Identification of functional mutations associated with environmental variance of litter size in rabbits

Genomic insights into selection signatures and candidate genes for milk production traits in buffalo population

Genetic variability in livestock driven by selection leaves distinct signatures within the genome. However, the comprehensive landscape of the selection responses for milk production traits in the Chinese buffalo population remains elusive. This study employed an integrated haplotype score (iHS) and runs of homozygosity (ROH) analyses of whole-genome sequence data from 100 Chinese buffaloes to decipher selection signatures. Using iHS and ROH, we identified 1 046 and 1 045 significant genomic regions, containing 717 and 263 candidate genes, respectively. The integration of iHS and ROH revealed 258 candidate regions and 108 overlapping genes, representing true selection signatures. Additionally, 94 candidate regions overlapped with 672 previously reported quantitative trait loci associated with key economically important traits. Annotation of the genomic regions highlighted candidate genes linked to milk production traits, including SNORD42, COX18, ANKRD17, ALB, RASSF6, CXCL8, TMEM232, ARHGAP26, and NR3C1. Transcriptome-wide association analysis supported ANKRD17 and CEP41 as potential candidates for affecting milk traits. This study unveils a comprehensive selection signature profile for the Chinese buffalo population by integrating iHS and ROH methods. The findings have broad implications for improving milk production traits in buffalo populations globally, contributing to more sustainable livestock systems. The identified candidate genes shed light on the selection response for milk production traits, offering crucial insights into optimising the breeding strategies for Chinese buffaloes.

Variability of daily feed intake as an indicator of resilience in Pietrain pigs

There is a growing need to produce more resilient livestock that can cope with extreme environments and their associated impacts. Daily feed intake (DFI) is a promising metric for the development of resilience indicators (RIs), as reduced feed consumption is widely recognised as a clinical sign of disease. However, there is no consensus on which DFI-based RIs are the most informative. The objectives of this study were: (i) to evaluate the most common DFI-based RIs and their relationships with feed efficiency traits (FETs), (ii) to investigate the relationship between these indicators and progeny mortality rates on commercial farms, and (iii) to gain insight into their biological mechanisms. A total of 111 121 DFI records of 1 634 healthy purebred Pietrain boars were used, ranging from 47 to 90 days, with an average of 69 DFI records per boar. Three RIs were calculated: residual variance, RMSE and logarithm of the variance of the deviations from an expected pattern (LnVar). A classical animal model was used to estimate the variance components of each RI, and a bivariate model was implemented to estimate the genetic correlation between RIs and the FET. Furthermore, a preliminary mortality study was carried out using data from 6 889 progeny of 55 boars on farms catalogued as virulent for porcine reproductive and respiratory syndrome. Progeny mortality was calculated for each contemporary group (farm and batch) of the offspring, and sires were classified into three levels of resilience. A Bayesian linear model was used to determine whether the differences in progeny mortality rate between the levels of resilience were relevant. On the other hand, a weighted single-step genome-wide association study was performed for each RI and the FET, using a total of 1 216 genotypes. RIs showed moderate heritability (h2 = 0.27-0.49) and moderate to strong genetic correlation with FET. Progeny of resilient sires had an 80% probability of at least a 2.5% higher survival rate. Overlapping genomic regions were found for RIs and feed conversion ratio, highlighting DOCK1, SYK and SPTLC1 genes for their potential roles in modulating immune responses and/or metabolism. The LnVar of deviations from the population mean was the most promising indicators (LnVar-Pop) for disease resilience, as it was the RI that better captured differences in progeny mortality. Furthermore, these results suggest a common biological basis for RIs and FET of interest to breeding programmes. Further studies are needed to validate them.

Adaptation in the Alleyways: Candidate Genes Under Potential Selection in Urban Coyotes

In the context of evolutionary time, cities are an extremely recent development. Although our understanding of how urbanization alters ecosystems is well developed, empirical work examining the consequences of urbanization on adaptive evolution remains limited. To facilitate future work, we offer candidate genes for one of the most prominent urban carnivores across North America. The coyote (Canis latrans) is a highly adaptable carnivore distributed throughout urban and nonurban regions in North America. As such, the coyote can serve as a blueprint for understanding the various pathways by which urbanization can influence the genomes of wildlife via comparisons along urban-rural gradients, as well as between metropolitan areas. Given the close evolutionary relationship between coyotes and domestic dogs, we leverage the well-annotated dog genome and highly conserved mammalian genes from model species to outline how urbanization may alter coyote genotypes and shape coyote phenotypes. We identify variables that may alter selection pressure for urban coyotes and offer suggestions of candidate genes to explore. Specifically, we focus on pathways related to diet, health, behavior, cognition, and reproduction. In a rapidly urbanizing world, understanding how species cope and adapt to anthropogenic change can facilitate the persistence of, and coexistence with, these species.

