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Alterations in robustness- and health-related traits lead to physiological changes, such as changes in the serum clinical chemical parameters in individuals. Therefore, clinical-chemical traits can be used as biomarkers to examine the health status of chickens. The aim of the present study was to detect the quantitative trait loci (QTLs) influencing eight clinical-chemical traits (glucose, total protein, creatinine, high-density lipoprotein cholesterol, total cholesterol, glutamic oxaloacetic transaminase, glutamic pyruvic transaminase, and α-amylase) in an F1 nuclear families comprising 83 F0 founders and 585 F1 progeny of Korean native chickens. Genotypic data on 135 DNA markers representing 26 autosomes have been generated for this resource pedigree. The total length of the map was 2729.4 cM. We used a multipoint variance component linkage approach to identify QTLs for the traits. A significant QTL affecting serum α-amylase levels was identified on chicken chromosome (GGA) 7 [logarithm of odds (LOD) = 3.02, P value = 1.92 × 10(-4)]. Additionally, we detected several suggestive linkage signals for the levels of total cholesterol, glutamic oxaloacetic transaminase, glutamic pyruvic transaminase, and creatinine on GGA 4, 12, 13, and 15. In this study, serum α-amylase levels related significant QTL was mapped on GGA7 and cholesterol, glutamic oxaloacetic transaminase, glutamic pyruvic transaminase, and creatinine traits related suggestive QTLs were detected on GGA4, 12, 13 and 15, respectively. Further verification and fine mapping of these identified QTLs can provide valuable information for understanding the variations of clinical chemical trait in chickens.

There are five native chicken lines in Korea, which are mainly classified by plumage colors (black, white, red, yellow, gray). These five lines are very important genetic resources in the Korean poultry industry. Based on a next generation sequencing technology, whole genome sequence and reference assemblies were performed using Gallus_gallus_4.0 (NCBI) with whole genome sequences from these lines to identify common and novel single nucleotide polymorphisms (SNPs). We obtained 36,660,731,136 ± 1,257,159,120 bp of raw sequence and average 26.6-fold of 25-29 billion reference assembly sequences representing 97.288 % coverage. Also, 4,006,068 ± 97,534 SNPs were observed from 29 autosomes and the Z chromosome and, of these, 752,309 SNPs are the common SNPs across lines. Among the identified SNPs, the number of novel- and known-location assigned SNPs was 1,047,951 ± 14,956 and 2,948,648 ± 81,414, respectively. The number of unassigned known SNPs was 1,181 ± 150 and unassigned novel SNPs was 8,238 ± 1,019. Synonymous SNPs, non-synonymous SNPs, and SNPs having character changes were 26,266 ± 1,456, 11,467 ± 604, 8,180 ± 458, respectively. Overall, 443,048 ± 26,389 SNPs in each bird were identified by comparing with dbSNP in NCBI. The presently obtained genome sequence and SNP information in Korean native chickens have wide applications for further genome studies such as genetic diversity studies to detect causative mutations for economic and disease related traits.

Most reproductive traits have low heritability and are greatly affected by environmental factors. Teat number and litter size are traits related to the reproduction ability of pigs. To identify quantitative trait loci (QTLs) for teat number traits, a genome-wide association study (GWAS) was conducted using an F2 intercross between Landrace and Korean native pigs. Genotype analysis was performed using the porcine SNP 60 K beadchip. The GWAS was performed using a mixed-effects model and linear regression approach. When a genome-wide threshold was determined using the Bonferroni method (P = 1.61 × 10(-6)), 38 single nucleotide polymorphism (SNP) markers in pig chromosome 7 (SSC7) were significantly associated with three teat number traits (total teat number, left teat number, and right teat number). Among these, SNPs in 5 genes (HDDC3, LOC100156276, LOC100155863, ANPEP, SCAMP2) were selected for further study based primarily on their statistical significance. A significant association was detected in SCAMP2 g.25280 G>A for total teat number (P = 2.0 × 10(-12)), HDDC3 g.1319 G>A SNP for left teat number (P = 2.3 × 10(-7)), and SCAMP2 g.14198 G>A for right teat number (P = 4.7 × 10(-12)). These results provide valuable information about the selective breeding for desirable teat numbers in pigs.

