Evaluation of mungbean lines for the resistance to sprout rot caused by pseudomonas species

Velusamy Vijayanand,Euiho Park 한국육종학회 2011 한국육종학회 학술발표회 발표요지 Vol.43 No.-

Evaluation of the Resistance of Mungbean Lines to Sprout Rot Caused by Pseudomonas species

Vijayanand Velusamy(벨루사미비제야난드),Euiho Park(박의호) 한국생명과학회 2012 생명과학회지 Vol.22 No.7

녹두나물(숙주나물)은 국내뿐만 아니라 세계적으로도 널리 이용되고 있는 채소다. 그런데 녹두나물 재배를 하는 과정에서 발생되는 녹두나물 무름병은 녹두나물 생산량은 물론 품질을 심각하게 저하시킨다. 본 연구에서는 녹두나물 부패 조직으로부터 70계통의 병원균을 분리하였으며, 각 병원균의 병원성을 검정하였다. 그 가운데 강한 병원성을 가진 Pseudomonas 균류의 계통 YV-St-033를 확인하여 선발하였으며, 분리된 병원균계의 16S rRNA 유전자 염기서열을 분석하고 유전학적 유연관계를 분석하였다. YV-St-033는 P. mosselii, P. putita, P. fluorescens, P. entomophila, P. lecoglossicida 등의 종이 속한 그룹으로 확인이 되었으며, Pseudomonas mosselii R10 strain과 가장 높은 염기서열 identity (약 99%)를 보였다. 또한 YV-St-033 strain을 이용하여 영남대학교에서 보유하고 있는 녹두 유전자원들에 대해 녹두나물 무름병 저항성을 검정하였다. 3일간 배양한 녹두에 병원균을 접종하고 녹두의 생장율을 비교한 결과 YV148 line에서 높은 저항성이 확인되었으며, 그 외 녹두 계통에서도 부분적인 저항성을 나타내었다. 숙주나물 무름병에 저항성을 보인 YV 148 계통은 나물이 가늘고 연하고 생장율이 우수하여 앞으로 품종 육종의 좋은 재료로 활용될 수 있을 것으로 판단되었다. Mungbean sprout rot is one of the most serious problems of the commercial mungbean sprout industry. In this study, 70 strains of mungbean sprout rot pathogens were isolated from rotten sprouts at different time intervals. The pathogenicity of the isolated pathogens was tested. The highly pathogenic strain (YV-St-033) was identified as Pseudomonas sp. by 16S rRNA gene sequencing. In phylogenetic analysis, the YV-St-033 strain was grouped with P. mosselii, P. putita, P. fluorescens, P. entomophila, and P. lecoglossicida. The results of the 16S rRNA gene sequence analysis revealed that the YV-St-033 strain shared the highest sequence identity (more than 99%) with the P. mosselii R10 strain. The mungbean lines of Yeungnam University germplasm were screened against the YV-St-033 strain. Based on the growth rate of the sprouts after 3 days of inoculation with the pathogen, the YV148 line was highly resistant to the pathogen. The remaining lines were either partially or fully infected. The highly resistant line YV 148 is suitable for future breeding programs due to their thin sprouts and fast growing nature.

High-throughput screening of protein variations in soybean seeds.

Vijayanand Velusamy,Kyung Jun Lee,Bo-Keun Ha,Jin Baek Kim,Sang Hoon Kim,Si-Yong Kang,Dong Sub Kim 한국육종학회 2012 한국육종학회 심포지엄 Vol.2012 No.07

The protein in soybean seeds accounts for approximately 40% of the dry seed weight. Two major storage proteins, 7S and 11S, constitute 70-80% of the total storage proteins in the seeds. In this study, the variation of total soluble protein extracts from 1152 soybean landraces that have been collected from South Korea were studied using high-throughput screening method with HT Protein Express Labchip (Caliper Life Sciences, Inc.). Seven distinct protein band patterns - four protein sub-units of 11S and three sub-units of 7S, were taken into account and their presence or absence were analyzed. Among the 1152 landraces, 525 genotypes were identified as lacking lipoxygenase, 255 lacking α1 subunit, 680 lacking α subunit, 169 lacking β subunit, 140 lacking acidic, 114 lacking Kunitz Trypsin Inhibitor (KTi) and 199 lacking basic protein patterns. The high-throughput protein analysis is helpful in screening a large number of populations with less time and minimum labor. The selected genotypes with low amounts or lacking of anti-nutritional factors such as trypsin inhibitor, lipoxygenase and α subunit would be used for future breeding purpose of quality improvement in soybean protein.

