Exploring the genetic factors behind the discrepancy in resistance to bovine tuberculosis between African zebu cattle and European taurine cattle.

Caused by the pathogenic agent Mycobacterium bovis, bovine tuberculosis (bTB) is a major concern in cattle breeding due to both its zoonotic potential and economic impact. Greater resistance to this disease has been reported in certain African zebu breeds compared to European taurine breeds. However the genetic basis for the lower susceptibility to bTB infection observed in zebu cattle remains poorly explored. This study was conducted on whole genome sequencing data of three bTB infection-resistant African zebu breeds and two bTB infection-susceptible taurine breeds to decipher the genetic background. A set of four selection signature statistics based on linkage disequilibrium, site frequency spectrum, and population differentiation were used on SNPs whereas between population variance based VST and t-test were used on CNVs. As a complement, genes from previous literature reported as candidate genes for bTB resistance were also inspected to identify genetic variations. Interestingly, the resulting nine candidate genes had deleterious missense variants (SHC3, IFNGR1, TLR2, TLR6, IL1A, LRRK2, EP300 and IRAK4) or a CNV difference (CD48) segregating between the groups. The genes found in the study play a role in immune pathways activated during Mycobacterium infection, contributing to the proliferation of immune cells and the granuloma formation, ultimately modulating the outcome of the infectious event. In particular, a deleterious variant in the LRRK2 gene, whose deficiency has been linked to improved prognosis upon tuberculosis infection, was found in the bTB infection-resistant zebu breeds. Therefore, these genes constitute credible candidates in explaining the discrepancy in Mycobacterium bovis infection susceptibility among different breed.

Designing a Multiepitope Vaccine against Eastern Equine Encephalitis Virus: Immunoinformatics and Computational Approaches.

Eastern equine encephalitis virus (EEEV) is a significant threat to human and animal populations, causing severe encephalitis, often leading to long-term neurological complications and even mortality. Despite this, no approved antiviral treatments or EEEV human vaccines currently exist. In response, we utilized immunoinformatics and computational approaches to design a multiepitope vaccine candidate for EEEV. By screening the structural polyprotein of EEEV, we predicted both T-cell and linear B-cell epitopes. These epitopes underwent comprehensive evaluations for their antigenicity, toxicity, and allergenicity. From these evaluations, we selected ten epitopes highly suitable for vaccine design, which were connected with adjuvants using a stable linker. The resulting vaccine construct demonstrated exceptional antigenic, nontoxic, nonallergenic, and physicochemical properties. Subsequently, we employed molecular docking and molecular dynamics simulations to reveal a stable interaction pattern between the vaccine candidate and Toll-like receptor 5. Besides, computational immune simulations predicted the vaccine's capability to induce robust immune responses. Our study addresses the urgent need for effective EEEV preventive strategies and offers valuable insights for EEEV vaccine development. As EEEV poses a severe threat with potential spread due to climate change, our research provides a crucial step in enhancing public health defenses against this menacing zoonotic disease.

Selenobaculum gbiensis gen. nov. sp. nov., a new bacterium isolated from the gut microbiota of a patient with Crohn's disease.

The human gut microbiota is a complex ecology comprising approximately 10 to 100 trillion microbial cells. Most of the bacteria detected by 16s rRNA sequencing have yet to be cultured, but intensive attempts to isolate the novel bacteria have improved our knowledge of the gut microbiome composition and its roles within human host. In our culturomics study, a novel gram-negative, motile, obligately anaerobic, rod-shaped bacteria, designated as strain ICN-92133T, was isolated from a fecal sample of a 26-year-old patient with Crohn's disease. Based on the 16s rRNA sequence of strain ICN-92133T, the phylogeny analysis placed the strain into the family Selenomonadaceae, showing 93.91% similarity with the closely related Massilibacillus massiliensis strain DSM 102838T. Strain ICN-92133T exhibited a genome size of 2,679,003 bp with a GC content of 35.5% which was predicted to contain 26 potential virulence factors and five antimicrobial resistance genes. In comparative genomic analysis, strain ICN-92133T showed digital DNA-DNA Hybridization and OrthoANI values lower than 21.9% and 71.9% with the closest type strains, respectively. In addition, comparing phenotypic, biochemical, and cellular fatty acids with those of closely related strains revealed the distinctiveness of strain ICN-92133T. Based on the taxonogenomic results, strain ICN-92133T is proposed as a novel species belonging to a new genus. Therefore, we suggest the name of the new genus Selenobaculum gen. nov. within the family Selenomonadaceae and strain ICN-92133T (= KCTC 25622T = JCM 36070T) as a type strain of new species Selenobaculum gbiensis sp. nov.

