Abstract:Postpartum dysgalactia syndrome (PDS) in sows is an important disease after parturition with a relevant economic impact, affecting the health and welfare of both sows and piglets. The genetic background of this disease has been discussed and its heritability estimated, but further genetic analyses are lacking in detail. The aim of the current study was to detect loci affecting the susceptibility to PDS through a genome-wide association approach. The study was designed as a family-based association study with m… Show more
“…Because of the incomplete pedigree information and different populations in the study, genomic kinship was used for PCA for the higher correctness and accuracy than pedigree. More importantly, the genomic kinship could connect and compare multiple breeds or lines, which could not be connected when the pedigree is unclear or unknown [36, 37]. Fig.…”
Section: Resultsmentioning
confidence: 99%
“…Fortunately this problem could be avoided by fitting the statistical model with the known breeds [38] or the PCs [37]. both of which could correct the population structure, while we ignored this problem in our previous study [39].…”
BackgroundPiglet splay leg syndrome (PSL) is one of the most frequent genetic defects, and can cause considerable economic loss in pig production. The present understanding of etiology and pathogenesis of PSL is poor. The current study focused on identifying loci associated with PSL through a genome-wide association study (GWAS) performed with the Illumina Porcine60 SNP Beadchip v2.0. The study was a case/control design with four pig populations (Duroc, Landrace, Yorkshire and one crossbred of Landrace × Yorkshire).ResultAfter quality control of the genotyping data, 185 animals (73 cases, 112 controls) and 43,495 SNPs were retained for further analysis. Principal components (PCs) identified from the genomic kinship matrix were included in the statistical model for correcting the effect of population structure. Seven chromosome-wide significant SNPs were identified on Sus scrofa chromosome 1 (SSC1), SSC2 (2 SNPs), SSC7, SSC15 (2 SNPs) and SSC16 after strict Bonferroni correction. Four genes (HOMER1 and JMY on SSC2, ITGA1 on SSC16, and RAB32 on SSC1) related to muscle development, glycogen metabolism and mitochondrial dynamics were identified as potential candidate genes for PSL.ConclusionsWe identified seven chromosome-wide significant SNPs associated with PSL and four potential candidate genes for PSL. To our knowledge, this is the first pilot study aiming to identify the loci associated with PSL using GWAS. Further investigations and validations for those findings are encouraged.
“…Because of the incomplete pedigree information and different populations in the study, genomic kinship was used for PCA for the higher correctness and accuracy than pedigree. More importantly, the genomic kinship could connect and compare multiple breeds or lines, which could not be connected when the pedigree is unclear or unknown [36, 37]. Fig.…”
Section: Resultsmentioning
confidence: 99%
“…Fortunately this problem could be avoided by fitting the statistical model with the known breeds [38] or the PCs [37]. both of which could correct the population structure, while we ignored this problem in our previous study [39].…”
BackgroundPiglet splay leg syndrome (PSL) is one of the most frequent genetic defects, and can cause considerable economic loss in pig production. The present understanding of etiology and pathogenesis of PSL is poor. The current study focused on identifying loci associated with PSL through a genome-wide association study (GWAS) performed with the Illumina Porcine60 SNP Beadchip v2.0. The study was a case/control design with four pig populations (Duroc, Landrace, Yorkshire and one crossbred of Landrace × Yorkshire).ResultAfter quality control of the genotyping data, 185 animals (73 cases, 112 controls) and 43,495 SNPs were retained for further analysis. Principal components (PCs) identified from the genomic kinship matrix were included in the statistical model for correcting the effect of population structure. Seven chromosome-wide significant SNPs were identified on Sus scrofa chromosome 1 (SSC1), SSC2 (2 SNPs), SSC7, SSC15 (2 SNPs) and SSC16 after strict Bonferroni correction. Four genes (HOMER1 and JMY on SSC2, ITGA1 on SSC16, and RAB32 on SSC1) related to muscle development, glycogen metabolism and mitochondrial dynamics were identified as potential candidate genes for PSL.ConclusionsWe identified seven chromosome-wide significant SNPs associated with PSL and four potential candidate genes for PSL. To our knowledge, this is the first pilot study aiming to identify the loci associated with PSL using GWAS. Further investigations and validations for those findings are encouraged.
