To identify and characterize aetiologic agent(s) associated with an outbreak of a severe diarrhoea in piglets in Jiangxi, China, in March 2015, a nested reverse transcription-polymerase chain reaction (RT-PCR) for the detection of porcine deltacoronavirus (PDCoV) was developed. A survey based on the nested RT-PCR established indicated that the monoinfection of PDCoV (33.71%) and coinfection of PDCoV (19.66%) with porcine epidemic diarrhoea virus (PEDV) were common in diarrhoeal pigs in Jiangxi, China. A high prevalence of PDCoV (58.33%) in diarrhoeal samples which were PEDV negative was observed. The complete genome sequence of a representative PDCoV strain, PDCoV/CHJXNI2/2015, was determined. Phylogenetic analysis of complete genome and S protein sequences of PDCoV/CHJXNI2/2015 demonstrated that it was most closely related to Hong Kong and US PDCoVs. To our knowledge, this is the first report on the identification, prevalence, complete genome sequencing and molecular characterizations of PDCoV in diarrhoeal samples in pigs in China.
A large proportion of gilts and sows are culled from reproduction populations because of anestrus and pubertal reproductive failure. Selecting early onset of puberty gilts has a favorable effect on sows' reproductivity. However, age at puberty is hard to be routinely measured in commercial herds. With molecular genetic predictors, identifying individuals that have a propensity for early onset of puberty can be simplified. We previously performed genome scanning and a genome-wide association study for puberty in an F2 resource population using 183 microsatellites and 62 125 SNPs respectively. The detection power and resolution of identified quantitative trait loci were very low. Herein, we re-sequenced 19 founders of the F2 resource population in high coverage, and whole genome sequences of F2 individuals were imputed to perform an association study for reproductive traits. A total of 2339 SNPs associated with pubertal reproductive failure were identified in the region of 30.94-40.74 Mb on SSC7, with the top one, positioned at 33.36 Mb, explaining 16% of the phenotypic variances. We improved the magnitude of the P-value by 10E+5 to 10E+7 using the whole genome sequence rather than using low/middle density markers as in previous studies, and we narrowed down the QTL confidence interval to 5.25 Mb. Combining the annotation of gene function, RAB23 and BAK1 were perceived as the most compelling candidate genes. The identified loci may be useful in culling sows failing to show estrus by marker-assisted selection to increase reproductive efficiency of swine herds.
Feed efficiency is of particular interest to the beef industry because feed is the largest variable cost in production and fatty acid composition is emerging as an important trait, both economically and socially, due to the potential implications of dietary fatty acids on human health. Quantifying correlations between feed efficiency and fatty acid composition will contribute to construction of optimal multiple-trait selection indexes to maximize beef production profitability. In the present study, we estimated phenotypic and genetic correlations of feed efficiency measures including residual feed intake (RFI), RFI adjusted for final ultrasound backfat thickness (RFIf); their component traits ADG, DMI, and metabolic BW; and final ultrasound backfat thickness measured at the end of feedlot test with 25 major fatty acids in the subcutaneous adipose tissues of 1,366 finishing steers and heifers using bivariate animal models. The phenotypic correlations of RFI and RFIf with the 25 individual and grouped fatty acid traits were generally low (<0.25 in magnitude). However, relatively stronger genetic correlation coefficients of RFI and RFIf with PUFA traits including the -6:-3 ratio (0.52 ± 0.29 and 0.45 ± 0.31, respectively), 18:2-6 (0.45 ± 0.18 and 0.40 ± 0.19, respectively), -6 (0.43 ± 0.18 and 0.38 ± 0.19, respectively), PUFA (0.42 ± 0.18 and 0.36 ± 0.20, respectively), and 9-16:1 (-0.43 ± 0.20 and -0.33 ± 0.22, respectively) were observed. Hence, selection for low-RFI or more efficient beef cattle will improve fatty acid profiles by lowering the content of -6 PUFA, thus reducing the ratio of -6 to -3 along with increasing the amount of 9-16:1. Moderate to moderately high genetic correlations were also observed for DMI with 9-14:1 (-0.32 ± 0.17) and the sum of CLA analyzed (SumCLA; -0.45 ± 0.21), suggesting that selection of beef cattle with lower DMI will lead to an increase amount of 9-14:1 and SumCLA in the subcutaneous adipose tissue. However, unfavorable genetic correlations were detected for ADG with 11-18:1 (-0.38 ± 0.23) and SumCLA (-0.73 ± 0.26), implying that selection of beef cattle with a better growth rate will decrease the contents of healthy fatty acids 11-18:1 and SumCLA. Therefore, it is recommended that a multiple-trait selection index be used when genetic improvements of fatty acid composition, feed efficiency, feed intake, and growth are important in the breeding objective.
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