De Novo Assembly of the Whole Transcriptome of the Wild Embryo, Preleptocephalus, Leptocephalus, and Glass Eel of Anguilla japonica and Deciphering the Digestive and Absorptive Capacities during Early Development
De Novo Assembly of the Whole Transcriptome of the Wild Embryo, Preleptocephalus, Leptocephalus, and Glass Eel of Anguilla japonica and Deciphering the Digestive and Absorptive Capacities during Early Development
Hsiang-Yi Hsu 0 1
Shu-Hwa Chen 0 1
Yuh-Ru Cha 0 1
Katsumi Tsukamoto 0 1
Chung- Yen Lin 0 1
Yu-San Han 0 1
0 1 Institute of Fisheries Science, College of Life Science, National Taiwan University , Taipei, Taiwan , 2 Institute of Information Science , Academia Sinica, Taipei, Taiwan , 3 Department of Marine Science and Resources, College of Bioresource Sciences, Nihon University , Fujisawa , Japan
1 Editor: Jorge M.O. Fernandes, University of Nordland , NORWAY
Natural stocks of Japanese eel (Anguilla japonica) have decreased drastically because of overfishing, habitat destruction, and changes in the ocean environment over the past few decades. However, to date, artificial mass production of glass eels is far from reality because of the lack of appropriate feed for the eel larvae. In this study, wild glass eel, leptocephali, preleptocephali, and embryos were collected to conduct RNA-seq. Approximately 279 million reads were generated and assembled into 224,043 transcripts. The transcript levels of genes coding for digestive enzymes and nutrient transporters were investigated to estimate the capacities for nutrient digestion and absorption during early development. The results showed that the transcript levels of protein digestion enzymes were higher than those of carbohydrate and lipid digestion enzymes in the preleptocephali and leptocephali, and the transcript levels of amino acid transporters were also higher than those of glucose and fructose transporters and the cholesterol transporter. In addition, the transcript levels of glucose and fructose transporters were significantly raising in the leptocephali. Moreover, the transcript levels of protein, carbohydrate, and lipid digestion enzymes were balanced in the glass eel, but the transcript levels of amino acid transporters were higher than those of glucose and cholesterol transporters. These findings implied that preleptocephali and leptocephali prefer high-protein food, and the nutritional requirements of monosaccharides and lipids for the eel larvae vary with growth. An online database (http://molas.iis.sinica.edu.tw/ jpeel/) that will provide the sequences and the annotated results of assembled transcripts was established for the eel research community.
Data Availability Statement: Four raw RNA-seq
datasets, Fertilized Egg (SRA, NCBI: SRR1930110),
Preleptocephalus (SRA, NCBI: SRR1930112),
Leptocephalus (SRA, NCBI: SRR1930115) and Glass
eel (SRA, NCBI: SRR1930117) are accessible
through NCBI's Sequence Read Archive. Other
relevant data can be accessed within the paper and
its Supporting Information files. In addition, the
sequence and the annotated results of assembled
transcripts can be obtained from a public online
Funding: YSH thanks the Ministry of Science and
Technology, Executive Yuan, Taiwan (NSC
99-2313B-002-021-MY3, NSC 102-2628-B-002 -023 -MY3),
and the Council of Agriculture, Executive Yuan,
Taiwan (103AS-11.3.4-FA-F1) for the funding. The
funders had no role in study design, data collection
and analysis, decision to publish, or preparation of
Competing Interests: The authors have declared
that no competing interests exist.
The Japanese eel, Anguilla japonica, is a typical catadromous fish found in the waters of Japan,
Korea, China, Taiwan, and the Northern Philippines [1–3]. In East Asia, the Japanese eel is a
highly-valued aquaculture species. Eel aquaculture is entirely dependent upon the use of wild
glass eels as seedlings because artificial propagation of Japanese eel at the commercial scale is
not yet developed. Unfortunately, overfishing, habitat destruction, and changes in the
ocean environment have led to the drastic depletion of natural eel stock over the past few
decades [4–6]. Therefore, in order to reduce the exploitation of the natural resource,
developing the techniques for commercial scale artificial propagation should be a top priority .
The artificial propagation of the Japanese eel has been studied for a long time. Yamamoto
and Yamauchi  first succeeded in producing fertilized eel eggs and larvae using hormone
treatments. Many researchers subsequently obtained eel larvae utilizing modified methods of
hormone treatments [9–11]. In 1998, Tanaka further indicated that yolk sac and oil droplets of
eel larvae would be completely absorbed at 7–9 days post-hatching (dph) . After
consuming the yolk sac and oil droplets, feeding becomes very important for the eel larvae.
In previous research, sustained growth and survival were not achieved in artificially
produced eel larvae when they were fed with the larvae of mussels, rotifers, or other zooplankton
[10, 13, 14]. After prolonged research, Tanaka et al.  formulated a slurry-type feed made
from shark-egg powder and a soybean peptide, which is appropriate for feeding artificially
produced eel larvae. These eel larvae survived for over 200 days and grew to an average total length
(TL) of 31 mm. A further modification to the feed formula was made by adding krill
hydrolysate and replacing the original soybean peptide with another soybean peptide treated with
phytase . Larvae eating this new diet developed into fully grown leptocephali, and then
metamorphosed into glass eels, approximately 200–250 dph. Recent studies have also suggested
that wild eel larvae may feed on marine snow, fecal pellets of zooplankton, or larvacean houses,
which are consistently present on the ocean surface [17–19].
Although the complete culture of the Japanese eel in captivity was achieved in 2010 [20, 21],
the growth rate of the artificially produced larvae (0.1–0.3 mm/day) was only half that of the wild
larvae (0.5 mm/day) [22, 23]. In addition to growth rate, the survival rate of artificially produced
larvae was also very low . Slow growth and low survival rates may occur because the slurry-type
feed is not well digested and absorbed in the intestine of eel larvae. In the past, several substantial
findings regarding the development of the digestive systems of artificially produced Japanese eel
larvae were reported. First, Otake (1996) indicated that the digestive tract of preleptocephali was
formed within twenty-four hours after hatching . Next, the pancreas developed around the
transitional region between the esophagus and the intestine at 3 dph, and the stomach did not
differentiate until the leptocephali metamorphosed into glass eel . Furthermore, the synthesis of
pancreatic enzymes (trypsin, chymotrypsin, lipase, and amylase) was initiated within 8 dph ,
and all of them were partially characterized . Additionally, Ozaki et al. (2006) suggested that
the absorptive capacity of the alimentary canal was fully developed at 7 dph . However, other
digestive enzymes and nutrient transporters of Japanese eel are not well studied, and no study has
addressed the food digestion and nutrition absorption during the early developmental stages.
