BackgroundIn recent years, there has been an increasing interest in the genetic determination of environmental variance. In the case of litter size, environmental variance can be related to the capacity of animals to adapt to new environmental conditions, which can improve animal welfare.ResultsWe developed a ten-generation divergent selection experiment on environmental variance. We selected one line of rabbits for litter size homogeneity and one line for litter size heterogeneity by measuring intra-doe phenotypic variance. We proved that environmental variance of litter size is genetically determined and can be modified by selection. Response to selection was 4.5% of the original environmental variance per generation. Litter size was consistently higher in the Low line than in the High line during the entire experiment.ConclusionsWe conclude that environmental variance of litter size is genetically determined based on the results of our divergent selection experiment. This has implications for animal welfare, since animals that cope better with their environment have better welfare than more sensitive animals. We also conclude that selection for reduced environmental variance of litter size does not depress litter size.

Martínez-Álvaro et al. Microbiome Network Explains Methane Emissions lactate and succinate and synthesis of more complex amino acids by γ-Proteobacteria. When analyzing low-and high-methane emitters data in separate networks, competition between methanogens in the methanogenesis cluster was uncovered by a broader diversity of methanogens involved in the three methanogenesis pathways and larger interactions within and between communities in low compared to high emitters. Generally, our results suggest that differences in CH 4 are mainly explained by other microbial communities and their activities rather than being only methanogens-driven. Our study provides insight into the interactions of the rumen microbial communities and their genes by uncovering functional niches affecting CH 4 , which will benefit the development of efficient CH 4 mitigation strategies.

Microbiome and omics datasets are, by their intrinsic biological nature, of high dimensionality, characterized by counts of large numbers of components (microbial genes, operational taxonomic units, RNA transcripts, etc.). These data are generally regarded as compositional since the total number of counts identified within a sample is irrelevant. The central concept in compositional data analysis is the logratio transformation, the simplest being the additive logratios with respect to a fixed reference component. A full set of additive logratios is not isometric, that is they do not reproduce the geometry of all pairwise logratios exactly, but their lack of isometry can be measured by the Procrustes correlation. The reference component can be chosen to maximize the Procrustes correlation between the additive logratio geometry and the exact logratio geometry, and for high-dimensional data there are many potential references. As a secondary criterion, minimizing the variance of the reference component's log-transformed relative abundance values makes the subsequent interpretation of the logratios even easier. On each of three high-dimensional omics datasets the additive logratio transformation was performed, using references that were identified according to the abovementioned criteria. For each dataset the compositional data structure was successfully reproduced, that is the additive logratios were very close to being isometric. The Procrustes correlations achieved for these datasets were 0.9991, 0.9974, and 0.9902, respectively. We thus demonstrate, for high-dimensional compositional data, that additive logratios can provide a valid choice as transformed variables, which (a) are subcompositionally coherent, (b) explain 100% of the total logratio variance and (c) come measurably very close to being isometric. The interpretation of additive logratios is much simpler than the complex isometric alternatives and, when the variance of the log-transformed reference is very low, it is even simpler since each additive logratio can be identified with a corresponding compositional component.

A divergent selection experiment on intramuscular fat (IMF) was performed in rabbits. The aim of this study is to estimate the response to selection, the correlated responses in carcass and meat quality traits, and their genetic parameters. Selection criterion was the averaged phenotypic value of IMF measured at 9 wk of age in 2 full-sibs of the candidate. Traits considered were IMF, BW, chilled carcass weight, reference carcass weight, scapular and perirenal fat weights, carcass and meat color, pH, protein and fatty acid composition of meat. Total direct response to selection for IMF was 2.6 phenotypic SD of the trait, around 5% of the mean (1.09 g/100 g) per generation, with both lines following a symmetrical trend. Heritability of IMF was high (0.54), and in general, all traits related to carcass fat depots and IMF fatty acid composition showed high heritabilities (dissectible fat of the carcass, 0.70; MUFA percentage, 0.61; PUFA percentage, 0.45; and PUFA:SFA ratio, 0.42), except SFA percentage (0.09). The other carcass and meat quality traits showed moderate to low heritabilities. Intramuscular fat and dissectible fat percentage showed a low genetic correlation (0.34). Intramuscular fat was positively correlated with MUFA percentage (0.95) and negatively correlated with PUFA percentage (-0.89) and PUFA:SFA ratio (-0.98), corroborated with high correlated responses to selection. The rest of the traits did not show any substantial correlated response except protein content, which was greater in the high-IMF line than in the low-IMF line.

