Literature DB >> 29186423

Improving amphibian genomic resources: a multitissue reference transcriptome of an iconic invader.

Mark F Richardson1,2, Fernando Sequeira3, Daniel Selechnik4, Miguel Carneiro3,5, Marcelo Vallinoto6, Jack G Reid2, Andrea J West2, Michael R Crossland4, Richard Shine4, Lee A Rollins2.   

Abstract

Background: Cane toads (Rhinella marina) are an iconic invasive species introduced to 4 continents and well utilized for studies of rapid evolution in introduced environments. Despite the long introduction history of this species, its profound ecological impacts, and its utility for demonstrating evolutionary principles, genetic information is sparse. Here we produce a de novo transcriptome spanning multiple tissues and life stages to enable investigation of the genetic basis of previously identified rapid phenotypic change over the introduced range. Findings: Using approximately 1.9 billion reads from developing tadpoles and 6 adult tissue-specific cDNA libraries, as well as a transcriptome assembly pipeline encompassing 100 separate de novo assemblies, we constructed 62 202 transcripts, of which we functionally annotated ∼50%. Our transcriptome assembly exhibits 90% full-length completeness of the Benchmarking Universal Single-Copy Orthologs data set. Robust assembly metrics and comparisons with several available anuran transcriptomes and genomes indicate that our cane toad assembly is one of the most complete anuran genomic resources available. Conclusions: This comprehensive anuran transcriptome will provide a valuable resource for investigation of genes under selection during invasion in cane toads, but will also greatly expand our general knowledge of anuran genomes, which are underrepresented in the literature. The data set is publically available in NCBI and GigaDB to serve as a resource for other researchers.
© The Authors 2017. Published by Oxford University Press.

Entities:  

Keywords:  Bufo marinus; RNA-Seq; Rhinella marina; amphibian; anuran; cane toad; de novo assembly; invasive species; transcriptome

Mesh:

Year:  2018        PMID: 29186423      PMCID: PMC5765561          DOI: 10.1093/gigascience/gix114

Source DB:  PubMed          Journal:  Gigascience        ISSN: 2047-217X            Impact factor:   6.524


Data Description

Background

It is well established that genome size across taxa is related to repetitive DNA content [1]. Highly repetitive genomes present significant challenges to genome assembly [2], which likely accounts for the scarcity of large genome sequences currently available. Anuran genome size is highly variable (C-values of 0.95–13.02) [3], and to date, genome sequences of only 3 anurans have been published: Xenopus tropicalis [4], X. laevis [5], and Nanorana parkeri [6]. Large genomes typify many Bufonids, including the cane toad (Rhinella marina; average reported C-value = 4.79) [3], and none have been sequenced to date. Transcriptome sequencing provides a tenable alternative to genome sequencing in anurans because the large, repetitive, noncoding regions typical of their large genomes are not sequenced [7]. Cane toads (NCBI Taxonomy ID: 8386) (Fig. 1) are an excellent model for the study of invasion. Because they were intentionally and repeatedly introduced to novel environments as a biocontrol agent, their introduction history is well documented [8]. A wealth of evolutionary and ecological knowledge about cane toads currently exists, documenting phenotypic evidence of rapid evolution in introduced environments, but genomic data are scarce [9]. Providing access to well-developed genomic resources for the cane toad will enable the investigation of the genetic basis of traits underlying invasion ability in this species, which will in turn significantly advance our understanding of invasion genetics for all species. Here we present a de novo transcriptome assembly covering multiple R. marina tissues and life stages, representing one of most complete anuran genomic resources reported to date.
Figure 1:

The cane toad, Rhinella marina. NCBI Taxonomy ID: 8386. Photographer credit: Matt Greenlees. Source: Matt Greenlees.

The cane toad, Rhinella marina. NCBI Taxonomy ID: 8386. Photographer credit: Matt Greenlees. Source: Matt Greenlees.