Because of the remarkable advances in computational and sequencing technology such as
next-generation sequencing (NGS), the production of genomic-scale data has become simpler
. For example, transcriptomic information can be obtained from RNA-seq using
nextgeneration sequencing and provide fundamental insights into biological processes and
applications such as levels of gene expression in specific tissues or developmental stages , gene
expression profiles after experimental treatments , gene expression in response to
environmental pollution [32, 33], discovery of tissue biomarkers , among others. In this study, wild
embryos, preleptocephali, leptocephali, and glass eel of the Japanese eel were collected for
RNA-seq and transcriptomic assembly. Our goals were to fill in the gaps of the transcriptomic
database with the early developmental stages, investigate the transcript levels of genes coding
for digestive enzymes and nutrient transporters, and use these transcript levels to evaluate the
capacities for nutrient digestion and absorption during larval development. Moreover, because
stable growth has not been attained in artificially produced eel larvae fed with only one kind of
slurry-type feed, it is vital to clarify whether nutritional requirements vary with different stages
in early development for Japanese eel.
Materials and Methods
Embryos, preleptocephali, and leptocephali of the Japanese eel were captured in the Northwest
Pacific Ocean (14–15°N, 139–140°E). As this area is in International waters, collection at this
location was legal. The glass eels were caught in the estuary of the Yilan River in Taiwan. The
Yilan country government and Fisheries Agency of the Council of Agriculture, Executive
Yuan, (Taiwan, ROC) issued a permit to us allowing collection activities in this area. Moreover,
we also applied for an “Approval of Animal Use Protocol” from the Animal Research
Committee of the National Taiwan University, and it was reviewed by the Institutional Animal Care
and Use Committee (IACUC). Our IUCAC approval Number is “NTU-101-EL-100”.
Biopsies of the Japanese eel at four different developmental stages were conducted in this
study: unhatched embryos (ten eggs, mean diameter: 1.6 mm, June, 2012), preleptocephali (five
individuals, body length: 5.44 ± 0.36 mm, June, 2012), and leptocephali (three individuals,
body length: 19.3 ± 5.1 mm, June, 2012) collected in the Northwest Pacific Ocean, and glass
eels caught in the estuary of the Yilan River in Taiwan (one on March 14, 2013 and six in April,
2015). These biopsies were preserved in RNAlater RNA Stabilization Reagent (QIAGEN,
Valencia, CA, USA) and stored at -20°C for subsequent total RNA extraction. Unhatched
embryos, preleptocephali, leptocephali, and one glass eel were used in the NGS study, and six
glass eels were used in the experiments of RT-qPCR.
RNA extraction, library construction, and sequencing
The total RNA of entire mass of the biopsies was extracted using Trizol1 Reagent (Invitrogen,
Carlsbad, CA, USA) according to the manufacturer’s instructions. Purified RNA was
quantified using a ND-1000 spectrophotometer (Nanodrop, Wilmington, DE, USA) and
characterized by a Bioanalyzer 2100 with a RNA 6000 labchip kit (Agilent Technologies, Santa Clara,
CA, USA). After analysis with the Bioanalyzer 2100, the numbers of all RNA samples prepared
in this study were greater than seven. Sequencing libraries of the unhatched embryos,
preleptocephali, leptocephali, and glass eel were constructed using Illumina TruSeq RNA Sample Prep
Kits v2 (Illumina, San Diego, CA, USA) according to the manufacturer’s instructions, and they
were subsequently sequenced using the Illumina HiSeq 2000.
Processing of sequence data and de novo assembly
Four raw RNA-seq datasets, Fertilized Egg (SRA, NCBI: SRR1930110), Preleptocephalus (SRA,
NCBI: SRR1930112), Leptocephalus (SRA, NCBI: SRR1930115) and Glass eel (SRA, NCBI:
SRR1930117) were obtained after sequencing. The raw RNA-seq data were filtered using the
TrimGalore program (Babraham Bioinformatics, Cambridge, UK), to discard adaptors and
low-quality reads (Q < 13). Then, low complexity reads (repeat sequences) were removed
using the prinSeq program . Finally, the general read properties were generated using the
FastQC program (Babraham Bioinformatics, Cambridge, UK).
The Trinity program (SourceForge, http://trinityrnaseq.sf.net) , a commonly used
method for the efficient and robust de novo reconstruction of transcriptome, was utilized to
assemble the transcriptome of the Japanese eel. Following assembly, the counts of transcripts
and the N50 were calculated. In addition, open reading frames of the assembled transcripts
were predicted using TransDecoder (SourceForge, http://transdecoder.sf.net).
Trinotate was used to perform the functional annotations of the transcriptomic data of the
Japanese eel. The homologous genes of the protein-coding transcripts were found by comparing the
transcripts to the SwissProt database. The transcripts were blasted against the Pfam database 
to identify specific protein domains and to acquire gene ontology (GO) annotations. The SignalP
 and tmHMM  were used to predict the signal peptide and transmembrane regions of the
transcripts. These transcripts were also blasted against the nr database to increase the number of
matched homologous genes . Furthermore, these protein-coding transcripts were annotated
using the KEGG (Kyoto Encyclopedia of Genes and Genomes) database on the KAAS (KEGG
Automatic Annotation Server, http://www.genome.jp/tools/kaas/), setting a parameter for only
mapping to the eukaryotic database . The KEGG database contained many important
pathways that participate in the regulation of physiological function and development [42, 43]. The
single-directional best hit (SBH) method was used to obtain the best match from the KEGG database.
Gene expression analysis
The assembled transcripts were utilized as templates, and all short reads from the Paired-End
data were mapped to the assembled transcripts using the Bowtie program . Subsequently,
RSEM (RNA-Seq by Expectation Maximization)  was used to calculate the FPKM
(Fragments per Kilobase of exon per Million fragments mapped) values of the assembled transcripts
[46, 47]. The formula is as follows:
mapped specific exon fragments
FPKM ¼ total mapped exon fragments ðmillionsÞ specific exon length ðKBÞ
In this study, transcript levels of genes coding for digestive enzymes and nutrient transporters
specifically existing in the digestive tract were investigated, and all the gene name abbreviations
followed the zebrafish nomenclature. Initially, the targeted transcripts of digestive enzymes and
nutrient transporters were selected through annotated KEGG pathways. However, each digestive
enzyme or transporter may contain many targeted transcripts, some of which were probably
alternative splicing forms. Digestive enzymes and nutrient transporters should have no expression at
the embryonic stage because the digestive tract was not formed at that time. This was viewed as
the standard to select reasonable transcripts of digestive enzymes and nutrient transporters.
