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ARS Home » Plains Area » Clay Center, Nebraska » U.S. Meat Animal Research Center » Genetics and Animal Breeding » Research » Research Project #433845

Research Project: Identifying Genomic Solutions to Improve Efficiency of Swine Production

Location: Genetics and Animal Breeding

2020 Annual Report

Objective 1: Utilize next-generation sequencing technologies to improve the contiguity of the swine genome assembly and better characterize genomic variation in pigs. Subobjective 1.A: Utilize segregation analysis to improve the porcine genome assembly. Subobjective 1.B: Develop more comprehensive gene models for the swine genome. Subobjective 1.C: Develop an electronic warehouse of genomic variants that can be utilized by the swine genomics research community. Objective 2: Develop genotyping products for commercial swine producers to increase the efficiency of swine production. Subobjective 2.A: Identify predictive genetic markers for traits associated with production efficiency in commercial swine populations. Subobjective 2.B: Develop strategies for inclusion of predictive markers in selection programs.

The principal goals of this project are to enhance our understanding of the biological processes important to swine production and provide the U.S. swine industry with genetic tools that will ensure that it remains the global leader in providing safe, nutritious, and economic pork products. The swine industry has been faced with significant challenges, many of which revolve around the production and performance of feeder pigs. The environment in which females are housed is continually evolving, and the increasing cost of feed has resulted in continuous shifts in the utilization of feed stuffs. Each new challenge requires an assessment of potential solutions. Genetic selection can be used to address many production issues. If DNA variants associated with changes in phenotype can be identified, then marker assisted selection can be implemented to expedite genetic progress. Predictive genetic markers need to be transferred to commercial entities that will rapidly evaluate and adopt them. The increasing improvements to the porcine genome, better annotations of genes from model organisms, and enhanced bioinformatics technologies provide researchers with the necessary tools to identify functional genetic variants. Objective 1 focuses on improving the porcine genome assembly and detecting polymorphisms from data generated by next-generation sequencing. Objective 2 will strive to effectively transfer the results of the research from Objective 1 to producers. Development of marker panels along with economical genotyping platforms will be essential. Our research will focus on the evaluation of genetic markers based on their predicted effects on gene products to discover causal genetic variants of phenotypic variation. This will lead to the development of marker panels and economical genotyping platforms for industry applications.

Progress Report
Progress has been made for all subobjectives this fiscal year. Objective 1A saw the publication of the updated genome sequence for the pig, an assembly with a magnitude of improvement in number of contigs and contig length. Research to support Objective 1B, develop more comprehensive porcine gene models, sequencing of the duodenum, ileum, and jejunum transcriptomes was conducted. Paired-end RNA-Seq libraries for each of the three tissues in 30 animals with divergent feed efficiency phenotypes were constructed, and sequencing was carried out on an Illumina NextSeq500 instrument, resulting in approximately 5.5 billion sequence reads being generated across the libraries. Read mapping percentages in the libraries were quite high, with averages of 98.25%, 99.47%, and 99.59% for duodenum, ileum, and jejunum, respectively. In addition, collection of pubertal phenotypes, tissues and genotypes from non-cycling gilts after 240 days of age has continued. Currently there are nearly 1500 records for non-cycling gilts and controls totaling 745 delayed puberty (no ovulation or estrus) and 747 behavioral anestrus gilts (no estrus but with at least one ovulation event). Tissues for RNAseq analysis have been collected from Yorkshire and Landrace sired females. RNA sequencing from medial basal hypothalamus, pituitary and hippocampal tissues from delayed puberty, behavioral anestrus and the appropriate control gilts has been completed. RNA-seq analysis has been completed for medial basal hypothalamus, amygdala, pituitary and hippocampal tissues. RNA-seq libraries are being constructed from ovarian tissue from delayed puberty, behavioral anestrus and the appropriate control gilts. Over 19,000 genes were expressed in the hypothalamus, amygdala, pituitary and hippocampal tissues at measurable levels and differential gene expression of hippocampus and amygdala showed a small number of genes differentially expressed between non-cycling gilts and controls, while pituitary had the greatest number (600) of differentially expressed genes (DEG). Normal cycling gilts had 61 to 124 genes differentially expressed in hippocampus and amygdala, respectively, depending upon their stage of the estrus cycle. And finally, to improve gene models in the porcine genome (Objective 1B), total RNA-Seq libraries from colostrum and mature milk samples, taken from 65 sows across parities 1-4, were sequenced. A stringent bioinformatic pipeline was used to identify and characterize 44,234 transcripts. These included 41,875 previously annotated transcripts and 2,359 novel transcripts. Differential gene expression analysis was conducted using a generalized linear model coupled with the Lancaster method for P-value aggregation across transcripts. In total, 1,900 DEG were identified for the milk type main effect, and 373 DEG were identified for the milk type x parity interaction. Gene ontology (GO) related to signaling receptor activity were significantly enriched in the milk x parity interaction DEG list, while GO terms related to signal transduction, cell adhesion, immune system process, inflammatory response, and ion transport were significantly enriched in the milk type DEG. Pathway analysis determined that extra cellular matrix (ECM)-receptor interaction, protein digestion and absorption, focal adhesion, and amoebiasis pathways were significantly enriched in the milk type DEG set. As reported in fiscal year 2018, a total of 240 animals from our resource populations have been deeply sequenced using short-read technologies to detect segregating genetic variation, and a total of 26,850,263 single nucleotide polymorphisms (SNP) have been identified (Objective 1C). Imputation to whole-genome sequence (WGS) level variants is an open problem in genomics research. Inaccurate imputation can influence the results of follow-up analyses such as genome-wide association studies (GWAS), especially when the accuracy of imputation is ignored in those analyses. Low coverage whole genome sequencing (lcWGS)(for example, 0.5× coverage) followed by imputation is a potential alternative to genotyping arrays for assessing the common genetic variants needed for GWAS and genomic prediction. Several recent studies have investigated the efficiency and accuracy of lcWGS for these applications, but currently, no “gold-standard” approach exists. As part of the effort to identify functional SNP in the swine genome (Objective 2A), a low-cost lcWGS approach, which utilizes random primers to capture non-targeted sequence across the genome, is being evaluated for use in imputation. Currently, 48 animals have been genotyped on this platform. ARS researchers in Clay Center, Nebraska, are also in the process of evaluating a commercial product to do similar imputation with a sample of 192 industry animals. ARS researchers in Clay Center, Nebraska, continue to collect phenotypic and genotypic data to support Objective 2A. As mentioned, pubertal phenotypes continue to be collected, along with data on about 1,150 feed efficiency animals and about 500 sows for lifetime productivity. In addition to these standard phenotypes, data for a sister project is being collected to evaluate structural soundness using objective measures. Approximately 2,500 gilts and nearly 1,000 sows have been evaluated to date. Research for Objective 2B has released version 2 of a genotyping platform which contains putative loss of function genetic variants (SowPro91). With this genotyping tool, over 2,000 non-cycling and control gilts were genotyped for 240 predicted functional variants in candidate genes for delayed puberty and behavioral anestrus. Candidate genes were identified from GWAS for these traits and whole-genome sequencing of commercial-type pigs. Preliminary analysis identified about 54 variants in 14 genes that were associated with delayed puberty and 22 variants in 14 genes that were associated with behavioral anestrus. In fiscal year 2019, a tensor decomposition approach, which utilizes gene expression data to guide GWAS, was reported. This method was used to identify 36 SNP that were associated with swine feed efficiency. As a follow up to this study and part of the effort to identify predictive markers (Objective 2B), a genotype-by-sequence panel, featuring those 36 SNP, was developed. Currently, 48 animals, whose genotypes were used in the tensor decomposition project, have been genotyped on this platform, and their genotypes have been shown to be concordant with those from commercial SNP arrays. DNA extractions for an additional 784 animals, with recorded feed efficiency phenotypes, is underway, and will be genotyped with this new panel.

