Characterization of the transcriptome of an ecologically important avian species, the Vinous-throated Parrotbill Paradoxornis webbianus bulomachus (Paradoxornithidae; Aves)
© Chu et al.; licensee BioMed Central Ltd. 2012
Received: 8 September 2011
Accepted: 24 April 2012
Published: 24 April 2012
Adaptive divergence driven by environmental heterogeneity has long been a fascinating topic in ecology and evolutionary biology. The study of the genetic basis of adaptive divergence has, however, been greatly hampered by a lack of genomic information. The recent development of transcriptome sequencing provides an unprecedented opportunity to generate large amounts of genomic data for detailed investigations of the genetics of adaptive divergence in non-model organisms. Herein, we used the Illumina sequencing platform to sequence the transcriptome of brain and liver tissues from a single individual of the Vinous-throated Parrotbill, Paradoxornis webbianus bulomachus, an ecologically important avian species in Taiwan with a wide elevational range of sea level to 3100 m.
Our 10.1 Gbp of sequences were first assembled based on Zebra Finch (Taeniopygia guttata) and chicken (Gallus gallus) RNA references. The remaining reads were then de novo assembled. After filtering out contigs with low coverage (<10X), we retained 67,791 of 487,336 contigs, which covered approximately 5.3% of the P. w. bulomachus genome. Of 7,779 contigs retained for a top-hit species distribution analysis, the majority (about 86%) were matched to known Zebra Finch and chicken transcripts. We also annotated 6,365 contigs to gene ontology (GO) terms: in total, 122 GO-slim terms were assigned, including biological process (41%), molecular function (32%), and cellular component (27%). Many potential genetic markers for future adaptive genomic studies were also identified: 8,589 single nucleotide polymorphisms, 1,344 simple sequence repeats and 109 candidate genes that might be involved in elevational or climate adaptation.
Our study shows that transcriptome data can serve as a rich genetic resource, even for a single run of short-read sequencing from a single individual of a non-model species. This is the first study providing transcriptomic information for species in the avian superfamily Sylvioidea, which comprises more than 1,000 species. Our data can be used to study adaptive divergence in heterogeneous environments and investigate other important ecological and evolutionary questions in parrotbills from different populations and even in other species in the Sylvioidea.
Adaptive divergence, driven by local adaptation to heterogeneous environments, has long been a fascinating topic in ecology and evolutionary biology . Local adaptation not only leads to adaptive divergence between populations, but may also drive the process of speciation, i.e., ecological speciation [2, 3]. It is often difficult to determine the extent of genetic differences associated with divergent selection. However, recent advances in genomic approaches such as genome scans and targeted resequencing provide illuminating ways to discover genes and genomic regions that might be involved in divergent selection . For example, using genome-wide scans, genes that might be responsible for adaptation to high-elevation hypoxia were found in human Tibetan populations . In addition, genes that might be associated with adaptation to serpentine soil have also been identified by genomic sequencing at the population level in the plant Arabidopsis lyrata. Moreover, targeted resequencing in a specific chromosome region implied a selective target locus between diversifying ecotypes (M and S forms) of the African malaria mosquito Anopheles gambiae. Those studies provide fresh insights into the genetic basis of adaptive evolution. However, genomic approaches are often applicable only to human or other model organisms for which genomic information is available. Although the cost of de novo genomic sequencing is much reduced by innovative sequencing technologies (e.g., Next Generation Sequencing, NGS, [8, 9]), it is still out of the reach of studies of most non-model organisms which collectively represent the diversity and complexity of life forms.
To sequence a subset of the genome of a non-model organism, for example, the transcribed DNA within a given set of tissues under specific developmental stages or environmental conditions (transcriptome) may be a good alternative approach. Sequences of the transcriptome were used to develop polymorphic markers, such as single nucleotide polymorphisms (SNPs) and simple sequence repeats (SSRs), e.g. [10, 11]. Because markers developed from the transcriptome are associated with expressed genes, they may better reveal intra- and inter-populational functional variations and are therefore suitable for studies of adaptive diversification or local adaptation . Recent developments in RNA sequencing technology (RNA-Seq; reviewed in ), which take advantage of the deep sequencing power of NGS (see reviews in [13, 14]) and efficient bioinformatic computations [15–17], have greatly enhanced the process of transcriptome characterization, and have turned transcriptome sequences into promising genetic resources for non-model organisms.