Samples

Cane toad samples and tissues (7 in total) used in this study were obtained from several sources within the invasive (Australian) and native (Brazilian) range. Several different methods were used to prepare and sequence samples; for simplicity, we describe the samples and data sources used based on the tissue types sequenced (Table 1).
Table 1:

Cane toad samples used to generate the de novo reference transcriptome

TissueOriginPlatformSample ID (library size)Sampling locationSexSRA
BrainAustraliaHiSeq 2500B19 (23.9 M)DurackFSRR5446736
(2 × 125 bp)B20 (27.7 M)DurackFSRR5446735
B31 (24.8 M)GordonvaleFSRR5446734
B32 (22.3 M)GordonvaleFSRR5446733
SpleenAustraliaHiSeq 2500S1 (23.8 M)GordonvaleFSRR5446732
(2 × 125 bp)S2 (25.0 M)GordonvaleFSRR5446732
S18 (24.7 M)DurackFSRR5446732
S19 (23.6 M)DurackFSRR5446732
MuscleAustraliaHiSeq 2000RM0021M (93.8 M)El QuestroFSRR1910534
(2 × 100 bp)SRR1910535
RM0094M (88.2 M)PurnululuFSRR1910543
RM0108M (97.6 M)InnisfailFSRR1910545
RM0169M (80.0 M)RossvilleFSRR1910549
TadpoleAustraliaHiSeq 2500T1 (26.4 M)OombulgurriBothSRR5446728
(2 × 125 bp)T4 (24.5 M)OombulgurriBothSRR5446727
T7 (23.2 M)InnisfailBothSRR5446726
T10 (25.7 M)InnisfailBothSRR5446725
LiverBrazilHiSeq 2000 RMTP (536.8 M)Macapá NASRR1514601
(2 × 75bp)
OvaryBrazilHiSeq 1500AR19 (434.1 M)Macapá FSRR5446724
(2 × 125 bp)
TestesBrazilHiSeq 1500AR05 (410.5 M)Macapá MSRR5446723
(2×125 bp)

Library size is given as raw sequenced reads in millions (M), sex denoted as female (F) and male (M). Both: sample contains mixed individuals of both sexes; NA: information unknown.

Cane toad samples used to generate the de novo reference transcriptome Library size is given as raw sequenced reads in millions (M), sex denoted as female (F) and male (M). Both: sample contains mixed individuals of both sexes; NA: information unknown. Brain and spleen Four adult female toads were collected across 2 sites in Australia, 2 from Durack (15.9419°S, 127.2202°E), Western Australia, and 2 from Gordonvale (17.0972°S, 145.7792°E), Queensland, in May 2015. Toads were euthanized using lethal injection of 150 mg/kg sodium pentobarbital, and the whole brain and spleen were harvested and immediately stored in RNAlater (Qiagen, USA), kept at 4°C, then transferred to –80°C for storage until RNA extraction. Tadpoles We conducted a tadpole rearing experiment in March 2015. Four adult toads (2 males and 2 females) were collected from both Oombulgurri (15.1818°S, 127.8413°E), Western Australia, and Innisfail (17.4963°S, 146.0465°E), Queensland, Australia. To obtain egg clutches, pairs of adult male and female toads per population (i.e., 2 separate male × female crosses) were subcutaneously injected with 0.25 mg/mL Leuproelin acetate (Lucrin Abbott Australasia, Kurnell, Australia) in amphibian Ringer's solution to stimulate spawning; males received 0.25 mL and females 0.75 mL. The pairs of male and female toads were left overnight in 750-L plastic enclosures that contained bore water to lay and fertilize egg clutches. Egg clutches were removed and placed in 17-L tanks containing continuously aerated bore water and monitored to ensure fertilization had occurred. Embryos were selected once they reached Gosner stage 16–17 [10]. Three replicates of 5 fertilized embryos were removed per clutch and placed in 1-L containers, each with 750 mL bore water, where they were raised until 10 days old; water was changed daily, and developing tadpoles were fed 12 mg of a commercial algae supplement (Hikari algae pellets, Kyorin, Himeji, Japan) after each water change. One tadpole from each of the 3 replicate tadpole tanks per clutch was euthanized (immersion in 2g/L Tricaine methanesulfonate) and immediately stored in RNAlater, kept at 4°C, then transferred to –80°C for storage until RNA extraction. Total RNA was extracted from each of the brain, spleen, and tadpole samples using Qiagen RNeasy kits (Qiagen, USA), following the manufacturers protocol with an additional DNase digestion step. Extracted RNA was quantified using a Quibit RNA HS assay on a Qubit 3.0 Fluorometer (Life Technologies, USA). For the tadpole sequencing, total RNA from the 3 “replicate” tadpoles per clutch was pooled in equal quantities, resulting in 4 pooled samples. Two μg of total RNA per sample was sent to Macrogen (Macrogen Inc., Seoul, ROK), where mRNA libraries were constructed using the TruSeq mRNA v2 sample kit (Illumina Inc, San Diego, CA, USA), which included a 300-bp size selection step. Libraries were sequenced on 1 lane of Illumina HiSeq 2500 (Illumina Inc, San Diego, CA, USA), generating 295.6 million paired-end 2×125-bp reads. Raw reads are available in the NCBI Short Read Archive (SRA) under the Bioproject Accession PRJNA382870. Muscle We downloaded raw fastq files (NCBI Bioproject Accession: PRJNA277985; paired-end 2×100 bp; Illumina HiSeq-2000) for 4 adult female toads (RM0021M, RM0094M, RM0108M, and RM0169M) across 4 populations in Australia (El Questro, 16.007872S, 128.020494E; Purnululu National Park, 17.4334°S, 128.3018°E, both Western Australia; Innisfail, 17.4963°S, 146.0465°E; Rossville, 15.7054°S, 145.2229°E, both Queensland) previously used to build a de novo muscle (triceps femoris) transcriptome [9]. Ovary and testes Two adult toads (1 male and 1 female) were collected from Macapá (0.0432°S, 51.1241°W), Amapá, Brazil, in December 2015. Toads were euthanized as described above, and ovary and testes were excised and immediately stored in RNAlater, then kept at 4°C for storage until RNA extraction. Total RNA was extracted using Qiagen RNeasy kits, following the manufacturer’s protocol with an additional DNase digestion step. Extracted RNA was quantified using a Qubit RNA BR assay, and RNA integrity was assessed using a Tapestation 2200 (Aligent Tech., Santa Clara, CA, USA) with an RNA screen. One μg of total RNA per sample was used to construct mRNA libraries using the TruSeq mRNA v2 sample kit, which included a 130–350-bp size selection step. Both libraries were run on a HiSeq 1500 using Illumina V4 PE chemistry across 2 lanes (1 lane for each sample), generating 844.6 million paired-end 2×125-bp reads. Raw reads are available in the NCBI SRA under the Bioproject Accession PRJNA382870. Liver We downloaded raw fastq files (NCBI Bioproject Accession: PRJNA255079; paired-end 2×75 bp; Illumina HiSeq-2000) from a pool of 5 adult toads from Macapá, Amapá, Brazil, previously used to build a de novo liver transcriptome [11].

