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Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host

BACKGROUND: Producing animal protein while reducing the animal’s impact on the environment, e.g., through improved feed efficiency and lowered methane emissions, has gained interest in recent years. Genetic selection is one possible path to reduce the environmental impact of livestock production, bu...

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Autores principales: Hess, Melanie K., Hodgkinson, Hannah E., Hess, Andrew S., Zetouni, Larissa, Budel, Juliana C. C., Henry, Hannah, Donaldson, Alistair, Bilton, Timothy P., van Stijn, Tracey C., Kirk, Michelle R., Dodds, Ken G., Brauning, Rudiger, McCulloch, Alan F., Hickey, Sharon M., Johnson, Patricia L., Jonker, Arjan, Morton, Nickolas, Hendy, Shaun, Oddy, V. Hutton, Janssen, Peter H., McEwan, John C., Rowe, Suzanne J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10506323/
https://www.ncbi.nlm.nih.gov/pubmed/37723422
http://dx.doi.org/10.1186/s12864-023-09660-3
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author Hess, Melanie K.
Hodgkinson, Hannah E.
Hess, Andrew S.
Zetouni, Larissa
Budel, Juliana C. C.
Henry, Hannah
Donaldson, Alistair
Bilton, Timothy P.
van Stijn, Tracey C.
Kirk, Michelle R.
Dodds, Ken G.
Brauning, Rudiger
McCulloch, Alan F.
Hickey, Sharon M.
Johnson, Patricia L.
Jonker, Arjan
Morton, Nickolas
Hendy, Shaun
Oddy, V. Hutton
Janssen, Peter H.
McEwan, John C.
Rowe, Suzanne J.
author_facet Hess, Melanie K.
Hodgkinson, Hannah E.
Hess, Andrew S.
Zetouni, Larissa
Budel, Juliana C. C.
Henry, Hannah
Donaldson, Alistair
Bilton, Timothy P.
van Stijn, Tracey C.
Kirk, Michelle R.
Dodds, Ken G.
Brauning, Rudiger
McCulloch, Alan F.
Hickey, Sharon M.
Johnson, Patricia L.
Jonker, Arjan
Morton, Nickolas
Hendy, Shaun
Oddy, V. Hutton
Janssen, Peter H.
McEwan, John C.
Rowe, Suzanne J.
author_sort Hess, Melanie K.
collection PubMed
description BACKGROUND: Producing animal protein while reducing the animal’s impact on the environment, e.g., through improved feed efficiency and lowered methane emissions, has gained interest in recent years. Genetic selection is one possible path to reduce the environmental impact of livestock production, but these traits are difficult and expensive to measure on many animals. The rumen microbiome may serve as a proxy for these traits due to its role in feed digestion. Restriction enzyme-reduced representation sequencing (RE-RRS) is a high-throughput and cost-effective approach to rumen metagenome profiling, but the systematic (e.g., sequencing) and biological factors influencing the resulting reference based (RB) and reference free (RF) profiles need to be explored before widespread industry adoption is possible. RESULTS: Metagenome profiles were generated by RE-RRS of 4,479 rumen samples collected from 1,708 sheep, and assigned to eight groups based on diet, age, time off feed, and country (New Zealand or Australia) at the time of sample collection. Systematic effects were found to have minimal influence on metagenome profiles. Diet was a major driver of differences between samples, followed by time off feed, then age of the sheep. The RF approach resulted in more reads being assigned per sample and afforded greater resolution when distinguishing between groups than the RB approach. Normalizing relative abundances within the sampling Cohort abolished structures related to age, diet, and time off feed, allowing a clear signal based on methane emissions to be elucidated. Genus-level abundances of rumen microbes showed low-to-moderate heritability and repeatability and were consistent between diets. CONCLUSIONS: Variation in rumen metagenomic profiles was influenced by diet, age, time off feed and genetics. Not accounting for environmental factors may limit the ability to associate the profile with traits of interest. However, these differences can be accounted for by adjusting for Cohort effects, revealing robust biological signals. The abundances of some genera were consistently heritable and repeatable across different environments, suggesting that metagenomic profiles could be used to predict an individual’s future performance, or performance of its offspring, in a range of environments. These results highlight the potential of using rumen metagenomic profiles for selection purposes in a practical, agricultural setting. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-023-09660-3.