Herein, we report the characterization of the transcriptome of an ecologically important avian species in East Asia, the Vinous-throated Parrotbill (Paradoxornis webbianus, Timaliidae). The Vinous-throated Parrotbill is one of the most widely distributed resident avian species in East Asia . It has a broad latitudinal and elevational distribution covering geographic ranges from northern Indochina to southern Siberia and from the eastern edge of the Tibetan Plateau to coastal China and the island of Taiwan. It occupies various types of habitats in China, while its island subspecies (P. w. bulomachus) is also considered to occupy the widest niche of any bird species in Taiwan with an extraordinary elevational distribution from sea level to 3100 m [18, 19]. A steep elevational gradient can lead to high environmental heterogeneity (e.g., wide ranges of temperature and partial pressure of oxygen) within a short horizontal distance, which is considered a ‘natural laboratory’ with many resources that can be used to examine adaptive responses of populations to different environmental contexts . The wide elevational distribution of P. w. bulomachus may provide a good system for addressing how divergent selection pressures posed by a steep elevational gradient may drive adaptive differentiation between populations living at different elevations.
In this study, we attempted to characterize the transcriptome sequenced from a single individual of P. w. bulomachus and explored its potential utility, for example, in developing genetic markers for use in future adaptive genetic studies. Specifically, we assembled and annotated transcriptome from Illumina short-read sequences and assigned them to different gene ontology (GO) categories. Putative genetic markers such as SNPs and SSRs were also identified from the transcriptome. Despite only sequencing a single individual’s transcriptome, SNPs were identified through heterozygous sites of the assembled contigs. We then identified genes in our transcriptome database which also appeared in an a priori list of candidate genes that might respond to hypoxia  and be involved in climate-related adaptation , and matched them to specific GO terms associated with environmental adaptation. Sequences of these genes can be used to design targeted gene-resequencing experiments to detect the genetic signature of elevational adaptation in the Vinous-throated Parrotbill. Our results demonstrate that transcriptome sequences, even from a single individual, can serve as a rich genetic resource to investigate ecological and evolutionary processes.
Results and discussion
Summary of the numbers of contigs retained in each step when characterizing the transcriptome of Paradoxornis webbianus bulomachus
De novo assembly
Because of similarities of the genomic structure and chromosomal organization among different species of birds , we assumed the genome size of P. w. bulomachus to be similar to that of the Zebra Finch at approximately 1.2 Gbp . The unique contigs retained in this study covered 64,330,421 bp and represented approximately 5.3% of the P. w. bulomachus genome. The reported RNA sequences (including protein-coding sequences and a small proportion of other functional RNAs) of the Zebra Finch and chicken respectively represent approximately 2.4% and 3.5% of their total genomes according to the NCBI database.
BLAST, top-hit species distribution and GO annotation
All contigs retained after filtering for base coverage (10,076 and 680 retained from the two reference-guided assemblies and 57,035 retained from de novo assembly) were BLASTed against the NCBI non-redundant (nr) protein database using Blast2GO [24, 25]. Accessions of BLAST hits were then used to retrieve associated sequence descriptions and GO terms.
Distribution of BLASTx top-hit species of Paradoxornis webbianus bulomachus contigs with a similarity of > 90% and an alignment length of > 200 amino acid residues to their best-hit sequences
De novo assembly
No. of contigs (%)
No. of contigs (%)
No. of contigs (%)
No. of contigs (%)
Other avian species1
Other reptile species3
Other plant species4
Identification of SNPs and SSRs
Number of single-nucleotide polymorphisms (SNPs) and simple-sequence repeats (SSRs) identified in the transcriptome of Paradoxornis webbianus bulomachus
Type of marker
De novo contigs
Using MSATCOMMADER , we found 1,344 di-, tri-, or tetra-nucleotide SSR regions with a minimum of seven continuous repeats in all contigs (Table 3). Di-nucleotide repeats were the most abundant SSRs (67.7%, N = 910) in the P. w. bulomachus transcriptome while tri- and tetra-nucleotide repeats were only present at smaller frequencies (tri-nucleotide SSRs 26.7%, N = 359 and tetra-nucleotide SSRs 5.6%, N = 75). These SSRs could provide a rich source for further development of a polymorphic marker system for all P. webbianus populations.
