Single molecule, full-length transcript sequencing provides insight into the extreme metabolism of ruby-throated hummingbird Archilochus colubris

  1. Rachael E. Workman
  2. Alexander M. Myrka
  3. Elizabeth Tseng
  4. G. William Wong
  5. Kenneth C. Welch
  6. Winston Timp

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Abstract

Hummingbirds can support their high metabolic rates exclusively by oxidizing ingested sugars, which is unsurprising given their sugar-rich nectar diet and use of energetically expensive hovering flight. However, they cannot rely on dietary sugars as a fuel during fasting periods, such as during the night, at first light, or when undertaking long-distance migratory flights, and must instead rely exclusively on onboard lipids. This metabolic flexibility is remarkable both in that the birds can switch between exclusive use of each fuel type within minutes and in that de novo lipogenesis from dietary sugar precursors is the principle way in which fat stores are built, sometimes at exceptionally high rates, such as during the few days prior to a migratory flight. The hummingbird hepatopancreas is the principle location of de novo lipogenesis and likely plays a key role in fuel selection, fuel switching, and glucose homeostasis. Yet understanding how this tissue, and the whole organism, achieves and moderates high rates of energy turnover is hampered by a fundamental lack of information regarding how genes coding for relevant enzymes differ in their sequence, expression, and regulation in these unique animals. To address this knowledge gap, we generated a de novo transcriptome of the hummingbird liver using PacBio full-length cDNA sequencing (Iso-Seq), yielding a total of 8.6Gb of sequencing data, or 2.6M reads from 4 different size fractions. We analyzed data using the SMRTAnalysis v3.1 Iso-Seq pipeline, including classification of reads and clustering of isoforms (ICE) followed by error-correction (Arrow). With COGENT, we clustered different isoforms into gene families to generate de novo gene contigs. We performed orthology analysis to identify closely related sequences between our transcriptome and other avian and human gene sets. We also aligned our transcriptome against the Calypte anna genome where possible. Finally, we closely examined homology of critical lipid metabolic genes between our transcriptome data and avian and human genomes. We confirmed high levels of sequence divergence within hummingbird lipogenic enzymes, suggesting a high probability of adaptive divergent function in the hepatic lipogenic pathways. Our results have leveraged cutting-edge technology and a novel bioinformatics pipeline to provide a compelling first direct look at the transcriptome of this incredible organism.

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  1. GigaScience

    Now published in GigaScience doi: 10.1093/gigascience/giy009

    Rachael E. Workman 1Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USAFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteAlexander M. Myrka 2Department of Biological Sciences, University of Toronto Scarborough, Toronto, Ontario, Canada and Department of Cell & Systems Biology, University of Toronto, Toronto, Ontario, CanadaFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteElizabeth Tseng 4Pacific Biosciences, Menlo Park, California, USAFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteG. William Wong 3Department of Physiology and Center for Metabolism and Obesity Research, Johns Hopkins University School of Medicine, Baltimore, MD, USAFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteKenneth C. Welch Jr.2Department of Biological Sciences, University of Toronto Scarborough, Toronto, Ontario, Canada and Department of Cell & Systems Biology, University of Toronto, Toronto, Ontario, CanadaFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteORCID record for Kenneth C. Welch Jr.Winston Timp 1Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USAFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteORCID record for Winston Timp

    A version of this preprint has been published in the Open Access journal GigaScience (see paper https://doi.org/10.1093/gigascience/giy009 ), where the paper and peer reviews are published openly under a CC-BY 4.0 license.

    These peer reviews were as follows:

    Reviewer 1: http://dx.doi.org/10.5524/REVIEW.101011 Reviewer 2: http://dx.doi.org/10.5524/REVIEW.101012

  2. Version published to 10.1101/117218 on bioRxiv