taken together, the different expression levels of oxygen-binding protein genes in each fish species examined resulted in four major clusters in the PCA and heatmap clustering analyses.

3.4. The Skeletal Muscle of Pacu Fish Has Multiple Myoglobin Transcripts with High Expression Level

Our meta-transcriptomic study provides molecular evidence that there is a high level of myoglobin expression in the skeletal muscle of pacu fish. This finding may help to explain their ability to cope with oxygen-deficiency habitats. Moreover, we identified 31 transcripts annotated as myoglobin. The numerous forms of myoglobin transcripts identified in the pacu fish muscle could be originated by a large number of duplications of myoglobin genes in its genome. In common carp, duplication and differentiation of myoglobin genes have been identified by bacterial artificial chromosome (BAC) analysis [32]. In West African lungfish, Protopterus annectens, at least seven distinct myoglobin genes (PanMb1–7) have been identified, and each of them displays differential expression patterns in different tissues [33]. Consistent with the hypothesis that myoglobin genes are highly duplicated in the pacu genome, we observed several non-redundant myoglobin transcripts encoding myoglobin with amino acid substitutions by multiple sequence alignment (Appendix A, Figure A1). Alternatively, we hypothesize that multiple myoglobin transcript contigs in pacu fish may be generated by alternative splicing. This hypothesis is based on a previous study that detected sixteen alternatively-spliced myoglobin transcripts in human cancer [34]. Future studies on whole-genome sequencing for pacu fish are required to validate the above hypotheses. In addition to myoglobin, this study also identified relative high-level hemoglobin expression in the skeletal muscle of blunt snout bream (Megalobrama amblycephala). Blunt snout bream is an oxygen-sensitive fish species showing massive mortality once the dissolved oxygen level declines in the pond. Therefore, the high-level hemoglobin expression in the skeletal muscle in blunt snout bream can be considered to be a physiological adaptation. More studies are needed to address the underlying mechanism for this interesting phenotype.

4. Conclusions

In conclusion, in this study, we provided good evidence to show the power of meta-transcriptomic analysis on mining and comparing oxygen-binding protein expression in fish muscle RNAseq data for the first time. This approach led us to identify pacu and loach fish with exceptional levels of myoglobin transcripts in their skeletal muscle that might be functionally associated with their high-tolerance potential for the oxygen-deficient environments. However, one has to keep in mind that deposited datasets in the SRA that were used in the present study often represent a relatively small number of biological samples, and there is a possibility that the different animals included were maintained under identical or comparable conditions. Thus, validation with RT-qPCR for the fish species is needed in the future. In addition, this approach opens up a new avenue to perform data mining on more species or tissue types, to validate myoglobin and hemoglobin expressional adaptation among diverse fish species.

Author Contributions

Conceptualization, M.-D.L. and C.-D.H.; Data curation and Formal analysis, R.-Y.C., B.T.N.H. and G.A.; Funding acquisition, C.-D.H.; Investigation and Methodology, B.T.N.H. and G.A.; Project administration, C.-D.H.; Resources, B.L.; Software, G.A.; Supervision, B.L. and C.-D.H.; Validation, B.T.N.H. and G.A.; Visualization, R.-Y.C.; Writing—original draft, R.-Y.C., M.-D.L. and C.-D.H. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by the grants sponsored by the Ministry of Science and Technology MOST 108-2313-B-033-001-MY3 and MOST 107-2622-B-033-001-CC2 to C.-D.H.

