Understanding the functional and genomic architecture of the rumen microbiome affecting performance traits in bovines
Lead Research Organisation:
University of Edinburgh
Department Name: The Roslin Institute
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Technical Summary
Rumen microbial fermentation confers a unique ability to efficiently convert human inedible feed into foods with high nutritional value (e.g. meat, milk). However, there is a disadvantage from the environmental and energetic efficiency point of view, in that microbial fermentation also results in methane production. There is a large variation between animals in feed conversion efficiency and methane emissions, so that the substantial lack of knowledge about the functional and genomic architecture of the rumen microbiome has to be closed to efficiently breed and feed those animals. We will use deep metagenomic sequencing to gain insight into the functional and genomic architecture of the rumen microbiome, identifying the key microbial taxa and genes. Our approach will use highly-phenotyped beef cattle (n=288) to discover and prioritise putative links between the microbiome and phenotypic performance. Host genetic and nutritional effects on the microbiome will be estimated utilising the unique structure of experimental data, including different sire progeny groups and diets. Preliminary analysis suggests a link between the microbiome, phenotypic performance, animal genetics and nutrition, but was not able to provide detailed information about the functional and genomic architecture of the ruminal microbiome affecting performance traits and whether and how these interact with the host animal and nutrition. This study will provide substantial insight into the structure and function of the microbiome and identity novel microbial genes. Based on the abundance of the microbial community and genes, the research will provide novel functional and genetic networks to explain the link between the microbiome, phenotypic performance and host genetics or nutrition (e.g. the cross-talk between host and microbiome). Comparative functional genomics will broaden the potential applications of the research.
Planned Impact
The beneficiaries of this research will include academic scientists, farmers, the livestock breeding and feed industries, national governments, climate scientists, environmentalists and the general public. The FAO predicts that by 2050, the human population will grow to over 9 billion people, and in the same time frame, global meat consumption is projected to increase by 73%. In order to address food security, as well as economic and environmental impacts of food production, sustainable intensification has been suggested by Godfray et al. (2010) - with genetic improvement of feed conversion efficiency of highest importance in farm animals. Rumen microbial fermentation confers a unique ability to efficiently convert human inedible feed (e.g. high-fibre forage) into food products, such as meat and milk, of high nutritional value. Performance traits, such as feed efficiency, vary substantially between cattle so that genetic improvement and nutritional intervention could have a substantial effect on the efficiency of using limited feed resources, as well as a major financial impact since feed is the largest variable cost in production. Furthermore, rumen fermentation contributes to greenhouse gas (GHG) emissions, in particular methane. Any marginal reduction in GHG emissions, achieved through genetic improvement, has the potential to contribute significantly to UK Climate Change Act commitments, including the need for an 11% reduction in agricultural emissions by 2020. Using animal breeding and nutritional interventions to alter the rumen microbiome is expected to improve feed efficiency, growth, body composition, meat quality or animal health and thus contribute to address the overall economic and environmental challenges. The academic partners (SRUC and Roslin Institute) have excellent links to the cattle breeding and feed industries, farmers and the entire food chain. They will ensure that any immediate impacts can be passed on, once IP has been suitably protected.
Overall, the research will deliver substantial contributions to fundamental understanding of the functional and genomic architecture of the rumen microbiome in bovines, whilst also offering insights for other ruminant species or monogastric species including humans. In particular, it will provide unprecedented new knowledge about the genomic and functional architecture of the microbiome and its impact on performance traits and methane emissions that will set the direction for animal breeding programmes and novel animal feeding strategies.
Comparative functional genomics will be used to uncover differences and similarities in functional and genetic architecture between species, providing unprecedented knowledge about the microbiome and host-microbiome interactions across species. In particular, we foresee longer-term benefits for research on host genetic effects on the rumen microbiota and its association with body composition (e.g. for human personalised medicine approaches to reduce obesity).
We will realise academic impact by publication of papers in high-impact peer-reviewed journals (open-access where possible), by presentations at scientific meetings and through deposition of datasets in public databases. We will also publish articles in trade journals to ensure that our findings are communicated to our stakeholders. SRUC and RI will present the project at public science events, such as the Roslin Open Doors Day, ensuring the general public are aware of our research and its importance. We will keep policy makers aware of the research findings and our appraisal of potential to help meet climate change targets in the medium- and longer-term. Significant findings will be communicated to the industry and general public through press releases and information on a specific project website hosted by SRUC.
Overall, the research will deliver substantial contributions to fundamental understanding of the functional and genomic architecture of the rumen microbiome in bovines, whilst also offering insights for other ruminant species or monogastric species including humans. In particular, it will provide unprecedented new knowledge about the genomic and functional architecture of the microbiome and its impact on performance traits and methane emissions that will set the direction for animal breeding programmes and novel animal feeding strategies.
Comparative functional genomics will be used to uncover differences and similarities in functional and genetic architecture between species, providing unprecedented knowledge about the microbiome and host-microbiome interactions across species. In particular, we foresee longer-term benefits for research on host genetic effects on the rumen microbiota and its association with body composition (e.g. for human personalised medicine approaches to reduce obesity).
