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Cited by 572Ruminant Nutrition and Digestive PhysiologyGenetic and phenotypic traits in livestockGut microbiota and health

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Host genetics influence the rumen microbiota and heritable rumen microbial features associate with feed efficiency in cattle

Open access
Li, Fuyong, Li, Changxi, Chen, Yanhong, Liu, Junhong, Zhang, Chunyan, Irving, Barry, Fitzsimmons, Carolyn, Plastow, Graham, Guan, Le Luo·2019·Microbiome
DOI 10.1186/s40168-019-0699-1PMC PMC6567441
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Abstract

The symbiotic rumen microbiota is essential for the digestion of plant fibers and contributes to the variation of production and health traits in ruminants. However, to date, the heritability of rumen microbial features and host genetic components associated with the rumen microbiota, as well as whether such genetic components are animal performance relevant, are largely unknown. In the present study, we assessed rumen microbiota from a cohort of 709 beef cattle and showed that multiple factors including breed, sex, and diet drove the variation of rumen microbiota among animals. The diversity indices, the relative abundance of ~ 34% of microbial taxa (59 out of 174), and the copy number of total bacteria had a heritability estimate ( h 2 ) ≥ 0.15, suggesting that they are heritable elements affected by host additive genetics. These moderately heritable rumen microbial features were also found to be associated with host feed efficiency traits and rumen metabolic measures (volatile fatty acids). Moreover, 19 single nucleotide polymorphisms (SNPs) located on 12 bovine chromosomes were found to be associated with 14 (12 of them had h 2 ≥ 0.15) rumen microbial taxa, and five of these SNPs were known quantitative trait loci for feed efficiency in cattle. These findings suggest that some rumen microbial features are heritable and could be influenced by host genetics, highlighting a potential to manipulate and obtain a desirable and efficient rumen microbiota using genetic selection and breeding. It could be a useful strategy to further improve feed efficiency and optimize rumen fermentation through targeting both cattle and their rumen microbiota.

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Fig. 1 Composition of rumen microbiota in beef cattle. Bacterial community composition was summarized at genus, family, order, class, and phylum levels (a), and archaeal community composition was summarized at species, genus, family, order, and class levels (b). Heritable taxa (heritability estimate [h2] ≥ 0.15) were indicated using diamonds. These graphs were created using the program GraPhlAn [44]
Fig. 1 Composition of rumen microbiota in beef cattle. Bacterial community composition was summarized at genus, family, order, class, and phylum levels (a), and archaeal community composition was summarized at species, genus, family, order, and class levels (b). Heritable taxa (heritability estimate [h2] ≥ 0.15) were indicated using diamonds. These graphs were created using the program GraPhlAn [44]CC BY · PubMed Central
Fig. 2 Factors (breed, sex, diet, and age) drive segregation of rumen bacterial communities (a) and archaeal communities (b), as visualized using principal coordinate analysis (PCoA). To performed PCoA, the number of bacterial and archaeal sequences per sample were normalized to 2000 and 500, respectively, and the PCoA was conducted using Bray-Curtis dissimilarity matrices
Fig. 2 Factors (breed, sex, diet, and age) drive segregation of rumen bacterial communities (a) and archaeal communities (b), as visualized using principal coordinate analysis (PCoA). To performed PCoA, the number of bacterial and archaeal sequences per sample were normalized to 2000 and 500, respectively, and the PCoA was conducted using Bray-Curtis dissimilarity matricesCC BY · PubMed Central
Fig. 3 Effects of breed, sex, diet, and age on the richness (a, b), evenness (c, d), and abundance (e, f) of rumen bacteria and archaea. The 16S rRNA gene copy numbers per milliliter of rumen sample were log10-transformed before statistical analysis. Values within each factor that do not have a common superscript are significantly different (P < 0.05) according to the Kruskal-Wallis rank sum test. The correlations between age and other indices were calculated using the Spearman’s rank correlation (ρ = correlation coefficient)
Fig. 3 Effects of breed, sex, diet, and age on the richness (a, b), evenness (c, d), and abundance (e, f) of rumen bacteria and archaea. The 16S rRNA gene copy numbers per milliliter of rumen sample were log10-transformed before statistical analysis. Values within each factor that do not have a common superscript are significantly different (P < 0.05) according to the Kruskal-Wallis rank sum test. The correlations between age and other indices were calculated using the Spearman’s rank correlation (ρ = correlation coefficient)CC BY · PubMed Central
Fig. 4 Relationships between predominant rumen microbial groups. a Ratio of bacterial abundance to archaeal abundance, represented by 16S rRNA gene copy number obtained using qPCR. b Ratio of Firmicutes to Bacteroidetes. c Ratio of Methanobrevibacter gottschalkii to Methanobrevibacter ruminantium. The 16S rRNA gene copy number and relative abundance were log10-transformed, and the correlation analysis was performed using the Spearman’s rank correlation (ρ = correlation coefficient)
Fig. 4 Relationships between predominant rumen microbial groups. a Ratio of bacterial abundance to archaeal abundance, represented by 16S rRNA gene copy number obtained using qPCR. b Ratio of Firmicutes to Bacteroidetes. c Ratio of Methanobrevibacter gottschalkii to Methanobrevibacter ruminantium. The 16S rRNA gene copy number and relative abundance were log10-transformed, and the correlation analysis was performed using the Spearman’s rank correlation (ρ = correlation coefficient)CC BY · PubMed Central
Fig. 5 Co-occurrence network of rumen microbial taxa (a). Four major co-occurrence network modules were centered by unclassified Clostridiales (b), unclassified Succinivibrionaceae (c), unclassified Coriobacteriaceae (d), and unclassified Christensenellaceae (e). Only correlations with coefficient > 0.3 or < −0.3 and with P value < 0.001 were displayed. Heritable taxa were represented by red triangle/hexagon, while inheritable taxa were represented by yellow circle. Values in the parentheses are heritability estimates of heritable taxa. A connection with a blue/gray line means a positive/negative correlation. ‘U_’ before the taxonomic name represents unclassified. The first two PCs were calculated using PCA for each module
Fig. 5 Co-occurrence network of rumen microbial taxa (a). Four major co-occurrence network modules were centered by unclassified Clostridiales (b), unclassified Succinivibrionaceae (c), unclassified Coriobacteriaceae (d), and unclassified Christensenellaceae (e). Only correlations with coefficient > 0.3 or < −0.3 and with P value < 0.001 were displayed. Heritable taxa were represented by red triangle/hexagon, while inheritable taxa were represented by yellow circle. Values in the parentheses are heritability estimates of heritable taxa. A connection with a blue/gray line means a positive/negative correlation. ‘U_’ before the taxonomic name represents unclassified. The first two PCs were calculated using PCA for each moduleCC BY · PubMed Central
Fig. 6 Correlation patterns showing that heritable rumen microbial features (h2 ≥ 0.15) associated with feed efficiency (a) and rumen volatile fatty acids (b). Correlation analyses were performed using Spearman’s rank correlation, and correlations with P values lower than 0.05 were considered significant. Relative abundance of heritable bacterial genera and archaeal species, proportion of VFAs, 16S rRNA gene copy numbers, and ratios were log10-transformed, and possible outliers (out of mean ± 3SD) were removed before the analysis. Negative and positive correlations were displayed in red and blue, respectively
Fig. 6 Correlation patterns showing that heritable rumen microbial features (h2 ≥ 0.15) associated with feed efficiency (a) and rumen volatile fatty acids (b). Correlation analyses were performed using Spearman’s rank correlation, and correlations with P values lower than 0.05 were considered significant. Relative abundance of heritable bacterial genera and archaeal species, proportion of VFAs, 16S rRNA gene copy numbers, and ratios were log10-transformed, and possible outliers (out of mean ± 3SD) were removed before the analysis. Negative and positive correlations were displayed in red and blue, respectivelyCC BY · PubMed Central
Fig. 7 SNPs associated with rumen microbial taxa at phylum (a), family (b), and genus (c) levels. Only associations with false discovery rates (FDR) < 0.1 (significant) and 0.1 < FDR < 0.2 (suggestively significant) are displayed. In each plot, values that do not have a common superscript are significantly different (P < 0.05) based on ANOVA. The x-axis represents genotype of a SNP, and the y-axis indicated the log10-transformed relative abundance after adjusting breed, sex, diet, and age factors
Fig. 7 SNPs associated with rumen microbial taxa at phylum (a), family (b), and genus (c) levels. Only associations with false discovery rates (FDR) < 0.1 (significant) and 0.1 < FDR < 0.2 (suggestively significant) are displayed. In each plot, values that do not have a common superscript are significantly different (P < 0.05) based on ANOVA. The x-axis represents genotype of a SNP, and the y-axis indicated the log10-transformed relative abundance after adjusting breed, sex, diet, and age factorsCC BY · PubMed Central

