Toward a data infrastructure for the Plant Cell Atlas.

We review how a data infrastructure for the Plant Cell Atlas might be built using existing infrastructure and platforms. The Human Cell Atlas has developed an extensive infrastructure for human and mouse single cell data, while the European Bioinformatics Institute has developed a Single Cell Expression Atlas, that currently houses several plant data sets. We discuss issues related to appropriate ontologies for describing a plant single cell experiment. We imagine how such an infrastructure will enable biologists and data scientists to glean new insights into plant biology in the coming decades, as long as such data are made accessible to the community in an open manner.

Assessment of DNA methylation in porcine immune cells reveals novel regulatory elements associated with cell-specific gene expression and immune capacity traits.

BACKGROUND: Genetics studies in the porcine immune system have enhanced selection practices for disease resistance phenotypes and increased the efficacy of porcine models in biomedical research; however limited functional annotation of the porcine immunome has hindered progress on both fronts. Among epigenetic mechanisms that regulate gene expression, DNA methylation is the most ubiquitous modification made to the DNA molecule and influences transcription factor binding as well as gene and phenotype expression. Human and mouse DNA methylation studies have improved mapping of regulatory elements in these species, but comparable studies in the pig have been limited in scope. RESULTS: We performed whole-genome bisulfite sequencing to assess DNA methylation patterns in nine pig immune cell populations: CD21+ and CD21- B cells, four T cell fractions (CD4+, CD8+, CD8+CD4+, and SWC6γδ+), natural killer and myeloid cells, and neutrophils. We identified 54,391 cell differentially methylated regions (cDMRs), and clustering by cDMR methylation rate grouped samples by cell lineage. 32,737 cDMRs were classified as cell lowly methylated regions (cLMRs) in at least one cell type, and cLMRs were broadly enriched in genes and regions of intermediate CpG density. We observed strong correlations between differential methylation and expression across immune cell populations, with cell-specific low methylation disproportionately impacting genes exhibiting enriched gene expression in the same cell type. Motif analysis of cLMRs revealed cell type-specific enrichment of transcription factor binding motifs, indicating that cell-specific methylation patterns may influence accessibility by trans-acting factors. Lastly, cDMRs were enriched for immune capacity GWAS SNPs, and many such overlaps occurred within genes known to influence immune cell development and function (CD8B, NDRG1). CONCLUSION: Our DNA methylation data improve functional annotation of the porcine genome through characterization of epigenomic regulatory patterns that contribute to immune cell identity and function, and increase the potential for identifying mechanistic links between genotype and phenotype.

Swine models for translational oncological research: an evolving landscape and regulatory considerations.

Swine biomedical models have been gaining in popularity over the last decade, particularly for applications in oncology research. Swine models for cancer research include pigs that have severe combined immunodeficiency for xenotransplantation studies, genetically modified swine models which are capable of developing tumors in vivo, as well as normal immunocompetent pigs. In recent years, there has been a low success rate for the approval of new oncological therapeutics in clinical trials. The two leading reasons for these failures are either due to toxicity and safety issues or lack of efficacy. As all therapeutics must be tested within animal models prior to clinical testing, there are opportunities to expand the ability to assess efficacy and toxicity profiles within the preclinical testing phases of new therapeutics. Most preclinical in vivo testing is performed in mice, canines, and non-human primates. However, swine models are an alternative large animal model for cancer research with similarity to human size, genetics, and physiology. Additionally, tumorigenesis pathways are similar between human and pigs in that similar driver mutations are required for transformation. Due to their larger size, the development of orthotopic tumors is easier than in smaller rodent models; additionally, porcine models can be harnessed for testing of new interventional devices and radiological/surgical approaches as well. Taken together, swine are a feasible option for preclinical therapeutic and device testing. The goals of this resource are to provide a broad overview on regulatory processes required for new therapeutics and devices for use in the clinic, cross-species differences in oncological therapeutic responses, as well as to provide an overview of swine oncology models that have been developed that could be used for preclinical testing to fulfill regulatory requirements.