We will realise academic impact by publication of papers in high-impact peer-reviewed journals (open-access where possible), by presentations at scientific meetings and through deposition of datasets in public databases. We will also publish articles in trade journals to ensure that our findings are communicated to our stakeholders. SRUC and RI will present the project at public science events, such as the Roslin Open Doors Day, ensuring the general public are aware of our research and its importance. We will keep policy makers aware of the research findings and our appraisal of potential to help meet climate change targets in the medium- and longer-term. Significant findings will be communicated to the industry and general public through press releases and information on a specific project website hosted by SRUC.
People |
ORCID iD |
Michael Watson (Principal Investigator) |
Publications
Stewart RD
(2019)
MAGpy: a reproducible pipeline for the downstream analysis of metagenome-assembled genomes (MAGs).
in Bioinformatics (Oxford, England)
Stewart RD
(2018)
Assembly of 913 microbial genomes from metagenomic sequencing of the cow rumen.
in Nature communications
Wilkinson T
(2020)
1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding
in Genome Biology
Description | • From the rumen of 43 Scottish cattle spanning 4 different breeds and multiple diets, we have assembled 913 novel microbial genomes, representing novel strains, species and genera of bacteria and archaea that live in the rumen and contribute to the breakdown of complex carbohydrates. • Identified that diet has a large effect on the prevalence of AMR genes in cattle. Specifically, that the diversity and abundance of 204 AMR genes are significantly higher in abundance in concentrate-fed animals • From 50 cattle and the associated rumen metagenome, we have defined a set of robust microbiome markers for methane emissions. 37 genes from the rumen microbiome, as part of our model including breed and diet, can explain 62% of the variance in methane emissions • We have published MAGpy, a reproducible pipeline for the analysis of metagenome-assembled genomes (MAGs). This is an open source implementation that is available for anyone in industry and academia to use • We have comprehensively reviewed the complex literature around biases in microbiome studies and have published a "consensus best practice" review which provides advice at every stage of the experimental process • From the rumen of 282 Scottish cattle spanning 4 different breeds and multiple diets, we have assembled 4941 novel microbial genomes, representing novel strains, species and genera of bacteria and archaea that live in the rumen and contribute to the breakdown of complex carbohydrates. • We have published PULpy, a reproducible pipeline for the identification of polysaccharide utilisation loci in genomes and metagenomes. This is an open source implementation that is available for anyone in industry and academia to use |
Exploitation Route | • We believe the 913 genomes we have published from the rumen microbiome will form the basis of hundreds of future studies into the structure and function of the rumen microbiome and how it contributes to beef and dairy production, and animal health and welfare. • Our robust methane markers may be used as an intermediary phenotype in selective breeding for lower methane cattle • Our AMR work may be used to adjust diets in cattle to help reduce the incidence of anti-microbial resistance genes in the human food chain • Our software could be used by scientists throughout the biological sciences who wish to discover and annotate novel microbial genomes • We believe the 4941 genomes we have published from the rumen microbiome will form the basis of hundreds of future studies into the structure and function of the rumen microbiome and how it contributes to beef and dairy production, and animal health and welfare. |
Sectors | Agriculture Food and Drink Manufacturing including Industrial Biotechology |
Description | We use the latest tools to assemble the genomes of important pathogens and commensal organisms; and we use metagenomics to study the structure and function of the rumen microbiome. These studies have resulted in the discovery of thousands of novel proteins which are of interest to our commercial partner Ingenza, a biofuels and biotechnology company. More widely, by making large datasets such as these available and demonstrating their novelty, we are pushing back the boundaries of human knowledge and enabling others to make similar discoveries. We have associated components of the rumen microbiome with methane emissions and feed-conversion-ratio, and demonstrated the microbiome is under host-genetic control. This will enable breeders and farmers to breed for both production (FCR) and environmental (lower methane emissions) traits. Our work in rumen metagenomics has led to us working with a local farmer to investigate performance issues in his dairy herd, which he believes to be linked to problems in the rumen. |
Sector | Agriculture, Food and Drink,Environment |
Impact Types | Economic |
Description | GCRF Data and Resources round 2 |
Amount | £220,000 (GBP) |
Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
Sector | Public |
Country | United Kingdom |
Start | 09/2017 |
End | 07/2018 |
Description | Microbiome and metagenomic study of the rumen microbial population and their microbial enzyme genes |
Amount | £90,000 (GBP) |
Organisation | Government of Scotland |
Sector | Public |
Country | United Kingdom |
Start | 08/2016 |
End | 09/2019 |
Title | Additional file 10 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 10: Table S7. Matrix of KO counts per Sample. KO counts per MAG (Table S3) were multiplied by the abundance of each MAG per sample (Table S5) to generate a KO per sample matrix representing the functional potential of the microbiome associated with each sample to be used as input for phyloseq and DESeq2 analyses. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_10_of_1200_high-quality_metagen... |