Data preprocessing and multiple de novo transcriptome assemblies

Raw reads from each sample were first processed with Trimmomatic v0.33 [12], using the following parameters: ILLUMINACLIP: TruSeq3-PE.fa:2:30:10:4 HEADCROP:13 AVGQUAL:30 MINLEN:36, to (i) remove adaptor sequences, (ii) trim the first 13 bp of a read, (iii) discard reads with an average quality 13], with –normalize_max_read_cov = 50, on both of the input data sets. The normalized Australia and Brazil data sets contained ∼42.2 million and ∼82.2 million reads, respectively. Multiple independent de novo transcriptome assemblies were conducted for each of the input data sets, resulting in 100 separate assemblies (Table 2). In brief, we used 3 assemblers: Trinity, with default parameters and –min_contig_length = 300; SOAPdenovo-Trans v1.03 (SOAPdenovo-Trans, RRID:SCR_013268) [14], with 13 different k-mers (apart from the Brazil input set, which had 12) for each combination of EdgeCovCutoff = 2, mergeLevel = 1, EdgeCovCutoff = 3, mergeLevel = 2; the parameters -f, -F, and minContigLen = 200 were the same for all assemblies; velvet v1.2.09/oases v0.2.08 (Velvet, RRID:SCR_010755/Oases, RRID:SCR_011896) [15, 16], with 12 different k-mers for each combination of -cov_cutoff = 3, -min_pair_count = 4, and -cov_cutoff = 5, -min_pair_count = 6, where -ins_length = 300 and -min_trans_lgth = 200, were consistent across assemblies. The individual assemblies were then compiled into an “over-assembly” of ∼42 million transcripts. To reduce redundancy in the “over-assembly,” we used the tr2aacds pipeline from the Evidential Gene package [17], which selects the “optimal” set of transcripts based on their coding potential. This reduced the redundant “over-assembly” to the final assembly of 62 202 transcripts. Of these, 50% (31 040) are commonly expressed among the 7 different tissues used in the assembly, while a total of 6.64% exhibit tissue-specific expression (Fig. S1: Additional file 1) [32]. We then used TransDecoder v3.0.0 to predict protein coding sequences (CDS) with a minimum CDS of 100 bp. Transvestigator [18] was used to prepare the final assembly for submission to NCBI’s Transcriptome Shotgun Assembly (TSA) database—accessible through the PRJNA383966 accession. Results from the assembly pipeline are described in Table 3. As the “dropset”—those transcripts not kept in the “optimal” tr2aacds output—may contain other biologically relevant transcripts, such as noncoding RNAs and active transposable elements, we also provide these transcripts in the associated GigaDB repository [32].
Table 2:

