Background & Summary

The big-headed turtle, Platysternon megacephalum (NCBI Taxonomy ID: 55544), as the sole member of the family Platysternidae, is native to Southeast Asian countries, including China, Cambodia, Laos, Myanmar Thailand and Vietnam1. The species inhabits flowing cool rocky mountain streams with water temperatures usually between 12–28 °C2. It is an aquatic predator with strong climbing abilities, preying on lizard, frogs, fish, shrimps, crabs, snails, earthworms, insects, and even small birds and mammals, along with consuming some fruit and plant matter3. The big-headed turtle has some defining features, such as an extra-large head, long tail, and flat carapace. Its head width is approximately equal to half of its carapace width and therefore cannot be retracted into the shell. This species has the longest tail relative to body size of any turtle, with tail length being more than half of the carapace length4. In addition, it has a very flat carapace and an eagle-like hooked upper jaw (Fig. 1). The species prefers its body temperature to be around 25.3 °C5. While big-headed turtles are unique in many morphological and physiological characteristics compared to other turtle species, they are not unique in the anthropogenic threats they face.

Fig. 1
figure 1

A representative big-headed turtle, Platysternon megacephalum in China.

The Asian turtle crisis has resulted in population declines in many species, including the big-headed turtle. Over harvesting for the pet trade, traditional medicine, and food represent the main drivers of the population decline and have resulted in an over 89% reduction in population density in South China6. The species was listed in the CITES (Convention on International Trade in Endangered Species of Wild Fauna and Flora) Appendix I in 2013 and as an endangered species in the IUCN (International Union for Conservation of Nature) Red List of Threatened Species in 20001. Conservation and restoration measures are needed to protect this endangered species, and a genomic resource will be an essential tool for conservation efforts. However, there is currently little knowledge about the big-headed turtle’s genetic information, with previous research mainly focusing on mitochondrial DNA and the development of microsatellite markers7,8,9,10,11.

In this study, we report the first sequencing, assembly, and annotation of the big-headed turtle genome. The final draft genome assembly was approximately 2.32 Gb with a contig N50 of 41.8 kb and scaffold N50 of 7.22 Mb. A total of 25,995 protein-coding genes and 19,177 non-coding RNAs (409 rRNAs, 2,089 tRNAs, 16,050 miRNAs, and 629 snRNAs) were predicted from the genome assembly. The genomic resource of the big-headed turtle will be a key tool in the study of conservation genetics for this species.


Sample collection and sequencing

The genomic DNA of the big-headed turtle was extracted from the leg muscles of a single adult male obtained from Heyuan, Guangdong Province, China. The sampled turtle was one of a number that the law enforcement agencies confiscated from the black market and then transferred to scientific research institutions for study and captive breeding. Our institute has government permission to use confiscated big-headed turtles for scientific research (e.g. conservation genetics, ecology). The sampled turtle was euthanized and the animal collection and utility protocols were reviewed and approved by the Animal Ethics Committee at the Guangdong Institute of Applied Biological Resources (No: GIABR20170103). Ten paired-end libraries including four short-insert libraries (250 bp × 2, and 500 bp × 2) and six long-insert libraries (2 kb × 2, 5 kb × 2, and 10 kb × 2) were constructed and sequenced on an Illumina HiSeq X platform according to the manufacturer’s instructions (Illumina, San Diego, California, USA). The sequenced read length was 150 bp for each library. A total of 497.1 Gb (208.9×) of raw sequences were eventually obtained (Table 1). Prior to assembly, quality control was performed for raw reads using a SOAPfilter to filter out the adaptor sequences, the reads containing more than 10% unidentified nucleotides, and low-quality reads containing more than 50% bases with Illumina phred quality score ≤8. We obtained approximately 469.2 Gb of clean reads for further assembly.

Table 1 Statistics of big-headed turtle genome sequencing data.