Quantitative analysis of the blood transcriptome of young healthy pigs and its relationship with subsequent disease resilience.

BACKGROUND: Disease resilience, which is the ability of an animal to maintain performance under disease, is important for pigs in commercial herds, where they are exposed to various pathogens. Our objective was to investigate population-level gene expression profiles in the blood of 912 healthy F1 barrows at ~ 27 days of age for associations with performance and health before and after their exposure to a natural polymicrobial disease challenge at ~ 43 days of age. RESULTS: Most significant (q < 0.20) associations of the level of expression of individual genes in blood of young healthy pigs were identified for concurrent growth rate and subjective health scores prior to the challenge, and for mortality, a combined mortality-treatment trait, and feed conversion rate after the challenge. Gene set enrichment analyses revealed three groups of gene ontology biological process terms that were related to disease resilience: 1) immune and stress response-related terms were enriched among genes whose increased expression was unfavorably associated with both pre- and post-challenge traits, 2) heme-related terms were enriched among genes that had favorable associations with both pre- and post-challenge traits, and 3) terms related to protein localization and viral gene expression were enriched among genes that were associated with reduced performance and health traits after but not before the challenge. CONCLUSIONS: Gene expression profiles in blood from young healthy piglets provide insight into their performance when exposed to disease and other stressors. The expression of genes involved in stress response, heme metabolism, and baseline expression of host genes related to virus propagation were found to be associated with host response to disease.

Gene expression in tonsils in swine following infection with porcine reproductive and respiratory syndrome virus.

BACKGROUND: Porcine reproductive and respiratory syndrome (PRRS) is a threat to pig production worldwide. Our objective was to understand mechanisms of persistence of PRRS virus (PRRSV) in tonsil. Transcriptome data from tonsil samples collected at 42 days post infection (dpi) were generated by RNA-seq and NanoString on 51 pigs that were selected to contrast the two PRRSV isolates used, NVSL and KS06, high and low tonsil viral level at 42 dpi, and the favorable and unfavorable genotypes at a genetic marker (WUR) for the putative PRRSV resistance gene GBP5. RESULTS: The number of differentially expressed genes (DEGs) differed markedly between models with and without accounting for cell-type enrichments (CE) in the samples that were predicted from the RNA-seq data. This indicates that differences in cell composition in tissues that consist of multiple cell types, such as tonsil, can have a large impact on observed differences in gene expression. Based on both the NanoString and the RNA-seq data, KS06-infected pigs showed greater activation, or less inhibition, of immune response in tonsils at 42 dpi than NVSL-infected pigs, with and without accounting for CE. This suggests that the NVSL virus may be better than the KS06 virus at evading host immune response and persists in tonsils by weakening, or preventing, host immune responses. Pigs with high viral levels showed larger CE of immune cells than low viral level pigs, potentially to trigger stronger immune responses. Presence of high tonsil virus was associated with a stronger immune response, especially innate immune response through interferon signaling, but these differences were not significant when accounting for CE. Genotype at WUR was associated with different effects on immune response in tonsils of pigs during the persistence stage, depending on viral isolate and tonsil viral level. CONCLUSIONS: Results of this study provide insights into the effects of PRRSV isolate, tonsil viral level, and WUR genotype on host immune response and into potential mechanisms of PRRSV persistence in tonsils that could be targeted to improve strategies to reduce viral rebreaks. Finally, to understand transcriptome responses in tissues that consist of multiple cell types, it is important to consider differences in cell composition.

A comparative analysis of chromatin accessibility in cattle, pig, and mouse tissues.

