Genetic analysis has great potential as a tool to differentiate between different species and breeds of livestock. In this study, the optimal combinations of single nucleotide polymorphism (SNP) markers for discriminating the Yeonsan Ogye chicken ( Gallus gallus domesticus ) breed were identified using high-density 600K SNP array data. In 3,904 individuals from 198 chicken breeds, SNP markers specific to the target population were discovered through a case-control genome-wide association study (GWAS) and filtered out based on the linkage disequilibrium blocks. Significant SNP markers were selected by feature selection applying two machine learning algorithms: Random Forest (RF) and AdaBoost (AB). Using a machine learning approach, the 38 (RF) and 43 (AB) optimal SNP marker combinations for the Yeonsan Ogye chicken population demonstrated 100% accuracy. Hence, the GWAS and machine learning models used in this study can be efficiently utilized to identify the optimal combination of markers for discriminating target populations using multiple SNP markers.

Chicken plumage colouration is an important trait related to productivity in poultry industry. Therefore, the genetic basis for pigmentation in chicken plumage is an area of great interest. However, the colour trait is generally regarded as a qualitative trait and representing colour variations is difficult. In this study, we developed a method to quantify and classify colour using an F2 population crossed from two pure lines: White Leghorn and the Korean indigenous breed Yeonsan Ogye. Using red, green, and blue values in the cropped body region, we identified significant genomic regions on chromosomes 33:3 160 480–7 447 197 and Z:78 748 287–79 173 793. Furthermore, we identified two potential candidate genes (PMEL and MTAP) that might have significant effects on melanin‐based plumage pigmentation. Our study presents a new phenotyping method using a computer vision approach and provides new insights into the genetic basis of melanin‐based feather colouration in chickens.

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Genome-wide association study for the free amino acid and nucleotide components of breast meat in an F2 crossbred chicken population Running Title (within 10 words)GWAS for free amino acid and nucleotide of chicken meat

Chickens are a species of vertebrate with varying colors. Various colors of chickens must be classified to find color-related genes. In the past, color scoring was performed based on human visual observation. Therefore, chicken colors have not been measured with precise standards. In order to solve this problem, a computer vision approach was used in this study. Image quantization based on k-means clustering for all pixels of RGB values can objectively distinguish inherited colors that are expressed in various ways. This study was also conducted to determine whether plumage color differences exist in the reciprocal cross lines between two breeds: black Yeonsan Ogye (YO) and White Leghorn (WL). Line B is a crossbred line between YO males and WL females while Line L is a reciprocal crossbred line between WL males and YO females. One male and ten females were selected for each F 1 line, and full-sib mating was conducted to generate 883 F 2 birds. The results indicate that the distribution of light and dark colors of k-means clustering converged to 7:3. Additionally, the color of Line B was lighter than that of Line L (P<0.01). This study suggests that the genes underlying plumage colors can be identified using quantification values from the computer vision approach described in this study.

Ogye, an indigenous Korean chicken breed has entirely black external features and internal organs. White Leghron, an transboundary breed has white color features as opposed to Ogye. We make crossbreed (Ogye x White Leghorn) to investigate how the phenotype appeared in F1. In F0, 5 females and 1 male were selected for each parental type; 1) Ogye(♂) x White leghorn(♀), 2) White leghron(♂) x Ogye(♀). We A total of 321 individuals of F1 were made through artificial insemination. We measured body weights at birth, 8 weeks, 16 weeks, 24 weeks, and 32 weeks of age. In 1) type females, the average of body weight at each period was 39.04±0.32, 613.18±6.86, 1149.37±7.76, 1463.97±13.25, 1718.02±14.83 respectively. In 2 type females, that was 30.57±0.21, 543.19±7.54, 1069.63±12.92, 1410.06±10.80, 1527.53±13.73. The P-value values for each period were less than 0.05. In 1) type males, the average of body weight at each period was 39.18±0.34, 744.70±7.84, 1579.39±15.76, 2014.63±19.15, 2310.89±20.58. In 2 type females, that was 30.71±0.24, 683.75±9.51, 1419.79±15.76, 1800.00±18.88, 2064.79±19.68. The P-value values for each period were also less than 0.05. In the case of feather color, it was generally white, but black spots appeared only in females produced in type 1). Comb and beak color was generally also red, but black appeared only in in females produced in type 1). From these results, it can be estimated that paternal factors such as weight and appearance are greatly affected, and we plan to investigate the genetic patterns of each trait through F2 construction in the future.

Application of genomic big data to analyze the genetic diversity and population structure of Korean domestic chickens Running Title (within 10 words) Genetic diversity and population structure of Korean domestic chickens Author