Title | Additional file 10 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 10: Table S7. Matrix of KO counts per Sample. KO counts per MAG (Table S3) were multiplied by the abundance of each MAG per sample (Table S5) to generate a KO per sample matrix representing the functional potential of the microbiome associated with each sample to be used as input for phyloseq and DESeq2 analyses. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_10_of_1200_high-quality_metagen... |
Title | Additional file 11 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 11: Table S8. Overall significantly differentially abundant KOs. Significantly differentially abundant KOs associated with metabolically important pathways in the rumen when comparing 40% (40vs80) and 60% (60vs80) MER diet treatments versus the 80% treatment. Differential abundance was calculated using the likelihood ratio test (LRT) in DESeq2 and was considered statistically significant at FDR (adjusted p-value) |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_11_of_1200_high-quality_metagen... |
Title | Additional file 11 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 11: Table S8. Overall significantly differentially abundant KOs. Significantly differentially abundant KOs associated with metabolically important pathways in the rumen when comparing 40% (40vs80) and 60% (60vs80) MER diet treatments versus the 80% treatment. Differential abundance was calculated using the likelihood ratio test (LRT) in DESeq2 and was considered statistically significant at FDR (adjusted p-value) |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_11_of_1200_high-quality_metagen... |
Title | Additional file 12 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 12: Table S9. Contribution of differentially abundant MAGs to metabolic pathways. Absolute counts of KOs associated with significantly differentially abundant MAGs comparing 40% and 60% MER diet treatments versus the 80% treatment. Counts for each taxonomic group in each diet treatment are aggregated into metabolically important pathways within the rumen (KO counts). Using the absolute counts, the log 2 fold change (LFC) of the counts in the 40% and 60% diet treatments has been calculated to give proportional change in contribution of each taxonomic group to each metabolic pathway when compared to the 80% diet treatment (LFC vs 80%). |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_12_of_1200_high-quality_metagen... |
Title | Additional file 12 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 12: Table S9. Contribution of differentially abundant MAGs to metabolic pathways. Absolute counts of KOs associated with significantly differentially abundant MAGs comparing 40% and 60% MER diet treatments versus the 80% treatment. Counts for each taxonomic group in each diet treatment are aggregated into metabolically important pathways within the rumen (KO counts). Using the absolute counts, the log 2 fold change (LFC) of the counts in the 40% and 60% diet treatments has been calculated to give proportional change in contribution of each taxonomic group to each metabolic pathway when compared to the 80% diet treatment (LFC vs 80%). |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_12_of_1200_high-quality_metagen... |
Title | Additional file 13 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 13: Table S10. Metadata Table for Metagenome Samples. Metadata table containing Sample ID, Period, Animal and Diet treatment information for each sample adapted from Table 7 to be used as input for phyloseq and DESeq2 analyses. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_13_of_1200_high-quality_metagen... |
Title | Additional file 13 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 13: Table S10. Metadata Table for Metagenome Samples. Metadata table containing Sample ID, Period, Animal and Diet treatment information for each sample adapted from Table 7 to be used as input for phyloseq and DESeq2 analyses. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_13_of_1200_high-quality_metagen... |
Title | Additional file 14 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 14: Table S11. Taxonomy Table of MAGs. Complete taxonomy table adapted from Table S1 to be used as input for phyloseq and DESeq2 analyses. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_14_of_1200_high-quality_metagen... |
Title | Additional file 14 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 14: Table S11. Taxonomy Table of MAGs. Complete taxonomy table adapted from Table S1 to be used as input for phyloseq and DESeq2 analyses. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_14_of_1200_high-quality_metagen... |
Title | Additional file 15 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 15: R Script for DESeq2 and phyloseq analyses. R script to perform MAG and KO level using the likelihood ratio test (LRT) in DESeq2. Analyses identify significantly differentially abundant MAGs and KOs when the more restrictive 40% and 60% MER diet treatments are contrasted against the 80% MER diet treatment. Statistical analysis of the ruminal community structure is performed using the Adonis2 PERMANOVA analysis. Principal coordinate analysis (PCoA) and canonical analysis of principal coordinates (CAP) ordination plots are generated using phyloseq and ggplot2. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_15_of_1200_high-quality_metagen... |