Reverse transcription quantitative PCR (RT-qPCR)
The first strand of cDNA was synthesized from 1 μg of total RNA using HiScript Reverse
Transcriptase (Bionova, Fremont, CA, USA) according to the manufacturer’s instructions. The
primers of six target genes for RT-qPCR were designed based on the assembled sequences, and
listed in Table 1. The acidic ribosomal phosphoprotein P0 (arp) which has constant expression
in the Japanese eel was used as a reference gene . To determine the specificity of each
Table 1. Nucleotide sequence of primers used in real-time quantitative PCR (arp: acidic ribosomal phosphoprotein P0, pep: pepsinogen, lip:
triglyceride lipase, amy: α-amylase, slc7a8: large neutral amino acids transporter small subunit 2, sglt1: sodium/glucose co-transporter member 1
and npc1l1: Niemann-Pick C1-Like 1).
primer pair, PCR analysis was performed on a cDNA pool. Subsequently, the PCR product was
checked for the expected band size (Table 1) via gel electrophoresis, and it was further validated
for sequence correctness by DNA sequencing.
RT-qPCR was performed on a Bio-Rad MyIQ real-time PCR system (Bio-Rad, Hercules,
CA, USA), within a 25-μL mixture containing 12.5 μL of 2X SYBR green supermix (Bionova,
Fremont, CA, USA), 1 μL of each primer, 1 μL of cDNA template (ten times dilution) and
9.5 μL DEPC-treated water. The RT-qPCR conditions were: (1) Pre-incubation, 95°C for 10
min; (2) Amplification (40 cycles), 95°C for 30 s, 58°C for 45 s, and 72°C for 45 s. The PCR
reaction efficiency (Table 1) for each gene assay was determined using a 2-fold serial dilution
of pooled cDNA . Six glass eel samples were used to conduct RT-qPCR experiments, and
all of them were repeated three times. The RT-qPCR data were analyzed in two steps. First, the
arp was used to normalize the data by subtracting its Ct value from the Ct value obtained for
each reaction (4Ct). Second, the pep and slc7a8 were individually viewed as control genes for
the different categories, digestive enzymes and nutrient transporters, to normalize the data by
subtracting their mean 4Ct values from the 4Ct values of all genes (44Ct). The normalized
mRNA expressions were calculated as 2^-(44Ct) and presented as the mean ± SD.
Constructing a transcriptomic database for the Japanese eel
An online transcriptomic database for the Japanese eel containing four transcriptomic datasets
(embryo, preleptocephalus, leptocephalus, and glass eel) was constructed using LAMP system
architecture (Linux, Apache, MySQL, and PHP). The annotations of all assembled transcripts
from nr, GO, Pfam, SignalP, and tmHMM, as well as expressional overview of the KEGG
pathway in the Japanese eel were integrated into the database.
Statistical analyses of all the RT-qPCR data (n = 6) were carried out using SAS Statistical
software version 9.2 (SAS Institute, Cary, North Carolina, USA). All the RT-qPCR data were tested
for the normality and the homogeneity of variance before conducting the statistical analyses.
Comparing the differences among the normalized mRNA expressions of different genes was
performed using a one-way ANOVA with the Tukey’s HSD multiple comparison tests, and the
P value < 0.05 was considered that the difference was significant.
The RNA sequencing generated a total of 291,159,035 raw reads, and 278,935,201 (95.8%)
clean reads were obtained after removing TruSeq adaptors and low quality reads (Table 2).
Thereafter, a total of 224,043 contigs whose length and FPKM values were higher than 200 bps
and 0.1 were produced after de novo assembly. The contig N50 was 1818 bp long, and the
average contig length was 989 bp (Table 3). Furthermore, a frequency diagram of the lengths of
assembled contigs was composed (Fig 1). Approximately 50% of contigs were shorter than 500
bp, and 33% of the contigs were longer than 1000 bp.
Functional annotation for protein-coding transcripts
A total of 116,146 contigs were predicted to be protein-coding transcripts (translated peptides
>50 a.a. long). These transcripts were blasted against the SwissProt database (E value < e-20),
and 21,120 positive matches were found (S1 Table). Pfam, tmHMM, and SignalP were
subsequently used to identify specific protein domains, trans-membrane regions, and signal
peptides. These transcripts were also blasted against the nr database, and 70,096 corresponding
homologous genes were discovered. These homologous genes were submitted for taxonomy
analysis, and the results showed that Actinopterygii accounted for 90.2% of all homologous
genes, followed by Mammalia (4.6%). The top-hit species distribution of Actinopterygii was
further analyzed, and the most representative fish species was Lepisosteus oculatus (33%),
followed by Danio rerio (25%), and Oreochromis niloticus (7%) (Fig 2).
Gene Ontology (GO) analysis
All protein-coding transcripts were classified into three main categories: biological processes,
cellular components, and molecular functions. Each category contains many GO terms representing
detailed protein functions. In the biological processes category, 21,852 (25.2%) transcripts were
related to cellular processes, 16,925 (19.5%) transcripts to metabolic processes, and 15,075
(17.4%) transcripts to single-organism processes (Fig 3A). In the cellular components category,
12,603 (26.3%) transcripts belonged to cell parts, 7,455 (15.5%) transcripts pertained to
membrane parts, and 6,682 (13.9%) transcripts were part of the membrane (Fig 3B). In the molecular
functions category, 32,004 (49.6%) transcripts were associated with binding, 17,955 (27.8%)
transcripts with catalytic activity, and 3,788 (5.9%) transcripts with transporter activity (Fig 3C).
KEGG pathway analysis
In all protein-coding transcripts, there were 43,033 transcripts matching genes in the KEGG
database (37%). Based on the classification by protein family, 21,533 hits were associated with
Number of raw read pairs
Number of cleaned read pairs
Growth stage of Japanese eel
metabolism, 9,424 hits with the processing of genetic information, and 6,956 hits with signaling
and cellular processes. A total of 336 KEGG pathways were identified in this study, and the top
10 well-annotated KEGG pathways are listed in Table 4. Although some of these pathways
were related to cancer, they may not display the same function in eels. Moreover, some of these
pathways assisted in signal transduction regulating the cell’s metabolism, development, and
differentiation. The top 10 well-annotated metabolic pathways are shown in Table 5. Nucleic
acid metabolism, essential amino acid metabolism, and fatty acid metabolism were found to be
important in eel larvae. Inositol phosphates may play crucial roles in cell growth, migration,
apoptosis, endocytosis, and differentiation during early development.
The targeted transcripts of digestive enzymes were selected from the assembled transcripts
annotated by the KEGG database (S2 Table). After screening, the targeted transcripts of each digestive
enzyme selected for expressional analysis were summarized in S3 Table. The transcript levels of
genes coding for digestive enzymes are presented according to the developmental stages in which
they are produced (S1 Fig). These enzymes were classified into three categories (protein,
carbohydrate, and lipid), and the expressional percentage of each category at different stages was
calculated (Fig 4A). The results showed that the transcript levels of protein digestion enzymes were
very high in the stages of preleptocephali and leptocephali, but those of lipid and carbohydrate
digestion enzymes were low. In addition, the transcript levels of protein, carbohydrate, and lipid
digestion enzymes were almost the same in the stage of glass eel.