Sequence variants associated with resilient responses in growing pigs

The current work aimed to identify genomic regions and candidate genes associated with resilience in pigs. In previous work, we proposed the body weight deviation from the expected growth curve (ΔBW) and the increase of the positive acute-phase protein haptoglobin (ΔHP) after a vaccine challenge as resilience indicators which may be improved through selective breeding in pigs. Individuals with steady growth rate and minor activation of haptoglobin (high ΔBW and low ΔHP values) were considered resilient. In contrast, pigs with perturbed growth rate and high activation of haptoglobin (low ΔBW and high ΔHP values) were considered susceptible. Both ∆BW and ∆HP were simultaneously considered to select the most resilient (N = 40) and susceptible (N = 40) pigs. A genome-wide association study was carried out for the pigs' response classification to the challenge test using whole-genome sequence data (7,760,720 variants). Eleven associated genomic regions were identified, harbouring relevant candidate genes related to the immune response (such as pro- and anti-inflammatory responses) and growth pathways. These associated genomic regions harboured 41 potential functional mutations (frameshift, splice donor, splice acceptor, start loss and stop loss/gain) in candidate genes. Overall, this study advances our knowledge about the genetic determinism of resilience, highlighting its polygenic nature and strong relationship with immunity and growth.

Selection for Resilience in Livestock Production Systems

Selective breeding for improved animal resilience is becoming critical to increase the sustainability of production systems. Despite the existence of a genetic component for resilience, breeding for improved resilience has been limited by the absence of a consensus on its definition and quantifying method. In this work, we provide a review of (i) the definition of resilience and related concepts such as robustness, resistance, and tolerance; (ii) possible quantifying methods for resilience; (iii) its genetic background; and (iv) insights about its improvement through selective breeding. We suggest that a resilient animal may be defined as an individual that is able to cope with a perturbation(s) and rapidly bounce back to normal functioning if altered. Furthermore, since challenging conditions lead to trade-offs and, consequently, deviations between basic physiological functions, we suggest using these deviations as indicators for resilience. These resilience indicators may also be used as proxies to study the genetic determinism and background of resilience in livestock species. Finally, we discuss possible strategies to improve resilience and review the implementation of associated genetic markers for resilience indicators in selection schemes.

Capturing resilience from phenotypic deviations: a case study using feed consumption and whole genome data in pigs

BACKGROUND

In recent years, interest has grown in quantifying resilience in livestock by examining deviations in target phenotypes. This method is based on the idea that variability in these phenotypes reflects an animal's ability to adapt to external factors. By utilizing routinely collected time-series feed intake data in pigs, researchers can obtain a broad measure of resilience. This measure extends beyond specific conditions, capturing the impact of various unknown external factors that influence phenotype variations. Importantly, this method does not require additional phenotyping investments. Despite growing interest, the relationship between resilience indicators-calculated as deviations from longitudinally recorded target traits-and the mean of those traits remains largely unexplored. This gap raises the risk of inadvertently selecting for the mean rather than accurately capturing true resilience. Additionally, distinguishing between random phenotype fluctuations (white noise) and structural variations linked to resilience poses a challenge. With the aim of developing general resilience indicators applicable to commercial swine populations, we devised four resilience indicators utilizing daily feed consumption as the target trait. These include a canonical resilience indicator (BALnVar) and three novel ones (BAMaxArea, SPLnVar, and SPMaxArea), designed to minimize noise and ensure independence from daily feed consumption. We subsequently integrated these indicators with Whole Genome Sequencing using SLEMM algorithm, data from 1,250 animals to assess their efficacy in capturing resilience and their independence from the mean of daily feed consumption.

RESULTS

Our findings revealed that conventional resilience indicators failed to differentiate from the mean of daily feed consumption, underscoring potential limitations in accurately capturing true resilience. Notably, significant associations involving conventional resilience indicators were identified on chromosome 1, which is commonly linked to body weight.