Acknowledgments

We appreciate the two anonymous reviewers and editors for their professional comments, which improved the quality of this paper. We also thank Jung-Ren Chen at the Department of Biological Science and Technology, College of Medicine, I-Shou University, for doing English editing.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table
Table A1. Summary of the assembled contigs annotated as transcripts of oxygen-binding protein genes in 25 fish species.
Table A1. Summary of the assembled contigs annotated as transcripts of oxygen-binding protein genes in 25 fish species.
Species NameHemoglobinMyoglobinCytoglobinNeuroglobin
Alosa alosa8120
Amia calva7100
Anguilla anguilla3000
Apteronotus albifrons2110
Callorhinchus milii0010
Coregonus lavaretus12100
Danio rerio8020
Esox lucius6000
Gnathonemus petersii6111
Harpadon nehereus7000
Larimichthys polyactis6110
Lepisosteus oculatus11100
Megalobrama amblycephala5100
Oryzias latipes7120
Osteoglossum bicirrhosum6200
Pangasianodon hypophthalmus9600
Pantodon buchholzi8020
Paramisgurnus dabryanus5100
Perca fluviatilis7000
Piaractus mesopotamicus653100
Plecoglossus altivelis7210
Salmo trutta4000
Thymallus thymallus6121
Trichiurus lepturus16000
Umbra pygmaea1110
Table
Table A2. Summary of the transcript expression level based on the RPKM method for oxygen-binding protein genes in 25 fish species.
Table A2. Summary of the transcript expression level based on the RPKM method for oxygen-binding protein genes in 25 fish species.
Species NameHemoglobinMyoglobin Cytoglobin Neuroglobin
Alosa alosa16.10.6 0.80
Amia calva0.50.8 00
Anguilla anguilla14.7000
Apteronotus albifrons2.21.1 0.90
Callorhinchus milii002.40
Coregonus lavaretus0.40.3 00
Danio rerio10.400.70
Esox lucius0.4000
Gnathonemus petersii0.30.20.30.3
Harpadon nehereus108.5000
Larimichthys polyactis38.63.9 2.50
Lepisosteus oculatus37.2000
Megalobrama amblycephala523.314.0 00
Oryzias latipes50.4 0.30
Osteoglossum bicirrhosum1.3100
Pangasianodon hypophthalmus20.843.500
Pantodon buchholzi2.200.20
Paramisgurnus dabryanus67.63136.4 00
Perca fluviatilis1.4000
Piaractus mesopotamicus461327.800
Plecoglossus altivelis20.81.4 0.30
Salmo trutta4.5000
Thymallus thymallus13.63.2 0.35.6
Trichiurus lepturus81.9000
Umbra pygmaea8.40.12 0.80
Animals 10 01130 g0a1 550
Figure A1. Sequence alignment of the translated contigs annotated as myoglobin in pacu fish. Thirty-one polypeptide translated from myoglobin contigs were used for multiple sequence alignment by using Geneious software. The conserved residues are marked as shaded black color, and the non-conserved residues are marked as open or gray-shaded colors.
Figure A1. Sequence alignment of the translated contigs annotated as myoglobin in pacu fish. Thirty-one polypeptide translated from myoglobin contigs were used for multiple sequence alignment by using Geneious software. The conserved residues are marked as shaded black color, and the non-conserved residues are marked as open or gray-shaded colors.
Animals 10 01130 g0a1

