Genetic relationships between efficiency traits and gut microbiota traits in growing pigs being fed with a conventional or a high-fiber diet.

In pigs, the gut microbiota composition plays a major role in the process of digestion, but is influenced by many external factors, especially diet. To be used in breeding applications, genotype by diet interactions on microbiota composition have to be quantified, as well as their impact on genetic covariances with feed efficiency (FE) and digestive efficiency (DE) traits. This study aimed at determining the impact of an alternative diet on variance components of microbiota traits (genera and alpha diversity indices) and estimating genetic correlations between microbiota and efficiency traits for pigs fed a conventional (CO) or a high-fiber (HF) diet. Fecal microbes of 812 full-siblings fed a CO diet and 752 pigs fed the HF diet were characterized at 16 weeks of age by sequencing the V3-V4 region of the 16S rRNA gene. A total of 231 genera were identified. Digestibility coefficients of nitrogen, organic matter, and energy were predicted analyzing the same fecal samples with near infrared spectrometry. Daily feed intake, feed conversion ratio, residual feed intake and average daily gain (ADG) were also recorded. The 71 genera present in more than 20% of individuals were retained for genetic analyses. Heritability (h²) of microbiota traits were similar between diets (from null to 0.38 ±â€…0.12 in the CO diet and to 0.39 ±â€…0.12 in the HF diet). Only three out of the 24 genera and two alpha diversity indices with significant h² in both diets had genetic correlations across diets significantly different from 0.99 (P < 0.05), indicating limited genetic by diet interactions for these traits. When both diets were analyzed jointly, 59 genera had h² significantly different from zero. Based on the genetic correlations between these genera and ADG, FE, and DE traits, three groups of genera could be identified. A group of 29 genera had abundances favorably correlated with DE and FE traits, 14 genera were unfavorably correlated with DE traits, and the last group of 16 genera had abundances with correlations close to zero with production traits. However, genera abundances favorably correlated with DE and FE traits were unfavorably correlated with ADG, and vice versa. Alpha diversity indices had correlation patterns similar to the first group. In the end, genetic by diet interactions on gut microbiota composition of growing pigs were limited in this study. Based on this study, microbiota-based traits could be used as proxies to improve FE and DE in growing pigs.

The link between the composition of the gut microbiota, i.e the composition of microorganisms in the gut, in pigs and their feed efficiency, i.e. their ability to utilize nutrients, as well as their ability to digest were studied from a genetic point of view. A family structure of 1,564 pigs were studied and fed with two different diets. One of the full-sib was fed a conventional diet used in breeding farms and the other one an alternative diet containing raw materials, less expensive but with a higher content of dietary fibers more difficult to digest. This study has shown that some microbiota microorganisms were genetically correlated with feed and digestive efficiency performances, positively or negatively, depending on the microorganisms. In addition, the diversity of microorganisms in the animal's gut was favorably correlated with the feed and digestive performances studied. Therefore, there is a genetic link between these performances and the composition of the animal's gut microbiota. Thus, a potential genetic selection on some intestinal microorganisms or diversity of microorganisms would allow to improve these performances, and in particular when pigs are fed with diet more difficult to digest.

Digestive efficiency traits in growing pigs are genetically correlated with sow litter traits in the Large White breed.

Digestive efficiency traits are promising selection criteria to improve feed efficiency in pigs. However, the genetic relationships between digestive efficiency and sow reproductive traits are mostly unknown and need to be estimated. In this study, reproductive traits were available for 61 601 litters recorded on 21 719 Large White purebred sows. The traits were comprised of the number of born alive (NBA) and the number of weaned piglets (NWP), the number of stillbirths (NSB) and piglet mortality during suckling (PM). For a subset of 32518 litters, the mean (MBW) and CV of piglet birth weights (CVBW) were deduced from individual piglet weights as well as the proportion of piglets weighing less than 1 kg (PPL1K). Growth and feed efficiency traits were available for 4 643 Large White male pigs related to sows with reproductive performances. They comprised average daily gain (ADG), daily feed intake (DFI) and feed conversion ratio (FCR). A subset of 1 391 pigs had predictions for digestibility coefficients (DC) of energy, organic matter and nitrogen obtained by analysing faecal samples with near-infrared spectrometry. Estimated heritabilities were low for NBA, NSB, NWP and PM (0.08 ± 0.01 to 0.11 ± 0.01) and low to moderate for litter weight characteristics (0.14 ± 0.02 to 0.38 ± 0.01). Heritability estimates were moderate to high for ADG, DFI and FCR (0.37 ± 0.04 to 0.54 ± 0.05) and moderate for DC traits (0.26 ± 0.06 to 0.38 ± 0.07). Genetic correlations were low between ADG, or alternatively FCR, and reproductive traits. They were significantly different from zero with MBW (0.19 ± 0.06 with ADG and -0.15 ± 0.06 with FCR) and PPL1K (-0.19 ± 0.07 with ADG and 0.18 ± 0.07 with FCR). All genetic correlations between DFI and reproductive traits were low and not significantly different from zero. Genetic correlations between DC traits and NBA were significantly different from zero for DC of organic matter and energy (<-0.25 ± 0.11). DC traits were moderately correlated with MBW (>0.30 ± 0.11), CVBW (<-0.36 ± 0.11) and PPL1K (<-0.37 ± 0.11) at the genetic level. Genetic correlations between DC traits and PM were significantly negative and hence favourable (<-0.38 ± 0.12). Finally, genetic correlations between DC traits and NWP were close to zero. These results suggested that sows closely related to growing pigs with the best digestive efficiency would produce heavier and more homogeneous piglets, with slightly smaller litter sizes at birth but better survival. Hence, there is usable genetic variation in DC that could be exploited to define new selection strategies in maternal lines aiming at improving not only feed efficiency but also piglet survival.

Impact of a high-fibre diet on genetic parameters of production traits in growing pigs.

The use of diets with increased fibre content from alternative feedstuffs less digestible for pigs is a solution considered to limit the impact of increased feed costs on pig production. This study aimed at determining the impact of an alternative diet on genetic parameters for growth, feed efficiency, carcass composition and meat quality traits. A total of 783 Large White pigs were fed a high-fibre (HF) diet and 880 of their sibs were fed a conventional (CO) cereal-based diet. Individual daily feed intake, average daily gain, feed conversion ratio and residual feed intake were recorded as well as lean meat percentage (LMP), carcass yield (CY) and meat quality traits. Pigs fed the CO diet had better performances for growth and feed efficiency than pigs fed the HF diet. They also had lower LMP and higher CY. In addition, pigs fed the CO diet had lower loin percentage and ham percentage and higher backfat percentage. No differences were observed in meat quality traits between diets, except for a* and b* values. For all traits, the genetic variances and heritability were not different between diets. Genetic correlations for traits between diets ranged between 0.80 ± 0.13 and 0.99 ± not estimable, and none were significantly different from 0.99, except for LMP. Thus, traits in both diets were considered as mainly affected by similar sets of genes in the two diets. A genetic correlation lower than 0.80 would justify redesigning the breeding scheme; however, some genetic correlations did not differ significantly from 0.80 either. Therefore, larger populations are needed for a more definitive answer regarding the design of the breeding scheme. To further evaluate selection strategies, a production index was computed within diets for the 29 sires with estimated breeding value reliability higher than 0.35. The rank correlation between indices estimated in the CO and in the HF diet was 0.72. Altogether, we concluded that limited interaction between feed and genetics could be evidenced, and based on these results there is no need to change pig selection schemes to adapt to the future increased use of alternative feedstuffs in production farms.