Genome-wide association study for feed efficiency in collective cage-raised rabbits under full and restricted feeding

Genome-wide association studies for diarrhoea outcomes identified genomic regions affecting resistance to a severe enteropathy in suckling rabbits

Selection and breeding strategies to improve resistance to enteropathies are essential to reaching the sustainability of the rabbit production systems. However, disease heterogeneity (having only as major visible symptom diarrhoea) and low disease heritability are two barriers for the implementation of these strategies. Diarrhoea condition can affect rabbits at different life stages, starting from the suckling period, with large negative economic impacts. In this study, from a commercial population of suckling rabbits (derived from 133 litters) that experienced an outbreak of enteropathy, we first selected a few animals that died with severe symptoms of diarrhoea and characterized their microbiota, using 16S rRNA gene sequencing data. Clostridium genus was consistently present in all affected specimens. In addition, with the aim to identify genetic markers in the rabbit genome that could be used as selection tools, we performed genome-wide association studies for symptoms of diarrhoea in the same commercial rabbit population. These studies were also complemented with FST analyses between the same groups of rabbits. A total of 332 suckling rabbits (151 with severe symptoms of diarrhoea, 42 with mild symptoms and 129 without any symptoms till the weaning period), derived from 45 different litters (a subset of the 133 litters) were genotyped with the Affymetrix Axiom OrcunSNP Array. In both genomic approaches, rabbits within litters were paired to constitute two groups (susceptible and resistant, including the mildly affected in one or the other group) and run case and control genome-wide association analyses. Genomic heritability estimated in the designed experimental structure integrated in a commercial breeding scheme was 0.19-0.21 (s.e. 0.09-0.10). A total of eight genomic regions on rabbit chromosome 2 (OCU2), OCU3, OCU7, OCU12, OCU13, OCU16 and in an unassembled scaffold had significant single nucleotide polymorphisms (SNPs) and/or markers that trespassed the FST percentile distribution. Among these regions, three main peaks of SNPs were identified on OCU12, OCU13 and OCU16. The QTL region on OCU13 encompasses several genes that encode members of a family of immunoglobulin Fc receptors (FCER1G, FCRLA, FCRLB and FCGR2A) involved in the immune innate system, which might be important candidate genes for this pathogenic condition. The results obtained in this study demonstrated that resistance to an enteropathy occurring in suckling rabbits is in part genetically determined and can be dissected at the genomic level, providing DNA markers that could be used in breeding programmes to increase resistance to enteropathies in meat rabbits.

Long-read sequencing-based transcriptomic landscape in longissimus dorsi and transcriptome-wide association studies for growth traits of meat rabbits

Rabbits are an attractive meat livestock species that can efficiently convert human-indigestible plant biomass, and have been commonly used in biological and medical researches. Yet, transcriptomic landscape in muscle tissue and association between gene expression level and growth traits have not been specially studied in meat rabbits. In this study Oxford Nanopore Technologies (ONT) long-read sequencing technology was used for comprehensively exploring transcriptomic landscape in Longissimus dorsi for 115 rabbits at 84 days of age, and transcriptome-wide association studies (TWAS) were performed for growth traits, including body weight at 84 days of age and average daily gain during three growth periods. The statistical analysis of TWAS was performed using a mixed linear model, in which polygenic effect was fitted as a random effect according to gene expression level-based relationships. A total of 18,842 genes and 42,010 transcripts were detected, among which 35% of genes and 47% of transcripts were novel in comparison with the reference genome annotation. Furthermore, 45% of genes were widely expressed among more than 90% of individuals. The proportions (±SE) of phenotype variance explained by genome-wide gene expression level ranged from 0.501 ± 0.216 to 0.956 ± 0.209, and the similar results were obtained when explained by transcript expression level. In contrast, neither gene nor transcript was detected by TWAS to be statistically significantly associated with these growth traits. In conclusion, these novel genes and transcripts that have been extensively profiled in a single muscle tissue using long-read sequencing technology will greatly improve our understanding on transcriptional diversity in rabbits. Our results with a relatively small sample size further revealed the important contribution of global gene expression to phenotypic variation on growth performance, but it seemed that no single gene has an outstanding effect; this knowledge is helpful to include intermediate omics data for implementing genetic evaluation of growth traits in meat rabbits.