CONCLUSION

We observed that deviations in feed consumption can effectively serve as indicators for selecting resilience in commercial pig farming, as confirmed by the identification of genes such as PKN1 and GYPC. However, the identification of other genes, such as RNF152, related to growth, suggests that common resilience quantification methods may be more closely related to the mean of daily feed consumption rather than capturing true resilience.

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.

A first characterization of the microbiota-resilience link in swine

BACKGROUND

The gut microbiome plays a crucial role in understanding complex biological mechanisms, including host resilience to stressors. Investigating the microbiota-resilience link in animals and plants holds relevance in addressing challenges like adaptation of agricultural species to a warming environment. This study aims to characterize the microbiota-resilience connection in swine. As resilience is not directly observable, we estimated it using four distinct indicators based on daily feed consumption variability, assuming animals with greater intake variation may face challenges in maintaining stable physiological status. These indicators were analyzed both as linear and categorical variables. In our first set of analyses, we explored the microbiota-resilience link using PERMANOVA, α-diversity analysis, and discriminant analysis. Additionally, we quantified the ratio of estimated microbiota variance to total phenotypic variance (microbiability). Finally, we conducted a Partial Least Squares-Discriminant Analysis (PLS-DA) to assess the classification performance of the microbiota with indicators expressed in classes.

RESULTS

This study offers four key insights. Firstly, among all indicators, two effectively captured resilience. Secondly, our analyses revealed robust relationship between microbial composition and resilience in terms of both composition and richness. We found decreased α-diversity in less-resilient animals, while specific amplicon sequence variants (ASVs) and KEGG pathways associated with inflammatory responses were negatively linked to resilience. Thirdly, considering resilience indicators in classes, we observed significant differences in microbial composition primarily in animals with lower resilience. Lastly, our study indicates that gut microbial composition can serve as a reliable biomarker for distinguishing individuals with lower resilience.

CONCLUSION

Our comprehensive analyses have highlighted the host-microbiota and resilience connection, contributing valuable insights to the existing scientific knowledge. The practical implications of PLS-DA and microbiability results are noteworthy. PLS-DA suggests that host-microbiota interactions could be utilized as biomarkers for monitoring resilience. Furthermore, the microbiability findings show that leveraging host-microbiota insights may improve the identification of resilient animals, supporting their adaptive capacity in response to changing environmental conditions. These practical implications offer promising avenues for enhancing animal well-being and adaptation strategies in the context of environmental challenges faced by livestock populations. Video Abstract.

Selection for environmental variance shifted the gut microbiome composition driving animal resilience

BACKGROUND

Understanding how the host's microbiome shapes phenotypes and participates in the host response to selection is fundamental for evolutionists and animal and plant breeders. Currently, selection for resilience is considered a critical step in improving the sustainability of livestock systems. Environmental variance (V _E), the within-individual variance of a trait, has been successfully used as a proxy for animal resilience. Selection for reduced V _E could effectively shift gut microbiome composition; reshape the inflammatory response, triglyceride, and cholesterol levels; and drive animal resilience. This study aimed to determine the gut microbiome composition underlying the V _E of litter size (LS), for which we performed a metagenomic analysis in two rabbit populations divergently selected for low (n = 36) and high (n = 34) V _E of LS. Partial least square-discriminant analysis and alpha- and beta-diversity were computed to determine the differences in gut microbiome composition among the rabbit populations.

RESULTS

We identified 116 KEGG IDs, 164 COG IDs, and 32 species with differences in abundance between the two rabbit populations studied. These variables achieved a classification performance of the V _E rabbit populations of over than 80%. Compared to the high V _E population, the low V _E (resilient) population was characterized by an underrepresentation of Megasphaera sp., Acetatifactor muris, Bacteroidetes rodentium, Ruminococcus bromii, Bacteroidetes togonis, and Eggerthella sp. and greater abundances of Alistipes shahii, Alistipes putredinis, Odoribacter splanchnicus, Limosilactobacillus fermentum, and Sutterella, among others. Differences in abundance were also found in pathways related to biofilm formation, quorum sensing, glutamate, and amino acid aromatic metabolism. All these results suggest differences in gut immunity modulation, closely related to resilience.