De novo assembler parameters used to produce the “over-assembly”

Assembler k-mersParameter combinationsNo. of assemblies
Trinity25DefaultAus 1, Brazil 1
SOAPdenovo-Trans21, 25, 29, 33, 37, 41, 45, 49, 59, 69, 79, 89, 99 (No. 99 for the Brazil input set) EdgeCovCutoff = 2 and mergeLevel = 1; EdgeCovCutoff = 3 and mergeLevel = 2Aus 13, Brazil 12; Aus 13, Brazil 12
Velvet/Oases21, 25, 29, 33, 37, 41, 45, 49, 59, 69, 79, 89 cov_cutoff = 3 and min_pair_count = 4; cov_cutoff = 5 and min_pair_count = 6Aus 12, Brazil 12; Aus 12, Brazil 12
Total: 100
Table 3:

Summary of transcriptome assembly and annotation statistics compared with previous cane toad transcriptomes

This studyMuscle[a]Liver[b]
Assembly
 Filtered read pairs945 348 78099 462 214265 684 605
In silico normalized reads129 051 00818 713 526-
 Assembly size, bp83 724 19360 388 68580 251 892
 Number of transcripts62 20257 580131 020
 N5023771871916
 Average length, bp13461049613
 Minimum length, bp297201201
 Maximum length, bp99 43840 54617 369
 Median length, bp698577331
 GC, %46.0545.0644.32
 Transcripts with CDS62 20219 751
Annotation
 Transcripts with BLASTx hit31 10321 533
 Transcripts with BLASTp hit28 56016 754
 Transcripts with GO terms28 39919 500

aRollins, Richardson, and Shine [9].

bArthofer et al. [11].

De novo assembler parameters used to produce the “over-assembly” Summary of transcriptome assembly and annotation statistics compared with previous cane toad transcriptomes aRollins, Richardson, and Shine [9]. bArthofer et al. [11].

Annotation

We conducted functional annotation based on our predicted protein sequences utilizing the automated Trinotate pipeline. Transcripts were first annotated based on sequence homology, where assembled nucleotides and translated CDS sequences were used in BLASTx (BLASTX, RRID:SCR_001653) and BLASTp (BLASTP, RRID:SCR_001010) searches, against the UniProt/Swiss-Prot database (downloaded Feb. 2017) using a standalone version of BLAST v2.2.26+ [19], with an e-value cutoff of 1×10−5. Pfam (Pfam, RRID:SCR_004726) [20] functional domains (downloaded Feb. 2017) were identified in protein coding sequences using hmmscan [21]; signal peptides and transmembrane domains were assigned using hidden Markov model prediction implemented in SignalP v4.1 [22] and TMHMM v2.0c [23], respectively. Finally, transcripts were compared with curated annotations in the eggNOG (eggNOG, RRID:SCR_002456) [24] and Gene Ontology (GO, RRID:SCR_002811) [25] databases. A summary of annotation metrics is provided in Table 3. The combined Trinotate functional annotations to the TSA assembly are available in the associated GigaDB [26].