BACKGROUND: Although considerable progress has been made towards annotating the noncoding portion of the human and mouse genomes, regulatory elements in other species, such as livestock, remain poorly characterized. This lack of functional annotation poses a substantial roadblock to agricultural research and diminishes the value of these species as model organisms. As active regulatory elements are typically characterized by chromatin accessibility, we implemented the Assay for Transposase Accessible Chromatin (ATAC-seq) to annotate and characterize regulatory elements in pigs and cattle, given a set of eight adult tissues. RESULTS: Overall, 306,304 and 273,594 active regulatory elements were identified in pig and cattle, respectively. 71,478 porcine and 47,454 bovine regulatory elements were highly tissue-specific and were correspondingly enriched for binding motifs of known tissue-specific transcription factors. However, in every tissue the most prevalent accessible motif corresponded to the insulator CTCF, suggesting pervasive involvement in 3-D chromatin organization. Taking advantage of a similar dataset in mouse, open chromatin in pig, cattle, and mice were compared, revealing that the conservation of regulatory elements, in terms of sequence identity and accessibility, was consistent with evolutionary distance; whereas pig and cattle shared about 20% of accessible sites, mice and ungulates only had about 10% of accessible sites in common. Furthermore, conservation of accessibility was more prevalent at promoters than at intergenic regions. CONCLUSIONS: The lack of conserved accessibility at distal elements is consistent with rapid evolution of enhancers, and further emphasizes the need to annotate regulatory elements in individual species, rather than inferring elements based on homology. This atlas of chromatin accessibility in cattle and pig constitutes a substantial step towards annotating livestock genomes and dissecting the regulatory link between genome and phenome.

The effects of a globin blocker on the resolution of 3'mRNA sequencing data in porcine blood.

BACKGROUND: Gene expression profiling in blood is a potential source of biomarkers to evaluate or predict phenotypic differences between pigs but is expensive and inefficient because of the high abundance of globin mRNA in porcine blood. These limitations can be overcome by the use of QuantSeq 3'mRNA sequencing (QuantSeq) combined with a method to deplete or block the processing of globin mRNA prior to or during library construction. Here, we validated the effectiveness of QuantSeq using a novel specific globin blocker (GB) that is included in the library preparation step of QuantSeq. RESULTS: In data set 1, four concentrations of the GB were applied to RNA samples from two pigs. The GB significantly reduced the proportion of globin reads compared to non-GB (NGB) samples (P = 0.005) and increased the number of detectable non-globin genes. The highest evaluated concentration (C1) of the GB resulted in the largest reduction of globin reads compared to the NGB (from 56.4 to 10.1%). The second highest concentration C2, which showed very similar globin depletion rates (12%) as C1 but a better correlation of the expression of non-globin genes between NGB and GB (r = 0.98), allowed the expression of an additional 1295 non-globin genes to be detected, although 40 genes that were detected in the NGB sample (at a low level) were not present in the GB library. Concentration C2 was applied in the rest of the study. In data set 2, the distribution of the percentage of globin reads for NGB (n = 184) and GB (n = 189) samples clearly showed the effects of the GB on reducing globin reads, in particular for HBB, similar to results from data set 1. Data set 3 (n = 84) revealed that the proportion of globin reads that remained in GB samples was significantly and positively correlated with the reticulocyte count in the original blood sample (P < 0.001). CONCLUSIONS: The effect of the GB on reducing the proportion of globin reads in porcine blood QuantSeq was demonstrated in three data sets. In addition to increasing the efficiency of sequencing non-globin mRNA, the GB for QuantSeq has an advantage that it does not require an additional step prior to or during library creation. Therefore, the GB is a useful tool in the quantification of whole gene expression profiles in porcine blood.

Acute systemic inflammatory response to lipopolysaccharide stimulation in pigs divergently selected for residual feed intake.

