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Overexpression of Oncidium MADS box (OMADS1) gene promotes early flowering in transgenic orchid (Oncidium Gower Ramsey)

100%

Thiruvengadam M. , Chung I.-M. , Yang C.-H.

2012

tom 34

nr 4

Oncidium is a popular ornamental orchid and is produced as a high value cash crop for cut flower sold worldwide. Genetically transformed plants of Oncidium were regenerated after cocultivating protocorm-like bodies (PLBs) with Agrobacterium tumefaciens strain LBA4404 harboring pBI121 with OMADS1. The chopped PLBs precultured for 3 days in darkness produced more kanamycinresistant PLBs. G10 medium containing 200 mg l⁻¹ kanamycin was effective for the selection of transformed lines at a frequency of 9%. The rooted plantlets were transferred to pots, acclimated for 3 weeks in the culture room and then moved to the greenhouse. OMADS1 transgene was detected in transgenic lines by PCR, Southern blot analysis and RT-PCR were performed, and the results confirmed that OMADS1 was expressed in these 35S::OMADS1 transgenic plants. CaMV35S::OMADS1 transgenic Oncidium orchid plants flowered significantly earlier, produced more flowers and pseudobulbs than nontransgenic plants. The flower organ conversions were not observed in 35S::OMADS1 transgenic flowers of Oncidium. This is the first report on the ectopic expression of MADS box gene in O. Gower Ramsey using a simple and efficient gene transfer protocol.

Genetic algorithm combined with a local search method for identifying susceptibility genes

100%

Yang C. H. , Moi S. H. , Lin Y. D. , Chuang L. Y.

2016

tom Vol. 6, No. 3

203--212

Detecting genetic association models between single nucleotide polymorphisms (SNPs) in various disease-related genes can help to understand susceptibility to disease. Statistical tools have been widely used to detect significant genetic association models, according to their related statistical values, including odds ratio (OR), chi-square test (χ2), p-value, etc. However, the high number of computations entailed in such operations may limit the capacity of such statistical tools to detect high-order genetic associations. In this study, we propose lsGA algorithm, a genetic algorithm based on local search method, to detect significant genetic association models amongst large numbers of SNP combinations. We used two disease models to simulate the large data sets considering the minor allele frequency (MAF), number of SNPs, and number of samples. The three-order epistasis models were evaluated by chi-square test (χ2) to evaluate the significance (P-value < 0.05). Analysis results showed that lsGA provided higher chi-square test values than that of GA. Simple linear regression indicated that lsGA provides a significant advantage over GA, providing the highest β values and significant p-value.

Effects of different cryoprotectants and freezing methods on post-thaw boar semen quality

88%

Yang C.-H. , Wu T.-W. , Cheng F.-P. , Wang J.-H. , Wu J.-T.

nr 1