Fatty acid (FA) composition is one of the most important parameters for the evaluation of meat quality. The stearoyl-CoA desaturase (SCD) gene is considered a positional candidate gene affecting FA composition in SSC14, based on previous quantitative trait loci studies. To evaluate the association of the SCD gene with FA composition in a Korean native pig × Landrace F(2) intercross population, we genotyped six single nucleotide polymorphisms (SNPs) of the SCD gene located in promoter region [2 SNPs (g.-353T>C, g.-233T>C)], exonic region [1 SNP (g.817C>T) in exon 2] and 3' UTR [3 SNPs (g.13311C>G, g.14384G>A, and g.14424C>T)] identified by massively parallel sequencing technology. Eighteen FA composition traits were measured in more than the 950 F(2) animals. A mixed-effect model was used to evaluate associations between these SNPs and FA composition traits in the F(2) intercross population. A detailed investigation detected that the five FA composition traits [palmitoleic acid (C16:1), stearic acid (C18:0), arachidic acid (C20:0), saturated FA, and unsaturated FA] were highly significant (P < 4.7 × 10(-5); C20:0) in association with the SNP g.-233T>C, SNP g.817C>T, SNP g.13311C>G and SNP g.14384G>A in the SCD gene, whereas SNP g.14424C>T was only significantly associated with palmitoleic acid (C16:1, P = 1.4 × 10(-3)). No significant association of FA composition traits with SNP g.-353T>C was detected. In particular, the SNP g.14384G>A accounted for 30.6 % of the additive genetic variance of palmitoleic acid (P = 1.9 × 10(-10)). These results suggest the SCD gene has a strong effect on FA composition in the crossbred pig population.

Serum Ca(++) levels play important roles in the humoral immunity. The aim of this study was to detect quantitative trait loci and the associated positional candidate genes affecting baseline serum Ca(++) concentrations. A genome-wide association study was conducted in an F(2) intercross population between Landrace and Korean native pigs using the porcine single nucleotide polymorphism (SNP) 60 K beadchip and the PLINK program based on linear regression. Data used in the study included 410 F(2) pigs. All experimental animals were genotyped with 36,613 SNP markers located throughout the pig autosomes. We identified a strong association between a SNP marker on chromosome 7 and serum Ca(++) levels (DIAS0002191, genomic control-corrected P = 7.7 × 10(-5)). The position of DIAS0002191 was closely located to SLA class III region containing the C2 gene encoding the complementary component 2 protein, a protein which is important in the humoral immune responses. De novo sequencing of the porcine C2 gene revealed a missense mutation [c.1963A

In this study, we conducted a genome-wide linkage analysis to identify the quantitative trait loci (QTL) that influence back fat thickness and carcass pH in an F(2) intercross between Landrace and Korean native pigs. Eight phenotypes related with back fat thickness and carcass pH were measured in more than 960 F(2) progeny. All experimental animals were subjected to genotypic analysis using 173 microsatellite markers located throughout the pig genome. The GridQTL program, based on the least squares regression model, was used to perform the QTL analysis. We identified 22 genome-wide significant QTL in 9 chromosomal regions (SSC1, 2, 5, 6, 7, 8, 12, 15, and 16) and 29 suggestive QTL in 16 chromosomal regions (SSC2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 14, 15, 16, 17, 18, and X). On SSC5, we detected a QTL affecting back fat thickness that accounted for 4.8 % of the phenotypic variance, which was the highest test statistic (F-ratio = 50.3 under the additive model, nominal P value = 2.5 × 10(-12)) observed in this study. Additionally, we showed that there were significant QTL on SSC16 affecting carcass pH traits. In conclusion, the QTL identified in this study together with associated positional candidate genes could play an important role in determining the genetic structure underlying the variation of back fat thickness and carcass pH in pigs.