BACKGROUND: It is unclear whether improving feed efficiency by selection for low residual feed intake (RFI) compromises pigs' immunocompetence. Here, we aimed at investigating whether pig lines divergently selected for RFI had different inflammatory responses to lipopolysaccharide (LPS) exposure, regarding to clinical presentations and transcriptomic changes in peripheral blood cells. RESULTS: LPS injection induced acute systemic inflammation in both the low-RFI and high-RFI line (n = 8 per line). At 4 h post injection (hpi), the low-RFI line had a significantly lower (p = 0.0075) mean rectal temperature compared to the high-RFI line. However, no significant differences in complete blood count or levels of several plasma cytokines were detected between the two lines. Profiling blood transcriptomes at 0, 2, 6, and 24 hpi by RNA-sequencing revealed that LPS induced dramatic transcriptional changes, with 6296 genes differentially expressed at at least one time point post injection relative to baseline in at least one line (n = 4 per line) (|log2(fold change)| ≥ log2(1.2); q < 0.05). Furthermore, applying the same cutoffs, we detected 334 genes differentially expressed between the two lines at at least one time point, including 33 genes differentially expressed between the two lines at baseline. But no significant line-by-time interaction effects were detected. Genes involved in protein translation, defense response, immune response, and signaling were enriched in different co-expression clusters of genes responsive to LPS stimulation. The two lines were largely similar in their peripheral blood transcriptomic responses to LPS stimulation at the pathway level, although the low-RFI line had a slightly lower level of inflammatory response than the high-RFI line from 2 to 6 hpi and a slightly higher level of inflammatory response than the high-RFI line at 24 hpi. CONCLUSIONS: The pig lines divergently selected for RFI had a largely similar response to LPS stimulation. However, the low-RFI line had a relatively lower-level, but longer-lasting, inflammatory response compared to the high-RFI line. Our results suggest selection for feed efficient pigs does not significantly compromise a pig's acute systemic inflammatory response to LPS, although slight differences in intensity and duration may occur.

Porcine signal regulatory protein alpha binds to human CD47 to inhibit phagocytosis: Implications for human hematopoietic stem cell transplantation into severe combined immunodeficient pigs.

BACKGROUND: Severe combined immunodeficient (SCID) pigs are an emerging animal model being developed for biomedical and regenerative medicine research. SCID pigs can successfully engraft human-induced pluripotent stem cells and cancer cell lines. The development of a humanized SCID pig through xenotransplantation of human hematopoietic stem cells (HSCs) would be a further demonstration of the value of such a large animal SCID model. Xenotransplantation success with HSCs into non-obese diabetic (NOD)-derived SCID mice is dependent on the ability of NOD mouse signal regulatory protein alpha (SIRPA) to bind human CD47, inducing higher phagocytic tolerance than other mouse strains. Therefore, we investigated whether porcine SIRPA binds human CD47 in the context of developing a humanized SCID pig. METHODS: Peripheral blood mononuclear cells (PBMCs) were collected from SCID and non-SCID pigs. Flow cytometry was used to assess whether porcine monocytes could bind to human CD47. Porcine monocytes were isolated from PBMCs and were subjected to phagocytosis assays with pig, human, and mouse red blood cell (RBC) targets. Blocking phagocytosis assays were performed by incubating human RBCs with anti-human CD47 blocking antibody B6H12, non-blocking antibody 2D3, and nonspecific IgG1 antibody and exposing to human or porcine monocytes. RESULTS: We found that porcine SIRPA binds to human CD47 in vitro by flow cytometric assays. Additionally, phagocytosis assays were performed, and we found that porcine monocytes phagocytose human and porcine RBCs at significantly lower levels than mouse RBCs. When human RBCs were preincubated with CD47 antibodies B6H12 or 2D3, phagocytosis was induced only after B6H12 incubation, indicating the lower phagocytic activity of porcine monocytes with human cells requires interaction between porcine SIRPA and human CD47. CONCLUSIONS: We have shown the first evidence that porcine monocytes can bind to human CD47 and are phagocytically tolerant to human cells, suggesting that porcine SCID models have the potential to support engraftment of human HSCs.

Genomic prediction of piglet response to infection with one of two porcine reproductive and respiratory syndrome virus isolates.