Disentangling the causal relationship between rabbit growth and cecal microbiota through structural equation models

BACKGROUND

The effect of the cecal microbiome on growth of rabbits that were fed under different regimes has been studied previously. However, the term "effect" carries a causal meaning that can be confounded because of potential genetic associations between the microbiome and production traits. Structural equation models (SEM) can help disentangle such a complex interplay by decomposing the effect on a production trait into direct host genetics effects and indirect host genetic effects that are exerted through microbiota effects. These indirect effects can be estimated via structural coefficients that measure the effect of the microbiota on growth while the effects of the host genetics are kept constant. In this study, we applied the SEM approach to infer causal relationships between the cecal microbiota and growth of rabbits fed under ad libitum (ADG_AL) or restricted feeding (ADG_R).

RESULTS

We identified structural coefficients that are statistically different from 0 for 138 of the 946 operational taxonomic units (OTU) analyzed. However, only 15 and 38 of these 138 OTU had an effect greater than 0.2 phenotypic standard deviations (SD) on ADG_AL and ADG_R, respectively. Many of these OTU had a negative effect on both traits. The largest effects on ADG_R were exerted by an OTU that is taxonomically assigned to the Desulfovibrio genus (- 1.929 g/d, CSS-normalized OTU units) and by an OTU that belongs to the Ruminococcaceae family (1.859 g/d, CSS-normalized OTU units). For ADG_AL, the largest effect was from OTU that belong to the S24-7 family (- 1.907 g/d, CSS-normalized OTU units). In general, OTU that had a substantial effect had low to moderate estimates of heritability.

CONCLUSIONS

Disentangling how direct and indirect effects act on production traits is relevant to fully describe the processes of mediation but also to understand how these traits change before considering the application of an external intervention aimed at changing a given microbial composition by blocking/promoting the presence of a particular microorganism.

The value of gut microbiota to predict feed efficiency and growth of rabbits under different feeding regimes

Gut microbiota plays an important role in nutrient absorption and could impact rabbit feed efficiency. This study aims at investigating such impact by evaluating the value added by microbial information for predicting individual growth and cage phenotypes related to feed efficiency. The dataset comprised individual average daily gain and cage-average daily feed intake from 425 meat rabbits, in which cecal microbiota was assessed, and their cage mates. Despite microbiota was not measured in all animals, consideration of pedigree relationships with mixed models allowed the study of cage-average traits. The inclusion of microbial information into certain mixed models increased their predictive ability up to 20% and 46% for cage-average feed efficiency and individual growth traits, respectively. These gains were associated with large microbiability estimates and with reductions in the heritability estimates. However, large microbiabililty estimates were also obtained with certain models but without any improvement in their predictive ability. A large proportion of OTUs seems to be responsible for the prediction improvement in growth and feed efficiency traits, although specific OTUs taxonomically assigned to 5 different phyla have a higher weight. Rabbit growth and feed efficiency are influenced by host cecal microbiota, thus considering microbial information in models improves the prediction of these complex phenotypes.

Using Linear Discriminant Analysis to Characterize Novel Single Nucleotide Polymorphisms and Expression Profile Changes in Genes of Three Breeds of Rabbit (Oryctolagus cuniculus)

The objectives of this study were to investigate polymorphisms and changes in expression patterns of the genes FGF5, PGAM2, TLR2 and IL10 in V-line, Baladi Black and Baladi Red rabbits. Blood samples were collected from 180 healthy rabbits (n = 60 for each breed) for DNA extraction and DNA sequencing. At 3 mo of age, 20 randomly selected females from each breed were euthanized for gene expression quantification in muscle and spleen samples. PCR-DNA sequencing revealed single nucleotide polymorphisms (SNPs) among the 3 breeds that provided a monomorphic pattern for 3 of the 4 genes analyzed. Linear discriminant analysis (LDA) was used to classify the SNPs of these genes in the 3 breeds. The overall percentage of correctly classified cases for the model was 75%, with percentages of 100% for FGF5, 63% for IL10, and 100% for TLR2. Breed was a significant predictor for gene classification with estimation (1.00). Expression profiles of the genes were higher in V-line as compared with Baladi Black or Baladi Red. The LDA discriminated the 3 breeds using results of the gene expression profile as predictors for classification. Overall, 73% of the cases were correctly classified by gene expression. The identified SNPs, along with changes in mRNA levels of FGF5, PGAM2, TLR2, and IL10, could provide a biomarker for efficient characterization of rabbit breeds and could thus help develop marker assisted selection for growth and immune traits in rabbits.