Analysis of biological networks and biological pathways associated with residual feed intake in beef cattle

Karisa, Brian K; Moore, S. S.; Plastow, Graham

doi:10.1111/asj.12159

Cited by 50 publications

(55 citation statements)

References 44 publications

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“…Moreover, some of the significantly enriched GO terms were associated with fat metabolisms, such as monocarboxylic acid and oxyacid metabolic processes. Interestingly, it has been shown that there is a relationship between lipid metabolism and feed efficiency (Nafikov and Beitz 2007;Karisa et al 2014). For example, by increasing the fat sources in a broiler diet, the FI amount is decreased and feed efficiency is improved (Firman et al 2010).…”

Section: Discussionmentioning

confidence: 99%

Gene expression profile analysis of residual feed intake for Isfahan native chickens using RNA-SEQ data

Izadnia

Tahmoorespur

Bakhtiarizadeh

et al. 2018

Italian Journal of Animal Science

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The factors that affect residual feed intake (RFI) of two chicken breeds (Ross as commercial and Isfahan as Iranian local breed with low and high RFI, respectively) were examined. We sequenced their liver transcriptomes using RNA-Seq while focusing on the identification of important candidate genes, which might influence RFI and growth rate. The differential gene expression analysis revealed that 121 and 279 known genes were significantly up-and downregulated in the local breed, respectively. QTL enrichment analysis revealed that 63 down-regulated genes in the local breed were enriched in the QTL regions related to feed efficiency traits. Moreover, the functional enrichment analysis showed that the down-regulated genes in the native chickens were mainly involved in the different metabolic processes, such as carboxylic acid metabolic process and response to stress. The Differentially Expressed Genes explored between the chickens of the two breeds led to the identification of some important candidate genes for further breed improvement programmes, including RSAD2, IL15, LIPI, EGR1 and DUSP16. These findings will be a useful resource for the biological investigations of RFI-related genes in Isfahan local chickens and may provide some clues for understanding the molecular genetic mechanisms in other chicken breeds. HIGHLIGHTS A global view of transcriptome differences in the liver tissues of commercial and local chicken breeds with different RFI values is obtained. This investigation will contribute to the improvement of chicken genome annotation through the identification of novel transcripts and novel gene. Some important candidate genes related to RFI is obtained.

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Section: Discussionmentioning

confidence: 99%

Gene expression profile analysis of residual feed intake for Isfahan native chickens using RNA-SEQ data

Izadnia

Tahmoorespur

Bakhtiarizadeh

et al. 2018

Italian Journal of Animal Science

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“…Ruminant production, especially beef cattle operation, is important for the production of high-quality animal protein (meat). Feed efficiency is one of the most important traits in beef cattle production because the feed cost accounts for approximately 60-70% of the total production cost (Karisa et al, 2014). Therefore, improving feed efficiency in beef cattle can maximize the production efficiency when lower or the same amount of feed is consumed by cattle under current management conditions.…”

Section: Introductionmentioning

confidence: 99%

Metatranscriptomic Profiling Reveals the Effect of Breed on Active Rumen Eukaryotic Composition in Beef Cattle With Varied Feed Efficiency

Zhang

Chen

et al. 2020

Front. Microbiol.

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Exploring the compositional characteristics of rumen eukaryotic community can expand our understanding of their role in rumen function and feed efficiency. In this study, we applied metatranscriptomics to characterize the active rumen eukaryotic community (protozoa and fungi) in beef cattle (n = 48) of three breeds [Angus (AN), Charolais (CH), and Kinsella Composite (KC)] and with divergent residual feed intake (RFI). The composition of active rumen eukaryotic microbiota was evaluated based on enriched 18S rRNAs from the metatranscriptomic datasets. At the phylum level, a total of four protozoal taxa (Ciliophora, Parabasalia, unclassified SAR, and unclassified Alveolata), six fungal taxa (Neocallimastigomycota, Basidiomycota, unclassified Fungi, Mucoromycota, Ascomycota, and Chytridiomycota), and one sister group of kingdom Fungi (unclassified Opisthokonta) were detected with relative abundances higher than 0.01% and in at least 50% of animals within each breed. Among these, Ciliophora, Parabasalia, unclassified Opisthokonta, and Neocallimastigomycota were the top four active eukaryotic phyla. At the genus level, a total of 8 ciliated protozoa, 5 flagellated protozoa, 5 anaerobic fungi, and 10 aerobic fungi taxa were detected, with unclassified Trichostomatia, Tetratrichomonas, unclassified Neocallimastigaceae, and Pleurotus being the most predominant taxa of ciliated protozoa, flagellated protozoa, anaerobic fungi, and aerobic fungi, respectively. Differential abundance analysis revealed that breed had a significant effect on the phylogenetic lineages of rumen eukaryotes, and seven fungal taxa were more abundant (linear discriminant analysis score > 2 with P < 0.05) in the rumen of KC steers than in the rumen of AN and CH steers. Although principal coordinate analysis (PCoA) revealed that the ruminal active eukaryotic profiles were not distinguishable between high-and low-RFI groups, the diversity indices, including Faith's phylogenetic diversity (PD), observed operational taxonomic units (OTUs), and Shannon index of rumen eukaryotes were higher in low-RFI steers than those in high-RFI steers. Meanwhile, the abundance of genus Entodinium and the kingdom Fungi was higher in low-RFI steers than that in high-RFI steers. This information on active rumen eukaryotic microbiota and identified differential abundance of taxa between high-and low-RFI animals suggests the possibility of improving feed efficiency through altering rumen eukaryotic microbiota.

