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

Associations of natural variation in the CD163 and other candidate genes on host response of nursery pigs to porcine reproductive and respiratory syndrome virus infection

Pigs with complete resistance to porcine reproductive and respiratory syndrome (PRRS) virus (PRRSV) have been produced by genetically knocking out the CD163 gene that encodes a receptor of the PRRSV for entry into macrophages. The objectives of this study were to evaluate associations of naturally occurring single nucleotide polymorphisms (SNPs) in the CD163 gene and in three other candidate genes (CD169, RGS16, and TRAF1) with host response to PRRSV-only infection and to PRRS vaccination and PRRSV/porcine circovirus 2b (PCV2b) coinfection. SNPs in the CD163 gene were not included on SNP genotyping panels that were used for previous genome-wide association analyses of these data. An additional objective was to identify the potential genetic interaction of variants at these four candidate genes with a mutation in the GBP5 gene that was previously identified to be associated with host response to PRRSV infection. Finally, the association of SNPs with expression level of the nearby gene was tested. Several SNPs in the CD163, CD169, and RGS16 genes were significantly associated with host response under PRRSV-only and/or PRRSV/PCV2b coinfection. The effects of all SNPs that were significant in the PRRSV-only infection trials depend on genetic background. The effects of some SNPs in the CD163, CD169, and RGS16 genes depend on genotype at the putative causative mutation in the GBP5 gene, which indicates a potential biological interaction of these genes with GBP5. In addition, genome-wide association results for the PRRSV-only infection trials revealed that SNPs located in the CDK5RAP2 or MEGF9 genes, near the TRAF1 gene, had suggestive effects on PRRS viral load, which indicates that these SNPs might contribute to PRRSV neuropathogenesis. In conclusion, natural genetic variants in the CD163, CD169, and RGS16 genes are associated with resistance to PRRSV and/or PCV2b infection and appear to interact with the resistance quantitative trait locus in the GBP5 gene. The identified SNPs can be used to select for increased natural resistance to PRRSV and/or PRRSV-PCV2b coinfection.

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07912-8.

A benchmark of hemoglobin blocking during library preparation for mRNA-Sequencing of human blood samples

RNA-Sequencing (RNA-Seq) of peripheral blood can be a valuable source of information for investigating the status and mechanism of diseases. However, blood contains 50–80% unwanted hemoglobin (Hb) transcripts. Lexogen’s QuantSeq mRNA-Seq-Kit for Illumina RNA-Seq features a ‘Globin Block’ (GB) module that depletes Hb cDNAs during library preparation. Here, we aimed to assess GB’s effectiveness and checked for technical biases attributable to GB. Using whole blood total RNA samples of 91 healthy individuals, we sequenced 91 pairs of GB and non-blocked samples (noGB) on Illumina HiSeq2500 and 8 pairs of GB/noGB technical replicates on HiSeq4000. GB reduced the fraction of Hb transcripts from 43% (s.d. 14%) to 8.0% (s.d. 4.3%). From GB samples we detected 1,397 more expressed genes at approximately 11 million reads per RNA-isolate. Enrichment and differential expression analyses did not reveal significant differences for GB and noGB samples with respect to molecular function. In contrast to results from studies that have examined the performance of GB during RNA isolation, we were able to assign GB to corresponding noGB samples (from multiple sequencing runs on HiSeq2500) with at least 89.8% accuracy from the complete correlation matrix of all GB/GB, noGB/noGB and GB/noGB pairs. However, the use of different sequencers (HiSeq2500 vs HiSeq4000) impaired assignment of technical replicates, whereas assignment of GB to corresponding noGB samples worked perfectly when sequencing on one lane on HiSeq4000. Lexogen’s GB RNA-Seq module is a valuable addition during mRNA-Seq library preparation which works even with low amounts of input total RNA (50 ng per sample). GB facilitated the detection of low abundant transcripts and yielded more non-hemoglobin reads, while preserving biological information. We observed that differences in sequencing run and platform have a far greater effect on technical variation than the use of GB.