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Christian Maltecca

Publications

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Grants

Date: 07/01/23 - 6/30/26
Amount: $650,000.00
Funding Agencies: US Dept. of Agriculture - National Institute of Food and Agriculture (USDA NIFA)

The overall goal of this integrated proposal is to develop a functional genomics approach to identify genomic and epigenomic biomarkers and enable selective breeding of sows that are at a minimal risk of producing offspring that display the negative IUHS phenotypes (Fig. 1). The genomic selection models will be biologically validated using complementary measures of offspring behavior and physiology in response to production stressors, immune challenges, heat stress exposure, and the determination of transgenerational effects on the pig epigenome. The success of genomic selection for sows that are at a minimal risk of producing offspring that display the negative IUHS phenotypes depends on the availability of phenotypes that are heritable and repeatable, can be measured on a large number of animals, and that are representative of the postnatal consequences of IUHS in swine offspring.

Date: 04/01/21 - 12/31/25
Amount: $189,307.00
Funding Agencies: National Institute of Animal Science, RDA

The objective of this project is to identify opportunities to optimize swine production systems for efficiency of nutrient utilization spanning the spectrum of variability generated by the pig microbiome interactions. The existence of genetic control over the abundance of particular taxa and the link of these with energy balance and growth has been shown in model organisms. Little evidence has been so far presented in pigs. The gut microbiome is an essential component of variability of growth in several species. Swine do not escape this rule and the identification of the significance of gut microbiota in the growth process will be a game changer in the achievement of sustainable and efficient lean meat production. Within this proposal we will: Characterize the interaction between host and longitudinal microbiome development in swine and its effect on efficient growth, Model the genomic of longitudinal variability in microbiota development, Link the fecal and cecal luminal metagenomic communities in pigs, Integrate data generated by longitudinal analysis with already generated evidence. Making microbiome composition part of the breeding objective or directly manipulating the microbiome in populations under selection through diet or other artificial means could revolutionize the swine industry. We will identify efficient individuals at maintaining a favorable microbiome. We hypothesize that a portion of this ability is under genetic control making these individuals better able to cope with changes in dietary and environmental conditions. We propose an innovative approach to develop new selection methods using a combination of genomics and microbiome.

Date: 07/01/23 - 6/30/25
Amount: $300,000.00
Funding Agencies: US Dept. of Agriculture - National Institute of Food and Agriculture (USDA NIFA)

Though genomic selection has been successful in accelerating genetic improvement, we still know very little about the genetic architecture of quantitative traits. This poses a challenge for researchers to develop a model that can achieve the full potential of genomic evaluation. Recent progress on functional annotation of animal genomes (FAANG) provides an opportunity to address the challenge in hopes that the functional information can help to decipher the genotype-to-phenotype relationship; however, there is a lack of methods for effectively using a variety of functional annotations in quantitative genetic analysis. The goal of this proposal is to develop a unified mixed-model method for integrating functional annotations into genome-to-phenome analysis. Our method can 1) reveal the genetic architecture of quantitative traits by jointly quantifying the contributions of various functional annotations to quantitative trait variation, 2) identify trait-relevant tissues or cell-types by the analysis of tissue-/cell-type-specific functional annotations, and 3) improve genomic predictions by incorporating functional annotations. The project will be addressing three main objectives, aimed at 1) developing a unified method for incorporating numerous functional annotations simultaneously in mixed-model genetic analysis, 2) implementing the method in an efficient software tool, and 3) demonstrating the method with dairy cattle data sets. This project will provide one of the first methods for integrating FAANG data into various genetic analyses and present several demonstrations of its use.