Repurposing existing drugs for monkeypox: applications of virtual screening methods.

BACKGROUND: Monkeypox is endemic to African region and has become of Global concern recently due to its outbreaks in non-endemic countries. Although, the disease was first recorded in 1970, no monkeypox specific drug or vaccine exists as of now. METHODS: We applied drug repositioning method, testing effectiveness of currently approved drugs against emerging disease, as one of the most affordable approaches for discovering novel treatment measures. Techniques such as virtual ligand-based and structure-based screening were applied to identify potential drug candidates against monkeypox. RESULTS: We narrowed down our results to 6 antiviral and 20 anti-tumor drugs that exhibit theoretically higher potency than tecovirimat, the currently approved drug for monkeypox disease. CONCLUSIONS: Our results indicated that selected drug compounds displayed strong binding affinity for p37 receptor of monkeypox virus and therefore can potentially be used in future studies to confirm their effectiveness against the disease.

Molecular dynamics simulation of pyruvate kinase to investigate improved thermostability of artificially selected strain in Enterococcus faecium.

BACKGROUND: Enterococcus faecium (E. faecium) is a member of symbiotic lactic acid bacteria in gastrointestinal tract and it was successfully used to treat diarrhea cases in humans. For a lactobacteria to survive during the pasteurization process, resistance of proteins to denaturation at high temperatures is crucial. Pyruvate kinase (PYK) is one of the proteins possessing such property. It plays a major role during glycolysis by producing pyruvate and adenosine triphosphate (ATP). OBJECTIVE: To assess the acquired thermostability of PYK of ALE strain using in silico methods. METHODS: First, we predicted and assessed tertiary structures of our proteins using SWISS-MODEL homology modelling server. Second, we then applied molecular dynamics (MD) simulation to simulate and assess multiple properties of molecules. Therefore, we implemented comparative MD to evaluate thermostability of PYK of recently developed high temperature resistant strain of E. faecium using Adaptive Laboratory Evolution (ALE) method. After 20ns of simulation at different temperatures, we observed that ALE enhanced strain demonstrated slightly better stability at 300, 340 and 350 K compared to that of the wild type (WT) strain. RESULTS: We collected the results of MD simulation at four temperature points: 300, 340, 350 and 400 K. Our results showed that the protein demonstrated increased stability at 340 and 350 K. CONCLUSION: Results of these study suggest that PYK of ALE enhanced strain of E. faecium demonstrates overall better stability at elevated temperatures compared to that of WT strain.

Widespread false gene gains caused by duplication errors in genome assemblies.

BACKGROUND: False duplications in genome assemblies lead to false biological conclusions. We quantified false duplications in popularly used previous genome assemblies for platypus, zebra finch, and Anna's Hummingbird, and their new counterparts of the same species generated by the Vertebrate Genomes Project, of which the Vertebrate Genomes Project pipeline attempted to eliminate false duplications through haplotype phasing and purging. These assemblies are among the first generated by the Vertebrate Genomes Project where there was a prior chromosomal level reference assembly to compare with. RESULTS: Whole genome alignments revealed that 4 to 16% of the sequences are falsely duplicated in the previous assemblies, impacting hundreds to thousands of genes. These lead to overestimated gene family expansions. The main source of the false duplications is heterotype duplications, where the haplotype sequences were relatively more divergent than other parts of the genome leading the assembly algorithms to classify them as separate genes or genomic regions. A minor source is sequencing errors. Ancient ATP nucleotide binding gene families have a higher prevalence of false duplications compared to other gene families. Although present in a smaller proportion, we observe false duplications remaining in the Vertebrate Genomes Project assemblies that can be identified and purged. CONCLUSIONS: This study highlights the need for more advanced assembly methods that better separate haplotypes and sequence errors, and the need for cautious analyses on gene gains.

Establishment and evaluation of prediction model for multiple disease classification based on gut microbial data.