CONCLUSIONS

This is the first study to show that selection for V _E of LS can shift the gut microbiome composition. The results revealed differences in microbiome composition related to gut immunity modulation, which could contribute to the differences in resilience among rabbit populations. The selection-driven shifts in gut microbiome composition should make a substantial contribution to the remarkable genetic response observed in the V _E rabbit populations. Video Abstract.

Effect of environmental variance-based resilience selection on the gut metabolome of rabbits

BACKGROUND

Gut metabolites are key actors in host-microbiota crosstalk with effect on health. The study of the gut metabolome is an emerging topic in livestock, which can help understand its effect on key traits such as animal resilience and welfare. Animal resilience has now become a major trait of interest because of the high demand for more sustainable production. Composition of the gut microbiome can reveal mechanisms that underlie animal resilience because of its influence on host immunity. Environmental variance (VE), specifically the residual variance, is one measure of resilience. The aim of this study was to identify gut metabolites that underlie differences in the resilience potential of animals originating from a divergent selection for VE of litter size (LS). We performed an untargeted gut metabolome analysis in two divergent rabbit populations for low (n = 13) and high (n = 13) VE of LS. Partial least square-discriminant analysis was undertaken, and Bayesian statistics were computed to determine dissimilarities in the gut metabolites between these two rabbit populations.

RESULTS

We identified 15 metabolites that discriminate rabbits from the divergent populations with a prediction performance of 99.2% and 90.4% for the resilient and non-resilient populations, respectively. These metabolites were suggested to be biomarkers of animal resilience as they were the most reliable. Among these, five that derived from the microbiota metabolism (3-(4-hydroxyphenyl)lactate, 5-aminovalerate, and equol, N6-acetyllysine, and serine), were suggested to be indicators of dissimilarities in the microbiome composition between the rabbit populations. The abundances of acylcarnitines and metabolites derived from the phenylalanine, tyrosine, and tryptophan metabolism were low in the resilient population and these pathways can, therefore impact the inflammatory response and health status of animals.

CONCLUSIONS

This is the first study to identify gut metabolites that could act as potential resilience biomarkers. The results support differences in resilience between the two studied rabbit populations that were generated by selection for VE of LS. Furthermore, selection for VE of LS modified the gut metabolome, which could be another factor that modulates animal resilience. Further studies are needed to determine the causal role of these metabolites in health and disease.

A genome-wide screen for resilient responses in growing pigs

Background

There is a growing interest to decipher the genetic background of resilience and its possible improvement through selective breeding. The objective of the present study was to provide new insights into the genetic make-up of resilience in growing pigs by identifying genomic regions and candidate genes associated with resilience indicators. Commercial Duroc pigs were challenged with an attenuated Aujeszky vaccine at 12 weeks of age. Two resilience indicators were used: deviation from the expected body weight at 16 weeks of age given the growth curve of non-vaccinated pigs (∆BW) and the increase in acute-phase protein haptoglobin at four days post-vaccination (∆HP). Genome-wide association analyses were carried out on 445 pigs, using genotypes at 41,165 single nucleotide polymorphisms (SNPs) and single-marker and Bayesian multiple-marker regression approaches.

Results

Genomic regions on pig chromosomes 2, 8, 9, 11 (∆BW) and 8, 9, 13 (∆HP) were found to be associated with the resilience indicators and explained high proportions of their genetic variance. The genomic regions that were associated explained 27 and 5% of the genetic variance of ∆BW and ∆HP, respectively. These genomic regions harbour promising candidate genes that are involved in pathways related to immune response, response to stress, or signal transduction (CD6, PTGDR2, IKZF1, RNASEL and MYD88), and growth (GRB10 and LCORL).

Conclusions

Our study identified novel genomic regions that are associated with two resilience indicators (∆BW and ∆HP) in pigs. These associated genomic regions harbour potential candidate genes involved in immune response and growth pathways, which emphasise the strong relationship between resilience and immune response.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-022-00739-1.