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spelling pubmed-105063232023-09-19 Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host Hess, Melanie K. Hodgkinson, Hannah E. Hess, Andrew S. Zetouni, Larissa Budel, Juliana C. C. Henry, Hannah Donaldson, Alistair Bilton, Timothy P. van Stijn, Tracey C. Kirk, Michelle R. Dodds, Ken G. Brauning, Rudiger McCulloch, Alan F. Hickey, Sharon M. Johnson, Patricia L. Jonker, Arjan Morton, Nickolas Hendy, Shaun Oddy, V. Hutton Janssen, Peter H. McEwan, John C. Rowe, Suzanne J. BMC Genomics Research BACKGROUND: Producing animal protein while reducing the animal’s impact on the environment, e.g., through improved feed efficiency and lowered methane emissions, has gained interest in recent years. Genetic selection is one possible path to reduce the environmental impact of livestock production, but these traits are difficult and expensive to measure on many animals. The rumen microbiome may serve as a proxy for these traits due to its role in feed digestion. Restriction enzyme-reduced representation sequencing (RE-RRS) is a high-throughput and cost-effective approach to rumen metagenome profiling, but the systematic (e.g., sequencing) and biological factors influencing the resulting reference based (RB) and reference free (RF) profiles need to be explored before widespread industry adoption is possible. RESULTS: Metagenome profiles were generated by RE-RRS of 4,479 rumen samples collected from 1,708 sheep, and assigned to eight groups based on diet, age, time off feed, and country (New Zealand or Australia) at the time of sample collection. Systematic effects were found to have minimal influence on metagenome profiles. Diet was a major driver of differences between samples, followed by time off feed, then age of the sheep. The RF approach resulted in more reads being assigned per sample and afforded greater resolution when distinguishing between groups than the RB approach. Normalizing relative abundances within the sampling Cohort abolished structures related to age, diet, and time off feed, allowing a clear signal based on methane emissions to be elucidated. Genus-level abundances of rumen microbes showed low-to-moderate heritability and repeatability and were consistent between diets. CONCLUSIONS: Variation in rumen metagenomic profiles was influenced by diet, age, time off feed and genetics. Not accounting for environmental factors may limit the ability to associate the profile with traits of interest. However, these differences can be accounted for by adjusting for Cohort effects, revealing robust biological signals. The abundances of some genera were consistently heritable and repeatable across different environments, suggesting that metagenomic profiles could be used to predict an individual’s future performance, or performance of its offspring, in a range of environments. These results highlight the potential of using rumen metagenomic profiles for selection purposes in a practical, agricultural setting. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-023-09660-3. BioMed Central 2023-09-18 /pmc/articles/PMC10506323/ /pubmed/37723422 http://dx.doi.org/10.1186/s12864-023-09660-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Hess, Melanie K.
Hodgkinson, Hannah E.
Hess, Andrew S.
Zetouni, Larissa
Budel, Juliana C. C.
Henry, Hannah
Donaldson, Alistair
Bilton, Timothy P.
van Stijn, Tracey C.
Kirk, Michelle R.
Dodds, Ken G.
Brauning, Rudiger
McCulloch, Alan F.
Hickey, Sharon M.
Johnson, Patricia L.
Jonker, Arjan
Morton, Nickolas
Hendy, Shaun
Oddy, V. Hutton
Janssen, Peter H.
McEwan, John C.
Rowe, Suzanne J.
Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host
title Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host
title_full Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host
title_fullStr Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host
title_full_unstemmed Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host
title_short Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host
title_sort large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10506323/
https://www.ncbi.nlm.nih.gov/pubmed/37723422
http://dx.doi.org/10.1186/s12864-023-09660-3
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