Diseases prediction has been performed by machine learning approaches with various biological data. One of the representative data is the gut microbial community, which interacts with the host's immune system. The abundance of a few microorganisms has been used as markers to predict diverse diseases. In this study, we hypothesized that multi-classification using machine learning approach could distinguish the gut microbiome from following six diseases: multiple sclerosis, juvenile idiopathic arthritis, myalgic encephalomyelitis/chronic fatigue syndrome, acquired immune deficiency syndrome, stroke and colorectal cancer. We used the abundance of microorganisms at five taxonomy levels as features in 696 samples collected from different studies to establish the best prediction model. We built classification models based on four multi-class classifiers and two feature selection methods including a forward selection and a backward elimination. As a result, we found that the performance of classification is improved as we use the lower taxonomy levels of features; the highest performance was observed at the genus level. Among four classifiers, LogitBoost-based prediction model outperformed other classifiers. Also, we suggested the optimal feature subsets at the genus-level obtained by backward elimination. We believe the selected feature subsets could be used as markers to distinguish various diseases simultaneously. The finding in this study suggests the potential use of selected features for the diagnosis of several diseases.

Identification of genes related to intramuscular fat content of pigs using genome-wide association study.

OBJECTIVE: The aim of this study is to identify single nucleotide polymorphisms (SNPs) and genes related to pig IMF and estimate the heritability of intramuscular fat content (IMF). METHODS: Genome-wide association study (GWAS) on 704 inbred Berkshires was performed for IMF. To consider the inbreeding among samples, associations of the SNPs with IMF were tested as random effects in a mixed linear model using the genetic relationship matrix by GEMMA. Significant genes were compared with reported pig IMF quantitative trait loci (QTL) regions and functional classification of the identified genes were also performed. Heritability of IMF was estimated by GCTA tool. RESULTS: Total 365 SNPs were found to be significant from a cutoff of p-value <0.01 and the 365 significant SNPs were annotated across 120 genes. Twenty five genes were on pig IMF QTL regions. Bone morphogenetic protein-binding endothelial cell precursor-derived regulator, forkhead box protein O1, ectodysplasin A receptor, ring finger protein 149, cluster of differentiation, tyrosine-protein phosphatase non-receptor type 1, SRY (sex determining region Y)-box 9 (SOX9), MYC proto-oncogene, and macrophage migration inhibitory factor were related to mitogen-activated protein kinase pathway, which regulates the differentiation to adipocytes. These genes and the genes mapped on QTLs could be the candidate genes affecting IMF. Heritability of IMF was estimated as 0.52, which was relatively high, suggesting that a considerable portion of the total variance of IMF is explained by the SNP information. CONCLUSION: Our results can contribute to breeding pigs with better IMF and therefore, producing pork with better sensory qualities.

Genome sequence of pacific abalone (Haliotis discus hannai): the first draft genome in family Haliotidae.

Background: Abalones are large marine snails in the family Haliotidae and the genus Haliotis belonging to the class Gastropoda of the phylum Mollusca. The family Haliotidae contains only one genus, Haliotis, and this single genus is known to contain several species of abalone. With 18 additional subspecies, the most comprehensive treatment of Haliotidae considers 56 species valid [ 1 ]. Abalone is an economically important fishery and aquaculture animal that is considered a highly prized seafood delicacy. The total global supply of abalone has increased 5-fold since the 1970s and farm production increased explosively from 50 mt to 103 464 mt in the past 40 years. Additionally, researchers have recently focused on abalone given their reported tumor suppression effect. However, despite the valuable features of this marine animal, no genomic information is available for the Haliotidae family and related research is still limited. To construct the H . discus hannai genome, a total of 580-G base pairs using Illumina and Pacbio platforms were generated with 322-fold coverage based on the 1.8-Gb estimated genome size of H . discus hannai using flow cytometry. The final genome assembly consisted of 1.86 Gb with 35 450 scaffolds (>2 kb). GC content level was 40.51%, and the N50 length of assembled scaffolds was 211 kb. We identified 29 449 genes using Evidence Modeler based on the gene information from ab initio prediction, protein homology with known genes, and transcriptome evidence of RNA-seq. Here we present the first Haliotidae genome, H . discus hannai , with sequencing data, assembly, and gene annotation information. This will be helpful for resolving the lack of genomic information in the Haliotidae family as well as providing more opportunities for understanding gastropod evolution.

Genomic Insights and Its Comparative Analysis with Yersinia enterocolitica Reveals the Potential Virulence Determinants and Further Pathogenicity for Foodborne Outbreaks.