Title | Additional file 15 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 15: R Script for DESeq2 and phyloseq analyses. R script to perform MAG and KO level using the likelihood ratio test (LRT) in DESeq2. Analyses identify significantly differentially abundant MAGs and KOs when the more restrictive 40% and 60% MER diet treatments are contrasted against the 80% MER diet treatment. Statistical analysis of the ruminal community structure is performed using the Adonis2 PERMANOVA analysis. Principal coordinate analysis (PCoA) and canonical analysis of principal coordinates (CAP) ordination plots are generated using phyloseq and ggplot2. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_15_of_1200_high-quality_metagen... |
Title | Additional file 2 of Microbiome-driven breeding strategy potentially improves beef fatty acid profile benefiting human health and reduces methane emissions |
Description | Additional file 2: Table S1. Microbial gene abundances in rumen microbiome (analyzed after an additive log-ratio transformation) with significant host genomic effects referred to as host-specific functional core microbiome (HGFC). Table S2. Occupancy rates and heritabilities of micobial gene abundances (analyzed after an additive log-ratio transformation) involved in lipolysis and biohydrogenation processes in rumen found in our population. Table S3. Host genomic correlations between heritable additive log-ratio transformed microbial gene abundances and N3 and CLA Indices in beef with propbability of being positive of negative >95% (marked in bold). Table S4. The 963 different microbial genera in rumen carrying the 372 heritable additive log-ratio transformed microbial gene abundances both positively or negatively genomically correlated with N3 and CLA inidces in beef. Table S5. Composition of clusters from a co-abundance network analysis1 among phenotypic values (after correction for trial and diet) of the 110 additive log-ratio transformed microbial gene abundances genomically correlated with N3 and CLA indices with the same sign. Table S6. Composition of clusters from a co-abundance network analysis1 among estimated genomic breeding values of the 110 additive log-ratio transformed microbial gene abundances genomically correlated with N3 and CLA indices with the same sign. Table S7. Micorbial genes selected for breeding purpouses based on mean relative abundance (RA)>0.01%, significant genomic effects, host genomic correlation with N3 and CLA indices positively or negatively (P0 > 0.95) and significantly explaining part of the genomic variance inherent in the 110 additive-log transformed microbial genes. Table S8. Host genomic correlations between additive log-ratio transformed micorbial genes selected for breeding purpouses and methane emissions (g/kg dry matter intake). Table S9. Experimental design displaying the number of animals within each breed, diet and experiment. Table S10. Raw fatty acid composition (% of total fatty acids) and methane emissions (g/kg of dry matter intake) in beef cattle measured in 245 and 285 animals, respectively. Table S11. Correspondance between COG abreviations and full names. |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_2_of_Microbiome-driven_breeding... |
Title | Additional file 2 of Microbiome-driven breeding strategy potentially improves beef fatty acid profile benefiting human health and reduces methane emissions |
Description | Additional file 2: Table S1. Microbial gene abundances in rumen microbiome (analyzed after an additive log-ratio transformation) with significant host genomic effects referred to as host-specific functional core microbiome (HGFC). Table S2. Occupancy rates and heritabilities of micobial gene abundances (analyzed after an additive log-ratio transformation) involved in lipolysis and biohydrogenation processes in rumen found in our population. Table S3. Host genomic correlations between heritable additive log-ratio transformed microbial gene abundances and N3 and CLA Indices in beef with propbability of being positive of negative >95% (marked in bold). Table S4. The 963 different microbial genera in rumen carrying the 372 heritable additive log-ratio transformed microbial gene abundances both positively or negatively genomically correlated with N3 and CLA inidces in beef. Table S5. Composition of clusters from a co-abundance network analysis1 among phenotypic values (after correction for trial and diet) of the 110 additive log-ratio transformed microbial gene abundances genomically correlated with N3 and CLA indices with the same sign. Table S6. Composition of clusters from a co-abundance network analysis1 among estimated genomic breeding values of the 110 additive log-ratio transformed microbial gene abundances genomically correlated with N3 and CLA indices with the same sign. Table S7. Micorbial genes selected for breeding purpouses based on mean relative abundance (RA)>0.01%, significant genomic effects, host genomic correlation with N3 and CLA indices positively or negatively (P0 > 0.95) and significantly explaining part of the genomic variance inherent in the 110 additive-log transformed microbial genes. Table S8. Host genomic correlations between additive log-ratio transformed micorbial genes selected for breeding purpouses and methane emissions (g/kg dry matter intake). Table S9. Experimental design displaying the number of animals within each breed, diet and experiment. Table S10. Raw fatty acid composition (% of total fatty acids) and methane emissions (g/kg of dry matter intake) in beef cattle measured in 245 and 285 animals, respectively. Table S11. Correspondance between COG abreviations and full names. |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_2_of_Microbiome-driven_breeding... |
Title | Additional file 4 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 4: Table S1. Taxonomic classifications of 850 winning African MAGs. Taxonomic classifications reported for each of the three following methods: CheckM, DIAMOND and PhyloPhlAn. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_4_of_1200_high-quality_metageno... |