Date: 07/01/22 - 6/30/25
Amount: $629,000.00
Funding Agencies: US Dept. of Agriculture - National Institute of Food and Agriculture (USDA NIFA)

While there is evidence of genetic variability for heat stress response in swine, there is a lack of (bio)markers that could allow the understanding and implementation of breeding programs aimed at selecting for a more heat tolerant sow. The use of the gut microbial flora as prognostic aid has been long investigated in humans and microbiota profiles related to heat stress could serve this function. The goal of this proposal is to develop an enhanced selection tool, including the most effective combination of gut microbiome and host genomic/metabolomic/phenomic features. We will extract these features from in-depth sow characterizations in research settings and translate them to a large-scale dataset collected at the commercial level. The project will be addressing two main objectives, aimed at 1) understanding how host genomic, metabolomic, and gut microbial features regulate sow tolerance to heat stress and their potential use as biomarkers and 2) developing microbiome-enhanced genomic prediction tool itself. The NCSU group (Dr. Tiezzi, Dr. Maltecca) is currently one of the most active in the USA working on the genomics of heat tolerance in swine and on the use of gut microbiome information in breeding programs. This project significantly expands the relevance of a current USDA-sponsored project (award number 2020-67015-31575), awarded to a part of the proposing investigators, adding gut microbiome, host transcriptomics and host metabolomics information. This project will provide the first omni-comprehensive characterization through unprecedented in-depth phenotyping. The project will also provide much-needed selection tools to exploit genomic selection for heat-tolerance in swine.     

Date: 07/01/20 - 12/31/23
Amount: $105,680.00
Funding Agencies: Select Sires, Inc.

The advent of genomic selection paved the way for an unprecedented acceleration in genetic progress. The increased ability to select superior individuals has been coupled with a drastic reduction in the generation interval for most dairy populations. This represents both an opportunity and a challenge. Homozygosity is now rapidly accumulating in dairy populations. Currently, inbreeding depression is managed mostly through culling at the farm level and by controlling the overall accumulation of homozygosity at the population level. A better understanding of how homozygosity and genomic load are related will guarantee continued genetic improvement while curtailing the accumulation of harmful recessives and maintain enough genetic variability to ensure the possibility of selection in the face of changing environmental conditions. In this proposal, we present a simple approach that can be used to control the accumulation of harmful recessives by penalizing recent inbreeding while maintaining sustained selection pressure.

Date: 07/01/20 - 6/30/23
Amount: $71,529.00
Funding Agencies: US Dept. of Agriculture - National Institute of Food and Agriculture (USDA NIFA)

This proposal addresses priorities of Diseases of Agricultural Animals (A1221): genomic/genetic or whole-animal aspects of animal health and disease as well as disease prevention and control such as breeding animals for disease resistance. We specifically focus on immune-related diseases including mastitis. Animal health is important for the dairy industry regarding profit, sustainability, labor, animal welfare, and consumer expectations. Mastitis and other cattle diseases directly cost 230 million dollars to the U.S dairy industry each year. After adding the indirect lost from reduced milk production, the total cost can easily exceed billions of dollars per year. Although host genetics only contribute to a small amount of variation in disease risk, genetic selection of health traits provides an economic and sustainable approach to deal with this health issue. The Council of Dairy Cattle Breeding and USDA Animal Genomics and Improvement Laboratory have included six common diseases including mastitis into the national genomic evaluation in 2018. Using the data from the US dairy genomics database, our genomic study and application will provide a better understanding the genetic mechanism of disease resistance and deliver a set of health SNPs to the industry to improve the selection of robust cows. The overall goal is to uncover the genetic mechanism of dairy health and to apply these genomic discoveries to improve cattle disease resistance and profitability of the dairy industry. Specific aims include: 1) Identify genomic regions and candidate genes associated with dairy health by using big data genome-wide association analysis of mastitis and other immune-related diseases; and 2) Combine sequence-level GWAS and functional annotation data to identify causal/tightly linked variants and apply them to optimize genomic selection of health traits. This project will be the largest such genomic study of disease resistance in dairy cattle and is expected to have a major impact on both dairy profitability and animal welfare.

Date: 06/01/20 - 5/31/23
Amount: $47,785.00
Funding Agencies: US Dept. of Agriculture - National Institute of Food and Agriculture (USDA NIFA)

This project aims at improving welfare and productivity of sows that undergo heat stress.

