Performing Department
(N/A)
Non Technical Summary
In utero heat stress (IUHS) is a threat to swine welfare that will become increasingly common as temperatures rise and extreme climatic events increase in frequency. Our group has demonstrated that IUHS causes a lifetime of poor health and welfare for pigs and have developed an effective model to study and characterize heat tolerance with a multidisciplinary perspective. Genomic selection is a promising IUHS mitigation strategy, given its permanent and cumulative gains over generations. This project will address the significant knowledge gap of heat stress tolerance in swine by taking a multi-dimensional analytical approach that integrates the effects ofgenomics, epigenomics, metagenomics, and metabolomicsto understand the transgenerational effects of IUHS in swine and its microbiome.This goal will be achieved efficiently, avoiding duplication of efforts, by leveraging current federally funded projects.The proposal will have two main objectivesObjective 1: To quantify the role of microbiota maturation in sows at a high or low risk of producing offspring displaying IUHS phenotypes.Objective 2: To develop a trans-generational multi-omics approach to identify genomic, microbiota, epigenomic, metabolomic biomarkers, that enable identifying sows at minimal risk of producing offspring with IUHS leveraging phenotypes from a behavioral and physiological model in genetically-divergent animals.Results from the current proposal will provide a comprehensive understanding of the mechanisms underlying the transgenerational effects of IUHS, develop biomarkers to be used to prioritize variants in genomic selection and help identifying, at an early stage, animals that could be more affected by transgenerational IUHS effects; thus allowing better management practices to reduce negative impact of IUHS.
Animal Health Component
100%
Research Effort Categories
Basic
50%
Applied
50%
Developmental
(N/A)
Goals / Objectives
Ourcentral hypothesisis that the risk factors for producing offspring that display the negative IUHS phenotypes across generations are controlled, to some extent, bymaternal and direct genetic and epigenetic components, the microbial makeup of individuals, and their interaction.This proposal aims to develop amulti-omics functional approachto identify genomic, epigenomic, microbial, and metabolomic biomarkers that will enable more accurate identification of sows at minimal risk of producing offspring that display the negative IUHS phenotypes in explaining tolerance and resilience to IUHS.Identifying appropriate biomarkers to aid genomic prediction models and optimize the use of genomic information routinely generated in commercial pig breeding farms is a crucial priority for the swine industry. The successful identification of sows at minimal risk of producing offspring that display the negative IUHS phenotypes depends on the availability of phenotypes and biomarkers that are heritable andWithin this proposal, we will disentangle the leading biological causes of the adverse effects of IUHS on the postnatal health, performance, and welfare of pigs through a comprehensive transgenerational multi-omics characterization of animals with divergent genetic merit for producing offspring that suffer from negative IUHS phenotypes.The specific objectives of the proposal, therefore, are as follows:Objective 1: To quantify the role of microbiota maturation in sows at a high or low risk of producing offspring displaying negative IUHS phenotypes.We hypothesize that microbiome composition and development play a significant role in shaping heat tolerance and postulate that genetic differences in maturation rate among pigs could be used as an additional criterion to select individuals better able to cope with heat stress.Objective 2: To develop a functional trans-generational multi-omics approach to identify genomic, microbiota, epigenomic, and metabolomic biomarkers that enable identifying sows at minimal risk of producing offspring IUHS leveraging phenotypes from an integrated behavioral and physiological model in genetically divergent animals.A group of divergently selected animals predicted to be atHigh RiskorLow Riskof producing offspring that display the negative IUHS phenotypeshas been generated from previous studies (see preliminary results). Here genomic, transcriptomic, and metabolomic variants measuredin parallel in the host and microbial communitiesacross three generations will be obtained from individuals genomically divergent for heat tolerance, for which in-depth behavioral and physiological assessments are being obtained. Furthermore, there is strong evidence of stable and heritable