References

  1. Wilson, M.T.; Reeder, B.J. Oxygen-binding haem proteins. Exp. Physiol. 2008, 93, 128–132. [Google Scholar] [CrossRef] [PubMed]
  2. Nikinmaa, M.; Rees, B.B. Oxygen-dependent gene expression in fishes. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2005, 288, R1079–R1090. [Google Scholar] [CrossRef] [Green Version]
  3. Terwilliger, N.B. Functional adaptations of oxygen-transport proteins. J. Exp. Biol. 1998, 201, 1085–1098. [Google Scholar]
  4. Lekang, O.I. Aquaculture Engineering; Wiley: Hoboken, NJ, USA, 2013. [Google Scholar]
  5. Wittenberg, B.A.; Wittenberg, J.B. Myoglobin-mediated oxygen delivery to mitochondria of isolated cardiac myocytes. Proc. Natl. Acad. Sci. USA 1987, 84, 7503–7507. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Ordway, G.A.; Garry, D.J. Myoglobin: An essential hemoprotein in striated muscle. J. Exp. Biol. 2004, 207, 3441–3446. [Google Scholar] [CrossRef] [Green Version]
  7. Singh, S.; Canseco, D.C.; Manda, S.M.; Shelton, J.M.; Chirumamilla, R.R.; Goetsch, S.C.; Ye, Q.; Gerard, R.D.; Schneider, J.W.; Richardson, J.A. Cytoglobin modulates myogenic progenitor cell viability and muscle regeneration. Proc. Natl. Acad. Sci. USA 2014, 111, E129–E138. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  8. Burmester, T.; Ebner, B.; Weich, B.; Hankeln, T. Cytoglobin: A novel globin type ubiquitously expressed invertebrate tissues. Mol. Biol. Evol. 2002, 19, 416–421. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  9. Jin, K.; Mao, X.O.; Xie, L.; Khan, A.A.; Greenberg, D.A. Neuroglobin protects against nitric oxide toxicity. Neurosci. Lett. 2008, 430, 135–137. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  10. Burmester, T.; Weich, B.; Reinhardt, S.; Hankeln, T. A vertebrate globin expressed in the brain. Nature 2000, 407, 520–523. [Google Scholar] [CrossRef] [PubMed]
  11. Nilsson, G.E.; Renshaw, G.M. Hypoxic survival strategies in two fishes: Extreme anoxia tolerance in the North European crucian carp and natural hypoxic preconditioning in a coral-reef shark. J. Exp. Biol. 2004, 207, 3131–3139. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Fagernes, C.E.; Stensløkken, K.-O.; Røhr, Å.K.; Berenbrink, M.; Ellefsen, S.; Nilsson, G.E. Extreme anoxia tolerance in crucian carp and goldfish through neofunctionalization of duplicated genes creating a new ethanol-producing pyruvate decarboxylase pathway. Sci. Rep. 2017, 7, 1–11. [Google Scholar] [CrossRef] [Green Version]
  13. Saint-Paul, U.; Bernardino, G. Behavioural and ecomorphological responses of the neotropical pacu Piaractus mesopotamicus (Teleostei, Serrasalmidae) to oxygen-deficient waters. Exp. Biol. 1988, 48, 19–26. [Google Scholar]
  14. Romagosa, E.; De Paiva, P.; Godinho, H.M. Pattern of oocyte diameter frequency distribution in females of the pacu, Piaractus mesopotamicus (Holmberg 1887)(= Colossoma mitrei Berg 1895), induced to spawn. Aquaculture 1990, 86, 105–110. [Google Scholar] [CrossRef]
  15. Souza, V.L.; Oliveira, E.; Urbinati, E. Effects of food restriction and refeeding on energy stores and growth of pacu, Piaractus mesopotamicus (Characidae). J. Aquac. Trop. 2000, 15, 371–379. [Google Scholar]
  16. Bechara, J.A.; Roux, J.P.; Ruiz Diaz, F.J.; Flores Quintana, C.I.; Longoni de Meabe, C.A. The effect of dietary protein level on pond water quality and feed utilization efficiency of pacuPiaractus mesopotamicus (Holmberg, 1887). Aquac. Res. 2005, 36, 546–553. [Google Scholar] [CrossRef]
  17. Takahashi, L.S.; de Abreu, J.S.; Biller, J.D.; Urbinati, E.C. Efeito do ambiente pós-transporte na recuperação dos indicadores de estresse de pacus juvenis, Piaractus mesopotamicus-doi:10.4025/actascianimsci. v28i4. 610. Acta Sci. Anim. Sci. 2008, 28, 469–475. [Google Scholar]
  18. Rantin, F.T.; Guerra, C.D.R.; Kalinin, A.L.; Glass, M.L. The influence of aquatic surface respiration (ASR) on cardio-respiratory function of the serrasalmid fish Piaractus mesopotamicus. Comp. Biochem. Physiol. Part A Mol. Integr. Physiol. 1998, 119, 991–997. [Google Scholar] [CrossRef]
  19. Jasiński, A. Air-blood barrier in the respiratory intestine of the pond-loach, Misgurnus fossilis L. Cells Tissues Organs 1973, 86, 376–393. [Google Scholar] [CrossRef]
  20. Mendez-Sanchez, J.F.; Burggren, W.W. Hypoxia-induced developmental plasticity of larval growth, gill and labyrinth organ morphometrics in two anabantoid fish: The facultative air-breather Siamese fighting fish (Betta splendens) and the obligate air-breather the blue gourami (Trichopodus trichopterus). J. Morphol. 2019, 280, 193–204. [Google Scholar]
  21. Herbert, N.A.; Skjæraasen, J.E.; Nilsen, T.; Salvanes, A.G.; Steffensen, J.F. The hypoxia avoidance behaviour of juvenile Atlantic cod (Gadus morhua L.) depends on the provision and pressure level of an O2 refuge. Mar. Biol. 2011, 158, 737–746. [Google Scholar] [CrossRef]
