Unveiling the role of differential growth in 3D morphogenesis: An inference method to analyze area expansion rate distribution in biological systems.

The three-dimensional (3D) morphologies of many organs in organisms, such as the curved shapes of leaves and flowers, the branching structure of lungs, and the exoskeletal shape of insects, are formed through surface growth. Although differential growth, a mode of surface growth, has been qualitatively identified as 3D morphogenesis, a quantitative understanding of the mechanical contribution of differential growth is lacking. To address this, we developed a quantitative inference method to analyze the distribution of the area expansion rate, which governs the growth of surfaces into 3D morphology.

The draft genome sequence of the Japanese rhinoceros beetle Trypoxylus dichotomus septentrionalis towards an understanding of horn formation.

The Japanese rhinoceros beetle Trypoxylus dichotomus is a giant beetle with distinctive exaggerated horns present on the head and prothoracic regions of the male. T. dichotomus has been used as a research model in various fields such as evolutionary developmental biology, ecology, ethology, biomimetics, and drug discovery.

RNA Interference Method for Gene Function Analysis in the Japanese Rhinoceros Beetle .

In the Japanese rhinoceros beetle , various candidate genes required for a specific phenotype of interest are listed by next-generation sequencing analysis. Their functions were investigated using RNA interference (RNAi) method, the only gene function analysis tool for developed so far. The summarized procedure for the RNAi method used for is to synthesize double-stranded RNA (dsRNA), and inject it in larvae or pupae of .

Recent advances in understanding horn formation in the Japanese rhinoceros beetle Trypoxylus dichotomus using next-generation sequencing technology.

The exaggerated horns of beetles are attractive models for studying the origin of novel traits and morphological evolution. Closely related species often differ profoundly in the size, number, and shape of their horns, and in the body region from which they extend. In addition, beetle horns exhibit exquisite nutrition-dependent phenotypic plasticity, leading to disproportionate growth of the horns in the largest, best-condition individuals and much smaller - even stunted - horn sizes in poor-condition individuals.

Adaptation of the Hierarchical Factor Segmentation method to noisy activity data.

The Hierarchical Factor Segmentation (HFS) method is a non-parametric statistical method for detection of the phase of a biological rhythm shown in an actogram. The detection accuracy of this method was measured on actograms showing only circadian rhythms with a constant ratio of signal to noise (S/N). In the present study, we generated 84 types of artificial actograms including circadian or circatidal rhythms by using three parameters: α/ρ, S/N and period length τ, and evaluated the effectiveness of our devised adaptation of the HFS method, the cycle-by-cycle adaptation.