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Transcriptional Signatures in Liver Reveal Metabolic Adaptations to Seasons in Migratory Blackheaded Buntings

The molecular underpinnings of metabolic adaptation to seasons are poorly understood in long- distance migrants. We measured changes in physiology and performed de novo sequencing of RNA extracted from liver samples collected at 4-h intervals over a period of 24 h from a long-distance avian migrant,...

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Autores principales: Singh, Devraj, Swarup, Vivek, Le, Hiep, Kumar, Vinod
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6277527/
https://www.ncbi.nlm.nih.gov/pubmed/30538637
http://dx.doi.org/10.3389/fphys.2018.01568
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author Singh, Devraj
Swarup, Vivek
Le, Hiep
Kumar, Vinod
author_facet Singh, Devraj
Swarup, Vivek
Le, Hiep
Kumar, Vinod
author_sort Singh, Devraj
collection PubMed
description The molecular underpinnings of metabolic adaptation to seasons are poorly understood in long- distance migrants. We measured changes in physiology and performed de novo sequencing of RNA extracted from liver samples collected at 4-h intervals over a period of 24 h from a long-distance avian migrant, the blackheaded bunting (Emberiza melanocephala), during two states: photostimulated vernal migratory (M) state and photorefractory non-migratory (nM) state. The M state was differentiated from the nM state based on body fattening and weight gain, as well as on Zugunruhe, that is, nocturnal migratory restlessness in caged birds. We found that baseline blood glucose and triglyceride levels were significantly higher in the M state than the nM state; conversely, surface body temperature was higher in the nM state than the M state. In a total of 6 liver samples that were sequenced from each state, 11,246 genes were annotated, including 4448 genes that were cyclic over 24 h. We found 569 differentially expressed genes (DEGs) between the M and the nM state, and the M state showed 131 upregulated and 438 downregulated genes. These DEGs formed core gene hubs associated with specific biological processes in both the states. In addition, weighted gene coexpression network analysis revealed two discrete modules of coexpressed genes, with a significant difference in the expression pattern of metab olism-associated genes between M and nM states. These results demonstrate, for the first time, transcriptome-wide changes in the liver between two distinct physiological states and give molecular insights into seasonal metabolic adaptations in latitudinal migrants.
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spelling pubmed-62775272018-12-11 Transcriptional Signatures in Liver Reveal Metabolic Adaptations to Seasons in Migratory Blackheaded Buntings Singh, Devraj Swarup, Vivek Le, Hiep Kumar, Vinod Front Physiol Physiology The molecular underpinnings of metabolic adaptation to seasons are poorly understood in long- distance migrants. We measured changes in physiology and performed de novo sequencing of RNA extracted from liver samples collected at 4-h intervals over a period of 24 h from a long-distance avian migrant, the blackheaded bunting (Emberiza melanocephala), during two states: photostimulated vernal migratory (M) state and photorefractory non-migratory (nM) state. The M state was differentiated from the nM state based on body fattening and weight gain, as well as on Zugunruhe, that is, nocturnal migratory restlessness in caged birds. We found that baseline blood glucose and triglyceride levels were significantly higher in the M state than the nM state; conversely, surface body temperature was higher in the nM state than the M state. In a total of 6 liver samples that were sequenced from each state, 11,246 genes were annotated, including 4448 genes that were cyclic over 24 h. We found 569 differentially expressed genes (DEGs) between the M and the nM state, and the M state showed 131 upregulated and 438 downregulated genes. These DEGs formed core gene hubs associated with specific biological processes in both the states. In addition, weighted gene coexpression network analysis revealed two discrete modules of coexpressed genes, with a significant difference in the expression pattern of metab olism-associated genes between M and nM states. These results demonstrate, for the first time, transcriptome-wide changes in the liver between two distinct physiological states and give molecular insights into seasonal metabolic adaptations in latitudinal migrants. Frontiers Media S.A. 2018-11-27 /pmc/articles/PMC6277527/ /pubmed/30538637 http://dx.doi.org/10.3389/fphys.2018.01568 Text en Copyright © 2018 Singh, Swarup, Le and Kumar. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Physiology
Singh, Devraj
Swarup, Vivek
Le, Hiep
Kumar, Vinod
Transcriptional Signatures in Liver Reveal Metabolic Adaptations to Seasons in Migratory Blackheaded Buntings
title Transcriptional Signatures in Liver Reveal Metabolic Adaptations to Seasons in Migratory Blackheaded Buntings
title_full Transcriptional Signatures in Liver Reveal Metabolic Adaptations to Seasons in Migratory Blackheaded Buntings
title_fullStr Transcriptional Signatures in Liver Reveal Metabolic Adaptations to Seasons in Migratory Blackheaded Buntings
title_full_unstemmed Transcriptional Signatures in Liver Reveal Metabolic Adaptations to Seasons in Migratory Blackheaded Buntings
title_short Transcriptional Signatures in Liver Reveal Metabolic Adaptations to Seasons in Migratory Blackheaded Buntings
title_sort transcriptional signatures in liver reveal metabolic adaptations to seasons in migratory blackheaded buntings
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6277527/
https://www.ncbi.nlm.nih.gov/pubmed/30538637
http://dx.doi.org/10.3389/fphys.2018.01568
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