Discovering candidate genes for hypoxic and climatic adaptations in the transcriptome of P. w. bulomachus
In order to understand how the genetic context of P. w. bulomachus populations might have adapted to harsher highland environments, we matched our annotated contigs with 329 candidate genes for high-elevation  and climatic adaptations . We found 69 matches: 61 for hypoxia, six for climatic adaptation and two for both hypoxia and climatic adaptations ( Additional file 1: Table S1). Among the 61 hypoxia-related candidate genes, we found five genes (i.e., PTEN, PPARA, HOMX2, ANGPTL4, and EDNRA) that are associated with the hypoxia-inducible factor (HIF) pathway and which were suggested to be under recent positive selection for human high-elevation adaptation [5, 29]. We also identified eight genes (CD36, EGFR, EPHX2, LEPR, LPA, MAPK1, SOD1, and TCF7L2) that may be correlated with thermal adaptation in humans . An additional 40 genes ( Additional file 1: Table S2) that may underpin environmental adaptation were found by searching GO terms of oxygen binding, response to hypoxia, response to cold and response to heat from the P. w. bulomachus transcriptome database. In total, we identified 109 genes that can serve as a priori candidates to investigate how populations of P. w. bulomachus have adapted to diverse ecological environments along an elevational gradient.
In this study, transcriptome information was obtained from a single individual of the Taiwan endemic subspecies of P. webbianus. The Vinous-throated Parrotbill, which occupies broad elevational and latitudinal ranges in East Asia, is an excellent organism to interpret adaptation to diverse environments. The various potential genetic markers obtained can be directly applied to understand how genetic contents can change and diversify under heterogeneous elevational environments in P. w. bulomachus, and they can also be applied to understand how the genetic structure may respond to the wide range of latitudes in which P. webbianus is found. The causal effect of natural selection on genetic aspects of ecological adaptation can be judged and compared from both vertical and horizontal environmental dimensions in a single species and may provide insights into adaptive evolution in natural populations. This is the first study providing transcriptomic information for species in the species-rich avian superfamily, the Sylvioidea . Therefore, the genomic resources of P. w. bulomachus can be used for various ecological and evolutionary studies across different parrotbill species (Paradoxornithidae) [18, 31], and can also be extended to the Sylvioidea that comprises more than 1,000 avian species in the world and is the most species-rich avian superfamily in Asia .
RNA extraction and sequencing
Fresh cerebrum and liver tissues were removed from an adult male P. w. bulomachus collected in Hualien, Taiwan (121′32.54E, 23′54.03 N, elevation: 40 m), and were immediately stored in RNAlater buffer (QIAGEN) to stabilize the RNA integrity. Tissues were later transferred to a −80°C freezer for long-term storage. Total RNA was isolated using two different commercial kits: RNeasy Lipid Tissue Kit (QIAGEN) for the fat-rich cerebrum and RNeasy Mini Kit (QIAGEN) for the liver. Extractions were performed following the manufacturer’s instructions with an additional DNase digestion procedure using an RNase-Free DNase Set (QIAGEN). The quality and quantity of the total RNA were measured on a 1.2% agarose gel and a NanoDrop spectrophotometer (ND-1000, Thermo). Equal amounts of RNA from each tissue were pooled for RNA-Seq sequencing (mRNA-Seq prep kit, Illumina) and paired-end sequences were obtained from one lane of a HiSeq 2000 Genome Analyzer (Illumina) at BGI (Shenzhen, China). Unfiltered sequences were deposited in the NCBI Short Read Archive under submission no. SRA045008. The original reads were cleaned by removing adaptor sequences and short reads (reads of < 15 bp). Subsequently, reads were trimmed by one nucleotide at both the 5′ and 3′ ends to improve the read quality.
We used a two-step strategy described below to assemble the transcriptome of P. w. bulomachus, i.e., assembly with guide reference sequences and de novo assembly. First, all reads were assembled according to 15,275 RNA reference sequences of Zebra Finch (T. guttata, NCBI genome project ID 32405, , available at ftp://ftp.ncbi.nlm.nih.gov/genomes/Taeniopygia_guttata/RNA/rna.fa.gz). Subsequently, the remaining reads were assembled according to 19,131 RNA reference sequences of the chicken (Gallus gallus, genome build 2.1, available at ftp://ftp.ncbi.nlm.nih.gov/genomes/Gallus_gallus/RNA/rna.fa.gz). Finally, unmatched reads were then de novo assembled. All assemblies were processed using CLC Genomics Workbench version 4.8 (CLC Bio) with an option for global alignment that requires exact matches of the 5′- and 3′-end sequences during assembly. For assembly with the reference genomes, parameters of similarity and overlap were set to 0.97 (as suggested in ) and 0.70, respectively. For de novo assembly, these two parameters were respectively set to 0.97 and 0.65. Thereafter, only contigs with a mean coverage > 10X per base were retained for subsequent analyses.