Date: 06/01/20 - 5/31/23
Amount: $47,714.00
Funding Agencies: US Dept. of Agriculture - National Institute of Food and Agriculture (USDA NIFA)

Declining fertility in dairy cattle is a serious threat to the profitability of dairy cattle. Fertility is one of the phenotypes affected most by crossbreeding. The discovery of genetic variants and their mechanism underlying reproductive heterosis will facilitate developing new strategies to improve dairy fertility. This proposed research is the first attempt to understand reproductive heterosis in dairy cattle and aims at the discovery and utilization of genetic variants and mechanisms underlying dairy reproductive heterosis for genetic improvement of dairy fertility. Specific objectives supporting this overall objective include: 1) Detect chromosome regions and assessing genetic mechanism associated with reproductive heterosis using genome-wide association study (GWAS); 2) Fine map and identify candidate causal variants underlying reproductive heterosis by an integrated analysis of comparative genomics, and 3) Improve Holstein using heterosis variants and mechanisms. This research will yield a list of genome variants associated reproductive heterosis and their specific effects potentially including additive, dominance and epistasis effects, verification and fine mapping 3 million SNPs from the sequence data of hypothetical HolsteinJersey crosses, functional relevance from mouse comparative analysis and from comparative analysis of genetic selection in Holstein cattle since 1964. The total contribution of all heterosis variants as well as the total contribution of candidate variants for gene editing will be estimated. The results from this research will be a significant contribution to the scientific understanding of reproductive heterosis in dairy cattle and to the genetic improvement of dairy fertility utilizing heterosis variants and mechanisms.

Date: 12/06/21 - 3/31/23
Amount: $76,781.00
Funding Agencies: Pepsico, Inc.

1) Literature review on genomic selection techniques in auto-polyploids (including auto-tetraploid potato) and other species where dominance variance may be present and utilized 2) Data Exploration and Preparation for Model Development : PepsiCo’s potato breeding program has genomic (8K SNP array) and phenotypic data (Target 3 traits: solids, field yield, chip color after storage) on a small number of new potato varieties in its advanced breeding stage (4th year) from an ~10 year period. The dataset consists of no more than 450 unique genotypes. Time is allocated to explore the dataset, familiarize with the traits, and prepare the dataset for downstream analysis. 3) polyBreedR Package Review: The R package polyBreedR was created by Jeff Endelman at UW and is considered the gold standard for auto-tetraploid potato genomic selection. PepsiCo is interested in having an outside expert review the package, the assumptions that are made, and to use the package on its data (item 2 above) to investigate its utility. Based on the literature review, exploration of PepsiCo’s data, and the findings of the polyBreedR package, other genomic selection modeling practices/approaches will be explored. It will be left up to the discretion of the researcher (Dr. Maltecca) to determine the exact number and type of models to test, and the best methods to perform model comparisons. Consideration should be applied to the investigation of methods that allow for different trait architectures to be modelled, as well the different types of genomic covariance matrices that may be included, as these variance types, if present, can be captured and selected upon in a clonally propagated crop like autotetraploid potato. This approach will be taken on the 3 phenotypic traits listed above.

Date: 09/15/21 - 12/31/22
Amount: $60,000.00
Funding Agencies: Elanco US Inc. (formerly Elanco Animal Health and Bayer Healthcare)

There is a growing body of evidence that the gut microbiome plays a fundamental role in animal health outcomes throughout life. The primary establishment of the microbiome is believed to occur at birth and shortly after in early lactation. We are interested in the microbiome relationship between the sow and piglet. Specifically, we hypothesize that the establishment of a healthy microbiome is transferred from the sow to the piglet in early life and the microbiome composition impacts piglet survivability and health outcomes long term. In this collaboration we seek to interrogate the following hypothesis: Is there an association with the microbiome composition and/or diversity in the piglet and piglet survivability. Aim 1: characterize the profile of a “healthy” microbiome in the sow & piglet that is associated with better health outcomes in piglets. Aim 2: characterize the fundamental source of the piglet microbiome prior to weaning.


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