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, 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.

Combining host and rumen metagenome profiling for selection in sheep: prediction of methane, feed efficiency, production, and health traits.

BACKGROUND: Rumen microbes break down complex dietary carbohydrates into energy sources for the host and are increasingly shown to be a key aspect of animal performance. Host genotypes can be combined with microbial DNA sequencing to predict performance traits or traits related to environmental impact, such as enteric methane emissions. Metagenome profiles were generated from 3139 rumen samples, collected from 1200 dual purpose ewes, using restriction enzyme-reduced representation sequencing (RE-RRS). Phenotypes were available for methane (CH4) and carbon dioxide (CO2) emissions, the ratio of CH4 to CH4 plus CO2 (CH4Ratio), feed efficiency (residual feed intake: RFI), liveweight at the time of methane collection (LW), liveweight at 8 months (LW8), fleece weight at 12 months (FW12) and parasite resistance measured by faecal egg count (FEC1). We estimated the proportion of phenotypic variance explained by host genetics and the rumen microbiome, as well as prediction accuracies for each of these traits. RESULTS: Incorporating metagenome profiles increased the variance explained and prediction accuracy compared to fitting only genomics for all traits except for CO2 emissions when animals were on a grass diet. Combining the metagenome profile with host genotype from lambs explained more than 70% of the variation in methane emissions and residual feed intake. Predictions were generally more accurate when incorporating metagenome profiles compared to genetics alone, even when considering profiles collected at different ages (lamb vs adult), or on different feeds (grass vs lucerne pellet). A reference-free approach to metagenome profiling performed better than metagenome profiles that were restricted to capturing genera from a reference database. We hypothesise that our reference-free approach is likely to outperform other reference-based approaches such as 16S rRNA gene sequencing for use in prediction of individual animal performance. CONCLUSIONS: This paper shows the potential of using RE-RRS as a low-cost, high-throughput approach for generating metagenome profiles on thousands of animals for improved prediction of economically and environmentally important traits. A reference-free approach using a microbial relationship matrix from log10 proportions of each tag normalized within cohort (i.e., the group of animals sampled at the same time) is recommended for future predictions using RE-RRS metagenome profiles.

Association of ADIPOQ, OLR1 and PPARGC1A gene polymorphisms with growth and carcass traits in Nelore cattle.

In beef cattle farming, growth and carcass traits are important for genetic breeding programs. Molecular markers can be used to assist selection and increase genetic gain. The ADIPOQ, OLR1 and PPARGC1A genes are involved in lipid synthesis and fat accumulation in adipose tissue. The objective of this study was to identify polymorphisms in these genes and to assess the association with growth and carcass traits in Nelore cattle. A total of 639 animals were genotyped by PCR-RFLP for rs208549452, rs109019599 and rs109163366 in ADIPOQ, OLR1 and PPARGC1A gene, respectively. We analyzed the association of SNPs identified with birth weight, weaning weight, female yearling weight, female hip height, male yearling weight, male hip height, loin eye area, rump fat thickness, and backfat thickness. The OLR1 marker was associated with rump fat thickness and weaning weight (P < 0.05) and the PPARGC1 marker was associated with female yearling weight.

Polymorphisms in the MTRN1A gene and their effects on the productive and reproductive traits in buffaloes.

The main environmental factor that affects the regulation of reproductive seasonality is photoperiod through its effects on melatonin secretion. The melatonin receptor MTRN1A appears to be involved in regulating the reproductive seasonality and milk production in the period. The aim of this study was to identify polymorphisms in the MTRN1A gene and their possible associations with milk, fat and protein productions, fat and protein percentages, age at first calving, and first calving interval in buffaloes. Three genotypes (CC, CT, and TT) were identified by PCR-RFLP, and there was a significant association with protein percentage (P < 0.0001). Further studies are necessary to better understand the influence of melatonin gene and their receptors in the productive functions of buffaloes.

Effects of a single nucleotide polymorphism in the leptin gene on the productive traits of dairy buffaloes (Bubalus bubalis).

The gene responsible for coding the leptin hormone has been associated with productive and reproductive traits in cattle. In dairy cattle, different polymorphisms found in the leptin gene have been associated with several traits of economic interest, such as energy balance, milk yield and composition, live weight, fertility and dry matter consumption. The aim of this study was to detect genetic variability in the leptin gene of buffaloes and to test possible associations with milk yield, fat and protein percentages, age at first calving and first calving interval. Three genotypes (AA, AG and GG) were identified by polymerase chain reaction-restriction fragment length polymorphism, which presented genotypic frequencies of 0.30, 0.54 and 0.16, respectively. The allele frequencies were 0.57 for the A allele and 0.43 for the G allele. No significant effects were found in the present study, but there is an indicative that leptin gene affects lipid metabolism.

First polymorphisms in JY-1 gene in cattle (Bos taurus indicus) and their association with sexual precocity and growth traits.

Protein JY-1 is a bovine oocyte-specific protein that regulates granulosa cell function and is involved in early embryonic development, influencing the chance of pregnancy. This study investigated molecular markers for the JY-1 gene. Seven SNPs were identified in exon 3 of the gene. The positions of the SNPs in the exon and the respective substitutions are: 163 (T/C), 281 (T/C), 321 (T/C), 532 (T/C), 652 (A/G), 679 (T/C), and 722 (G/C) (GenBank: JN592587 and JF262042.2). SNP 163 is located in a coding region and causes a proline-to-leucine substitution. The other SNPs are located in the 3'UTR region. SNPs 163, 281, 321, and 679 were genotyped in 297 Nellore heifers and the haplotypes were constructed. The haplotypes of JY-1 were not correlated with the traits studied at 5 %.