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The whole-genome sequences of progenies with low-density single-nucleotide polymorphism (SNP) genotypes can be imputed with high accuracy based on the deep-coverage sequences of key ancestors. With this imputation technology, a more powerful genome-wide association study (GWAS) can be carried out using imputed whole-genome variants and the phenotypes of interest to overcome the shortcomings of low-power detection and the large confidence interval derived from low-density SNP markers in classic association studies. In this study, 19 ancestors of a large-scale swine F2 White Duroc × Erhualian population were deeply sequenced for their genome with an average coverage of 25×. Considering 98 pigs from 10 different breeds with high-quality deep sequenced genomes, we imputed the whole genomic variants of 1020 F2 pigs genotyped by the PorcineSNP60 BeadChip with high accuracy and obtained 14,851,440 sequence variants after quality control. Based on this, 87 novel quantitative traits loci (QTLs) for 18 hematological traits at three different physiological stages of the F2 pigs were identified, among which most of the novel QTLs have been repeated in two of the three stages. Literature mining pinpointed that the FGF14 and LCLAT1 genes at SSC11 and SSC3 may affect the MCH at day 240 and MCV at day 18, respectively. The present study shows that combining high-quality imputed genomic variants and correlated phenomic traits into GWAS can improve the capability to detect QTL considerably. The large number of different QTLs for hematological traits identified at multiple growth stages implies the complexity and time specificity of these traits. [ABSTRACT FROM AUTHOR]

IFN regulatory factor 7 (IRF7) exerts anti-infective effects by promoting the production of IFNs in various bacterial and viral infections, but its role in highly morbid and fatal Candida albicans infections is unknown. We unexpectedly found that Irf7 gene expression levels were significantly upregulated in tissues or cells after C. albicans infection in humans and mice and that IRF7 actually exacerbates C. albicans infection in mice independent of its classical function in inducing IFNs production. Compared to controls, Irf7-/- mice showed stronger phagocytosis of fungus, upregulation of C-type lectin receptor CD209 expression, and enhanced P53-AMPK-mTOR-mediated autophagic signaling in macrophages after C. albicans infection. The administration of the CD209-neutralizing Ab significantly hindered the phagocytosis of Irf7-/- mouse macrophages, whereas the inhibition of p53 or autophagy impaired the killing function of these macrophages. Thus, IRF7 exacerbates C. albicans infection by compromising the phagocytosis and killing capacity of macrophages via regulating CD209 expression and p53-AMPK-mTOR-mediated autophagy, respectively. This finding reveals a novel function of IRF7 independent of its canonical IFNs production and its unexpected role in enhancing fungal infections, thus providing more specific and effective targets for antifungal therapy., (Copyright © 2024 by The American Association of Immunologists, Inc.)

The whole-genome sequences of progenies with low-density single-nucleotide polymorphism (SNP) genotypes can be imputed with high accuracy based on the deep-coverage sequences of key ancestors. With this imputation technology, a more powerful genome-wide association study (GWAS) can be carried out using imputed whole-genome variants and the phenotypes of interest to overcome the shortcomings of low-power detection and the large confidence interval derived from low-density SNP markers in classic association studies. In this study, 19 ancestors of a large-scale swine F 2 White Duroc × Erhualian population were deeply sequenced for their genome with an average coverage of 25×. Considering 98 pigs from 10 different breeds with high-quality deep sequenced genomes, we imputed the whole genomic variants of 1020 F 2 pigs genotyped by the PorcineSNP60 BeadChip with high accuracy and obtained 14,851,440 sequence variants after quality control. Based on this, 87 novel quantitative traits loci (QTLs) for 18 hematological traits at three different physiological stages of the F 2 pigs were identified, among which most of the novel QTLs have been repeated in two of the three stages. Literature mining pinpointed that the FGF14 and LCLAT1 genes at SSC11 and SSC3 may affect the MCH at day 240 and MCV at day 18, respectively. The present study shows that combining high-quality imputed genomic variants and correlated phenomic traits into GWAS can improve the capability to detect QTL considerably. The large number of different QTLs for hematological traits identified at multiple growth stages implies the complexity and time specificity of these traits.