Yersinia enterocolitica is a well-known foodborne pathogen causing gastrointestinal infections worldwide. The strain Y. enterocolitica FORC_002 was isolated from the gill of flatfish (plaice) and its genome was sequenced. The genomic DNA consists of 4,837,317 bp with a GC content of 47.1%, and is predicted to contain 4,221 open reading frames, 81 tRNA genes, and 26 rRNA genes. Interestingly, genomic analysis revealed pathogenesis and host immune evasion-associated genes encoding guanylate cyclase (Yst), invasin (Ail and Inv), outer membrane protein (Yops), autotransporter adhesin A (YadA), RTX-like toxins, and a type III secretion system. In particular, guanylate cyclase is a heat-stable enterotoxin causing Yersinia-associated diarrhea, and RTX-like toxins are responsible for attachment to integrin on the target cell for cytotoxic action. This genome can be used to identify virulence factors that can be applied for the development of novel biomarkers for the rapid detection of this pathogen in foods.

Evolutionary constraints over microsatellite abundance in larger mammals as a potential mechanism against carcinogenic burden.

Larger organisms tend to live longer, have more potentially carcinogenic cells, and undergo more cell divisions. While one might intuitively expect cancer incidence to scale with body size, this assertion does not hold over the range of different mammals. Explaining this lack of correlation, so-called 'Peto's paradox' can likely increase our understanding of how cancer defense mechanisms are shaped by natural selection. Here, we study the occurrence of microsatellite in mammal genomes and observe that animals with expanded body size restrain the number of microsatellite. To take into account of higher mutation rate in the microsatellite region compared to that of genome, limiting the abundance of somatic mutations might explain how larger organisms could overcome the burden of cancer. These observations may serve as the basis to better understand how evolution has modeled protective mechanisms against cancer development.

The Prediction of the Expected Current Selection Coefficient of Single Nucleotide Polymorphism Associated with Holstein Milk Yield, Fat and Protein Contents.

Milk-related traits (milk yield, fat and protein) have been crucial to selection of Holstein. It is essential to find the current selection trends of Holstein. Despite this, uncovering the current trends of selection have been ignored in previous studies. We suggest a new formula to detect the current selection trends based on single nucleotide polymorphisms (SNP). This suggestion is based on the best linear unbiased prediction (BLUP) and the Fisher's fundamental theorem of natural selection both of which are trait-dependent. Fisher's theorem links the additive genetic variance to the selection coefficient. For Holstein milk production traits, we estimated the additive genetic variance using SNP effect from BLUP and selection coefficients based on genetic variance to search highly selective SNPs. Through these processes, we identified significantly selective SNPs. The number of genes containing highly selective SNPs with p-value <0.01 (nearly top 1% SNPs) in all traits and p-value <0.001 (nearly top 0.1%) in any traits was 14. They are phosphodiesterase 4B (PDE4B), serine/threonine kinase 40 (STK40), collagen, type XI, alpha 1 (COL11A1), ephrin-A1 (EFNA1), netrin 4 (NTN4), neuron specific gene family member 1 (NSG1), estrogen receptor 1 (ESR1), neurexin 3 (NRXN3), spectrin, beta, non-erythrocytic 1 (SPTBN1), ADP-ribosylation factor interacting protein 1 (ARFIP1), mutL homolog 1 (MLH1), transmembrane channel-like 7 (TMC7), carboxypeptidase X, member 2 (CPXM2) and ADAM metallopeptidase domain 12 (ADAM12). These genes may be important for future artificial selection trends. Also, we found that the SNP effect predicted from BLUP was the key factor to determine the expected current selection coefficient of SNP. Under Hardy-Weinberg equilibrium of SNP markers in current generation, the selection coefficient is equivalent to 2*SNP effect.

Analysis of Stage-Specific Gene Expression Profiles in the Uterine Endometrium during Pregnancy in Pigs.

The uterine endometrium plays a critical role in regulating the estrous cycle and the establishment and maintenance of pregnancy in mammalian species. Many studies have investigated the expression and function of genes in the uterine endometrium, but the global expression pattern of genes and relationships among genes differentially expressed in the uterine endometrium during gestation in pigs remain unclear. Thus, this study investigated global gene expression profiles using microarray in pigs. Diverse transcriptome analyses including clustering, network, and differentially expressed gene (DEG) analyses were performed to detect endometrial gene expression changes during the different gestation stages. In total, 6,991 genes were found to be differentially expressed by comparing genes expressed on day (D) 12 of pregnancy with those on D15, D30, D60, D90 and D114 of pregnancy, and clustering analysis of detected DEGs distinguished 8 clusters. Furthermore, several pregnancy-related hub genes such as ALPPL2, RANBP17, NF1B, SPP1, and CST6 were discovered through network analysis. Finally, detected hub genes were technically validated by quantitative RT-PCR. These results suggest the complex network characteristics involved in uterine endometrial gene expression during pregnancy and indicate that diverse patterns of stage-specific gene expression and network connections may play a critical role in endometrial remodeling and in placental and fetal development to establish and maintenance of pregnancy in pigs.