  22. Salem, M.; Kenney, P.B.; Rexroad, C.E., 3rd; Yao, J. Microarray gene expression analysis in atrophying rainbow trout muscle: A unique nonmammalian muscle degradation model. Physiol. Genom. 2006, 28, 33–45. [Google Scholar] [CrossRef] [Green Version]
  23. Denslow, N.D.; Garcia-Reyero, N.; Barber, D.S. Fish ‘n’chips: The use of microarrays for aquatic toxicology. Mol. Biosyst. 2007, 3, 172–177. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Sarropoulou, E.; Kotoulas, G.; Power, D.M.; Geisler, R. Gene expression profiling of gilthead sea bream during early development and detection of stress-related genes by the application of cDNA microarray technology. Physiol. Genom. 2005, 23, 182–191. [Google Scholar] [CrossRef]
  25. Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet. J. 2011, 17, 10–12. [Google Scholar] [CrossRef]
  26. Kassambara, A. Practical Guide To Principal Component Methods in R: PCA, M(CA), FAMD, MFA, HCPC, Factoextra; CreateSpace Independent Publishing Platform: Scotts Valley, CA, USA, 2017. [Google Scholar]
  27. Zhang, H.; Audira, G.; Li, Y.; Xian, W.; Varikkodan, M.M.; Hsiao, C.-D. Comparative study the expression of calcium cycling genes in Bombay duck (Harpadon nehereus) and beltfish (Trichiurus lepturus) with different swimming activities. Genom. Data 2017, 12, 58–61. [Google Scholar] [CrossRef]
  28. Zhang, H.; Chang, C.-M.; Shen, K.-N.; Xian, W.; Hsiao, C.-D. Identification of myogenic regulatory genes in the muscle transcriptome of beltfish (Trichiurus lepturus): A major commercial marine fish species with robust swimming ability. Genom. Data 2016, 8, 81–84. [Google Scholar] [CrossRef] [Green Version]
  29. Sidell, B.D.; O’Brien, K.M. When bad things happen to good fish: The loss of hemoglobin and myoglobin expression in Antarctic icefishes. J. Exp. Biol. 2006, 209, 1791–1802. [Google Scholar] [CrossRef] [Green Version]
  30. Grove, T.J.; Hendrickson, J.W.; Sidell, B.D. Two species of Antarctic icefishes (genus Champsocephalus) share a common genetic lesion leading to the loss of myoglobin expression. Polar Biol. 2004, 27, 579–585. [Google Scholar] [CrossRef]
  31. Wagner, G.P.; Kin, K.; Lynch, V.J. Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples. Theory Biosci. 2012, 131, 281–285. [Google Scholar] [CrossRef]
  32. Zhao, Z.-X.; Xu, P.; Cao, D.-C.; Kuang, Y.-Y.; Deng, H.-X.; Zhang, Y.; Xu, L.-M.; Li, J.-T.; Xu, J.; Sun, X.-W. Duplication and differentiation of common carp (Cyprinus carpio) myoglobin genes revealed by BAC analysis. Gene 2014, 548, 210–216. [Google Scholar] [CrossRef]
  33. Koch, J.; Lüdemann, J.; Spies, R.; Last, M.; Amemiya, C.T.; Burmester, T. Unusual diversity of myoglobin genes in the lungfish. Mol. Biol. 2016, 33, 3033–3041. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Bicker, A.; Dietrich, D.; Gleixner, E.; Kristiansen, G.; Gorr, T.A.; Hankeln, T. Extensive transcriptional complexity during hypoxia-regulated expression of the myoglobin gene in cancer. Hum. Mol. Genet. 2014, 23, 479–490. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Animals 10 01130 g001 550
Figure 1. Summary of the experimental workflow from bioinformatic analysis of the expression of oxygen-binding proteins in fish. We performed de novo gene assembly, gene mining by BLAST search, and gene mapping to compare the expressional level of four major oxygen-binding proteins (hemoglobin, myoglobin, cytoglobin, and neuroglobin) in 25 different fish species.
Figure 1. Summary of the experimental workflow from bioinformatic analysis of the expression of oxygen-binding proteins in fish. We performed de novo gene assembly, gene mining by BLAST search, and gene mapping to compare the expressional level of four major oxygen-binding proteins (hemoglobin, myoglobin, cytoglobin, and neuroglobin) in 25 different fish species.
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Animals 10 01130 g002 550
Figure 2. The assembled contig number and relative expression levels of myoglobin and hemoglobin of 25 diverse fish species. (A) The gene contig number (red color) and expression level (blue color) comparison for myoglobin in fish. (B) The gene contig number (red color) and expression level (blue color) comparison for hemoglobin in fish. The gene expression level was normalized and compared by Reads per Kilobase Million (RPKM) values. (C) The phylogenetic tree based on complete mitochondrial DNA sequences from 25 fish species. The multiple sequence alignment and phylogenetic tree construction were performed by Geneious software and bootstrap value, to support the tree topology, and are indicated in the root position of each branch. The red- and blue-shaded color column represents cartilaginous and teleost lineages, respectively. The green dots represent two fish species that were identified with high myoglobin expression in the skeletal muscle.
