Background: With the growing interest in the health of companion dogs, their average lifespan has increased, leading to an increase in the proportion of elderly dogs. As elderly dogs are vulnerable to various diseases, there is a need for alternatives to predict the risk of major diseases in senior dogs, prevent them in advance, and manage their health effectively. Therefore, this study was conducted to identify candidate genes and single nucleotide polymorphisms (SNPs) influencing primary angle-closure glaucoma, a major disease in elderly dogs, using the Axiom Canine HD Array and establishing foundational data. Methods: Samples from 95 dogs of 26 breeds from South Korea were analyzed using an SNP chip. Ultimately, two SNPs were selected. To assess the impact of non-synonymous SNP (nsSNPs), functional analysis of candidate genes, Hazard Assessment, and protein structure prediction were conducted. Sequencing for SNP validation involved samples from 95 dogs of ten breeds with reported domestic and international glaucoma cases. Results: The candidate gene TNS1 was associated with the integrin signaling pathway. The selected nsSNP was found to cause a mutation at the ninth position of the amino acid sequence, changing serine to leucine and resulting in alterations to the overall protein structure. Sequencing analysis results for SNP validation revealed differences in frequency among breeds. Conclusions: The identified SNP markers are potential risk prediction tools. Utilizing genotype frequency data by breed and individual could aid in disease management and contribute to advancements in the medical industry.

본 연구는 국내의 세 품종 돼지에 대하여 혈통자료를 이용한 근교계수와 유전체자료를 이용한 근교계수를 분석하고 비교하기 위하여 수행되었다. 분석에 이용된 혈통자료는 듀록, 랜드레이스 및 요크셔 종에서 각각 137,302두, 228,651두와 657,079두였고, 유전체자료의 경우 Illumina Porcine SNP 60K bead chip V2를 이용하여 수집하였으며 세 품종에서 각각 2,567개, 7,594개 및 12,906개의 자료를 이용하였다. 듀록, 랜드레이스와 요크셔에서 혈통자료를 이용하여 추정된 근교계수는 각각 0.04, 0.02 및 0.02였으며, 유전체자료를 이용하여 추정된 근교계수는 각각 0.184, 0.098 및 0.063이었다. 듀록에서 두 근교계수의 상관이 0.466으로 가장 높게 나타났다. 본 연구를 통하여 혈통완성도는 유전체 정보를 이용하여 보완할 수 있음이 확인되었으며, 유전체 정보는 집단의 유전자원 관리에도 활용도가 높아 국내 양돈산업의 근친도 관리에서 중요한 역할을 할 것으로 기대된다.

Animal genomics and breeding center works for development of livestock industry through development of breeding technologies based on genomes. Through analysis technology of genomic information with commercialization of DNA chip and development of NGS technique at present, we can select and improve superior breeding stock. DNA chip technique using microarray can analyze millions of SNP genotypes in a short period and we are studying these techniques to make a tool for genomic selection. In the United States, they made a guideline for genomic selection in dairy cattle and this guideline is utilized. In addition Semex company and CRV center use genomic selection for Holstein dairy cattle. Semex says genomic selection reduce two years compared to the existing selection, cost will be shortened 50% and improving speed will be more than 30% accelerated. In Australia, the case of using genomic information has more 10% accuracy than the case of using parent's breeding value without phenotype information. Recently development of NGS technology leads to reduction of analysis costs, increase in analysis data quantity and shorten time of analysis genome. NGS technology is innovative tool in life science. With development of NGS technology, we can expect to increase the efficiency of genomic analysis. Development of NGS technology leads us to expand whole genome study from limited gene study. Human and rodential genome is researched over the past five years, but only recently lots of livestock's genomes like cattle and pig are researched. Also for domestic, studies on livestock genome and genomic information are accomplished but we have a poor infrastructure of genomic analysis. Thus, through the application technology using SNP chip data and NGS, new breeding technology is very important for prior occupation. Animal genomics and breeding center has four strategies and these are divided by application technology. 1. Development of animal breeding and statistical genetics based on genomic information. 2. Development of genomic analysis and application technology through analysis of genetic diversity and structure. 3. Registration of traditional breeds and securing intellectual property rights based on the genome of the unique genetic resources. 4. Development of technologies for improvement of disease resistance and economic traits.

Economic traits are quantitative traits and are mostly controlled by a large number of genes. Some these genes tend to have a large effect on quantitative traits in cattle and are known as major genes primarily located at quantitative traits loci (QTL). However, in practice, QTL is linked to allele associates of the gene controlling traits of interest. It is hypothesized that if QTL explaining a part of genetic differences between animals are detected, the effect of the genes located at QTL could assist in estimating an animal’s true genetic value. Therefore, QTL information could probably provides accuracy of breeding value estimation as well as more genetic gain through selection of animals at relatively younger age. Marker assisted selection (MAS) is the indirect selection process where a quantitative trait of economic importance is selected not just based on the trait itself but also on the basis of marker linked to QTL. MAS could be useful for traits that are difficult to measure, exhibit low heritability, and are expressed late in development. Major genes which are responsible for QTL could possibly be identified first by using different techniques such as gene expression analysis and QTL mapping. Thereafter, the information generated could be implemented for MAS in estimating breeding value. In this review we focused on delivering genome information into Hanwoo breeding program.

Comparative analysis is a typically useful tool for translating genomic information from one species to another. However, currently available softwares are relatively difficult to directly use for researchers that are not familiar with use of bioinformatic tools. Therefore, we intended to develop a new platforms and/or interface through which one can use in more comfortable way, based on the concept of interactive comparative analysis. Towards this direction, we, firstly, constructed relational database to store the information on abiotic stress genes identified from multiple plant species using various resources, such as the TAIR (http://www.arabidopsis.org), gene expression profiles and relevant literatures, and linked with comparative analysis interface. For purposes of comparative analysis and identification of synteny blocks, cross-species orthologous genes were determined using a combination of tBlastX and BlastP homology searches. We adapted and developed a Circos-like format to present resulting comparative maps. Users can readily choose analysis parameters, for example individual genes and specific chromosomes for chosen species, in the pane of analysis DB, which is useful feature to avoid complexity of comparative genomic analysis. This DB-associated comparative analysis tool, developed in this study, will be able to provide customer-friendly interface for comparative analysis and extend its utility across a broader range of plant genomes.

Cross-species translation of genomic information may play a pivotal role in applying biological knowledge gained from one species to other genomes. Abiotic stress-responsive genes in Arabidopsis have been translated to a legume model system, Medicago truncatula. A total of 1,370 Arabidopsis genes were identified by searching TAIR database, expression profiling data and literatures. For purposes of cross-genome identification of orthologous genes, tBlastX or BlastP were employed between these two model systems. Candidate genes potentially associated with abiotic stress responses were classified into 18 functional criteria and corresponding genomic locations were analyzed by Circos program. To do this, user-friendly bioinformatic analysis platform was established. In order to discover abiotic stress-associated genes, gene network and/or interactome analyses were conducted using a combination of AraNet web-based platform and CytoScape program. As a result, we could identify 240 key genes that appeared to play an important role within central gene networks. We anticipate that these genes may impact molecular breeding programs by developing them into genetic markers and discovering trait-associated nucleotide variations.