1. Characterization of porcine colostrum and mature milk transcriptomes across multiple parities. Piglet growth and survival are critical to the swine industry. Progeny born to primiparous sows (gilts) are born lighter, grow slower, and have higher mortality rates than those born to multiparous sows. It has been hypothesized that differences in lifetime performance between progeny of gilts versus sows may be due to differences in lactation performance, yet a very limited number of transcriptomic studies related to porcine milk production have ever been reported. ARS scientists at Clay Center, Nebraska, performed RNA-sequencing on porcine colostrum and mature milk samples, from parity one through parity four females, to characterize gene expression differences between colostrum and mature milk across parities. A total of 44,234 transcripts were identified in the samples, including 2,359 novel transcripts. A total of 1,900 genes were determined to be differentially expressed between colostrum and mature milk samples, regardless of parity, and 373 genes were differentially expressed between colostrum and mature milk across parity. Many of these genes are involved in immune response, cellular transport, and cell adhesion. Several highly specialized, functional candidate genes identified likely contribute to postnatal growth and development as well as survival of piglets, which is a major concern of the industry.

Review Publications
Keel, B.N., Snelling, W.M., Lindholm-Perry, A.K., Oliver, W.T., Kuehn, L.A., Rohrer, G.A. 2020. Using SNP weights derived from gene expression modules to improve GWAS power for feed efficiency in pigs. Frontiers in Genetics. 10:1339.
Leonard, S.M., Xin, H., Brown-Brandl, T.M., Ramirez, B.C., Dutta, S., Rohrer, G.A. 2020. Effects of farrowing stall layout and number of heat lamps on sow and piglet production performance. Animals. 10(2).Article 348.
Lindholm-Perry, A.K., Freetly, H.C., Oliver, W.T., Rempel, L.A., Keel, B.N. 2020. Genes associated with body weight gain and feed intake identified by meta-analysis of the mesenteric fat from crossbred beef steers. PLoS One. 15(1):e0227154.
Cross, A.J., Brown-Brandl, T.M., Keel, B.N., Cassady, J.P., Rohrer, G.A. 2020. Feeding behavior of grow-finish swine and the impacts of heat stress. Translational Animal Science. 4(2):986-992.
Warr, A., Affara, N., Aken, B., Beiki, H., Bickhart, D.M., Billis, K., Chow, W., Eory, L., Finlayson, H.A., Flicek, P., Giron, C.G., Griffin, D.K., Hall, R., Hannum, G., Hourlier, T., Howe, K., Hume, D.A., Izuogu, O., Kim, K., Koren, S., Liu, H., Manchanda, N., Martin, F.J., Nonneman, D.J., O'Connor, R.E., Phillippy, A.M., Rohrer, G.A., Rosen, B.D., Rund, L.A., Sargent, C.A., Schook, L.B., Schroeder, S.G., Shwartz, A.S., Skinner, B.M., Talbot, R., Tseng, E., Tuggle, C.K., Watson, M., Smith, T.P., Archibald, A.L. 2020. An improved pig reference genome sequence to enable pig genetics and genomics research. GigaScience. 9(6):giaa051.