Figure 2. The assembled contig number and relative expression levels of myoglobin and hemoglobin of 25 diverse fish species. (A) The gene contig number (red color) and expression level (blue color) comparison for myoglobin in fish. (B) The gene contig number (red color) and expression level (blue color) comparison for hemoglobin in fish. The gene expression level was normalized and compared by Reads per Kilobase Million (RPKM) values. (C) The phylogenetic tree based on complete mitochondrial DNA sequences from 25 fish species. The multiple sequence alignment and phylogenetic tree construction were performed by Geneious software and bootstrap value, to support the tree topology, and are indicated in the root position of each branch. The red- and blue-shaded color column represents cartilaginous and teleost lineages, respectively. The green dots represent two fish species that were identified with high myoglobin expression in the skeletal muscle.
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Figure 3. Comparison of the relative oxygen-binding protein gene expression among 25 diverse fish species. (A) Hierarchical clustering analysis of the relative oxygen-binding protein gene expression levels among 25 diverse fish species. (B) Principal component analysis (PCA) of the relative oxygen-binding protein gene expression levels among 25 diverse fish species. Totally, 25 fish species can be categorized into four major groups (shown by different color labeling). Pacu (Piaractus mesopotamicus) and loach (Paramisgurnus dabryanus) fish were identified with high myoglobin expression in skeletal muscle and were grouped in the second group (blue color).
Figure 3. Comparison of the relative oxygen-binding protein gene expression among 25 diverse fish species. (A) Hierarchical clustering analysis of the relative oxygen-binding protein gene expression levels among 25 diverse fish species. (B) Principal component analysis (PCA) of the relative oxygen-binding protein gene expression levels among 25 diverse fish species. Totally, 25 fish species can be categorized into four major groups (shown by different color labeling). Pacu (Piaractus mesopotamicus) and loach (Paramisgurnus dabryanus) fish were identified with high myoglobin expression in skeletal muscle and were grouped in the second group (blue color).
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Table
Table 1. Summary of the fish species and muscle transcriptomic data used in this study.
Table 1. Summary of the fish species and muscle transcriptomic data used in this study.
SRR IDSpecies NameData Size (Gb)Sequencing PlatformSequencing MethodAssembled ContigsN50
SRR1613325Megalobrama amblycephala2.3Illumina HiSeq 20002X101 bp35052557
SRR1652342Paramisgurnus dabryanus3.6Illumina HiSeq 20002X102 bp49125972
SRR1533666Thymallus thymallus3Illumina HiSeq 20002X101 bp102377489
SRR1533644Pangasianodon hypophthalmus3.6Illumina HiSeq 20002X101 bp86400454
SRR1056356Piaractus mesopotamicus8.1Illumina HiSeq 20002X101 bp131747483
SRR514104Callorhinchus milii6.4Illumina Genome Analyzer II2X77 bp44417338
SRR1524253Lepisosteus oculatus3.7Illumina HiSeq 20002X101 bp82408517
SRR1524264Amia calva4.1Illumina HiSeq 20002X101 bp94702554
SRR1524274Oryzias latipes4.6Illumina HiSeq 20002X101 bp100420560
SRR1532750Apteronotus albifrons3.6Illumina HiSeq 20002X101 bp124794551
SRR1532760Anguilla anguilla2.7Illumina HiSeq 20002X101 bp86397429
SRR1532781Salmo trutta5.5Illumina HiSeq 20002X101 bp121092486
SRR1532792Osteoglossum bicirrhosum3.2Illumina HiSeq 20002X101 bp107973469
SRR1532803Alosa alosa4.8Illumina HiSeq 20002X101 bp115049502
SRR1532771Pantodon buchholzi2.6Illumina HiSeq 20002X101 bp93563567
SRR1533633Umbra pygmaea3.2Illumina HiSeq 20002X101 bp107513583
SRR1533655Esox lucius4Illumina HiSeq 20002X101 bp73132550
SRR1533677Coregonus lavaretus3.9Illumina HiSeq 20002X101 bp93899481
SRR1533689Perca fluviatilis5.1Illumina HiSeq 20002X101 bp75135563
SRR1533701Gnathonemus petersii4.3Illumina HiSeq 20002X101 bp136066569
SRR1533711Plecoglossus altivelis3.1Illumina HiSeq 20002X101 bp115114537
SRR3029231Larimichthys polyactis1.9Illumina HiSeq 20002X101 bp60237715
SRR1524241Danio rerio4.3Illumina HiSeq 20002X101 bp118459509
SRR332188 1Trichiurus lepturus5.7Illumina NextSeq 5002X151 bp36214860
SRR338795 1Harpadon nehereus2.3Illumina NextSeq 5002X151 bp21599615
1 Those two RNAseq data were performed in the current study and were partly reported in our previous publications [27,28]. The other 23 RNAseq data were downloaded from the public Sequence Read Archive (SRA) database.