Next, three representative genes, pep, amy, and lip, were selected for the validation of the
transcriptomic results via RT-qPCR. Because samples of wild embryos, preleptocephali, and
leptocephali were difficult to collect, only the glass eel can be used for the validation. The
RTqPCR data showed that the gene expression of pepsinogen was approximately six times higher
than that of α-amylase, and four times higher than that of triglyceride lipase (Fig 5A), which
were consistent with the transcriptomic data.
Expressional profiles of nutrient transporters existing in intestinal
epithelial cells at different ontogenetic stages
The targeted transcripts of nutrient transporters are listed in S4 Table. After screening, the
transcripts for expressional analysis were summarized in S5 Table, and the transcript levels of
genes coding for nutrient transporters were displayed based on different developmental stages
(S2 Fig). Similarly, these nutrient transporters were also classified into three categories (amino
Fig 1. Frequency diagram of contig length This diagram presents an overview of the contigs. In all, approximately 40% of the contigs were <500 bp and
33% of the contigs were >1000 bp. The bar and the solid line individually represent the number of assembled contigs in a specific length interval and the
cumulative percentage over a certain length.
acid, glucose and fructose, and cholesterol), and the expressional percentage of each category at
different stages was calculated (Fig 4B). The transcript levels of amino acid transporters were
the highest in the stages of preleptocephali, leptocephali, and glass eel, followed by glucose
and fructose transporters and cholesterol transporter. Moreover, expressional percentage of
glucose and fructose transporters was much higher in leptocephali than in preleptocephali and
For the nutrient transporters, slc7a8, sglt1, and npc1l1 were chosen for validating the
transcriptomic results via RT-qPCR. The results of RT-qPCR showed that gene expression of
slc7a8 was approximately four point five times higher than that of sglt1, and five times higher
than that of npc1l1 (Fig 5B). However, the transcriptomic results indicated that gene expression
of slc7a8 was nearly twenty-five times higher than that of sglt1, and more than one hundred
times higher than that of npc1l1 (S2 Fig). Although the expressional differences among the
three genes from the RT-qPCR data were not as great as those from the transcriptomic data,
the similar tendency that gene expression of slc7a8 was higher than those of sglt1 and npc1l1
could be observed.
Fig 2. Relative abundance of the main taxonomic groups among the BLAST hits using a simplified Tree of Life diagram Eukaryotes accounted for
99.8% of all positive hits, and Chordata accounted for 98.9%. Among Chordata, Actinopterygii accounted for 90.2% of all positive hits, followed by Mammalia
(4.6%). The top-hit species distribution of Actinopterygii was analyzed further: the most heavily represented fish species being Lepisosteus oculatus (33%),
followed by Danio rerio (25%), and Oreochromis niloticus (7%).
Online transcriptome database for Japanese eel
An online transcriptomic database for Japanese eel was established in this study, and the URL
of the online database was http://molas.iis.sinica.edu.tw/jpeel/. This database integrated the
annotations from the BLAST/nr, GO, Pfam, SignalP, tmHMM, and KEGG databases. Users
can find the genes that they interested in by entering keywords through “Full-text search on
Annotation tables”. Uploading sequences to the “Sequence Search/BLAST” section can blast
against the transcriptomic database for discovering homologous genes. Furthermore, users
can also search for specific KEGG pathways as well as the annotated results via “KEGG
Recently, next-generation sequencing has been extensively utilized to reconstruct the genomes
[50, 51] and the transcriptomes of aquatic organisms [52–54], which can efficiently improve
the quality of basic studies. The first transcriptome research on the Japanese eel was performed
on the adult eels, in order to investigate the osmoregulation during adaption to changes in
salinity . The gills of silver eels undergoing adaptation to altered salinity were collected for
deep sequencing, and a total of 20,826 contigs were generated. All contigs were submitted for
Fig 3. Functional annotation of assembled contigs associated with GO terms (A) In biological processes, 21,852 (25.2%) protein coding transcripts
participated in cellular processes, 16,925 (19.5%) transcripts were related to metabolic processes, and 15,075 (17.4%) transcripts were associated with
single-organism processes. (B) In the cellular component, 12,603 (26.3%) protein-coding transcripts belonged to cell parts, 7,455 (15.5%) transcripts
pertained to membrane parts, and 6,682 (13.9%) protein coding transcripts were part of the membrane. (C) Of those related to molecular functions, 32,004
(49.6%) protein coding transcripts were related to binding, 17,955 (27.8%) were believed to display catalytic activity, and 3,788 (5.9%) transcripts showed
taxonomy analysis, in which 11,033 (53%) positive hits were obtained. In our research, the
biopsies of early developmental stages of Japanese eel were collected to perform RNA-seq to
decipher the digestive and absorptive capacities during larval development.
Detailed knowledge of digestive physiology during larval development in fish species with
good potential for aquaculture is essential for the production of healthy fingerlings. In the past,
many studies focused on which feed and feed additives were suitable for Japanese eel larvae
[14–16], however, the digestive and absorptive capacities were seldom the focus of research. In
this study, the results showed that the transcript levels of protein digestion enzymes and amino
acid transporters were very high in the stages of preleptocephali and leptocephali. Wild
leptocephali mainly fed on marine snow, which is made up of a variety of types of organic matter,
including dead or dying gelatinous zooplankton, protists, and fecal matter [17, 18]. These
foods are primarily protein detritus, thus, the capacity for protein digestion and amino acid
absorption is most important for preleptocephali and leptocephali. In our research, we also
found that the transcript levels of carbohydrate-digestion enzymes were low in the stages of
preleptocephali and leptocephali, whereas those of glucose and fructose transporters were
much higher, indicating that the digestion of carbohydrates would be poor, but the absorption
of monosaccharides would be good. A previous study suggested that the gut microbiota of fish
may play an important role in nutrient digestion and immunological processes . In
addition, activity of β-glucosidase was detected in the bacteria isolated from marine snow .
Therefore, the monosaccharides required for the synthesis of hyaluronan, which is the main
component of the bodies of preleptocephali and leptocephali , may be produced with the
help of gut microbiota of eel larvae or microbiota in the marine snow.