epigenetic markers (e.g., DNA methylation) impacting health, adaptation, heat tolerance, and performance. However, there are no trans-generational studies investigating how the DNA methylation patterns in pigs are related to climatic resilience, especially IUHS. We hypothesize that IUHS drives postnatal phenotypic changes by altering DNA methylation of key regulatory gene pathways associated with heat tolerance and other biological functions. As part of this objective, DNA methylation will be measuredthroughout the entire three generations of the experiment.Furthermore, a growing body of evidence links microbial composition to transgenerational effects on host phenotypes, directly affecting the parental generation's immune and metabolic functions and altering the progeny's methylation status. Most of these studies have been conducted in model organisms, and evidence of these potentially fundamental mechanisms is currently almost nonexistent in swine. Our research will assess methylation status and microbial composition (meta)transcriptome and (meta)metabolome on F1, F2, and F3 individuals. We will first determine whether genetically divergent individuals for heat tolerance also have different methylation and microbial profiles, whether epigenomic changes are passed across generations and whether the microbiome has a role in this mechanism. The epigenomic profiles and change patterns will then be correlated with whole-genome polymorphisms (SNPs), transcriptome, metabolome, and microbial compositions to identify biomarkers affecting epigenomic changes so that a greater emphasis can be placed on significant variants when predicting heat tolerance in pigs (i.e., biology-driven genomic prediction methods). Furthermore, F3 generation pregnant replacement gilts (derived from Objective 2) will be exposed to the same temperature cycles as their dams.
Project Methods
Obj1:Microbiome maturation plays a significant role in shaping heat tolerance and postulate that genetic differences in maturation rate among pigs could be used as an additional criterion to identify individuals better able to cope with heat stress. From the F0 population, we will identify 50 LR and 50 HR individuals based on their GEBV For these individuals, we will collect fecal microbiome at 10 time points from weaning to farrowing We will identify key statistical parameters for the microbiota maturation function of LR and HR pigs. Parameters will be established based on individuals' richness, evenness, and diversity. Absolute Richness Change (ARC) will be obtained. Similarly, the Absolute Evenness Change (AEC) will be obtained. Finally, the Absolute Diversity Change (ADC) will be obtained. We will develop individual prediction equations for the microbiota development curve.Obj2:LR gilts will be more thermotolerant and produce more viable and healthy offspring under heat stress conditions versus HR gilts. We further hypothesize that a combination of host (epi)genomic and microbiome effects will partially explain these differences. A group of 36 Landrace x Large white gilts with divergent genomic breeding values for IUHS progeny LR or HR will be selected from F0 progeny. Gilts will be housed in individual pens within 1 of 2 environmental chambers (n = 9 Low Risk and 9 High Risk gilts/chamber). One environmental chamber will be assigned to thermoneutral (TN) conditions , and one chamber will be assigned to HS conditions. Humidity will be maintained at 40-50% for all pigs. For HS, all pregnant gilts will be maintained under TN conditions for 5 d following artificial insemination. From d 6 to d 10 post-artificial insemination, cyclic HS temperatures of 26°C night-time to 32°C daytime will be applied to pregnant gilts. From d 11 to d 59 post-artificial insemination, cyclic HS temperatures of 28°C nighttime to 36°C day-time will be applied to pregnant gilts. From d 60 of gestation to farrowing, all pregnant gilts will be exposed to TN conditions. This procedure has been previously described and validated by our group. The treatment combinations will be (each 9 gilts): LR + TN; LR + HS; HR + TN; HR + HS.Microbiome evolution will be traced for all 36 gilts. Three time points will be sampled (feces):at the beginning of the experiment (5d after AI); at the end of HS; and at farrowing.At the end of the HS cycles for 4 LR + TN; 4 LR + HS; 4 HR + TN; 4 HR + HSwe will also collect material for the following essays: metabolome (blood), meta-metabolome (feces), transcriptome (blood), and meta-transcriptome (feces). Finally, from the 18 HR gilts at the end of HS cycles , we will measure methylation on 4 TN and 4 HS (4 HR TN; 4 HR HS).Microbial composition at each time point will be