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Immunomics of the koala (Phascolarctos cinereus)

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Abstract

The study of the koala transcriptome has the potential to advance our understanding of its immunome—immunological reaction of a given host to foreign antigens—and to help combat infectious diseases (e.g., chlamydiosis) that impede ongoing conservation efforts. We used Illumina sequencing of cDNA to characterize genes expressed in two different koala tissues of immunological importance, blood and spleen. We generated nearly 600 million raw sequence reads, and about 285 million of these were subsequently assembled and condensed into ~70,000 subcomponents that represent putative transcripts. We annotated ~16 % of these subcomponents and identified those related to infection and the immune response, including Toll-like receptors (TLRs), RIG-I-like receptors (RLRs), major histocompatibility complex (MHC) genes, and koala retrovirus (KoRV). Using phylogenetic analyses, we identified 29 koala genes in these target categories and report their concordance with currently accepted gene groups. By mapping multiple sequencing reads to transcripts, we identified 56 putative SNPs in genes of interest. The distribution of these SNPs indicates that MHC genes (34 SNPs) are more diverse than KoRV (12 SNPs), TLRs (8 SNPs), or RLRs (2 SNPs). Our sequence data also indicate that KoRV sequences are highly expressed in the transcriptome. Our efforts have produced full-length sequences for potentially important immune genes in koala, which should serve as targets for future investigations that aim to conserve koala populations.

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Acknowledgments

This project was supported by the Purdue University Faculty Scholar program (JAD), the National Science Foundation Graduate Research Fellowship Program (Grant Number: DGE-1333468; KCA), the San Diego Zoo and the participants of the Koala Education and Conservation Program (JAI).We thank the personnel of the Genomics Core Facility and the Rosen Center for Advanced Computing at Purdue, as well as the National Center for Genome Analysis Support for their assistance. We also thank current and former members of the DeWoody lab for their feedback on this manuscript.

Ethical standards and conflicts of interest

The blood samples were collected under the auspices of an Institutional Animal Care and Use Committee (IACUC) approved protocol at the San Diego Zoo. The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. Department of Forestry and Natural Resources, Purdue University, 195 Marsteller St, West Lafayette, IN, 47907, USA

    Kendra C. Abts & J. Andrew DeWoody

  2. Life Sciences, San Diego Zoo Global, PO Box 120551, San Diego, CA, 92112, USA

    Jamie A. Ivy

  3. Department of Biological Sciences, Purdue University, West Lafayette, IN, 47907, USA

    J. Andrew DeWoody

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  1. Kendra C. Abts
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Correspondence to Kendra C. Abts.

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Online Resource 1

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Online Resource 3

All Subcomponents Annotation Summary. This table contains all of the subcomponents in the koala transcriptomes, which pass the minimum abundance threshold of 10 reads in at least one sample. “Read Count” refers to the number of reads mapped back to the subcomponent from all samples. “GO terms” stands for gene ontology terms. Immune subcomponent refers to those subcomponents that possess at least one child GO term of the “immune system process” GO terms and are indicated by a “Yes” in the “Immune” column. (XLSX 1950 kb)

Online Resource 4

All GO Terms Annotation Summary. GO term stands for gene ontology term, and this table contains all of the GO terms that are associated with subcomponents that pass the minimum threshold of 10 reads in at least one sample. “Read Count” refers to the number of reads mapped back from all tissues (via RSEM) to the subcomponents possessing a given GO term. “Frequency” refers to the number of times the GO terms appears in the Trinotate output. Immune GO term refers to a GO term, which is a child of the “immune system process” GO term, and these are indicated by a “Yes” in the “Immune” column. The “Tissue” column refers to the library or libraries to which mapped at least 10 of the subcomponent’s reads. “BC” stands for buffy coat. (XLSX 689 kb)

Online Resource 5

Additional Immune Transcripts Using IDMM. This table contains all of the transcripts from subcomponents in the koala transcriptomes that pass the minimum abundance threshold of 10 reads in at least one sample and have a blast hit from the Immunome Database for Monotremes and Marsupials (IDMM; Wong et al. 2011) with an E-value equal to or less than the E-value for the hit from the Trinotate analysis. “Read Count” refers to the number of reads mapped back to the subcomponent from all samples. The “Tissue” column refers to the library or libraries to which mapped at least 10 of the subcomponent’s reads. “BC” stands for buffy coat. (XLSX 71 kb)

Online Resource 6

SNP Details. Below are listed the SNPs identified from the target subcomponents via both the SAMtools and GATK analysis. The location of the SNP is indicated by the “TRANSCRIPT” and the “POS” (base pair number). The “REF” column represents the nucleotide present in the subcomponent sequence while the “ALT” column represents the other allele present in the reads. “QUAL” represents the quality score of the alternative allele on the PHRED scale. “DEPTH” represents the coverage at the site of the SNP. The columns with sample names (i.e. “BC_504219”, “BC_510113”, and “Spleen_501090”), represent the un-phased genotypes in those samples where “0” represents the reference allele and “1” represents the alternative allele. The “In_ORF” column represents the location of the SNP in relation to the transcript’s open reading frame (ORF). “No” indicates that the SNP is located outside of the ORF. “Non-Synonymous” and “Synonymous” indicate that the SNP is located inside the ORF and results in a change or no change to the amino acid sequence, respectively. The change in amino acid is reflected in the “AA_change” column with the original amino acid followed by the substituted amino acid, using the one-letter amino acid abbreviations. SNPs that are shaded grey could be due to the combination of transcripts from multiple genetic loci because of the presence of more than two possible haplotypes in a single individual. (XLSX 63 kb)

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Abts, K.C., Ivy, J.A. & DeWoody, J.A. Immunomics of the koala (Phascolarctos cinereus). Immunogenetics 67, 305–321 (2015). https://doi.org/10.1007/s00251-015-0833-6

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