BACKGROUND: Genomic prediction of the pig's response to the porcine reproductive and respiratory syndrome (PRRS) virus (PRRSV) would be a useful tool in the swine industry. This study investigated the accuracy of genomic prediction based on porcine SNP60 Beadchip data using training and validation datasets from populations with different genetic backgrounds that were challenged with different PRRSV isolates. RESULTS: Genomic prediction accuracy averaged 0.34 for viral load (VL) and 0.23 for weight gain (WG) following experimental PRRSV challenge, which demonstrates that genomic selection could be used to improve response to PRRSV infection. Training on WG data during infection with a less virulent PRRSV, KS06, resulted in poor accuracy of prediction for WG during infection with a more virulent PRRSV, NVSL. Inclusion of single nucleotide polymorphisms (SNPs) that are in linkage disequilibrium with a major quantitative trait locus (QTL) on chromosome 4 was vital for accurate prediction of VL. Overall, SNPs that were significantly associated with either trait in single SNP genome-wide association analysis were unable to predict the phenotypes with an accuracy as high as that obtained by using all genotyped SNPs across the genome. Inclusion of data from close relatives into the training population increased whole genome prediction accuracy by 33% for VL and by 37% for WG but did not affect the accuracy of prediction when using only SNPs in the major QTL region. CONCLUSIONS: Results show that genomic prediction of response to PRRSV infection is moderately accurate and, when using all SNPs on the porcine SNP60 Beadchip, is not very sensitive to differences in virulence of the PRRSV in training and validation populations. Including close relatives in the training population increased prediction accuracy when using the whole genome or SNPs other than those near a major QTL.

Analyses of pig genomes provide insight into porcine demography and evolution.

For 10,000 years pigs and humans have shared a close and complex relationship. From domestication to modern breeding practices, humans have shaped the genomes of domestic pigs. Here we present the assembly and analysis of the genome sequence of a female domestic Duroc pig (Sus scrofa) and a comparison with the genomes of wild and domestic pigs from Europe and Asia. Wild pigs emerged in South East Asia and subsequently spread across Eurasia. Our results reveal a deep phylogenetic split between European and Asian wild boars ∼1 million years ago, and a selective sweep analysis indicates selection on genes involved in RNA processing and regulation. Genes associated with immune response and olfaction exhibit fast evolution. Pigs have the largest repertoire of functional olfactory receptor genes, reflecting the importance of smell in this scavenging animal. The pig genome sequence provides an important resource for further improvements of this important livestock species, and our identification of many putative disease-causing variants extends the potential of the pig as a biomedical model.

A high-quality annotated transcriptome of swine peripheral blood.

BACKGROUND: High throughput gene expression profiling assays of peripheral blood are widely used in biomedicine, as well as in animal genetics and physiology research. Accurate, comprehensive, and precise interpretation of such high throughput assays relies on well-characterized reference genomes and/or transcriptomes. However, neither the reference genome nor the peripheral blood transcriptome of the pig have been sufficiently assembled and annotated to support such profiling assays in this emerging biomedical model organism. We aimed to assemble published and novel RNA-seq data to provide a comprehensive, well-annotated blood transcriptome for pigs by integrating a de novo assembly with a genome-guided assembly. RESULTS: A de novo and a genome-guided transcriptome of porcine whole peripheral blood was assembled with ~162 million pairs of paired-end and ~183 million single-end, trimmed and normalized Illumina RNA-seq reads (~6 billion initial reads from 146 RNA-seq libraries) from five independent studies by using the Trinity and Cufflinks software, respectively. We then removed putative transcripts (PTs) of low confidence from both assemblies and merged the remaining PTs into an integrated transcriptome consisting of 132,928 PTs, with 126,225 (~95%) PTs from the de novo assembly and more than 91% of PTs spliced. In the integrated transcriptome, ~90% and 63% of PTs had significant sequence similarity to sequences in the NCBI NT and NR databases, respectively; 68,754 (~52%) PTs were annotated with 15,965 unique gene ontology (GO) terms; and 7618 PTs annotated with Enzyme Commission codes were assigned to 134 pathways curated by the Kyoto Encyclopedia of Genes and Genomes (KEGG). Full exon-intron junctions of 17,528 PTs were validated by PacBio IsoSeq full-length cDNA reads from 3 other porcine tissues, NCBI pig RefSeq mRNAs and transcripts from Ensembl Sscrofa10.2 annotation. Completeness of the 5' termini of 37,569 PTs was validated by public cap analysis of gene expression (CAGE) data. By comparison to the Ensembl transcripts, we found that (1) the deduced precursors of 54,402 PTs shared at least one intron or exon with those of 18,437 Ensembl transcripts; (2) 12,262 PTs had both longer 5' and 3' termini than their maximally overlapping Ensembl transcripts; and (3) 41,838 spliced PTs were totally missing from the Sscrofa10.2 annotation. Similar results were obtained when the PTs were compared to the pig NCBI RefSeq mRNA collection. CONCLUSIONS: We built, validated and annotated a comprehensive porcine blood transcriptome with significant improvement over the annotation of Ensembl Sscrofa10.2 and the pig NCBI RefSeq mRNAs, and laid a foundation for blood-based high throughput transcriptomic assays in pigs and for advancing annotation of the pig genome.