“…Array-based variant screenings also are a rapid and efficient technique to detect known variants. A recently developed genome-wide association approach to detect loci affecting PDS susceptibility used 597 genotyped sows with 62,163 single nucleotide polymorphisms (SNPs) [11]. We developed a microarray to detect 240 variants underlying syndromic and nonsyndromic sensorineural hearing loss, including 11 distinct variants in SLC26A4 [12].…”
Enlarged vestibular aqueduct (EVA) is one of the most common congenital inner ear malformations and accounts for 1–12% of sensorineural deafness in children and adolescents. Multiple genetic defects contribute to EVA; therefore, early molecular diagnosis is critical for EVA patients to ensure that the most effective treatment strategies are employed. This study explored a new genetic diagnosis method for EVA and applied it to clinic diagnoses of EVA patients. Using next-generation sequencing technology, we set up a multiple polymerase chain reaction enrichment system for target regions of EVA pathogenic genes (SLC26A4, FOXI1, and KCNJ10). Forty-six EVA samples were sequenced by this system. Variants were detected in 87.0% (40/46) of cases, including three novel variants (SLC26A4 c.923_929del, c.1002-8C>G, and FOXI1 c.519C>A). Biallelic potential pathogenic variants were detected in 27/46 patient samples, leading to a purported diagnostic rate of 59%. All results were verified by Sanger sequencing. Our target region capture system was validated to amplify and measure SLC26A4, FOXI1, and KCNJ10 in one reaction system. The result supplemented the mutation spectrum of EVA. Thus, this strategy is an economic, rapid, accurate, and reliable method with many useful applications in the clinical diagnosis of EVA patients.
“…Nevertheless, a good rearing performance is supported by a good and persistent udder quality, low extra time per sow and no complications at farrowing. A successful farrowing without any assistance even decreases the risk of postparturient disorders (Preissler et al, 2013).…”
Section: Correlations Of the Behavioural Traitsmentioning
The present study examined the possibilities and consequences of selecting pigs for reduced aggression and desirable maternal behaviour. Data were recorded from 798 purebred Large White gilts, with an age of 217 ± 17.7 (mean ± SD) days, which were observed at mixing with unfamiliar conspecifics. The reaction of the sows towards separation from their litter was assessed for 2022 litters from 848 Large White sows. Sows' performance during their time in the farrowing unit was scored based on the traits farrowing behaviour (i.e. need of birth assistance), rearing performance (i.e. litter quality at day 10 postpartum (pp)), usability (i.e. additional labour input during lactation period e.g. for treatments) and udder quality of the sow (i.e. udder attachment). For agonistic behaviour, traits heritabilities of h 2 = 0.11 ± 0.04 to h 2 = 0.28 ± 0.06 were estimated. For the sow's reaction towards separation from her litter low heritabilities were found (h 2 = 0.03 ± 0.03 for separation test on day 1 pp and h 2 = 0.02 ± 0.03 for separation test on day 10 pp). Heritabilities for lactating sow's performance (farrowing behaviour, rearing performance, usability of the sow and udder quality) in the farrowing unit ranged from h 2 = 0.03 ± 0.02 to h 2 = 0.19 ± 0.03. Due to these results it can be assumed that selection for these traits, for example, for udder quality or reduced aggression, is possible. Antagonistic associations were found between separation test on day 1 pp and different measures of aggressiveness (r g = − 0.22 ± 0.26 aggressive attack and r g = − 0.41 ± 0.33 reciprocal fighting). Future studies should determine economic as well as welfare-related values of these traits in order to decide whether selection for these traits will be reasonable.
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