Title | Additional file 4 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 4: Table S1. Taxonomic classifications of 850 winning African MAGs. Taxonomic classifications reported for each of the three following methods: CheckM, DIAMOND and PhyloPhlAn. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_4_of_1200_high-quality_metageno... |
Title | Additional file 5 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 5: Table S2. Minimum Jaccard distances. Minimum Jaccard distance between all genomes within a single dataset from either African MAGs (MAG), Scottish RUGs (RUG1), RUG 2.0 (RUG2) or Hungate collection (HUN); between two datasets (MAGvRUG1, MAGvRUG2, MAGvHUN, RUG1vRUG2, RUG1vHUN, RUG1vMAG, HUNvRUG1, HUNvRUG2, HUNvMAG, RUG2vRUG1, RUG2vHUN, RUG2vMAG); between a given dataset and all other datasets combined (MAGvAll, RUGvAll, RUG2vAll, HUNvAll). |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_5_of_1200_high-quality_metageno... |
Title | Additional file 5 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 5: Table S2. Minimum Jaccard distances. Minimum Jaccard distance between all genomes within a single dataset from either African MAGs (MAG), Scottish RUGs (RUG1), RUG 2.0 (RUG2) or Hungate collection (HUN); between two datasets (MAGvRUG1, MAGvRUG2, MAGvHUN, RUG1vRUG2, RUG1vHUN, RUG1vMAG, HUNvRUG1, HUNvRUG2, HUNvMAG, RUG2vRUG1, RUG2vHUN, RUG2vMAG); between a given dataset and all other datasets combined (MAGvAll, RUGvAll, RUG2vAll, HUNvAll). |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_5_of_1200_high-quality_metageno... |
Title | Additional file 6 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 6: Table S3. KEGG Functional Annotations of MAGs. Counts of proteins in each MAG with a hit in the KEGG database for a KEGG ortholog (KO_Counts). |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_6_of_1200_high-quality_metageno... |
Title | Additional file 6 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 6: Table S3. KEGG Functional Annotations of MAGs. Counts of proteins in each MAG with a hit in the KEGG database for a KEGG ortholog (KO_Counts). |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_6_of_1200_high-quality_metageno... |
Title | Additional file 7 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 7: Table S4. CAZyme Functional Annotations of MAGs. Counts of proteins in each MAG with a hit in the dbCAN CAZyme database (CAZy_Counts). |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_7_of_1200_high-quality_metageno... |
Title | Additional file 7 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 7: Table S4. CAZyme Functional Annotations of MAGs. Counts of proteins in each MAG with a hit in the dbCAN CAZyme database (CAZy_Counts). |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_7_of_1200_high-quality_metageno... |
Title | Additional file 8 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 8: Table S5. Matrix of read counts per MAG. Read counts per MAG were calculated based on reads mapped to all contigs of a MAG, corrected for contig length and GC content bias. Used as input for phyloseq and DESeq2 analyses. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_8_of_1200_high-quality_metageno... |
Title | Additional file 8 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 8: Table S5. Matrix of read counts per MAG. Read counts per MAG were calculated based on reads mapped to all contigs of a MAG, corrected for contig length and GC content bias. Used as input for phyloseq and DESeq2 analyses. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_8_of_1200_high-quality_metageno... |
Title | Additional file 9 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 9: Table S6. Significantly differentially abundant MAGs. Significantly differentially abundant MAGs comparing 40% (40vs80) and 60% (60vs80) MER diet treatments versus the 80% treatment. Differential abundance was calculated using the likelihood ratio test (LRT) in DESeq2 and was considered statistically significant at FDR (adjusted p-value) |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_9_of_1200_high-quality_metageno... |
Title | Additional file 9 of 1200 high-quality metagenome-assembled genomes from the rumen of African cattle and their relevance in the context of sub-optimal feeding |
Description | Additional file 9: Table S6. Significantly differentially abundant MAGs. Significantly differentially abundant MAGs comparing 40% (40vs80) and 60% (60vs80) MER diet treatments versus the 80% treatment. Differential abundance was calculated using the likelihood ratio test (LRT) in DESeq2 and was considered statistically significant at FDR (adjusted p-value) |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_9_of_1200_high-quality_metageno... |
Title | Assembly of 913 microbial genomes from metagenomic sequencing of the cow rumen |
Description | This dataset represents 913 draft bacterial and archaeal genomes assembled from over 800 gigabases of rumen metagenomic sequence data derived from 43 Scottish cattle, using both metagenomic binning and Hi-C-based proximity-guided assembly. Most of these genomes represent previously unsequenced strains and species. The draft genomes contain over 1.2 million predicted protein sequences, and 69,000 proteins predicted to be involved in carbohydrate metabolism. ## Relation to earlier versions ## This data is referenced by Watson et al. (In Submission). A previous paper, in bioRXiv, referenced the earlier dataset "Assembly of hundreds of microbial genomes from the cow rumen reveals novel microbial species encoding enzymes with roles in carbohydrate metabolism" https://datashare.is.ed.ac.uk/handle/10283/2772. This in turn was superseded by the more recent version Hi-C genomes from "Assembly of hundreds of microbial genomes from the cow rumen reveals novel microbial species encoding enzymes with roles in carbohydrate metabolism" https://datashare.is.ed.ac.uk/handle/10283/2911. The paper underwent many rounds of review, the first-round revised paper referenced the second (Hi-C) dataset and the final, accepted version will reference the DOI of this dataset. The datasets changed in nature and in name during this process. |