Dietary lipids were usually composed of cholesterol and triacylglyceride. Cholesterol can
travel through the plasma membrane via transporters, or directly diffuse into the intestinal
enterocytes with the help of bile salt . Triacylglyceride must be broken down into free fatty
acids and monoglycerides by triacylglyceride lipase and bile salt-stimulated lipase , then
the free fatty acids and monoglycerides are able to diffuse into intestinal enterocytes with the
help of bile salt, or be carried by transporters . In the preleptocephali and leptocephali, the
transcript levels of lipid digestion enzymes were higher than those of carbohydrate digestion
enzymes. Thus, it appears that the capacity for lipid digestion was better than that of
carbohydrate digestion in preleptocephali and leptocephali. In addition, the cholesterol transporter was
Fig 4. Expressional percentages of different categories of digestive enzymes and nutrient transporters at different stages (A) In preleptocephali,
transcript levels of protein digestion enzymes accounted for 98.27% of the total, followed by lipid digestion enzymes (1.48%) and carbohydrate digestion
enzymes (0.25%). In leptocephali, the transcript levels of protein digestion enzymes accounted for 90.47% of the total, followed by lipid digestion enzymes
(8.77%) and carbohydrate digestion enzymes (0.76%). In glass eels, transcript levels of lipid digestion enzymes accounted for 36.36%, followed by protein
digestion enzymes (33.33%) and carbohydrate digestion enzymes (30.3%). (B) In preleptocephali, transcript levels of amino acid transporters accounted for
82.6%, followed by glucose and fructose transporters (9.04%) and cholesterol transporters (8.36%). In leptocephali, transcript levels of amino acid
transporters accounted for 52.61%, followed by glucose and fructose transporters (35.34%) and cholesterol transporters (12.05%). In glass eels, transcript
levels of amino acid transporters accounted for 89.32%, followed by glucose and fructose transporters (10.26%) and cholesterol transporters (0.42%).
also expressed in the intestine of preleptocephali and leptocephali, indicating that cholesterol
may be absorbed into the body for utilization.
In the stage of glass eel, our results showed that the transcript levels of protein digestion
enzymes did not significantly differ from the lipid and carbohydrate digestion enzymes.
Moreover, the transcript levels of amino acid transporters were higher than those of glucose and
fructose transporters and the cholesterol transporter. The glass eel, which is formed from the
metamorphosis of leptocephalus , has a well-developed digestive tract and stomach .
Therefore, it would have a more balanced performance of enzymes activity than that of the
leptocephali. Additionally, in the life cycle of Japanese eel, the stage of glass eel is the main stage
during which the Japanese eel begin to enter the rivers that are their main habitat . To enter
the rivers, glass eel would need strong muscles and sufficient energy, leading to higher
absorptive ability of amino acids.
In this study, the glass eels were used to conduct the RT-qPCR experiments for the
validation of transcriptomic data. For the digestive enzymes, the RT-qPCR data were consistent with
the transcriptomic data. However, for the nutrient transporters, gene expressions of slc7a8,
sglt1 and npc1l1 were not in line with the transcriptomic data. The main possible reason
bringing about the discrepancy between the RT-qPCR data and the transcriptomic data may be
Fig 5. Relative mRNA expression levels of digestive enzymes and nutrient transporters in glass eel The mRNA expression levels were presented as
mean ± SD (n = 6). (A) For the digestive enzymes, the mRNA expression level of pepsinogen (pep) was approximately six times higher than that of
αamylase (amy), and four times higher than that of triglyceride lipase (lip). (B) For the nutrient transporters, the mRNA expression level of large neutral amino
acids transporter small subunit 2 (slc7a8) was approximately four point five times higher than that of sodium/glucose co-transporter member 1 (sglt1), and
five times higher than that of Niemann-Pick C1-like 1 (npc1l1). Means with the same letter were not significantly different at the 5% level, as determined by
Tukey’s HSD test.
individual variance among different individuals. Secondly, according to the formula of FPKM
calculation, the length of transcripts and incomplete paired-end data could affect the FPKM
value. Although there was discrepancy between the RT-qPCR data and the transcriptomic
data, the general tendency was similar in both data.
The nutritional requirements of most marine fish larvae are not well known, and they may
differ from those of juveniles and adults owing to the strong morphological and physiological
changes during ontogenesis . The eel larvae, preleptocephali and leptocephali, are an
extraordinary type of fish larvae because of their extreme lateral body compression and
transparency . They also undergo substantial morphological and physiological changes during
early development. Therefore, the nutritional requirements of Japanese eel larvae may vary
with different stages. A previous study showed that the growth rate of the artificially produced
leptocephali, which fed on the Squalus acanthias egg-based diet, was lower than that of wild
leptocephali . The organic compounds present in the S. acanthias egg-based diet are
protein (26.3%), lipids (17.5%), carbohydrates (0.1%), and moisture (54.4%) . Based on our
results, we think that the content of carbohydrates in the S. acanthias egg-based diet does not
satisfy the nutritional requirements of preleptocephali and leptocephali, especially leptocephali.
Okamura et al.  indicated that the growth rate of early-stage larvae was drastically
improved by supplying a diet containing more sugars such as N-acetylglucosamine, glucose,
and maltose. On the other hand, we also think that the content of lipids in the S. acanthias
eggbased diet would exceed the nutritional requirements of preleptocephali and leptocephali.
Furuita et al.  found that decreasing dietary lipids can enhance the nutritional value of shark
eggs and subsequently increase the survival rate of eel larvae.
These results of previous studies are in agreement with the results of our experiments.
Moreover, we further conclude that the nutritional requirements of Japanese eel vary with
different stages during early development according to our results. This information will be
important as reference for developing adequate feeds and feeding protocols during early
development of Japanese eel. For example, at the start of feeding, a high-protein,
low-carbohydrate, and low-fat diet could be prepared for the preleptocephali. In addition, the contents of
carbohydrates and lipids could be gradually increased as the eel larvae grew. However,
determining the actual dietary formulas will require more research.
To our knowledge, this is the first study focusing on the evaluation of the digestive and
absorptive capacities of the Japanese eel during early development. An online transcriptomic database
containing many transcripts and detailed annotations has also been established. Our research
indicated that the capacity for protein digestion and amino acid absorption may be most
important in eel larvae. The capacity for carbohydrate and lipid digestion may be poor in the
preleptocephali stage. The nutritional requirements of monosaccharides and lipids appeared to
increase as larvae grow. Moreover, at the glass eel stage, the absorption of amino acids may
arise from the need to produce strong muscles and sufficient energy to migrate to the rivers. In
the future, more detailed information, such as what kinds of amino acids, fatty acids, vitamins,
and microelements can be greatly utilized by eel larvae, shall need to be further clarified.
S1 Fig. Expressional profiles of digestive enzymes categorized by developmental stage. This
figure shows the transcript levels of digestive enzymes, which existed in digestive tract at
different stages. (A) In the preleptocephalus stage, ctr, cpb, and cela3b were highly transcribed.