Evaluation of Genetic Diversity in Korean Soybean Landraces by Protein Banding Patterns Using High-Throughput Screening

Velusamy, Vijayanand,Lee, Kyung Jun,Ha, Bo-Keun,Kim, Jin-Baek,Kim, Sang Hoon,Ahn, Joon-Woo,Kang, Si-Yong,Kim, Dong Sub 한국작물학회 2013 Journal of crop science and biotechnology Vol.16 No.3

The agronomic performance and storage protein patterns of 722 soybean landraces collected from eight geographically different Korean locations were investigated. The days to 50% flowering, days to maturity, and 100-seed weight ranged from 68.9 to 71.9 (d), 140.1 to 146.6 (d), and 22.4 to 26.8 (g), respectively. High-throughput protein profiling electrophoresis was performed, and the banding patterns were analyzed. Among the 722 soybean landraces, lipoxygenase bands were found to be absent in 21 lines. Nei's gene diversity (h) ranged from 0 to 0.2642, with an average value of 0.1565. The mean coefficient of gene differentiation (Gst) was 0.0944, and the estimated gene flow (Nm) in the population was 4.7971. In a correlation matrix between the agronomic traits and protein banding patterns, the acidic banding pattern was significantly associated with all the other factors. The phenotypic and genotypic differences of the collection areas were evaluated, and the excellent soybean lines with high-value proteins, including 11S globulins, or without antinutritional factors such as lipoxygenase and trypsin inhibitor were selected.

Evaluation of Genetic Diversity in Korean Soybean Landraces by Protein Banding Patterns Using High-Throughput Screening

Vijayanand Velusamy,김동섭,Kyung Jun Lee,하보근,김진백,김상훈,안준우,강시용 한국작물학회 2013 Journal of crop science and biotechnology Vol.16 No.3

The agronomic performance and storage protein patterns of 722 soybean landraces collected from eight geographically different Korean locations were investigated. The days to 50% flowering, days to maturity, and 100-seed weight ranged from 68.9 to 71.9 (d),140.1 to 146.6 (d), and 22.4 to 26.8 (g), respectively. High-throughput protein profiling electrophoresis was performed, and the banding patterns were analyzed. Among the 722 soybean landraces, lipoxygenase bands were found to be absent in 21 lines. Nei’s gene diversity (h) ranged from 0 to 0.2642, with an average value of 0.1565. The mean coefficient of gene differentiation (Gst) was 0.0944, and the estimated gene flow (Nm) in the population was 4.7971. In a correlation matrix between the agronomic traits and protein banding patterns, the acidic banding pattern was significantly associated with all the other factors. The phenotypic and genotypic differences of the collection areas were evaluated, and the excellent soybean lines with high-value proteins, including 11S globulins,or without antinutritional factors such as lipoxygenase and trypsin inhibitor were selected

Comparative gene expression analysis in a highly anthocyanin pigmented mutant of colorless chrysanthemum

Sung, Sang Yeop,Kim, Sang Hoon,Velusamy, Vijayanand,Lee, Yu-Mi,Ha, Bo-Keun,Kim, Jin-Baek,Kang, Si-Yong,Kim, Hong Gi,Kim, Dong Sub Springer-Verlag 2013 Molecular biology reports Vol.40 No.8

The identification of candidate radio marker genes using a coexpression network analysis in gamma‐irradiated rice

Kim, Sun‐,Hee,Hwang, Sun‐,Goo,Hwang, Jung Eun,Jang, Cheol Seong,Velusamy, Vijayanand,Kim, Jin‐,Baek,Kim, Sang Hoon,Ha, Bo‐,Keun,Kang, Si‐,Yong,Kim, Dong Sub Blackwell Publishing Ltd 2013 Physiologia Plantarum Vol.149 No.4

<P>Plant physiological and biochemical processes are significantly affected by gamma irradiation stress. In addition, gamma‐ray (GA) differentially affects gene expression across the whole genome. In this study, we identified radio marker genes (RMGs) responding only to GA stress compared with six abiotic stresses (chilling, cold, anoxia, heat, drought and salt) in rice. To analyze the expression patterns of differentially expressed genes (DEGs) in gamma‐irradiated rice plants against six abiotic stresses, we conducted a hierarchical clustering analysis by using a complete linkage algorithm. The up‐ and downregulated DEGs were observed against six abiotic stresses in three and four clusters among a total of 31 clusters, respectively. The common gene ontology functions of upregulated DEGs in clusters 9 and 19 are associated with oxidative stress. In a Pearson's correlation coefficient analysis, GA stress showed highly negative correlation with salt stress. On the basis of specific data about the upregulated DEGs, we identified the 40 candidate RMGs that are induced by gamma irradiation. These candidate RMGs, except two genes, were more highly induced in rice roots than in other tissues. In addition, we obtained other 38 root‐induced genes by using a coexpression network analysis of the specific upregulated candidate RMGs in an ARACNE algorithm. Among these genes, we selected 16 RMGs and 11 genes coexpressed with three RMGs to validate coexpression network results. RT‐PCR assay confirmed that these genes were highly upregulated in GA treatment. All 76 genes (38 root‐induced genes and 38 candidate RMGs) might be useful for the detection of GA sensitivity in rice roots.</P>