Quality and completeness of the cane toad transcriptome

To evaluate our new multitissue transcriptome assembly, we used 3 comparative approaches to assess relative quality and completeness. First, we compared core assembly statistics of the new assembly to our 2 previous cane toad single-tissue transcriptomes derived from muscle and liver tissue (Table 3). The inclusion of data from multiple tissues (encompassing 9.5- and 3.5-fold increases in read input compared with the muscle and liver transcriptomes, respectively) resulted in increases of all assembly metrics, apart from the number of assembled transcripts, which fell compared with the liver transcriptome (Table 3). Notably, mean transcript length increased from 613 (liver) to 1346 bp, and transcript n50 increased from 916 (liver) to 2377 bp. The total assembled bases were similar between the multitissue transcriptome and that assembled from liver, yet higher (∼20 million bp) than that produced from muscle tissue. Additionally, our assembly exhibits comparable lengths of mRNAs and CDS to those from X. tropicalis (gene build v9.0, downloaded Xenbase.org, Aug. 2017) (Fig. S2: Additional file 1), albeit with a greater frequency of shorter features. This is not unexpected given that we are comparing a de novo transcriptome assembly to gene models from a genome assembly. Also, our assembly shows good coverage of the lengths of CDS features compared with X. tropicalis (Fig. S3: Additional file 1), given both species are substantially divergent. Importantly, the new R. marina multitissue assembly increases the coverage of transcripts containing protein coding sequences with associated BLAST matches and Gene Ontology annotations compared with the previously available R. marina assemblies. Second, we evaluated the new assembly using the Benchmarking Universal Single-Copy Orthologs (BUSCO) vertebrate gene set (BUSCO, RRID:SCR_015008) [27], which uses 3023 near-universal orthologs (hereafter BUSCOs) to evaluate the relative completeness of assemblies and compares the results with the previous R. marina assemblies and those of several available amphibian transcriptomes and genomes (Table 4). We used BUSCO v1.2 [27] with the default e-value cutoff of 0.01 and –mode = Trans for all the transcriptomes compared and –mode = OGS for the genome comparisons (using the N. parkeri v2.0, X. tropicalis v9.0 and X. laevis v9.1_1.8.3.2 gene builds downloaded from Xenbase.org, Aug. 2017). Our multitissue assembly had a much higher percentage of complete BUSCOs (90%), apart from the 2 Xenopus genomes, which exhibited comparable results (X. tropicalis, 91% and X. laevis, 97%). Additionally, our multitissue transcriptome has low BUSCO missingness, intermediate duplication of complete BUSCOs, and the second lowest level of fragmented BUSCOs. In contrast to the previous R. marina transcriptomes specifically, the new assembly has less fragmented and 20%–30% more complete BUSCO genes—suggesting the presence of more full-length transcripts. Overall, the comparison of BUSCO results revealed our assembly to be one of the most complete references available for anurans.
Table 4:

BUSCO analysis of transcriptome completeness

CompleteComplete and duplicatedFragmentedMissing
BUSCOs, %BUSCOs, %BUSCOs, %BUSCOs, %
R. marina transcriptomes
 This study904.71.77.8
 Muscle[a]604.65.733
 Liver[b]690.64.126
Select anuran transcriptomes
Bufotes viridis[c]260.31557
Rana catesbeiana[d]79422.817
Pelohylax nigromaculatus[e]500.47.841
Microhyla fissipes[f]731.24.721
Select anuran genomes
Xenopus laevis[g]97511.41.4
Xenopus tropicalis[h]914.13.74.9
Nanorana parkeri[i]762.89.014

“Complete BUSCOs” refers to those with a full-length match in the assembly. “Complete and duplicated” refers to those BUSCOs that are complete within an assembly but have multiple matches present. “Fragmented” are those BUSCOs that only have a partial match in the assembly, and “Missing” refers to those BUSCOs that do not have a corresponding match in the assembly.

aRollins, Richardson, and Shine [9].

bArthofer et al. [11].

cGerhchen et al. [7].

dBirol et al. [28].

eHuang et al. [29].

fZhao et al. [30].

gSession et al. [5].

hHellsten et al. [4].

iSun et al. [6].

BUSCO analysis of transcriptome completeness “Complete BUSCOs” refers to those with a full-length match in the assembly. “Complete and duplicated” refers to those BUSCOs that are complete within an assembly but have multiple matches present. “Fragmented” are those BUSCOs that only have a partial match in the assembly, and “Missing” refers to those BUSCOs that do not have a corresponding match in the assembly. aRollins, Richardson, and Shine [9]. bArthofer et al. [11]. cGerhchen et al. [7]. dBirol et al. [28]. eHuang et al. [29]. fZhao et al. [30]. gSession et al. [5]. hHellsten et al. [4]. iSun et al. [6]. Third, we compared the multitissue transcriptome with the previous cane toad transcriptomes and the 3 currently available Anuran genomes through both standard and reciprocal best-hit BLAST approaches. The standard approach revealed that 40 741 (65.5%) and 31 189 (50.1%) of our new assembly had significant matches (e-value < 10−3) to the liver and muscle transcriptomes, respectively. The reciprocal best-hit approach reduced the number of significant matches to both the liver (23 943; 38.5%) and muscle (15 892; 25.5%) transcriptomes, which may in part be due to transcripts mapping to multiple isoforms in the different assemblies. This, together with the high number of protein-coding transcripts in the multitissue assembly, indicates that the new assembly still contains some redundancy and that we have assembled multiple transcript variants for some genes. Standard BLAST comparisons of our assembly with the X. tropicalis, X. laevis, and N. parkeri proteins exhibited 40 275 (64.7%), 40 218 (64.7%), and 40 244 (64.7%) significant matches, respectively; 37 064 of our assembled transcripts with significant matches are common to all 3 species (Fig. S4: Additional file 1). Of our 31 103 assembled transcripts with annotations, 97.8% (30 423) have significant matches to X. tropicalis, while 97.9% (30 465) have matches to X. laevis and 98.3% (30 574) to N. parkeri; 96.3% (29 967) are common to all 3 species (Fig. S5: Additional file 1). The high percentage of annotated transcripts with matches to X. tropicalis, X. laevis, and N. parkeri provides further evidence that our assembly pipeline produced transcripts with strong anuran homology.