Bovine Genome-wide Association Study for Genetic Elements to Resist the Infection of Foot-and-mouth Disease in the Field.

Foot-and-mouth disease (FMD) is a highly contagious disease affecting cloven-hoofed animals and causes severe economic loss and devastating effect on international trade of animal or animal products. Since FMD outbreaks have recently occurred in some Asian countries, it is important to understand the relationship between diverse immunogenomic structures of host animals and the immunity to foot-and-mouth disease virus (FMDV). We performed genome wide association study based on high-density bovine single nucleotide polymorphism (SNP) chip for identifying FMD resistant loci in Holstein cattle. Among 624532 SNP after quality control, we found that 11 SNPs on 3 chromosomes (chr17, 22, and 15) were significantly associated with the trait at the p.adjust <0.05 after PERMORY test. Most significantly associated SNPs were located on chromosome 17, around the genes Myosin XVIIIB and Seizure related 6 homolog (mouse)-like, which were associated with lung cancer. Based on the known function of the genes nearby the significant SNPs, the FMD resistant animals might have ability to improve their innate immune response to FMDV infection.

Gene expression profiling of bovine mammary gland epithelial cells stimulated with lipoteichoic acid plus peptidoglycan from Staphylococcus aureus.

A Gram-positive bacterium, Staphylococcus aureus is known to be one of the major pathogenic bacteria responsible for causing bovine mastitis. Among the various cell wall components of S. aureus, lipoteichoic acid (LTA) and peptidoglycan (PGN) are closely associated with inflammatory responses. However, the role of LTA and PGN derived from S. aureus in bovine mastitis has not been clearly elucidated. In this study, we characterized the gene expression profile of a bovine mammary gland epithelial cell line, MAC-T cells, in the presence of LTA and PGN from S. aureus. LTA plus PGN, but not LTA or PGN alone, activated MAC-T cells. The analysis of transcriptional profiles using an Affymetrix genechip microarray showed that stimulation with LTA plus PGN produced a total of 2019 (fold change >1.2) differentially expressed genes (DEGs), with 801 up-regulated genes and 1218 down-regulated genes. Of the up-regulated genes, 14 inflammatory mediator-related DEGs, 22 intra-cellular signaling molecule-related DEGs, and 15 transcription factor-related DEGs were observed, whereas among the down-regulated DEGs 17 inflammation-related DEGs were found. The microarray results were confirmed using real-time RT-PCR of 18 genes with substantial changes in expression (9 each from the up-regulated and down-regulated DEGs). These results provide a comprehensive analysis of gene-expression profiles elicited by S. aureus LTA and PGN in MAC-T cells, contributing to an understanding of the pathogenesis for S. aureus-induced bovine mastitis.

Semantic Modeling for SNPs Associated with Ethnic Disparities in HapMap Samples.

Single-nucleotide polymorphisms (SNPs) have been emerging out of the efforts to research human diseases and ethnic disparities. A semantic network is needed for in-depth understanding of the impacts of SNPs, because phenotypes are modulated by complex networks, including biochemical and physiological pathways. We identified ethnicity-specific SNPs by eliminating overlapped SNPs from HapMap samples, and the ethnicity-specific SNPs were mapped to the UCSC RefGene lists. Ethnicity-specific genes were identified as follows: 22 genes in the USA (CEU) individuals, 25 genes in the Japanese (JPT) individuals, and 332 genes in the African (YRI) individuals. To analyze the biologically functional implications for ethnicity-specific SNPs, we focused on constructing a semantic network model. Entities for the network represented by "Gene," "Pathway," "Disease," "Chemical," "Drug," "ClinicalTrials," "SNP," and relationships between entity-entity were obtained through curation. Our semantic modeling for ethnicity-specific SNPs showed interesting results in the three categories, including three diseases ("AIDS-associated nephropathy," "Hypertension," and "Pelvic infection"), one drug ("Methylphenidate"), and five pathways ("Hemostasis," "Systemic lupus erythematosus," "Prostate cancer," "Hepatitis C virus," and "Rheumatoid arthritis"). We found ethnicity-specific genes using the semantic modeling, and the majority of our findings was consistent with the previous studies - that an understanding of genetic variability explained ethnicity-specific disparities.