Our study provides substantial evidence that the host genome affects the comprehensive function of the microbiome in the rumen of bovines. Of 1,107/225/1,141 rumen microbial genera/metagenome assembled uncultured genomes (RUGs)/genes identified from whole metagenomics sequencing, 194/14/337 had significant host genomic effects (heritabilities ranging from 0.13 to 0.61), revealing that substantial variation of the microbiome is under host genomic control. We found 29/22/115 microbial genera/RUGs/genes host-genomically correlated (|0.59| to |0.93|) with emissions of the potent greenhouse gas methane (CH4), highlighting the strength of a common host genomic control of specific microbial processes and CH4. Only one of these microbial genes was directly involved in methanogenesis (cofG), whereas others were involved in providing substrates for archaea (e.g. bcd and pccB), important microbial interspecies communication mechanisms (ABC.PE.P), host-microbiome interaction (TSTA3) and genetic information processes (RP-L35). In our population, selection based on abundances of the 30 most informative microbial genes provided a mitigation potential of 17% of mean CH4 emissions per generation, which is higher than for selection based on measured CH4 using respiration chambers (13%), indicating the high potential of microbiome-driven breeding to cumulatively reduce CH4 emissions and mitigate climate change.

The aim of this study was to evaluate the effect of six generations of selection for intramuscular fat (IMF) in muscle Longissimus thoracis et lumborum (LTL) at 9 wk. in IMF and fatty acid (FA) composition of muscles with diverse metabolic profile in rabbits. Direct response to selection was 0.33 g of IMF/ 100 g of LTL, around 0.4 SD per generation. A positive correlated response was observed in IMF of Biceps femoris, Supraspinatus and Semimembranosus proprius muscles at 9 wk., representing around 0.2 SD of the trait per generation. Selection affected similarly the FA composition of all muscles at 9 wk., high-IMF line showing greater monounsaturated but lower polyunsaturated FA percentages than low-IMF line, whereas no differences were observed for saturated FA. Traits were also measured at 13 wk. and correlated responses were in the same direction. Our results suggest a common genetic background for IMF and FA composition in muscles with different metabolic profile in rabbits.

Our study provides an exhaustive comparison of the microbiome core functionalities (captured by 3,936 microbial gene abundances) between hosts with divergent genotypes for intramuscular lipid deposition. After 10 generations of divergent selection for intramuscular fat in rabbits and 4.14 phenotypic standard deviations (SD) of selection response, we applied a combination of compositional and multivariate statistical techniques to identify 122 cecum microbial genes with differential abundances between the lines (ranging from −0.75 to +0.73 SD). This work elucidates that microbial biosynthesis lipopolysaccharides, peptidoglycans, lipoproteins, mucin components, and NADH reductases, amongst others, are influenced by the host genetic determination for lipid accretion in muscle. We also differentiated between host-genetically influenced microbial mechanisms regulating lipid deposition in body or intramuscular reservoirs, with only 28 out of 122 MGs commonly contributing to both. Importantly, the results of this study are of relevant interest for the efficient development of strategies fighting obesity.

Intramuscular fat (IMF) content and composition are relevant for the meat industry due to their effect on human health and meat organoleptic properties. A divergent selection experiment for IMF of Longissimus dorsi (LD) muscle was performed in rabbits during eight generations. The aim of this study is to estimate the correlated responses to selection for IMF on the fatty acid composition of LD. Response to selection for IMF was 0.34 g/100 g of LD, representing 2.4 phenotypic SD of the trait. High-IMF line showed 9.20% more monounsaturated fatty acids (MUFA) and 0.39%, 9.97% and 10.3% less n-3, n-6 and polyunsaturated fatty acids (PUFA), respectively, than low-IMF line. The main MUFA and PUFA individual fatty acids followed a similar pattern, except for C18:3n-3 that was greater in the high-IMF line. We did not observe differences between lines for the percentage of total saturated fatty acids, although high-IMF line showed greater C14:0 and C16:0 and lower C18:0 percentages than low-IMF line. Heritability estimates were generally high for all fatty acids percentages, ranging from 0.43 to 0.59 with a SD around 0.08, showing an important genetic component on these traits. Genetic correlations between IMF and LD fatty acid percentages were strong and positive for C14:0, C16:1, C18:1n-9, and MUFA, ranging from 0.88 to 0.97, and strong and negative for C18:0, C18:2n-6, C20:4n-6, n-6 and PUFA, ranging from -0.83 to -0.91. These correlations were accurately estimated, with SD ranging from 0.02 to 0.06. The genetic correlations between IMF and other fatty acids were estimated with lower accuracy. In general, phenotypic and genetic correlations were of the same order. Our experiment shows that selection for IMF strongly affects the fatty acid composition of meat, due the high heritabilities of fatty acids and their high genetic correlations with IMF.