한반도에서의 기후 변화는 최근까지 해충이 아니던 토착 곤충이나 비례 곤충들이 해충화 될 수 있는 가능성을 높여주고 있다. 가장 중요한 예가 토착 곤충이던 풀무치의 대량 발생에 따른 해충화가 있다. 낮은 밀도에서는 식생에 위험을 주지 않는 단독형으로 존재를 하던 풀무치가 평균온도의 상승과 강우 패턴의 변화로 대량 발생을 하여 강력한 이동성을 가지고 식생을 파괴하는 군집형으로 변화된 예가 있다. 하지만, 아직까지, 단독형에서 군집형으 로의 변화에 대한 기전이해는 완성이 되지 않은 상태이다. 기후의 변화는 겨울철 평균기온의 상승을 가져와서 한반도에서 월동이 불가능했던 해충이나 약제 저항성 계통들이 급속도로 번식할 수 있는 가능성을 열어 놓았다. 그러므로, 이러한 약제 저항성과 기후변화와 관련성에 대한 유전자 수준에서의 변화에 대한 이해가 필요한 실정이다. 위의 목적을 달성하기 위하여 우리는 다중분석학을 이용하여 연구를 진행하여 왔고, 연구 결과를 바탕으로 종 특이적이면 환경 친화적인 방제방법의 개발 연구를 진행하여 와서 이에 대한 연구결과를 발표한다(RDA Grant No. PJ010821032018).

It became possible to perform genomic predictions using single nucleotide polymorphism (SNP) with advancements in genomics technology, not only in human but in livestock as well. There are strong interests in improving economical traits in livestock through identifying causative mutation, genes or predicting genomic breeding values. We present the current status of genome prediction studies for phenotype estimation of economic traits in livestock from various perspectives based on the genomic area. First, we introduce theoretical background of genomic prediction methods and newest development on SNP information. Thanks to develop sequencing technology, multi-omics data can be used to predict phenotypes associated with the economic traits. In particular, many studies show that genomic prediction accuracy of genomic partitioning data based on the biological information is higher than that of commercial SNP chip. Therefore, multi-omics data can be useful for genomic prediction studies. It is also important that researchers should consider factors affecting genomic prediction accuracy such as heritability, Quantitative Trait Loci (QTL) and marker density, size and structure of reference population. We also introduce genomic prediction studies based on the integration of multi-omics data that shows improvement of prediction accuracy than typical Genomic Best Linear Unbiased Prediction (GBLUP) models. We concluded that genomic prediction studies can be expanded to apply social issues, new phenotypes, or precision agriculture such as diseases, climate change, and metabolism including economic traits with multi-omics data using high-throughput technologies.

The detrimental effect of high salinity on crop production is a serious problem. However, the number of genes with known functions relating to salinity tolerance is very limited in rice. To effectively address this limitation, selection of useful candidate genes and identification of major regulatory factors through global approaches are necessary. To this end, we used three data series of affymetrix array data produced with salt-treated samples from NCBI Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/) and identified 653 rice genes commonly differentially expressed under three salt-stress conditions. While evaluating the quality of selected candidate genes for salt-stress responses, Gene ontology enrichment analysis revealed that responses to salt and water stresses of biological process category are highly overrepresented in salt-stress conditions. In addition, the major salt stress-responsive metabolism process and regulatory gene modules are classified through MapMan analysis, and detailed elements for further studies are suggested. Based on this, we proposed a salt stress-responsive signaling pathway in rice. The functional analysis of the main signal transduction and transcription regulation factors identified in this pathway will shed light on a novel regulatory metabolism process that can be manipulated to develop crops with enhanced salinity tolerance.

NABIC(National Agricultural Biotechnology Information Center) established integrated management system of agricultural omics information to achieve the agricultural bio-information resources of Korea. The amount of bio-information is enormously increasing due to emergence of NGS(Next Generation Sequencing) technology. We has building, maintaining and providing agricultural bio-information databases and information services. Various data type for submission is available such as genome, proteome, transcriptome, metabolome, molecular marker, etc. We issue the submission confirmation which is available for research achievement. Currently, the amount of data submitted on our system is 4.3Tb. We are planning to integrate genome annotation system and NGS analysis system this year. The Agricultural Omics Information Submission System is available through web site(http://nabic.naas.go.kr/submission).