Not All SCID Pigs Are Created Equally: Two Independent Mutations in the Artemis Gene Cause SCID in Pigs.

Mutations in >30 genes are known to result in impairment of the adaptive immune system, causing a group of disorders collectively known as SCID. SCID disorders are split into groups based on their presence and/or functionality of B, T, and NK cells. Piglets from a line of Yorkshire pigs at Iowa State University were shown to be affected by T(-)B(-)NK(+) SCID, representing, to our knowledge, the first example of naturally occurring SCID in pigs. In this study, we present evidence for two spontaneous mutations as the molecular basis for this SCID phenotype. Flow cytometry analysis of thymocytes showed an increased frequency of immature T cells in SCID pigs. Fibroblasts from these pigs were more sensitive to ionizing radiation than non-SCID piglets, eliminating the RAG1 and RAG2 genes. Genetic and molecular analyses showed that two mutations were present in the Artemis gene, which in the homozygous or compound heterozygous state cause the immunodeficient phenotype. Rescue of SCID fibroblast radiosensitivity by human Artemis protein demonstrated that the identified Artemis mutations are the direct cause of this cellular phenotype. The work presented in the present study reveals two mutations in the Artemis gene that cause T(-)B(-)NK(+) SCID in pigs. The SCID pig can be an important biomedical model, but these mutations would be undesirable in commercial pig populations. The identified mutations and associated genetic tests can be used to address both of these issues.

Post-weaning blood transcriptomic differences between Yorkshire pigs divergently selected for residual feed intake.

BACKGROUND: Improving feed efficiency (FE) of pigs by genetic selection is of economic and environmental significance. An increasingly accepted measure of feed efficiency is residual feed intake (RFI). Currently, the molecular mechanisms underlying RFI are largely unknown. Additionally, to incorporate RFI into animal breeding programs, feed intake must be recorded on individual pigs, which is costly and time-consuming. Thus, convenient and predictive biomarkers for RFI that can be measured at an early age are greatly desired. In this study, we aimed to explore whether differences exist in the global gene expression profiles of peripheral blood of 35 to 42 day-old pigs with extremely low (more efficient) and high RFI (less efficient) values from two lines that were divergently selected for RFI during the grow-finish phase, to use such information to explore the potential molecular basis of RFI differences, and to initiate development of predictive biomarkers for RFI. RESULTS: We identified 1972 differentially expressed genes (DEGs) (q ≤ 0.15) between the low (n = 15) and high (n = 16) RFI groups of animals by using RNA sequencing technology. We validated 24 of 37 selected DEGs by reverse transcription-quantitative PCR (RT-qPCR) in a joint analysis of 24 (12 per line) of the 31 samples already used for RNA-seq plus 24 (12 per line) novel samples from the same contemporary group of pigs. Using an analysis of the 24 novel samples alone, only nine of the 37 selected DEGs were validated. Genes involved in small molecule biosynthetic process, antigen processing and presentation of peptide antigen via major histocompatibility complex (MHC) class I, and steroid biosynthetic process were overrepresented among DEGs that had higher expression in the low versus high RFI animals. Genes known to function in the proteasome complex or mitochondrion were also significantly enriched among genes with higher expression in the low versus high RFI animals. Alternatively, genes involved in signal transduction, bone mineralization and regulation of phosphorylation were overrepresented among DEGs with lower expression in the low versus high RFI animals. The DEGs significantly overlapped with genes associated with disease, including hyperphagia, eating disorders and mitochondrial diseases (q < 1E-05). A weighted gene co-expression network analysis (WGCNA) identified four co-expression modules that were differentially expressed between the low and high RFI groups. Genes involved in lipid metabolism, regulation of bone mineralization, cellular immunity and response to stimulus were overrepresented within the two modules that were most significantly differentially expressed between the low and high RFI groups. We also found five of the DEGs and one of the co-expression modules were significantly associated with the RFI phenotype of individual animals (q < 0.05). CONCLUSIONS: The post-weaning blood transcriptome was clearly different between the low and high RFI groups. The identified DEGs suggested potential differences in mitochondrial and proteasomal activities, small molecule biosynthetic process, and signal transduction between the two RFI groups and provided potential new insights into the molecular basis of RFI in pigs, although the observed relationship between the post-weaning blood gene expression and RFI phenotype measured during the grow-finish phase was not strong. DEGs and representative genes in co-expression modules that were associated with RFI phenotype provide a preliminary list for developing predictive biomarkers for RFI in pigs.