Assembly and evaluation

A total of 170 Gb high-quality reads from the short-insert reads (350 bp) were used to estimate the genomic information of the big-headed turtle, and 17-mer frequency information was generated based on the K-mer analysis as implemented in the software GEC12. The heterozygous ratio was also evaluated based on the frequency of the heterozygous k-mers and homozygous k-mers using GCE software12,13. According to 17-mer analysis the estimated genome size of big-headed turtle was 2,383.87 Mb (~2.38 Gb), and the estimated heterozygous and repeat sequencing ratios were calculated to be 0.33 and 53%, respectively (Fig. 2 and Table 2).

Fig. 2
figure 2

Distribution of 17-mer frequency. In total 170.2 Gb of high-quality short-insert reads (350 bp) were used to generate the 17-mer depth distribution curve frequency information.

Table 2 Estimation of the genome size using K-mer analysis.

De novo assembly was performed from the generated clean reads using SOAPdenovo14, a de Bruijn graph algorithm-based de novo genome assembler. We assembled the big-headed turtle genome in three steps: contig construction, scaffolding, and gap filling. First, three K (45, 59, 71) values were used to assemble the genome, according to the N50 length of contig and the BUSCO assessments of three genomes. The genome of 59-mer was chosen as the final genome for subsequent analysis. The clean reads of short-insert libraries (250 bp and 500 bp) were used to construct the contigs with 59-mer. Then reads of long-insert libraries (2 kb, 5 kb and 10 kb) were implemented to link the contig sequences into scaffold sequences. To further improve assembly quality, GAPcloser14 and SSPACE15 were applied to reduce gap regions and raise scaffold length using a genome sketch assembled by SOAPdenovo. This last step improved the contig N50 and N90 sizes to 41,757 and 5,528 bp, and the scaffold N50 and N90 sizes to 7,221,511 and 257,323 bp, respectively, with the fragments being longer than 100 bp (Table 3). The final assembly of the big-headed turtle genome had a total length of 2.32 Gb, which was similar to the three previously published turtle genomes: Chrysemys picta bellii16, Chelonia mydas and Pelodiscus sinensis17. The key assembly statistics of the big-headed turtle genome are comparable to or better than those of previously published turtle genomes (Table 4).

Table 3 Summary of the genome assembly.
Table 4 Summary statistics of four turtle genomes.


Repeat annotation

There are two major types of repetitive sequences: tandem repeats and interspersed repeats18. For the repeat annotation of the big-headed turtle genome, both homology-based predictions and de novo methods were performed. In the homolog-based methods, interspersed repeats were identified using RepeatMasker19 and RepeatProteinMask to search against the published RepBase sequences. In the de novo method, RepeatMasker and RepeatModeler ( were used to detect interspersed repeats in the genome. Tandem Repeats Finder (TRF)20 was subsequently used to search for tandem repeats. Overall, the results identified a total of 924 Mb of non-redundant repetitive sequences in the big-headed turtle genome, which account for 39.84% of the whole genome (Table 5). The most predominant elements were long interspersed nuclear elements (LINEs), which accounted for 27.47% (637 Mb) of the genome (Table 6).

Table 5 Prediction of repeat elements in the big-headed turtle genome.
Table 6 Statistics of repeat elements in the big-headed turtle genome.

Structural annotation of genes

Three methods (homology-based, ab initio and transcriptome-based predictions) were used to predict gene structure in the big-headed turtle genome. In the homology-based method, the protein repertoires of Alligator sinensis, Chelonia mydas, Chrysemys picta bellii, Deinagkistrodon acutus, Gallus gallus, Gekko japonicus, Nanorana parkeri, Parus major, Pelodiscus sinensis, Philomachus pugnax and Xenopus laevis were downloaded from the NCBI database and mapped onto the big-headed turtle genome using TBLASTn21 with an E-value cutoff of 1 E−5. Then, homologous genome sequences were aligned against the matching proteins using GeneWise22 to define gene models. In the ab initio prediction, Augustus23, GlimmerHMM24 and SNAP25 were used to predict the coding regions of genes. To optimize the genome annotation, seven RNA tissue libraries (liver, skin, lung, intestine, heart, muscle and stomach) were constructed according to the manufacturer’s instructions (Illumina, San Diego, California, USA) and a total of 61.27 Gb of sequence data was generated. RNA-seq reads were used in de novo assembly with Trinity26. The unique transcriptional sequences were employed to predict gene models using PASA27. In total, 25,995 non-redundant protein-coding genes were annotated in the big-headed turtle genome (Table 7).

