A New and Fast Technique to Generate Offspring after Germ Cells Transplantation in Adult Fish: The Nile Tilapia (Oreochromis niloticus) Model

Background: Germ cell transplantation results in fertile recipients and is the only available approach to functionally investigate the spermatogonial stem cell biology in mammals and probably in other vertebrates. In the current study, we describe a novel non-surgical methodology for efficient spermatogonial transplantation into the testes of adult tilapia (O. niloticus), in which endogenous spermatogenesis had been depleted with the cytostatic drug busulfan. Methodology/Principal Findings: Using two different tilapia strains, the production of fertile spermatozoa with donor characteristics was demonstrated in adult recipient, which also sired progeny with the donor genotype. Also, after cryopreservation tilapia spermatogonial cells were able to differentiate to spermatozoa in the testes of recipient fishes. These findings indicate that injecting germ cells directly into adult testis facilitates and enable fast generation of donor spermatogenesis and offspring compared to previously described methods. Conclusion: Therefore, a new suitable methodology for biotechnological investigations in aquaculture was established, with a high potential to improve the production of commercially valuable fish, generate transgenic animals and preserv

Classification of heterogeneous microarray data by maximum entropy kernel

<p>Abstract</p> <p>Background</p> <p>There is a large amount of microarray data accumulating in public databases, providing various data waiting to be analyzed jointly. Powerful kernel-based methods are commonly used in microarray analyses with support vector machines (SVMs) to approach a wide range of classification problems. However, the standard vectorial data kernel family (linear, RBF, etc.) that takes vectorial data as input, often fails in prediction if the data come from different platforms or laboratories, due to the low gene overlaps or consistencies between the different datasets.</p> <p>Results</p> <p>We introduce a new type of kernel called maximum entropy (ME) kernel, which has no pre-defined function but is generated by kernel entropy maximization with sample distance matrices as constraints, into the field of SVM classification of microarray data. We assessed the performance of the ME kernel with three different data: heterogeneous kidney carcinoma, noise-introduced leukemia, and heterogeneous oral cavity carcinoma metastasis data. The results clearly show that the ME kernel is very robust for heterogeneous data containing missing values and high-noise, and gives higher prediction accuracies than the standard kernels, namely, linear, polynomial and RBF.</p> <p>Conclusion</p> <p>The results demonstrate its utility in effectively analyzing promiscuous microarray data of rare specimens, e.g., minor diseases or species, that present difficulty in compiling homogeneous data in a single laboratory.</p

Sex Determination:Why So Many Ways of Doing It?

Sexual reproduction is an ancient feature of life on earth, and the familiar X and Y chromosomes in humans and other model species have led to the impression that sex determination mechanisms are old and conserved. In fact, males and females are determined by diverse mechanisms that evolve rapidly in many taxa. Yet this diversity in primary sex-determining signals is coupled with conserved molecular pathways that trigger male or female development. Conflicting selection on different parts of the genome and on the two sexes may drive many of these transitions, but few systems with rapid turnover of sex determination mechanisms have been rigorously studied. Here we survey our current understanding of how and why sex determination evolves in animals and plants and identify important gaps in our knowledge that present exciting research opportunities to characterize the evolutionary forces and molecular pathways underlying the evolution of sex determination