Type Of Material | Database/Collection of data |
Year Produced | 2017 |
Provided To Others? | Yes |
Impact | The dataset is expected to underpin global rumen microbiome research in the next 5-10 years |
URL | https://datashare.is.ed.ac.uk/handle/10283/3009 |
Title | Assembly of hundreds of microbial genomes from the cow rumen reveals novel microbial species encoding enzymes with roles in carbohydrate metabolism |
Description | The cow rumen is a specialised organ adapted for the efficient breakdown of plant material into energy and nutrients, and it is the rumen microbiome that encodes the enzymes responsible. Many of these enzymes are of huge industrial interest. Despite this, rumen microbes are under-represented in the public databases. Here we present 220 high quality bacterial and archaeal genomes assembled directly from 768 gigabases of rumen metagenomic sequence data. Comparative analysis with current publicly available genomes reveals that the majority of these represent previously unsequenced strains and species of bacteria and archaea. The genomes contain over 13,000 proteins predicted to be involved in carbohydrate metabolism, over 90% of which do not have a good match in the public databases. Inclusion of the 220 genomes presented here improves metagenomic read classification by 2-3-fold, both in our data and in other publicly available rumen datasets. This release improves the coverage of rumen microbes in the public databases, and represents a hugely valuable resource for biomass-degrading enzyme discovery and studies of the rumen microbiome. |
Type Of Material | Database/Collection of data |
Year Produced | 2017 |
Provided To Others? | Yes |
Impact | This dataset is expected to underpin research in rumen microbiomes over the next 5-10 years |
URL | https://datashare.is.ed.ac.uk/handle/10283/2772 |
Title | Hi-C genomes from "Assembly of hundreds of microbial genomes from the cow rumen reveals novel microbial species encoding enzymes with roles in carbohydrate metabolism" |
Description | The cow rumen is a specialised organ adapted for the efficient breakdown of plant material into energy and nutrients, and it is largely the rumen microbiome that encodes the enzymes responsible. Many of these enzymes are of significant industrial interest. Despite this, rumen microbes are under-represented in public databases. Here we present 283 draft bacterial and archaeal genomes assembled directly from over 800 gigabases of rumen metagenomic sequence data and 43 samples, using both metagenomic binning and Hi-C-based Proximity-Guided Assembly. Comparative analysis with current publicly available genomes reveals that the majority of these represent previously unsequenced strains and species of bacteria and archaea. The genomes contain over 16,000 proteins predicted to be involved in carbohydrate metabolism, over 90% of which do not have a good match in public databases. Inclusion of the 283 genomes presented here improves metagenomic read classification by 2-3-fold, both in our data and in other publicly available rumen datasets. This release improves the coverage of rumen microbes in the public databases, and represents a highly valuable resource for biomass-degrading enzyme discovery and studies of the rumen microbiome. |
Type Of Material | Database/Collection of data |
Year Produced | 2017 |
Provided To Others? | Yes |
Title | MOESM1 of Correction to: The rumen microbiome as a reservoir of antimicrobial resistance and pathogenicity genes is directly affected by diet in beef cattle |
Description | Additional file 1: Figure S1.Relative abundance (%) of 20 groups of functional genes representing 204 selected genes (number of animals, n = 50 samples). The sum of the relative abundance (%) of genes grouping within the same function is shown in this figure. Figure S2A. Total abundance of 204 selected genes based on diet treatments (n = 50). *P value |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/MOESM1_of_Correction_to_The_rumen_microbiome_as_a_reser... |
Title | MOESM1 of Correction to: The rumen microbiome as a reservoir of antimicrobial resistance and pathogenicity genes is directly affected by diet in beef cattle |
Description | Additional file 1: Figure S1.Relative abundance (%) of 20 groups of functional genes representing 204 selected genes (number of animals, n = 50 samples). The sum of the relative abundance (%) of genes grouping within the same function is shown in this figure. Figure S2A. Total abundance of 204 selected genes based on diet treatments (n = 50). *P value |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/MOESM1_of_Correction_to_The_rumen_microbiome_as_a_reser... |
Title | PRJEB21624 |
Description | This is one of the largest rumen metagenomics datasets ever released and represents 43 Scottish cattle from diverse breeds, different in methane emissions and feed conversion ratio. These data were used to assemble over 913 novel rumen microbial genomes. |
Type Of Material | Database/Collection of data |
Year Produced | 2017 |
Provided To Others? | Yes |
Impact | These data were used to assemble over 913 novel rumen microbial genomes, which are expected to impact global rumen microbiome research over the next 5-10 years |
URL | https://www.ebi.ac.uk/ena/data/view/PRJEB21624 |
Description | Aviagen |
Organisation | Aviagen Group |
Country | United States |
Sector | Private |
