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PLoS One
2015 Jun 18;106:e0130720. doi: 10.1371/journal.pone.0130720.
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De novo Transcriptome Assemblies of Rana (Lithobates) catesbeiana and Xenopus laevis Tadpole Livers for Comparative Genomics without Reference Genomes.
Birol I
,
Behsaz B
,
Hammond SA
,
Kucuk E
,
Veldhoen N
,
Helbing CC
.
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In this work we studied the liver transcriptomes of two frog species, the American bullfrog (Rana (Lithobates) catesbeiana) and the African clawed frog (Xenopus laevis). We used high throughput RNA sequencing (RNA-seq) data to assemble and annotate these transcriptomes, and compared how their baseline expression profiles change when tadpoles of the two species are exposed to thyroid hormone. We generated more than 1.5 billion RNA-seq reads in total for the two species under two conditions as treatment/control pairs. We de novo assembled these reads using Trans-ABySS to reconstruct reference transcriptomes, obtaining over 350,000 and 130,000 putative transcripts for R. catesbeiana and X. laevis, respectively. Using available genomics resources for X. laevis, we annotated over 97% of our X. laevis transcriptome contigs, demonstrating the utility and efficacy of our methodology. Leveraging this validated analysis pipeline, we also annotated the assembled R. catesbeiana transcriptome. We used the expression profiles of the annotated genes of the two species to examine the similarities and differences between the tadpoleliver transcriptomes. We also compared the gene ontology terms of expressed genes to measure how the animals react to a challenge by thyroid hormone. Our study reports three main conclusions. First, de novo assembly of RNA-seq data is a powerful method for annotating and establishing transcriptomes of non-model organisms. Second, the liver transcriptomes of the two frog species, R. catesbeiana and X. laevis, show many common features, and the distribution of their gene ontology profiles are statistically indistinguishable. Third, although they broadly respond the same way to the presence of thyroid hormone in their environment, their receptor/signal transduction pathways display marked differences.
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Fig 2. Differential expression of assembled transcripts for (A) R. catesbeiana and (B) X. laevis.Three shades of purple designate p-values of differential expression estimates 0.05, 0.02 and 0.002, lighter colours indicating lower thresholds.
Fig 3. Gene ontology classification of DESeq-selected, TH-responsive R. catesbeiana and X. laevis liver transcripts with UniProtKB AC numbers.The two series in each stacked bar plot correspond to differentially expressed R. catesbeiana (CAT) and X. laevis (LAE) transcripts, with a p-value threshold of 5%.
Fig 4. Pathway analysis for liver transcripts from R. catesbeiana (CAT) and X. laevis (LAE).Top 25 impacted pathways after TH treatment for R. catesbeiana ranked by the highest proportion of overall observed genes. The pathway names are indicated in the center of the figure with the total number of genes known in each IGA pathway indicated. The asterisk indicates those pathways that are found in the top 25 list of X. laevis. The colour coded bar plots illustrate the percentage of the total number of gene transcripts in a pathway that are downregulated (blue), non-responsive (yellow), upregulated (red) or not observed in the experiment (gray) relative to the control condition. Differentially expressed transcripts were determined using a p-value threshold of 5%.
Fig 5. Pathway analysis for liver transcripts from R. catesbeiana (CAT) and X. laevis (LAE).Top 25 impacted pathways after TH treatment for X. laevis ranked by the highest proportion of overall observed genes. The asterisk indicates those pathways that are found in the top 25 list of R. catesbeiana. Plot details are as in the Fig 4 legend.
Fig 1. Gene ontology classification of all reconstructed R. catesbeiana and X. laevis liver transcripts with UniProtKB AC numbers.The two series in each stacked bar plot correspond to all R. catesbeiana (CAT) and X. laevis (LAE) transcripts.
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