However, the rest of the enzymes had low or almost nonexistent transcript levels. (B) The transcript
levels of the digestive enzymes in leptocephali were similar to those in preleptocephali. (C) In
the glass eel stage, pep, chia.3, mgam, and lipf were more highly transcribed than the rest of
enzymes. The gene name abbreviations are as follows; pep: pepsinogen, try: trypsinogen, ctr:
chymotrypsin, cela3b: chymotrypsin-like elastase family member 3B-like, cpa2:
carboxypeptidase A2, cpb: carboxypeptidase B, tmprss7: enteropeptidase (transmembrane protease, serine
7), chia.3: chitinase, acidic.3, amy: α-amylase, mgam: maltase-glucoamylase, intestinal-like, lip:
triglyceride lipase (pancreatic lipase-related protein 1), clps: colipase, bal1: bile salt-activated
lipase 1, and lipf: lysosomal acid lipase/cholesteryl ester hydrolase.
S2 Fig. Expressional profiles of nutrient transporters categorized by developmental stage.
This figure shows the transcript levels of the nutrient transporters existing in the digestive tract
at different stages. (A) In the preleptocephalus stage, pept1, slc31, and slc7a8 had higher
transcript levels than others. (B) With the exception of slc2a5, the rest of transporters had high
transcript levels in the leptocephalus stage. (C) In the glass eel stage, pept1, slc7a8, sglt1, and
slc2a2 had higher transcript levels. The gene name abbreviations are as follows; pept1: peptide
transporter 1, slc31: Neutral and basic amino acid transport protein rBAT (solute carrier family
3 (amino acid transporter), member 1), slc7a8: Large neutral amino acid transporter small
subunit 2 (solute carrier family 7 (L-type amino acid transporter)), member 8), sglt1:
Sodium/glucose co-transporter member 1, slc2a5: solute carrier family 2 (facilitated glucose/fructose
transporter) member 5-like, slc2a2: solute carrier family 2 facilitated glucose transporter
member 2, and npc1l1: Niemann-Pick C1-Like protein 1.
The authors thank the Ministry of Science and Technology, Executive Yuan, Taiwan (NSC
992313-B-002-021-MY3, NSC 102-2628-B-002–023-MY3), and the Council of Agriculture,
Executive Yuan, Taiwan (103AS-11.3.4-FA-F1) for funding this project. We sincerely thank the
anonymous reviewers, whose valuable comments helped us to improve the quality of the
manuscript. Jun Aoyama, Mike Miller, Shun Watanabe, and Mari Kuroki helped with the collection
of eel samples during the Hakuho Maru Cruise in 2012.
Conceived and designed the experiments: YSH CYL. Performed the experiments: HYH SHC
YRC. Analyzed the data: HYH SHC. Contributed reagents/materials/analysis tools: KT YSH
CYL. Wrote the paper: HYH SHC.
endangered European eel. BMC genomics. 2012; 13:507. doi: 10.1186/1471-2164-13-507 PMID:
23009661; PubMed Central PMCID: PMC3532374.
1. Cheng PW , Tzeng WN . Timing of metamorphosis and estuarine arrival across the dispersal range of the Japanese eel Anguilla japonica . Marine Ecology Progress Series . 1996 ; 131 : 87 - 96 .
2. Tesch FW . Developmental stages and distribution of the eel species . 2003 . In: The eel [Internet]. 3. [ 73 - 118 ].
3. Kuroki M , Aoyama J , Miller MJ , Yoshinaga T , Shinoda A , Hagihara S , et al. Sympatric spawning of Anguilla marmorata and Anguilla japonica in the western North Pacific Ocean . Journal of Fish Biology . 2009 ; 74 ( 9 ): 1853 - 65 . doi: 10.1111/j.1095- 8649 . 2009 .02299.x PMID: 20735676.
4. Tatsukawa K. Eel resources in east asia . 2003 . In: Eel Biology [Internet]. Tokyo: Springer-Verlag; [ 293 -8].
5. Tsukamoto K , Aoyama J , Miller MJ . Present status of the Japanese eel: resources and recent research . In: Casselman JM, Cairns D, editors. Eels at the edge: American Fisheries Society, Symposium 58; Bethesda, Maryland2009 . p. 21 - 35 .
6. Chen JZ , Huang SL , Han YS . Impact of long-term habitat loss on the Japanese eel Anguilla japonica . Estuar Coast Shelf S . 2014 ; 151 : 361 - 9 . doi: 10.1016/j.ecss. 2014 .06.004 PMID: WOS:000347768800038.
7. Tsukamoto K. Aquaculture production of glass eels as a possible conservation measure for freshwater eels . 144th Annual Meeting of the American Fisheries Society; August 17-21 , 2014 ; Québec City, Canada2014 .
8. Yamamoto J , Yamauchi K. Sexual maturation of Japanese eel and production of eel larvae in the aquarium . Nature . 1974 ; 251 : 220 - 2 . PMID: 4417634
9. Wang Y , Zhao C , Shin Z , Ten Y , Zhang K , Li Y , et al. Studies on the artificial inducement of reproduction in common eel (in Chinese, with English abstract) . Journal of Fisheries of China 1980 ; 4 : 147 - 58
10. Yu TC , Tsai CL , Tsai YS , Lai JY . Induced breeding of Japanese eels, Anguilla japonica (in Chinese, with English abstract) . Journal of Taiwan Fisheries Research . 1993 ; 1 : 27 - 34 .
11. Ohta H , Kagawa H , Tanaka H , Okuzawa K , Iinuma N , Hirose K. Artificial induction of maturation and fertilization in the Japanese eel, Anguilla japonica . Fish physiology and biochemistry . 1997 ; 17 : 163 - 9 .
12. Tanaka H. Production of eel fry . Farming Japan . 1998 ; 32 : 22 - 7 .
13. Satoh H. Try for perfect culture of the Japanese eel (in Japanese) . Industrial Design Educators Network . 1979 ; 33 : 23 - 30
14. Tanaka H , Kagawa H , Ohta H , Okuzawa K , Hirose K. The first report of eel larvae ingesting rotifers . Fisheries Science . 1995 ; 61 ( 1 ): 171 - 2 .
15. Tanaka H , Kagawa H , Ohta H. Production of leptocephali of Japanese eel (Anguilla japonica) in captivity . Aquaculture . 2001 ; 201 : 51 - 60 .
16. Tanaka H , Kagawa H , Ohta H , Unuma T , Nomura K. The first production of glass eel in captivity: fish reproductive physiology facilitates great progress in aquaculture . Fish physiology and biochemistry . 2003 ; 28 : 493 - 7 .
17. Otake T , Nogami K , Maruyama K. Dissolved and particulate organic matter as possible food sources for eel leptocephali . Marine Ecology Progress Series 1993 ; 92 : 27 - 34 .
18. Mochioka N , Iwamizu M. Diet of anguillid larvae: leptocephali feed selectively on larvacean houses and fecal pellets . Marine Biology . 1996 ; 125 : 447 - 52 .