PI Contribution | We are working with Aviagen to explore the role of the chicken gut microbiome in performance of their chickens in diverse environments. So far this includes the placement of one of their staff members in my group for a short period of time for training and development |
Collaborator Contribution | Aviagen provide access to large commercial flocks of chickens under both controlled and natural environments |
Impact | No outputs so far |
Start Year | 2017 |
Description | Charoen Pokphand (CP) group |
Organisation | Charoen Pokphand Group |
Country | Thailand |
Sector | Private |
PI Contribution | Charoen Pokphand (CP) group are a large Asian conglomerate with an interest in farming, food production and feed additives. They have placed one of their staff members with me for PhD training, fully funded by them. We are training the staff member in laboratory and bioinformatics techniques related to microbiome research in chickens. |
Collaborator Contribution | CP provide access to large chicken flocks both in at their farms and in their production facility. This enables us to study chicken breeds in the actual environments in which they live throughout Asia. |
Impact | This is a multi-disciplinary project involving both laboratory and computational techniques. The major outcome so far include a review paper (http://aem.asm.org/content/early/2018/01/29/AEM.02627-17.abstract) and the technology transfer from our group into the commercial partner. |
Start Year | 2017 |
Description | EBI metagenomics |
Organisation | EMBL European Bioinformatics Institute (EMBL - EBI) |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | We have been working with EBI since 2018 on methods and infrastructure around metagenomic data analysis and storage. We have been providing use cases, expertise and biologucal knowledge |
Collaborator Contribution | EBI provide advice on large scale data analysis and the infrastructure they provide |
Impact | We were funded by BBSRC BBR in 2018 to continue this collaboration BB/R015023/1 |
Start Year | 2018 |
Description | SRUC - Rainer Roehe |
Organisation | Scotland's Rural College |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | We have collaborated with Rainer Roehe at SRUC since 2011, and we provide expertise in genomics, DNA sequencing, metagenomics and bioinformatics. We use this to investigate the role of the microbiome in methane emissions and feed conversion ratio. |
Collaborator Contribution | The SRUC partners provide expertise in rumen biology and function, alongside samples collected and measured for methane emissions and feed conversion ratio |
Impact | • Rumen metagenomics: we have sequenced the rumen metagenome of 8 cattle selected for high- and low- methane emissions, matched for breed and diet; and we have demonstrated that high methane emitters are enriched for (i) methanogenic Archaea and (ii) enzymes involved in the methane production pathway. Of the latter, we show that there exists over 5000 novel versions of known enzymes involved in methane production. We have made available a database of over 1.9 million proteins, the majority of them novel, as part of this study (10.1186/s12864-015-2032-0) • Host control of the microbiome: using the same dataset, we demonstrate that largely speaking the rumen microbiome structure and function if under genetic control; and can be significantly associated with both methane emissions and feed-conversion-ratio (FCR) (journal.pgen.1005846) • We have subsequently sequenced over 300 Scottish cattle rumens as part of a project funded by BBSRC. These ruminant metagenomes have resulted in the assembly and publication of several hundred novel rumen microbial genomes (10.1101/162578), publication of a novel pipeline for annotating such genomes (10.1101/233544), publication of robust methane markers in across multiple breeds (10.3389/fmicb.2017.02642) and associations between diet, rumen microbes and anti-microbial resistance (10.1186/s40168-017-0378-z) |
Start Year | 2011 |
Description | The University of Aberdeen |
Organisation | University of Aberdeen |
Department | Institute of Medical Sciences |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | We have been working with Alan Walker and Tim Snelling in the field of rumen metagenomic profiling |
Collaborator Contribution | Alan and Tim are experts in rumen microbiology and 16S sequencing, whereas my group is expert in whole-genome-shotgun metagenomics and bioinformatics |
Impact | As part of a Scottish government project, we have sequenced 90 rumen metagenomes using whole genome sequencing, and almost 300 using 16S profiling. Data analysis is ongoing, but my team have assembled hundreds of microbial genomes from the rumen (10.1101/162578) and written a pipeline for analysiing such data(10.1101/233544) |
Start Year | 2016 |
Title | MAGpy |
Description | Recent advances in bioinformatics have enabled the rapid assembly of genomes from metagenomes (MAGs), and there is a need for reproducible pipelines that can annotate and characterise thousands of genomes simultaneously. Here we present MAGpy, a Snakemake pipeline that takes FASTA input and compares MAGs to several public databases, checks quality, assigns a taxonomy and draws a phylogenetic tree. |
Type Of Technology | Software |
Year Produced | 2017 |
Open Source License? | Yes |
Impact | This software was used to annotate 913 metagenome assembled genomes from the cattle rumen, a dataset which is expected to underpin rumen metagenomics research for the next 5-10 years |
URL | https://datashare.is.ed.ac.uk/handle/10283/3009 |
Title | PULpy |
Description | Polysaccharide utilisation loci (PUL) are regions within bacterial genomes that encode all the necessary machinery for the cleavage of particular carbohydrates. For the Bacteroidetes phylum, prediction of PUL from genomic data alone involves the identification of carbohydrate-active enzymes (CAZymes) co-localised with susCD gene pairs. Here we present the open prediction of PUL in 5414 public Bacteroidetes genomes, and an open-source pipeline to reproduce or extend the results. |
