Proliferation-coupled osteoclast differentiation by RANKL: Cell density as a determinant of osteoclast formation.

Although it is widely recognized that the osteoclast differentiation induced by RANKL is linked to the anti-proliferative activity of the cytokine, we report here that RANKL in the presence of M-CSF actually stimulates DNA synthesis and cell proliferation during the early proliferative phase (0-48 h) of osteoclastogenesis ex vivo, while the same cytokine exerts an anti-proliferative activity in the latter half (48-96 h). A tracing of the individual cells using Fucci cell cycle indicators showed that waves of active DNA synthesis in the S phase during the period 0-48 h are followed by cell-cycle arrest and cell fusion after 48 h. Inhibition of DNA synthesis with hydroxyurea (HU) during the first half almost completely inhibited osteoclastogenesis; however, the same HU-treated cells, when re-plated at 48 h at increasing cell densities, exhibited restored osteoclast formation, suggesting that a sufficient number of cells, rather than prior DNA synthesis, is the most critical requirement for osteoclast formation. In addition, varying either the number of bone marrow macrophages at the start of osteoclastogenic cultures or pre-osteoclasts halfway through the process had a substantial impact on the number of osteoclasts that finally formed, as well as the timing of the peak of osteoclast formation. Thus, caution should be exerted in the performance of any manipulative procedure, whether pharmacological or genetic, that affects the cell number prior to cell fusion. Such procedures can have a profound effect on the number of osteoclasts that form, the final outcome of "differentiation", leading to misinterpretation of the results.

Microsatellite and minisatellite markers based DNA fingerprinting and genetic diversity of blast and ufra resistant genotypes.

A total of 78 alleles and 29 loci were detected from nine microsatellite and three minisatellite markers, respectively across 26 blast and ufra disease resistant genotypes. For blast resistant genotypes, the Polymorphic Information Content (PIC) values ranged from 0.280 to 0.726 and RM21 was considered as the best marker. PIC values ranged from 0.5953 to 0.8296 for ufra resistant genotypes and RM23 was the best marker for characterization of ufra resistant genotypes. The genetic similarity analysis using UPGMA clustering generated nine clusters with coefficient of 0.66 for blast resistant genotypes while five genetic clusters with similarity coefficient of 0.42 for ufra resistant genotypes. In order to develop resistant varieties of two major diseases of rice, hybridisation should be made using the parents, BR29 and NJ70507, BR36 and NJ70507 for blast, while BR11 and Aokazi, BR3 and Aokazi, Rayda and BR3 and Rayda and BR11 for ufra.