Transcriptome sequencing efficiency of reference-guided assembly was evaluated in two ways. First, by assuming that P. w. bulomachus contigs were assembled to their orthologous Zebra Finch transcripts, we calculated the ratio of the number of contigs to the number of Zebra Finch transcripts (i.e., 15,275) to reveal the efficiency of retrieving P. w. bulomachus transcripts. Second, by assuming that no indels occurred between orthologues of the two species, we divided the lengths of P. w. bulomachus contigs by the lengths of their Zebra Finch orthologues to show the efficiency of recovering full-length transcripts.
Following the Blast2GO pipeline [33, 34], annotations of transcribed contigs were first BLASTed (BLASTx) against the NCBI non-redundant (nr) protein database, mapped to extract GO terms  and then annotated. A standard cutoff E-value of 1.0E−3 was use in the BLAST process to collect at most 20 hits for each query sequence. The hits returned by BLASTx were further filtered for matches with significant E-values of < 1.0E−15 and with high-scoring segment pairs (HSPs) covering at least 80% of the length of the hit in annotation. The species distribution for matched sequences was analyzed from the best hit of each contig. Instead of using the top-hit species information from all contigs, a subset of information was analyzed to preserve a better genealogical homology between our query sequences and their best matches from the NCBI nr database. Two criteria were applied to retain valid contigs: a similarity of at least 90% and a length alignment of more than 200 amino acid residues to their best matches. A cutoff of 200 amino acid residues was chosen since protein domains have an average length of around 100 amino acid residues , and since 75% of proteins with single domains and 87% of those with multiple domains are shorter than 200 amino acid residues . Thus, only retaining contigs with a hit alignment length of more than 200 amino acid residues should have greatly improved the homological aspect of the top-hit species distribution. The Annex function implemented in Blast2GO was performed to improve the annotation density (enrich GO terms for annotating). Finally, an additional GO-Slim procedure (with generic GO-Slim terms) was processed to cut down GOs in order to provide a broad overview of GO annotation of the P. w. bulomachus transcriptome.
SNP and SSR identification
We used the SNP detection algorithm implemented in CLC Genomics Workbench to identify SNPs from this ecologically important species. The quality parameters for SNP detection were set as follows: a window length of 11, a maximum number of gaps and mismatches of 10, an average quality of surrounding bases of 20, and a minimum quality of the central base of 30. To minimize the chance of false positives due to sequencing errors, the minimum variant frequency was set to 35%, and only sites with more than 10X coverage were included for SNP detection. To validate the SNPs called by CLC Genomic Workbench, we used another program, the Genome Analysis Toolkit (GATK) version 1.3.21 , to independently detect SNPs in the Zebra Finch RNA reference-guided assembly. We first attempted to conduct the GATK analysis with the CLC output contig alignment. However, because the current version of CLC Genomics Workbench does not keep track of which is the first and second reads of a pair in an assembly (confirmed in consultation with CLC bio global technical support), its exported SAM/BAM files could not be processed in the subsequent GATK procedure. In order to obtain an executable BAM file, we performed an independent alignment with Zebra Finch RNA sequences using the Burrows-Wheeler Aligner (BWA) version 0.6.1 . Duplicates in the mapping results were marked using MarkDuplicates in Picard version 1.57 (http://picard.sourceforge.net/index.html). After running a local realignment and base quality score recalibration, SNP calling was conducted using the GATK UnifiedGenotyper. Variants with a Phred quality score of > 30 (Q30) were exported as SNPs. The SNPs identified by both the CLC Genomics Workbench and the GATK were considered promising SNPs for future investigation.
We used the software, MSATCOMMANDER version 0.8.1 , to search for SSRs in the Vinous-throated Parrotbill transcriptome database. Series arrays of di-, tri-, and tetra-nucleotide repeats were searched through all contigs assembled. SSR motifs with more than six repeats were considered to be potential SSR loci for the Vinous-throated Parrotbill.
Finding candidate genes associated with hypoxia and cold-weather adaptation
We matched the annotated results of the P. w. bulomachus transcriptome with an a priori list of candidate genes that may be associated with hypoxia  and cold-weather adaptation  to highland environments. We also searched the annotated results for specific GO terms such as “oxygen binding”, “response to hypoxia”, “response to cold” and “response to heat” to identify additional genes that might also be associated with highland adaptation. Sequences of these candidate gene-associated contigs are in the supplementary information.
We are grateful to Alan Watson who greatly improved the readability of this manuscript. The study was supported by a grant from the National Science Council (NSC) of Taiwan to SHL. JHC is a post-doctoral researcher funded by a grant from the NSC.
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