Phylogenomics and molecular evolution of foot-and-mouth disease virus.

This report describes the use of Bayesian methods to analyze polyprotein coding region sequences (n = 217) obtained from GenBank to define the genome-wide phylogeny of foot and mouth disease virus (FMDV). The results strongly supported the monophyly of five FMDV serotypes, O, A, Asia 1, C, and SAT 3, while sequences for the two remaining FMDV serotypes, SAT 1 and SAT 2 did not separate into entirely distinct clades. The phylogenomic tree revealed three sister-group relationships, serotype O + Asia 1, A + C, and SAT 1 + 3 + 2, with a new branching pattern: {[(O, Asia 1), (A, C)], (SAT 1, 2, 3)}. Within each serotype, there was no apparent periodic, geographic, or host species influence on the evolution of global FMDVs. Analysis of the polyprotein coding region of these sequences provided evidence for the influence of purifying selection on the evolution of FMDV. Using a Bayesian coalescent approach, the evolutionary rate of FMDV isolates that circulated during the years 1932-2007 was estimated to be 1.46 × 10(-3) substitutions/site/year, and the most recent common ancestor of the virus existed approximately 481 years ago. Bayesian skyline plot revealed a population expansion in the early 20(th) century that was followed by a rapid decline in population size from the late 20(th) century to the present day. These findings provide new insights into the mechanisms that impact on the evolution of this important livestock pathogen.

Improved establishment of autologous stem cells derived from preantral follicle culture and oocyte parthenogenesis.

This study was conducted to improve establishing autologous embryonic stem cells (ESCs) by culture of preantral follicles and parthenogenetic activation of oocytes. First, paternal inheritance of the follicle donor was changed without altering maternal heredity by employing B6CBAF1 instead of B6D2F1 mice. A significant increase in the establishment of parthenogenetic ESCs was detected after the change, and a different gene expression pro-file was detected in the ESCs established. Among 62 stemness-related genes showing different expression level between two strains, 35 (56.5%) were lower in the rarely established ESCs (B6D2F1) than in the easily established ESCs (B6CBAF1). Several paternally expressed genes were aberrantly expressed in the rarely established ESCs. Second, the establishment of parthenogenetic ESCs in B6D2F1 was significantly improved when preantral follicles were cultured in glutathione (GSH)-containing medium. In the ESCs derived from GSH-treated follicles, 77% of the 62 genes showing the difference increased their expression. Translation of several proteins related to stemness (Wnt-1, beta-catenin, p-p44/42, and smad) was similar between the parthenogenetic ESCs established after GSH treatment and the control E14 ESCs. We concluded that change in genetic inheritance and exposure of in vitro-growing ovarian follicles to GSH contributes to improving establishment of parthenogenetic ESCs, which may help increase the feasibility of the established lines for patient-specific, stem cell therapy.

Identification of breed-specific DNA polymorphisms for a simple and unambiguous screening system in germline chimeric chickens.

In the chicken, Dominant white is one of the major loci affecting feather color. Germline chimeric chickens are identified by testcross analysis using this genetic marker. The testcross, however, is a time-consuming and laborious procedure, resulting in the need for a faster and simpler molecular method. A recent study showed that Dominant white was exclusively associated with a 9-bp insertion in the PMEL17 gene. We searched for breed-specific sequence polymorphisms in the PMEL17 gene among White Leghorn (WL) (white feather), Korean Ogol Chicken (KOC) (black feather), and Barred Plymouth Rock (grayish-white, each feather regularly crossed with parallel blue-black bars). In addition to the 9-bp insertion, WLs and KOCs have unique bases in single nucleotide polymorphisms (SNPs) at the 1,777th and 3,118th bases in the PMEL17 gene. To detect these sequence polymorphisms, allele-specific polymerase chain reaction (AS-PCR) was performed, which successfully distinguished the different breeds. We confirmed the ability of the AS primers to detect germline chimerism. This simple method can be widely used for the screening of germline chimeric chickens.