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“…To date, multiple studies have reported that the rumen microbial composition is associated with feed efficiency in beef (5-9) and dairy (10) cattle, suggesting that rumen microbial function is one of the factors that impact the cattle's feed efficiency. Feed efficiency is one of the most important traits in cattle farming because the feed cost accounts for most of the production expense, accounting for 60 to 70% of the total cost in beef production (11). In addition, efficient beef cattle produce 20% less methane than inefficient ones (12); hence, enhancing the feed efficiency of beef cattle can also decrease their environmental footprint.…”

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confidence: 99%

Metatranscriptomic Profiling Reveals Linkages between the Active Rumen Microbiome and Feed Efficiency in Beef Cattle

Guan

2017

Appl Environ Microbiol

258

216

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Exploring compositional and functional characteristics of the rumen microbiome can improve the understanding of its role in rumen function and cattle feed efficiency. In this study, we applied metatranscriptomics to characterize the active rumen microbiomes of beef cattle with different feed efficiencies (efficient, n ϭ 10; inefficient, n ϭ 10) using total RNA sequencing. Active bacterial and archaeal compositions were estimated based on 16S rRNAs, and active microbial metabolic functions including carbohydrate-active enzymes (CAZymes) were assessed based on mRNAs from the same metatranscriptomic data sets. In total, six bacterial phyla (Proteobacteria, Firmicutes, Bacteroidetes, Spirochaetes, Cyanobacteria, and Synergistetes), eight bacterial families (Succinivibrionaceae, Prevotellaceae, Ruminococcaceae, Lachnospiraceae, Veillonellaceae, Spirochaetaceae, Dethiosulfovibrionaceae, and Mogibacteriaceae), four archaeal clades (Methanomassiliicoccales, Methanobrevibacter ruminantium, Methanobrevibacter gottschalkii, and Methanosphaera), 112 metabolic pathways, and 126 CAZymes were identified as core components of the active rumen microbiome. As determined by comparative analysis, three bacterial families (Lachnospiraceae, Lactobacillaceae, and Veillonellaceae) tended to be more abundant in low-feed-efficiency (inefficient) animals (P Ͻ 0.10), and one archaeal taxon (Methanomassiliicoccales) tended to be more abundant in high-feed-efficiency (efficient) cattle (P Ͻ 0.10). Meanwhile, 32 microbial metabolic pathways and 12 CAZymes were differentially abundant (linear discriminant analysis score of Ͼ2 with a P value of Ͻ0.05) between two groups. Among them, 30 metabolic pathways and 11 CAZymes were more abundant in the rumen of inefficient cattle, while 2 metabolic pathways and 1 CAZyme were more abundant in efficient animals. These findings suggest that the rumen microbiomes of inefficient cattle have more diverse activities than those of efficient cattle, which may be related to the host feed efficiency variation.IMPORTANCE This study applied total RNA-based metatranscriptomics and showed the linkage between the active rumen microbiome and feed efficiency (residual feed intake) in beef cattle. The data generated from the current study provide fundamental information on active rumen microbiome at both compositional and functional levels, which serve as a foundation to study rumen function and its role in cattle feed efficiency. The findings that the active rumen microbiome may contribute to variations in feed efficiency of beef cattle highlight the possibility of enhancing nutrient utilization and improve cattle feed efficiency through modification of rumen microbial functions.KEYWORDS metatranscriptome, RNA-seq, rumen microbiome, beef cattle, feed efficiency R uminants can convert fibrous plant materials into edible meat and milk products for human consumption through rumen microbial fermentation. The symbiotic rumen microbiota mainly consists of bacteria, archaea, fungi, and ciliated protozoa (1)

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Analysis of biological networks and biological pathways associated with residual feed intake in beef cattle

Cited by 50 publications

References 44 publications

Gene expression profile analysis of residual feed intake for Isfahan native chickens using RNA-SEQ data

Gene expression profile analysis of residual feed intake for Isfahan native chickens using RNA-SEQ data

Metatranscriptomic Profiling Reveals the Effect of Breed on Active Rumen Eukaryotic Composition in Beef Cattle With Varied Feed Efficiency

Metatranscriptomic Profiling Reveals Linkages between the Active Rumen Microbiome and Feed Efficiency in Beef Cattle

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