In order to evaluate the genetic diversity and discrimination among five Korean native chicken lines, a total of 86 individuals were genotyped using 150 microsatellite (MS) markers, and 15 highly polymorphic MS markers were selected. Based on the highest value of the number of alleles, the expected heterozygosity (He) and polymorphic information content (PIC) for the selected markers ranged from 6 to 12, 0.466 to 0.852, 0.709 to 0.882 and 0.648 to 0.865, respectively. Using these markers, the calculated genetic distance (Fst), the heterozygote deficit among chicken lines (Fit) and the heterozygote deficit within chicken line (Fis) values ranged from 0.0309 to 0.2473, 0.0013 to 0.4513 and −0.1002 to 0.271, respectively. The expected probability of identity values in random individuals (PI), random half-sib (PIhalf-sibs) and random sibs (PIsibs) were estimated at 7.98×10−29, 2.88×10−20 and 1.25×10−08, respectively, indicating that these markers can be used for traceability systems in Korean native chickens. The unrooted phylogenetic neighbor-joining (NJ) tree was constructed using 15 MS markers that clearly differentiated among the five native chicken lines. Also, the structure was estimated by the individual clustering with the K value of 5. The selected 15 MS markers were found to be useful for the conservation, breeding plan, and traceability system in Korean native chickens.
Haematological traits play important roles in disease resistance and defence functions. The objective of this study was to locate quantitative trait loci (QTL) and the associated positional candidate genes influencing haematological traits in an F(2) intercross between Landrace and Korean native pigs. Eight blood-related traits (six erythrocyte traits, one leucocyte trait and one platelet trait) were measured in 816 F(2) progeny. All experimental animals were genotyped with 173 informative microsatellite markers located throughout the pig genome. We report that nine chromosomes harboured QTL for the baseline blood parameters: genomic regions on SSC 1, 4, 5, 6, 8, 9, 11, 13 and 17. Eight of twenty identified QTL reached genome-wide significance. In addition, we evaluated the KIT locus, an obvious candidate gene locus affecting variation in blood-related traits. Using dense single nucleotide polymorphism marker data on SSC 8 and the marker-assisted association test, the strong association of the KIT locus with blood phenotypes was confirmed. In conclusion, our study identified both previously reported and novel QTL affecting baseline haematological parameters in pigs. Additionally, the positional candidate genes identified here could play an important role in elucidating the genetic architecture of haematological phenotype variation in swine and in humans.
Changes affecting the status of health and robustness can bring about physiological alterations including hematological parameters in swine. To identify quantitative trait loci (QTL) associated with eight hematological traits (one leukocyte trait, six erythrocyte traits and one platelet trait), we conducted a genome-wide association study using the PorcineSNP60K BeadChip in a resource population derived from an intercross between Landrace and Korean native pigs. A total of 36 740 SNPs from 816 F2 progeny were analyzed for each blood-related trait after filtering for quality control. Data were analyzed by the genome-wide rapid association using mixed model and regression (GRAMMAR) approach. A total of 257 significant SNPs (P < 1.36 × 10(-6) ) on SSC3, 6, 8, 13 and 17 were identified for blood-related traits in this study. Interestingly, the genomic region between 17.9 and 130 Mb on SSC8 was found to be significantly associated with red blood cell, mean corpuscular volume and mean corpuscular hemoglobin. Our results include the identification of five significant SNPs within five candidate genes (KIT, IL15, TXK, ARAP2 and ERG) for hematopoiesis. Further validation of these identified SNPs could give valuable information for understanding the variation of hematological traits in pigs.
The KIT locus has been suggested to be a strong candidate region linked with whole-body roan in the F(2) population produced by intercrosses between Landrace and Korean Native pigs. In this manuscript, we report the finding of a novel alternative splicing event in the porcine KIT gene that results in the skipping of exon 5 in the I(Rn) allele. KIT mRNAs that lack exon 5 were identified in the large intestine and skin, suggesting that the mechanism responsible for the skipping of exon 5 may be tissue specific. A U(26) repeat in intron 5 showed complete linkage (LOD = 11.8) with the roan phenotype and absolute association with the black phenotype of the Korean Native pig (KNP) population samples, inferring that the repeat pattern may alter the complementary base-pairing-mediated looping-out of introns 4 and 5, which may mediate the exon 5-skipping event. Although the sample size in our study was relatively small, we speculate that the R3 allele containing the U(26) repeat is a causative element for the roan phenotype via alternative control of the exon skipping in our roan pedigree.
Growth traits, such as body weight and carcass body length, directly affect productivity and economic efficiency in the livestock industry. We performed a genome-wide linkage analysis to detect the quantitative trait loci (QTL) that affect body weight, growth curve parameters and carcass body length in an F2 intercross between Landrace and Korean native pigs. Eight phenotypes related to growth were measured in approximately 1000 F2 progeny. All experimental animals were subjected to genotypic analysis using 173 microsatellite markers located throughout the pig genome. The least squares regression approach was used to conduct the QTL analysis. For body weight traits, we mapped 16 genome-wide significant QTL on SSC1, 3, 5, 6, 8, 9 and 12 as well as 22 suggestive QTL on SSC2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 16 and 17. On SSC12, we identified a major QTL affecting body weight at 140 days of age that accounted for 4.3% of the phenotypic variance, which was the highest test statistic (F-ratio = 45.6 under the additive model, nominal P = 2.4 × 10(-11) ) observed in this study. We also showed that there were significant QTL on SSC2, 5, 7, 8, 9 and 12 affecting carcass body length and growth curve parameters. Interestingly, the QTL on SSC2, 3, 5, 6, 8, 9, 10, 12 and 17 influencing the growth-related traits showed an obvious trend for co-localization. In conclusion, the identified QTL may play an important role in investigating the genetic structure underlying the phenotypic variation of growth in pigs.
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