19. Miller MJ , Otake T , Aoyama J , Wouthuyzen S , Suharti S , Sugeha HY , et al. Observations of gut contents of leptocephali in the North Equatorial Current and Tomini Bay , Indonesia. Coastal marine science. 2012 ; 35 ( 1 ): 277 - 88 .
20. Ijiri S , Tsukamoto K , Chow S , Kurogi H , Adachi S , Tanaka H. Controlled reproduction in the Japanese eel (Anguilla japonica), past and present . Aquaculture Europe . 2011 ; 36 ( 2 ): 13 - 7 .
21. Masuda Y , Imaizumi H , Usuki H , Oda K , Hashimoto H , Teruya K. Artificial completion of the Japanese eel, Anguilla japonica, life cycle: Challenge to mass production . Bulletin of Fisheries Research Agency 2012 ; 35 : 111 - 7 .
22. Ishikawa S , Suzuki K , Inagaki T , Watanabe S , Kimura Y , Okamura A , et al. Spawning time and place of the Japanese eel (Anguilla japonica) in the North Equatorial Current of the western North Pacific Ocean . Fisheries Science. 2001 ; 67 : 1097 - 103 .
23. Okamura A , Horie N , Mikawa N , Yamada Y , Tsukamoto K. Recent advances in artificial production of glass eels for conservation of anguillid eel populations . Ecology of Freshwater Fish . 2014 ; 23 ( 1 ): 95 - 110 . doi: 10.1111/eff.12086
24. Otake T. Fine structure and function of the alimentary canal in leptocephali of the Japanese eel Anguilla japonica . Fisheries Science . 1996 ; 62 ( 1 ): 28 - 34 .
25. Kurokawa T , Pedersen BH . The digestive system of eel larvae . 2003 . In: Eel biology [Internet]. Tokyo Springer-Verlag; [ 435 - 44 ].
26. Kurokawa T , Suzuki T , Ohta H , Kagawa H , Tanaka H , Unuma T. Expression of pancreatic enzyme genes during the early larval stage of Japanese eel, Anguilla japonica . Fisheries Science . 2002 ; 68 : 736 - 44 .
27. Murashita K , Furuita H , Matsunari H , Yamamoto T , Awaji M , Nomura K , et al. Partial characterization and ontogenetic development of pancreatic digestive enzymes in Japanese eel Anguilla japonica larvae . Fish physiology and biochemistry . 2013 ; 39 ( 4 ): 895 - 905 . doi: 10.1007/s10695- 012 - 9749 - 3 PMID: 23179912 .
28. Ozaki Y , Tanaka H , Kagawa H , Ohta H , Adachi S , Yamauchi K. Fine structure and differentiation of the alimentary canal in captive-bred Japanese eel Anguilla japonica preleptocephali . Fisheries Science . 2006 ; 72 : 13 - 9 .
29. Mardis ER . Next-generation DNA sequencing methods . Annual Reviews of Genomics and Human Genetics . 2008 ; 9 : 387 - 402 . doi: 10.1146/annurev. genom.9.081307.164359 PMID: 18576944.
30. Churcher AM , Hubbard PC , Marques JP , Canario AV , Huertas M. Deep sequencing of the olfactory epithelium reveals specific chemosensory receptors are expressed at sexual maturity in the European eel Anguilla anguilla . Molecular ecology . 2015 ; 24 ( 4 ): 822 - 34 . doi: 10.1111/mec.13065 PMID: 25580852.
31. Tse WK , Sun J , Zhang H , Law AY , Yeung BH , Chow SC , et al. Transcriptomic and iTRAQ proteomic approaches reveal novel short-term hyperosmotic stress responsive proteins in the gill of the Japanese eel (Anguilla japonica) . Journal of proteomics . 2013 ; 89 : 81 - 94 . doi: 10.1016/j.jprot. 2013 .05.026 PMID: 23735544.
32. Pujolar JM , Marino IA , Milan M , Coppe A , Maes GE , Capoccioni F , et al. Surviving in a toxic world: transcriptomics and gene expression profiling in response to environmental pollution in the critically
33. Baillon L , Pierron F , Coudret R , Normendeau E , Caron A , Peluhet L , et al. Transcriptome profile analysis reveals specific signatures of pollutants in Atlantic eels . Ecotoxicology . 2015 ; 24 ( 1 ): 71 - 84 . doi: 10. 1007/s10646- 014 - 1356 -x PMID: 25258179.
34. Dirks RP , Burgerhout E , Brittijn SA , de Wijze DL , Ozupek H , Tuinhof-Koelma N , et al. Identification of molecular markers in pectoral fin to predict artificial maturation of female European eels (Anguilla anguilla) . General Comparative Endocrinology . 2014 ; 204 : 267 - 76 . doi: 10.1016/j.ygcen. 2014 .06.023 PMID: 24992558.
35. Schmieder R , Edwards R. Quality control and preprocessing of metagenomic datasets . Bioinformatics . 2011 ; 27 ( 6 ): 863 - 4 . doi: 10.1093/bioinformatics/btr026 PMID: 21278185 ; PubMed Central PMCID : PMC3051327 .
36. Grabherr MG , Haas BJ , Yassour M , Levin JZ , Thompson DA , Amit I , et al. Full-length transcriptome assembly from RNA-Seq data without a reference genome . Nature biotechnology . 2011 ; 29 ( 7 ): 644 - 52 . doi: 10.1038/nbt.1883 PMID: 21572440; PubMed Central PMCID: PMC3571712.
37. Finn RD , Tate J , Mistry J , Coggill PC , Sammut SJ , Hotz HR , et al. The Pfam protein families database . Nucleic acids research . 2008 ; 36(Database issue):D281-8 . doi: 10.1093/nar/gkm960 PMID: 18039703 ; PubMed Central PMCID : PMC2238907 .
38. Petersen TN , Brunak S , von Heijne G , Nielsen H. SignalP 4.0: discriminating signal peptides from transmembrane regions . Nature methods . 2011 ; 8 ( 10 ): 785 - 6 . doi: 10.1038/nmeth.1701 PMID: 21959131.
39. Sonnhammer ELL , von Heijne G , Krogh A , editors. A hidden Markov model for predicting transmembrane helices in protein sequences . ISMB-98 Proceedings; 1998 .
40. Altschul SF , Madden TL , Schäffer AA , Zhang J , Zhang Z , Miller W , et al. Gapped BLAST and PSIBLAST: a new generation of protein database search programs . Nucleic acids research . 1997 ; 25 ( 17 ): 3389 - 402 . PMID: 9254694
41. Moriya Y , Itoh M , Okuda S , Yoshizawa AC , Kanehisa M. KAAS: an automatic genome annotation and pathway reconstruction server . Nucleic acids research . 2007 ; 35(Web Server issue):W182-5 . doi: 10. 1093/nar/gkm321 PMID: 17526522 ; PubMed Central PMCID : PMC1933193 .