Table 7 Statistics of predicted genes.

Functional annotation of genes

The functional annotation of protein-coding genes of the big-headed turtle genome were predicted by aligning protein sequences against public databases including SwissProt (, KEGG ( and TrEMBL ( using BLASTp with an E-value cutoff of 1 E−5. Protein motifs and domains were annotated using InterPro28, and Gene Ontology (GO)29 terms for each gene were retrieved from the corresponding InterPro results. Overall, 22,400 protein-coding genes (86.2%) were successfully annotated (Table 8).

Table 8 Statistics of functional annotation.

Non-coding RNA annotation

The non-coding RNAs were predicted in the big-head genome based on four categories: ribosomal RNA (rRNA), transfer RNA (tRNA), microRNAs (miRNA) and small nuclear RNA (snRNA). tRNAscan-SE30 was applied to identify tRNA with eukaryotic parameters according to the characteristics of tRNA. Because of the highly conserved characteristics of rRNA, BLASTN31 was used to predict rRNA sequences by aligning with a human template with an E-value of 1 E−10. The miRNA and snRNA sequences were identified using INFERNAL32 by searching against the Rfam database. We identified a total of 409 rRNA, 2,089 tRNA, 16,050 miRNA, and 629 snRNA genes in the big-headed turtle genome (Table 9).

Table 9 Summary of non-coding RNA.

Data Records

This Whole Genome Shotgun project including the assembled genome sequence and the structural and functional annotation of genes has been deposited at DDBJ/ENA/GenBank under the accession QXTE0000000033. The version described in this paper is version QXTE01000000. Repeat annotation and Non-coding RNA annotation have been deposited at Figshare34. Raw read files have been deposited at NCBI Sequence Read Archive under the accession SRP15641935.

Technical Validation

Assessing the completeness of the genome assembly

To assess the quality of the genome assembly, we performed three independent evaluations as described below. First, the base content was counted with scaffolds longer than 100 bp and the results showed that the GC content for the big-headed turtle was 44.63% (Table 10), which was comparable to those of Chrysemys picta bellii, Chelonia mydas and Pelodiscus sinensis (Table 4). Second, the short-insert paired-end reads (250 bp and 500 bp) were mapped to the genome with BWA36. The mapping rate was 98.84% and the genome coverage was 99.57% (Table 11), indicating high reliability of genome assembly. Third, the SNPs (Single Nucleotide Polymorphisms) were counted to validate the uniformity of the genome using SAMtools37, and we found the ratio of homozygous SNPs was only 0.014% (Table 12), indicating that the assembly had a high base accuracy. Finally, CEGMA ( and BUSCO ( were used to evaluate the completeness of the assembly. CEGMA assessment showed that our assembly captured 226 (91.13%) of the 248 ultra-conserved core eukaryotic genes, of which 202 (81.45%) were complete (Table 13). BUSCO analysis showed that 95.2% and 2.6% of the expected vertebrate genes were identified as complete and fragmented, respectively, while 2.2% were considered missing in the assembly (Table 14).

Table 10 Base content statistics of the genome.
Table 11 Statistics of mapping ratio in genome.
Table 12 Number and density of SNPs in big-headed turtle genome.
Table 13 Assessment of CEGMA.
Table 14 Assessment of BUSCO.

Annotation filtering and validation

The EVM software38 was used to merge the above results of gene annotation and 39,212 genes were obtained from the merged set. To further revise the genome annotation, we removed the following type of genes: (1) genes with overlap regions of TE ≥ 20%; (2) premature termination genes; (3) genes with only de novo predictive support. After filtering, 25,995 genes were retained. In addition, total RNA-seq reads of 7 tissues were mapped onto the big-headed turtle genome to further identify exon regions and splice positions using Tophat39 and Cufflinks40, and 20,028 (77.05%) genes had evidence supports of RNA data (RPKM value > 1) cross above 7 tissues.