Bioinformatic analyses in early host response to Porcine Reproductive and Respiratory Syndrome virus (PRRSV) reveals pathway differences between pigs with alternate genotypes for a major host response QTL.

BACKGROUND: A region on Sus scrofa chromosome 4 (SSC4) surrounding single nucleotide polymorphism (SNP) marker WUR10000125 (WUR) has been reported to be strongly associated with both weight gain and serum viremia in pigs after infection with PRRS virus (PRRSV). A proposed causal mutation in the guanylate binding protein 5 gene (GBP5) is predicted to truncate the encoded protein. To investigate transcriptional differences between WUR genotypes in early host response to PRRSV infection, an RNA-seq experiment was performed on globin depleted whole blood RNA collected on 0, 4, 7, 10 and 14 days post-infection (dpi) from eight littermate pairs with one AB (favorable) and one AA (unfavorable) WUR genotype animal per litter. RESULTS: Gene Ontology (GO) enrichment analysis of transcripts that were differentially expressed (DE) between dpi across both genotypes revealed an inflammatory response for all dpi when compared to day 0. However, at the early time points of 4 and 7dpi, several GO terms had higher enrichment scores compared to later dpi, including inflammatory response (p < 10(-7)), specifically regulation of NFkappaB (p < 0.01), cytokine, and chemokine activity (p < 0.01). At 10 and 14dpi, GO term enrichment indicated a switch to DNA damage response, cell cycle checkpoints, and DNA replication. Few transcripts were DE between WUR genotypes on individual dpi or averaged over all dpi, and little enrichment of any GO term was found. However, there were differences in expression patterns over time between AA and AB animals, which was confirmed by genotype-specific expression patterns of several modules that were identified in weighted gene co-expression network analyses (WGCNA). Minor differences between AA and AB animals were observed in immune response and DNA damage response (p = 0.64 and p = 0.11, respectively), but a significant effect between genotypes pointed to a difference in ion transport/homeostasis and the participation of G-coupled protein receptors (p = 8e-4), which was reinforced by results from regulatory and phenotypic impact factor analyses between genotypes. CONCLUSION: We propose these pathway differences between WUR genotypes are the result of the inability of the truncated GBP5 of the AA genotyped pigs to inhibit viral entry and replication as quickly as the intact GBP5 protein of the AB genotyped pigs.

GO-FAANG meeting: a Gathering On Functional Annotation of Animal Genomes.