42. Kanehisa M , Goto S. KEGG: Kyoto encyclopedia of genes and genomes . Nucleic acids research . 2000 ; 28 ( 1 ): 27 - 30 . PMID: 10592173
43. Kanehisa M , Goto S , Sato Y , Furumichi M , Tanabe M. KEGG for integration and interpretation of largescale molecular data sets . Nucleic acids research . 2012 ; 40 (Database issue): D109 - 14 . doi: 10.1093/ nar/gkr988 PMID: 22080510 ; PubMed Central PMCID : PMC3245020 .
44. Langmead B , Trapnell C , Pop M , Salzberg SL . Ultrafast and memory-efficient alignment of short DNA sequences to the human genome . Genome biology . 2009 ; 10 ( 3 ):R25. doi: 10. 1186/gb-2009-10-3-r25 PMID: 19261174; PubMed Central PMCID: PMC2690996.
45. Li B , Dewey CN . RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome . BMC bioinformatics . 2011 ; 12 :323. doi: 10.1186/ 1471 - 2105 - 12 -323 PMID: 21816040; PubMed Central PMCID: PMC3163565.
46. Mortazavi A , Williams BA , McCue K , Schaeffer L , Wold B. Mapping and quantifying mammalian transcriptomes by RNA-Seq . Nature methods . 2008 ; 5 ( 7 ): 621 - 8 . doi: 10.1038/nmeth.1226 PMID: 18516045.
47. Trapnell C , Williams BA , Pertea G , Mortazavi A , Kwan G , van Baren MJ , et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation . Natuer Biotechnology . 2010 ; 28 ( 5 ): 511 - 5 . doi: 10.1038/nbt.1621 PMID: 20436464; PubMed Central PMCID: PMC3146043.
48. Sudo R , Suetake H , Suzuki Y , Aoyama J , Tsukamoto K. Profiles of mRNA expression for prolactin, growth hormone, and somatolactin in Japanese eels, Anguilla japonica: The effect of salinity, silvering and seasonal change . Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology . 2013 ; 164 ( 1 ): 10 - 6 . doi: 10.1016/j.cbpa. 2012 .09.019 PMID: 23047050.
49. Bustin SA , Benes V , Garson JA , Hellemans J , Huggett J , Kubista M , et al. The MIQE Guidelines: Minimum Information for Publication of Quantitative Real-Time PCR Experiments. Clin Chem . 2009 ; 55 ( 4 ): 611 - 22 .
50. Schartl M , Walter RB , Shen Y , Garcia T , Catchen J , Amores A , et al. The genome of the platyfish, Xiphophorus maculatus, provides insights into evolutionary adaptation and several complex traits . Nature genetics . 2013 ; 45 ( 5 ): 567 - 72 . doi: 10.1038/ng.2604 PMID: 23542700; PubMed Central PMCID: PMC3677569.
51. Chen S , Zhang G , Shao C , Huang Q , Liu G , Zhang P , et al. Whole-genome sequence of a flatfish provides insights into ZW sex chromosome evolution and adaptation to a benthic lifestyle . Nature genetics . 2014 ; 46 ( 3 ): 253 - 60 . doi: 10.1038/ng.2890 PMID: 24487278.
52. Jung H , Lyons RE , Dinh H , Hurwood DA , McWilliam S , Mather PB . Transcriptomics of a Giant Freshwater Prawn (Macrobrachium rosenbergii): De Novo Assembly , Annotation and Marker Discovery . PLoS ONE . 2011 ; 6 ( 12 ) :e27938 . doi: 10.1371/journal. pone.0027938.t001 PMID: 22174756
53. Calduch-Giner JA , Bermejo-Nogales A , Benedito-Palos L , Estensoro I , Ballester-Lozano G , Sitja-Bobadilla A , et al. Deep sequencing for de novo construction of a marine fish (Sparus aurata) transcriptome database with a large coverage of protein-coding transcripts . BMC genomics . 2013 ; 14. doi: Artn 178 doi: 10.1186/ 1471 - 2164 - 14 -178 PMID: WOS:000316683300001.
54. Kleppe L , Edvardsen RB , Furmanek T , Taranger GL , Wargelius A. Global transcriptome analysis identifies regulated transcripts and pathways activated during oogenesis and early embryogenesis in Atlantic cod . Molecular reproduction and development . 2014 ; 81 ( 7 ): 619 - 35 . doi: 10.1002/mrd.22328 PMID: 24687555; PubMed Central PMCID: PMC4265210.
55. Nayak SK . Role of gastrointestinal microbiota in fish . Aquaculture Research . 2010 ; 41 ( 11 ): 1553 - 73 . doi: 10.1111/j.1365- 2109 . 2010 .02546.x
56. Rath J , Herndl GJ . Characteristics and diversity of beta-d- glucosidase (EC 3 .2.1.21) activity in marine snow . Applied and Environmental Microbiology . 1994 ; 60 ( 3 ): 807 - 13 . PMID: 16349214
57. Pfeiler E. Glycosaminoglycan composition of anguilliform and elopiform leptocephali . Journal of Fish Biology . 1991 ; 38 : 533 - 40 .
58. Altmann SW , Davis HRJ , Zhu LJ , Yao X , Hoos LM , Tetzloff G , et al. Niemann-Pick C1 Like 1 protein is critical for intestinal cholesterol absorption . Science . 2004 ; 303 ( 5661 ): 1201 - 4 . doi: 10.1126/science. 1093131 PMID: 14976318.
59. Bernback S , Blackberg L , Hernell O. The complete digestion of human milk triacylglycerol in vitro requires gastric lipase, pancreatic colipase-dependent lipase, and bile salt-stimulated lipase . Journal of Clinical Investigation . 1990 ; 85 ( 4 ): 1221 - 6 . doi: 10.1172/JCI114556 PMID: 2318975 ; PubMed Central PMCID : PMC296555 .
60. Michael D , Sitrin MD . Digestion and Absorption of Dietary Triglycerides . 2014 . In: The Gastrointestinal System [Internet]. Springer Netherlands; [ 159 - 78 ].
61. Holt J . Larval Fish Nutrition. Chichester, UK: Wiley-Blackwell ; 2011 .
62. Miller MJ . Ecology of anguilliform leptocephali: remarkable transparent fish larvae of the ocean surface layer . Aqua-BioScience Monographs (ABSM)2009 . p. 1 - 94 .
63. Furuita H , Murashita K , Matsunari H , Yamamoto T , Nagao J , Nomura K , et al. Decreasing dietary lipids improves larval survival and growth of Japanese eel Anguilla japonica . Fisheries Science . 2014 ; 80 ( 3 ): 581 - 7 . doi: 10.1007/s12562- 014 - 0713 -2