Selection for environmental variance of litter size in rabbits involves genes in pathways controlling animal resilience

Background

Environmental variance (V_E) is partially under genetic control, which means that the V_E of individuals that share the same environment can differ because they have different genotypes. Previously, a divergent selection experiment for V_E of litter size (LS) during 13 generations in rabbit yielded a successful response and revealed differences in resilience between the divergent lines. The aim of the current study was to identify signatures of selection in these divergent lines to better understand the molecular mechanisms and pathways that control V_E of LS and animal resilience. Three methods (F_ST, ROH and varLD) were used to identify signatures of selection in a set of 473 genotypes from these rabbit lines (377) and a base population (96). A whole-genome sequencing (WGS) analysis was performed on 54 animals to detect genes with functional mutations.

Results

By combining signatures of selection and WGS data, we detected 373 genes with functional mutations in their transcription units, among which 111 had functions related to the immune system, stress response, reproduction and embryo development, and/or carbohydrate and lipid metabolism. The genes TTC23L, FBXL20, GHDC, ENSOCUG00000031631, SLC18A1, CD300LG, MC2R, and ENSOCUG00000006264 were particularly relevant, since each one carried a functional mutation that was fixed in one of the rabbit lines and absent in the other line. In the 3ʹUTR region of the MC2R and ENSOCUG00000006264 genes, we detected a novel insertion/deletion (INDEL) variant.

Conclusions

Our findings provide further evidence in favour of V_E as a measure of animal resilience. Signatures of selection were identified for V_E of LS in genes that have a functional mutation in their transcription units and are mostly implicated in the immune response and stress response pathways. However, the real implications of these genes for V_E and animal resilience will need to be assessed through functional analyses.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00653-y.

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.

Novel Genomic Regions Associated with Intramuscular Fatty Acid Composition in Rabbits

Intramuscular fat (IMF) content and its composition affect the quality of meat. Selection for IMF generated a correlated response on its fatty acid composition. The increase of IMF content is associated with an increase of its saturated (SFA) and monounsaturated (MUFA) fatty acids, and consequently a decrease of polyunsaturated fatty acids (PUFA). We carried out a genome wide association study (GWAS) for IMF composition on two rabbit lines divergently selected for IMF content, using a Bayes B procedure. Association analyses were performed using 475 individuals and 90,235 Single Nucleotide Polymorphisms (SNPs). The main objectives were to identify genomic regions associated with the IMF composition and to generate a list of candidate genes. Genomic regions associated with the intramuscular fatty acid composition were spread across different rabbit chromosomes (OCU). An important region at 34.0-37.9 Mb on OCU1 was associated with C14:0, C16:0, SFA, and C18:2n6, explaining 3.5%, 11.2%, 11.3%, and 3.2% of the genomic variance, respectively. Another relevant genomic region was found to be associated at 46.0-48.9 Mb on OCU18, explaining up to 8% of the genomic variance of MUFA/SFA. The associated regions harbor several genes related to lipid metabolism, such as SCD, PLIN2, and ERLIN1. The main genomic regions associated with the fatty acids were not previously associated with IMF content in rabbits. Nonetheless, MTMR2 is the only gene that was associated with both the IMF content and composition in rabbits. Our study highlighted the polygenic nature of the fatty acids in rabbits and elucidated its genetic background.

Inflammatory Correlated Response in Two Lines of Rabbit Selected Divergently for Litter Size Environmental Variability

A divergent selection experiment for environmental variance of litter size variance was carried out in rabbits over thirteen generations. The aim of this study was to evaluate the inflammatory response in the two lines of the experiment, in order to analyse the effect of selection on susceptibility to diseases after challenging to stressful situations, such as 24 h after the first delivery. A total of 78 females were used in this study, 39 from each line. The line selected for litter size heterogeneity (the high line) showed lower white blood leukocyte count (WBC; -0.87 × 103/µL), lower percentage of basophils (-0.11%), higher concentration of TNF-α (+13.8 pg/mL), and greater concentration of CRP (+38.1 µg/mL) than the line selected for litter size homogeneity (the low line). The high line had also higher concentrations of bilirubin, cholesterol, gamma-glutamyl transferase (GGT) and alkaline phosphatase (ALP) compared to the low line (difference between lines were +0.08 µmol/L, +0.14 µmol/L, +0.35 U/L and +2.4 U/L, respectively). The high line showed higher inflammatory response than the low line, in accordance with a larger susceptibility to infectious disorders. In conclusion, the line selected to increase litter size environmental variability seems to have poor capacity coping with environmental stressors. Therefore, selection for litter size environmental variability can be a useful way to improve animal welfare.