Identification of anuran orthologues

Current efforts to identify amphibian-specific genes have been hampered by a lack of high-quality full-length genes for numerous amphibian species [31]. So far, the identification of amphibian-specific genes has not been possible as orthologous counterparts have only been identified between the 2 Xenopus genomes. We used OrthoFinder v1.1.10 [32] with default parameters to identify orthologues between our newly assembled R. marina CDS-containing transcripts and the proteomes from N. parkeri, X. tropicalis, and X. laevis (using the same gene build versions as in the BUSCO analysis). OrthoFinder identifies “orthogroups” (a group of genes descended from a single gene in the last common ancestor of a group of species) [32] and then orthologues between each pair of species in the comparison. Because OrthoFinder classifies genes with multiple orthologues (i.e., many to many relationships) in “orthogroups,” it may reduce the impact that multiple isoforms of the same gene have in such analyses. We assigned 60.2% (94 516) of all the genes examined to 18 776 “orthogroups” (see Additional file 2), of which 50% of all genes were found in “orthogroups” with 4 or more genes. Additionally, we identified 12 674 “orthogroups” that contained genes from all 4 species, and 4586 of these consisted entirely of single-copy genes. The data set presented here may be useful for further research into identifying amphibian-specific genes, so we have included this analysis in its entirety in the associated GigaDB repository [25].

Conclusions

This comprehensive anuran transcriptome will not only serve as a valuable reference for investigation of genes under selection during invasion in cane toads, but will also expand our general knowledge of anuran genomes. Additionally, we have identified numerous orthologous transcripts to X. tropicalis, X. laevis, and N. parkeri proteins, which may aid the identification of amphibian-specific genes—an important objective of AmphiBase [31].

Availability of supporting data

The data sets supporting the results presented here are available in the associated GigaDB repository [25]. All raw sequencing data used in this study are available in the SRA and associated with the following BioProject accessions: PRJNA277985, PRJNA255079, PRJNA382870, and PRJNA383966. The final transcriptome assembly has been deposited at DDBJ/EMBL/GenBank under the accession GFMT00000000. The version described in this paper is the first version, GFMT01000000.

Additional file

Additional file 1: Figure S1: Schematic diagram showing the percentage (%) of expressed transcripts among the 7 different tissues used in the assembly. For brevity, we only show those common to all tissues (centre of elements) and those uniquely expressed in each separate tissue. Transcript expression was quantified using Salmon v0.8.0 [1] using –l IU and default parameters. Additionally, detailed comparative analysis of expression among all tissue combinations is provided in the associated GigaDB repository [2]. Additional file 1: Figure S2: Histogram of the lengths of R. marina assembled mRNAs and CDS compared with those from X. tropicalis (gene build v9.0, Xenbase.org, Aug. 2017). Additional file 1: Figure S3: Scatterplot showing the coverage of each R. marina CDS length in base pairs compared with the corresponding CDS match in X. tropicalis (gene build v9.0, Xenbase.org, Aug. 2017). CDS length matches were extracted from BLASTx queries with evalue = 10E-3 and –max_target_seqs=1. Additional file 1: Figure S4: Venn diagram showing an overview of the significant BLASTx matches (e-value < 10–3) for our R. marina assembly against the proteins from X. tropicalis, X. laevis, and N. parkeri. Venn diagram build using the Venn diagram webserver: http://bioinformatics.psb.ugent.be/webtools/Venn/. Additional file 1: Figure S5. Venn diagram showing an overview of the significant BLASTx matches (e-value < 10–3) for our R. marina transcripts with annotations (31 103) against proteins from X. tropicalis, X. laevis, and N. parkeri. Venn diagram built using the Venn diagram webserver: http://bioinformatics.psb.ugent.be/webtools/Venn/ Additional file 2: Table S1: Summary of OrthoFinder analysis. Gene build versions are given in the species heading where appropriate.