The Functional Annotation of Animal Genomes (FAANG) Consortium recently held a Gathering On FAANG (GO-FAANG) Workshop in Washington, DC on October 7-8, 2015. This consortium is a grass-roots organization formed to advance the annotation of newly assembled genomes of domesticated and non-model organisms (www.faang.org). The workshop gathered together from around the world a group of 100+ genome scientists, administrators, representatives of funding agencies and commodity groups to discuss the latest advancements of the consortium, new perspectives, next steps and implementation plans. The workshop was streamed live and recorded, and all talks, along with speaker slide presentations, are available at www.faang.org. In this report, we describe the major activities and outcomes of this meeting. We also provide updates on ongoing efforts to implement discussions and decisions taken at GO-FAANG to guide future FAANG activities. In summary, reference datasets are being established under pilot projects; plans for tissue sets, morphological classification and methods of sample collection for different tissues were organized; and core assays and data and meta-data analysis standards were established.

Whole blood microarray analysis of pigs showing extreme phenotypes after a porcine reproductive and respiratory syndrome virus infection.

BACKGROUND: The presence of variability in the response of pigs to Porcine Reproductive and Respiratory Syndrome virus (PRRSv) infection, and recent demonstration of significant genetic control of such responses, leads us to believe that selection towards more disease resistant pigs could be a valid strategy to reduce its economic impact on the swine industry. To find underlying molecular differences in PRRS susceptible versus more resistant pigs, 100 animals with extremely different growth rates and viremia levels after PRRSv infection were selected from a total of 600 infected pigs. A microarray experiment was conducted on whole blood RNA samples taken at 0, 4 and 7 days post infection (dpi) from these pigs. From these data, we examined associations of gene expression with weight gain and viral load phenotypes. The single nucleotide polymorphism (SNP) marker WUR10000125 (WUR) on the porcine 60 K SNP chip was shown to be associated with viral load and weight gain after PRRSv infection, and so the effect of the WUR10000125 (WUR) genotype on expression in whole blood was also examined. RESULTS: Limited information was obtained through linear modeling of blood gene differential expression (DE) that contrasted pigs with extreme phenotypes, for growth or viral load or between animals with different WUR genotype. However, using network-based approaches, molecular pathway differences between extreme phenotypic classes could be identified. Several gene clusters of interest were found when Weighted Gene Co-expression Network Analysis (WGCNA) was applied to 4 dpi contrasted with 0 dpi data. The expression pattern of one such cluster of genes correlated with weight gain and WUR genotype, contained numerous immune response genes such as cytokines, chemokines, interferon type I stimulated genes, apoptotic genes and genes regulating complement activation. In addition, Partial Correlation and Information Theory (PCIT) identified differentially hubbed (DH) genes between the phenotypically divergent groups. GO enrichment revealed that the target genes of these DH genes are enriched in adaptive immune pathways. CONCLUSION: There are molecular differences in blood RNA patterns between pigs with extreme phenotypes or with a different WUR genotype in early responses to PRRSv infection, though they can be quite subtle and more difficult to discover with conventional DE expression analyses. Co-expression analyses such as WGCNA and PCIT can be used to reveal network differences between such extreme response groups.

Current transcriptomics in pig immunity research.

Swine performance in the face of disease challenge is becoming progressively more important. To improve the pig's robustness and resilience against pathogens through selection, a better understanding of the genetic and epigenetic factors in the immune response is required. This review highlights results from the most recent transcriptome research, and the meta-analyses performed, in the context of pig immunity. A technological overview is given including wholegenome microarrays, immune-specific arrays, small-scale high-throughput expression methods, high-density tiling arrays, and next generation sequencing (NGS). Although whole genome microarray techniques will remain complementary to NGS for some time in domestic species, research will transition to sequencing-based methods due to cost-effectiveness and the extra information that such methods provide. Furthermore, upcoming high-throughput epigenomic studies, which will add greatly to our knowledge concerning the impact of epigenetic modifications on pig immune response, are listed in this review. With emphasis on the insights obtained from transcriptomic analyses for porcine immunity, we also discuss the experimental design in pig immunity research and the value of the newly published porcine genome assembly in using the pig as a model for human immune response. We conclude by discussing the importance of establishing community standards to maximize the possibility of integrative computational analyses, such as was clearly beneficial for the human ENCODE project.