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Research works printed but not linked: 3

  1. Olfert ED, Cross BM, McWilliams AA. Guide to the care and use of experimental steers. Ottawa: Canadian Council on Animal Care; 1993.
  2. Gilmour AR, Gogel BJ, Cullis BR, Welham SJ, Thompson R, Butler D, Cherry M, Collins D, Dutkowski G, Harding SA. ASReml user guide. Release 4.1 structural specification. Hemel Hempstead: VSN International Ltd; 2014.
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Metadata

Authors
Li, F., Li, C., Chen, Y., Liu, J., Zhang, C., Irving, B., Fitzsimmons, C., Plastow, G., & Guan, L. L.
Affiliations
  • University of Alberta (CA)
  • Agriculture and Agri-Food Canada (CA)
Corresponding author
Guan, Le Luo
ORCID
Venue
Microbiome
Publisher
Springer Science and Business Media LLC
Published
2019-06-13
Volume
7
Issue
1
Pages
92-92
ISSN
2049-2618 (ISSN-L)
DOI
10.1186/s40168-019-0699-1
PMC
PMC6567441
OpenAlex
W2953135971
Cited by
530
References
71
Citations by year
2026: 44 · 2025: 77 · 2024: 94 · 2023: 65 · 2022: 62 · 2021: 120 · 2020: 58 · 2019: 10
FWCI
93.43
Type
journal article
Language
en
Open access
Licence
Locations
  • Microbiome (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Federal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Alberta Livestock and Meat Agency (2013R029R)
  • Natural Sciences and Engineering Research Council of Canada (Discovery)
  • Alberta Innovates - Technology Futures (Graduate student scholarship)
  • Alberta Agriculture and Forestry (2018F095R)
Topics
  • Life Sciences › Agricultural and Biological Sciences › Animal Science and Zoology › Ruminant Nutrition and Digestive Physiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
Keywords
rumen microbiota, host genetics, heritability, feed efficiency, beef cattle, single nucleotide polymorphisms, quantitative trait loci, volatile fatty acids, rumen fermentation, genetic selection
MeSH terms
Host Microbial Interactions, Animals, Animal Feed, Animal Nutritional Physiological Phenomena, Archaea, Bacteria, Breeding, Cattle, Female, Fermentation, Genotype, Male, Phylogeny, Rumen, Microbiota

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