Type Of Technology | Software |
Year Produced | 2018 |
Open Source License? | Yes |
Impact | We use this software in our metagenomics and microbiome research |
URL | https://github.com/WatsonLab/PULpy |
Description | Animal Microbiome Congress London |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Mick Watson presented his work on functional microbiome analysis at the Animal Microbiome Congress London. Attendees included industry/business, farmers, professional practitioners and academics |
Year(s) Of Engagement Activity | 2017 |
Description | Aviagen / CP workshop |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Industry/Business |
Results and Impact | I presented our work on functional microbiome analysis during a one-day workshop which I set up and organised at The Roslin Institute. In attendance were employees of CP (a large Asian conglomerate) and Aviagen (one of the world's largest chicken breeding companies). The focus of the workshop was animal genetics and microbiome. |
Year(s) Of Engagement Activity | 2010,2017 |
Description | Evonik research day |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Industry/Business |
Results and Impact | I presented my work on precision analysis of microbiomes to Evonik, an international company with over 13000 employees and with interests in chemical and food production. This was part of a one day workshop with Evonik, hosted by Roslin and focused on microbiomes |
Year(s) Of Engagement Activity | 2018 |
Description | ISAG 2017 |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Mick Watson presented work on cutting edge techniques that can be used to analyse metagenomics sequence data. ISAG is the international society for animal genetics and this was the very first microbiome session. In attendance were industry practitioners and academics |
Year(s) Of Engagement Activity | 2017 |
URL | http://www.isag.us/2017/ |
Description | Mick Watson Roslin Industry Day |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Industry/Business |
Results and Impact | Mick Watson presented on how genomic technologies are transforming biological research, to an audience of industry and professional practitioners invited to The Roslin Institute to discuss science and policy |
Year(s) Of Engagement Activity | 2016 |
Description | PAG 2017 |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Mick Watson gave a talk at PAG 2017 on Comparison of Methods for Functional and Phylogenetic Characterisation of Rumen Metagenomic Data. Attendees include industry, professional practitioners and academics |
Year(s) Of Engagement Activity | 2017 |
Description | PAG 2018 microbiome talk |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | I gave a talk on microbiome bioinformatics at PAG 2018 in San Diego in the microbiome session. PAG includes attendees from industry, farming and academia. |
Year(s) Of Engagement Activity | 2018 |
Description | Rumen microbiome article in Farmer's Weekly |
Form Of Engagement Activity | A magazine, newsletter or online publication |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Mick Watson was personally interviewed for an article in Farmer's weekly on the potential impact of our rumen microbiome work (doi:10.1038/s41467-018-03317-6) on breeding for production traits in beef and dairy cattle. |
Year(s) Of Engagement Activity | 2018 |
URL | http://www.fwi.co.uk/livestock/rumen-genotyping-advances-enhance-cattle-breeding.htm |
Description | Rumen microbiome work in the national press (print editions) |
Form Of Engagement Activity | A magazine, newsletter or online publication |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Public/other audiences |
Results and Impact | Various articles about our rumen microbiome work appeared in the national press, including: Scottish Daily Express, Scottish Sun, The Scotsman and the Press and Journal |
Year(s) Of Engagement Activity | 2018 |
URL | https://www.pressandjournal.co.uk/fp/business/farming/1427948/cow-digestion-discovery-could-boost-pr... |
Description | Rumen microbiome work on National Public Radio (NPR) in the USA |
Form Of Engagement Activity | A magazine, newsletter or online publication |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Public/other audiences |
Results and Impact | Our rumen microbiome work was featured on NPR.org, (National Public Radio), a US news network that has over 7 million followers on Twitter and reaches millions of people online and via radio. The article was immediately syndicated across an additional ~40 NPR-associated websites |
Year(s) Of Engagement Activity | 2018 |
URL | https://www.npr.org/sections/thesalt/2018/03/06/589997622/mysteries-of-the-moo-crobiome-could-tweaki... |
Description | Various articles on rumen microbiome work |
Form Of Engagement Activity | A magazine, newsletter or online publication |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Various online websites picked up our press release on our rumen microbiome work (doi:10.1038/s41467-018-03317-6) including: https://phys.org/news/2018-02-dna-cow-stomachs-aid-meat.html https://www.sciencedaily.com/releases/2018/02/180228085347.htm http://www.labmanager.com/news/2018/02/dna-study-of-cow-stomachs-could-aid-meat-and-dairy-production#.WpwhWOjFLZs https://www.technologynetworks.com/genomics/news/cows-guts-could-hold-secrets-to-more-meat-and-milk-298080 http://www.sciencenewsline.com/news/2018030111510072.html https://www.eurekalert.org/pub_releases/2018-02/uoe-dso022718.php http://biofuelsdigest.com/nuudigest/2018/02/28/cow-stomach-microbes-could-hold-key-for-increased-food-and-biofuel-production/ |
Year(s) Of Engagement Activity | 2018 |
URL | https://www.sciencedaily.com/releases/2018/02/180228085347.htm |