Competing interests

We declare no competing interests.

Abbreviations

BUSCO: Benchmarking universal single copy orthologs; bp = base pair; CDS: coding sequence; GO: Gene Ontology; SRA: Short Read Archive; TSA: Transcriptome Shotgun Assembly.

Ethics statement

Ethics approval for the capture of wild Australian samples was provided under the University of Sydney permit 2014/562, the rearing of tadpoles by the University of Sydney permit 2013/6033, and Brazilian samples under the Brazilian Federal Chico Mendes Institute for Biodiversity Conservation (ICMBio), through license number 38 047–3.

Author contributions

M.F.R., M.V., and L.A.R. collected animals and conducted the sample preparation. J.G.R. and M.R.C. conducted tadpole rearing. M.F.R., F.S., D.M.S., M.C., and L.A.R. conducted RNA isolation for sequencing and library construction. AJW contributed samples. M.F.R. conducted transcriptome assemblies and analysis. M.F.R., F.S., R.S., and L.A.R. wrote the manuscript and participated in study design. All authors commented on the manuscript and approved the final submission. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. 04 Jun 2017 Reviewed Click here for additional data file. 04 Oct 2017 Reviewed Click here for additional data file. 08 Jun 2017 Reviewed Click here for additional data file. 10 Oct 2017 Reviewed Click here for additional data file. 14 Jun 2017 Reviewed Click here for additional data file. Click here for additional data file.
  26 in total

1.  SignalP 4.0: discriminating signal peptides from transmembrane regions.

Authors:  Thomas Nordahl Petersen; Søren Brunak; Gunnar von Heijne; Henrik Nielsen
Journal:  Nat Methods       Date:  2011-09-29       Impact factor: 28.547

2.  Velvet: algorithms for de novo short read assembly using de Bruijn graphs.

Authors:  Daniel R Zerbino; Ewan Birney
Journal:  Genome Res       Date:  2008-03-18       Impact factor: 9.043

3.  Genomic resources notes accepted 1 August 2014-30 September 2014.

Authors:  Wolfgang Arthofer; B L Banbury; Miguel Carneiro; Francesco Cicconardi; Thomas F Duda; R B Harris; David S Kang; A D Leaché; Viola Nolte; Coralie Nourisson; Nicola Palmieri; Birgit C Schlick-Steiner; Christian Schlötterer; Fernando Sequeira; Cheolho Sim; Florian M Steiner; Marcelo Vallinoto; David A Weese
Journal:  Mol Ecol Resour       Date:  2014-11-25       Impact factor: 7.090

Review 4.  Repetitive DNA and next-generation sequencing: computational challenges and solutions.

Authors:  Todd J Treangen; Steven L Salzberg
Journal:  Nat Rev Genet       Date:  2011-11-29       Impact factor: 53.242

5.  De novo Transcriptome Assemblies of Rana (Lithobates) catesbeiana and Xenopus laevis Tadpole Livers for Comparative Genomics without Reference Genomes.

Authors:  Inanc Birol; Bahar Behsaz; S Austin Hammond; Erdi Kucuk; Nik Veldhoen; Caren C Helbing
Journal:  PLoS One       Date:  2015-06-29       Impact factor: 3.240

6.  A Single Transcriptome of a Green Toad (Bufo viridis) Yields Candidate Genes for Sex Determination and -Differentiation and Non-Anonymous Population Genetic Markers.

Authors:  Jörn F Gerchen; Samuel J Reichert; Johannes T Röhr; Christoph Dieterich; Werner Kloas; Matthias Stöck
Journal:  PLoS One       Date:  2016-05-27       Impact factor: 3.240

7.  Full-length transcriptome assembly from RNA-Seq data without a reference genome.

Authors:  Manfred G Grabherr; Brian J Haas; Moran Yassour; Joshua Z Levin; Dawn A Thompson; Ido Amit; Xian Adiconis; Lin Fan; Raktima Raychowdhury; Qiandong Zeng; Zehua Chen; Evan Mauceli; Nir Hacohen; Andreas Gnirke; Nicholas Rhind; Federica di Palma; Bruce W Birren; Chad Nusbaum; Kerstin Lindblad-Toh; Nir Friedman; Aviv Regev
Journal:  Nat Biotechnol       Date:  2011-05-15       Impact factor: 54.908