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MDPI and ACS Style

Chen, R.-Y.; Ngoc Hieu, B.T.; Audira, G.; Lou, B.; Lin, M.-D.; Hsiao, C.-D. Meta-Transcriptomic Analysis of RNAseq Data Reveals Pacu and Loach Fish with Unusually High Levels of Myoglobin Expression in Skeletal Muscles. Animals 2020, 10, 1130. https://doi.org/10.3390/ani10071130

AMA Style

Chen R-Y, Ngoc Hieu BT, Audira G, Lou B, Lin M-D, Hsiao C-D. Meta-Transcriptomic Analysis of RNAseq Data Reveals Pacu and Loach Fish with Unusually High Levels of Myoglobin Expression in Skeletal Muscles. Animals. 2020; 10(7):1130. https://doi.org/10.3390/ani10071130

Chicago/Turabian Style

Chen, Rui-Yi, Bui Thi Ngoc Hieu, Gilbert Audira, Bao Lou, Ming-Der Lin, and Chung-Der Hsiao. 2020. "Meta-Transcriptomic Analysis of RNAseq Data Reveals Pacu and Loach Fish with Unusually High Levels of Myoglobin Expression in Skeletal Muscles" Animals 10, no. 7: 1130. https://doi.org/10.3390/ani10071130

APA Style

Chen, R.-Y., Ngoc Hieu, B. T., Audira, G., Lou, B., Lin, M.-D., & Hsiao, C.-D. (2020). Meta-Transcriptomic Analysis of RNAseq Data Reveals Pacu and Loach Fish with Unusually High Levels of Myoglobin Expression in Skeletal Muscles. Animals, 10(7), 1130. https://doi.org/10.3390/ani10071130

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