compared between LR and HR, and meaningful contrasts will be constructed for diversity measures and individual taxa. For all other omics measures, contrasts will be built for the main HR/LR effect as well as for HS TN within and across groups.We hypothesize that IUHS offspring derived from Low Risk replacement gilts will present a distinctive microbiome signature which will make it be more stress resistant when compared to IUHS offspring derived from High Risk replacement gilts.Piglets used in Exp. 2 (F2) will be derived from those generated in Exp. 1 40 pigs will be chosen to represent the following combinations (n = 10 for all): LR + IUTN; LR + IUHS; HR + IUTN; HR + IUHS. Pigs will be on trial from weaning until the end of the nursery phase . Pigs will be maintained in TN conditions. Stressor will be represented by the transitioning from nursery to weaning. Microbiome evolution will be traced for all 40 pigs. Five time points will be sampled from the beginning of the trial.Longitudinal measures developed in Objective #1 will be obtained and contrasted among the groups. IUHS offspring derived from High Risk replacement gilts will present a distinctive (epi)genome microbiome meta(transcriptome) and meta(metabolome) signature that will make it less thermotolerant when compared to IUTN offspring derived from High Risk replacement gilts.Piglets used in Exp. 3 will be derived from those generated in Exp. 1. From the 216 piglets remaining from (F1), 16 piglets evenly distributed across litters will be randomly selected (F2), representing the following combinations (n = 4 for all). HR + IUTN + TN; HR + IUTN +HS; HR + IUHS+TN; HR + IUHS+HS. The experiment will begin at week 17 of age. Seven days before the experiment, all pigs will be implanted intraperitoneally with calibrated thermochon temperature recorders. Pigs will be housed individually in environmental chambers, and the experiment will last 20 d. On d 1 to 6, all pigs will be maintained under constant TN conditions (TN-1; 18 to 22°C; 40-50% relative humidity). On d 7 to 12, all pigs will be exposed to cycling HS conditions (HS-1; 28 to 36°C; 40-50% relative humidity). On d 13 to 14, all pigs will be exposed to constant TN conditions (TN-2; 18 to 22°C; 40-50% relative humidity). On d 15 to 20, all pigs will be exposed to cycling HS conditions For all these individuals at d6 (TN) and d20 (end of HS), we will measure: microbiome, metabolome, meta-metabolome, and transcriptome. We will also measure whole-genome DNA methylation for 8 HR piglets (4 HR IUTN; 4 HR IUHS).Microbial composition at each time point will be compared between different groups, and meaningful contrasts will be constructed for diversity measures as well as individual taxa. For all other omics measures, contrasts will be constructed for the four groups at each of the time points evaluated. Changes in each measure will be contrasted within each group and across groups. In addition, each of the omics measures will be included in models explaining ancillary phenotypes. Finally, microbial composition will be associated with subsequent multi-omics measures.We hypothesize that IUHS alters DNA methylation of key regulatory gene pathways involved in HS physiology. We further hypothesize that microbial composition has transgenerational effects on host phenotypes, directly affecting the parental generation's immune and metabolic functions and altering the progeny's methylation status. By identifying genomic regions that are differentially methylated either directly or mediated by microbial composition and their associated genetic markers, we can optimize genomic selection for improved heat tolerance and reducing pig susceptibility to IUHS-induced epigenetic changes. Furthermore, we can identify remediation strategies through microbiome interventions to mitigate the effects of IUHS.Pigs in this experiment will be derived from those generated in Exp. 1. At the conclusion of Exp. 3, 32 replacement gilts (F3) will be selected to represent 8 groups (n= 4 for each group) within 1 of 2 environmental chambers (TN and HS) LR + IUTN + TN; LR + IUTN + HS; HR + IUTN + TN; HR+ IUTN + HS; LR+ IUHS + TN; LR + IUHS + HS; HR+ IUHS + TN; HR+ IUHS + HS. All gilts will be bred to the same Duroc sire and then exposed to the same temperature cycles as their dams as described in Exp 3.For all these individuals at d6 (TN) and d20 (end of HS) and farrowing, we will measure: microbiome. At d6 and d20, we will measure metabolome, meta-metabolome, transcriptome, and meta-transcriptome. Additionally, for all individuals, we will measure whole-genome DNA methylation ?Within experiment (generation), analyses will follow those described for Exp.3.