8.  Pfam: the protein families database.

Authors:  Robert D Finn; Alex Bateman; Jody Clements; Penelope Coggill; Ruth Y Eberhardt; Sean R Eddy; Andreas Heger; Kirstie Hetherington; Liisa Holm; Jaina Mistry; Erik L L Sonnhammer; John Tate; Marco Punta
Journal:  Nucleic Acids Res       Date:  2013-11-27       Impact factor: 16.971

9.  Trimmomatic: a flexible trimmer for Illumina sequence data.

Authors:  Anthony M Bolger; Marc Lohse; Bjoern Usadel
Journal:  Bioinformatics       Date:  2014-04-01       Impact factor: 6.937

10.  Transcriptome profiles of metamorphosis in the ornamented pygmy frog Microhyla fissipes clarify the functions of thyroid hormone receptors in metamorphosis.

Authors:  Lanying Zhao; Lusha Liu; Shouhong Wang; Hongyuan Wang; Jianping Jiang
Journal:  Sci Rep       Date:  2016-06-02       Impact factor: 4.379

View more
  8 in total

1.  RNA Sequencing of Peripheral Blood Revealed that the Neurotropic TRK Receptor Signaling Pathway Shows Apparent Correlation in Recovery Following Spinal Cord Injury at Small Cohort.

Authors:  Chunqing Wang; Hangzhou Lv; Qing Li; Ke Gong; Lei Luo Yang; Zean Wei; Yujie Pan; Mingyong Wang
Journal:  J Mol Neurosci       Date:  2019-04-16       Impact factor: 3.444

2.  Benchmarking differential expression analysis tools for RNA-Seq: normalization-based vs. log-ratio transformation-based methods.

Authors:  Thomas P Quinn; Tamsyn M Crowley; Mark F Richardson
Journal:  BMC Bioinformatics       Date:  2018-07-18       Impact factor: 3.169

3.  Genomic Takeover by Transposable Elements in the Strawberry Poison Frog.

Authors:  Rebekah L Rogers; Long Zhou; Chong Chu; Roberto Márquez; Ammon Corl; Tyler Linderoth; Layla Freeborn; Matthew D MacManes; Zijun Xiong; Jiao Zheng; Chunxue Guo; Xu Xun; Marcus R Kronforst; Kyle Summers; Yufeng Wu; Huanming Yang; Corinne L Richards-Zawacki; Guojie Zhang; Rasmus Nielsen
Journal:  Mol Biol Evol       Date:  2018-12-01       Impact factor: 16.240

4.  De Novo Assembly and Annotation of the Larval Transcriptome of Two Spadefoot Toads Widely Divergent in Developmental Rate.

Authors:  H Christoph Liedtke; Jèssica Gómez Garrido; Anna Esteve-Codina; Marta Gut; Tyler Alioto; Ivan Gomez-Mestre
Journal:  G3 (Bethesda)       Date:  2019-08-08       Impact factor: 3.154

5.  Increased Adaptive Variation Despite Reduced Overall Genetic Diversity in a Rapidly Adapting Invader.

Authors:  Daniel Selechnik; Mark F Richardson; Richard Shine; Jayna L DeVore; Simon Ducatez; Lee A Rollins
Journal:  Front Genet       Date:  2019-11-26       Impact factor: 4.599

6.  Brain transcriptome analysis reveals gene expression differences associated with dispersal behaviour between range-front and range-core populations of invasive cane toads in Australia.

Authors:  Boris Yagound; Andrea J West; Mark F Richardson; Daniel Selechnik; Richard Shine; Lee A Rollins
Journal:  Mol Ecol       Date:  2022-01-28       Impact factor: 6.622

7.  Draft genome assembly of the invasive cane toad, Rhinella marina.

Authors:  Richard J Edwards; Daniel Enosi Tuipulotu; Timothy G Amos; Denis O'Meally; Mark F Richardson; Tonia L Russell; Marcelo Vallinoto; Miguel Carneiro; Nuno Ferrand; Marc R Wilkins; Fernando Sequeira; Lee A Rollins; Edward C Holmes; Richard Shine; Peter A White
Journal:  Gigascience       Date:  2018-09-01       Impact factor: 6.524

Review 8.  The physiology of movement.

Authors:  Steven Goossens; Nicky Wybouw; Thomas Van Leeuwen; Dries Bonte
Journal:  Mov Ecol       Date:  2020-02-04       Impact factor: 3.600

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.