Towards cryopreservation of Greenshell mussel (Perna canaliculus) oocytes.

Cryopreservation is a powerful tool for selective breeding in aquaculture as it enables genetic material from selected stock to be stored and crossed at will. The aim of this study was to develop a method for cryopreserving oocytes of the Greenshelltrade mark mussel (Perna canaliculus), New Zealand's main aquaculture species. The ability of oocytes to be fertilized post-thawing was used as the criterion for success in initial experiments and then subsequently, the ability of frozen oocytes to develop further to D-stage larvae was assessed. Ethylene glycol, propylene glycol, dimethyl sulphoxide and glycerol were evaluated at a range of concentrations with and without the addition of 0.2M trehalose using post-thaw fertilization as the endpoint. Ethylene glycol was most effective, particularly when used in combination with trehalose. A more detailed investigation revealed that ethylene glycol at 9% or 10% in the presence of 0.2-0.4M trehalose afforded the best protection. In experiments varying sperm to egg ratio and egg density in post-thaw fertilization procedures, D-larval yield averaged less than 1%. Following these results, a detailed experiment was conducted to determine the damaging steps in the cryopreservation process. Fertilization losses occurred at each step whereas D-larval yield approximately halved following CPA addition and was almost zero following cooling to -10 degrees C. Cryomicroscopy studies and fertilization results suggest that the inability of oocytes to develop to D-larvae stage after cooling to -10 degrees C and beyond are most likely related to some form of chilling injury rather than extracellular ice triggering intracellular ice formation. Further research is needed to determine the causes of this injury and to reduce CPA toxicity and/or osmotic effects.

Developing Successful Breeding Programs for New Zealand Aquaculture: A Perspective on Progress and Future Genomic Opportunities.

Over the past 40 years New Zealand (NZ) aquaculture has grown into a significant primary industry. Tonnage is small on a global scale, but the industry has built an international reputation for the supply of high quality seafood to many overseas markets. Since the early 1990s the industry has recognized the potential gains from selective breeding and the challenge has been to develop programs that can overcome biological obstacles (such as larval rearing and mortality) and operate cost-effectively on a relatively small scale while still providing significant gains in multiple traits of economic value. This paper provides an overview of the current status, and a perspective on genomic technology implementation, for the family based genetic improvement programs established for the two main species farmed in NZ: Chinook (king) salmon (Oncorhynchus tshawytscha) and GreenshellTM mussel (Perna canaliculus). These programs have provided significant benefit to the industry in which we are now developing genomic resources based on genotyping-by-sequencing to complement the breeding programs, enable evaluation of the genetic diversity and identify the potential benefits of genomic selection. This represents an opportunity to increase genetic gain and more effectively utilize the potential for within family selection.

Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks.

Neuroimaging in combination with graph theory has been successful in analyzing the functional connectome. However almost all analysis are performed based on static graph theory. The derived quantitative graph measures can only describe a snap shot of the disease over time. Neurodegenerative disease evolution is poorly understood and treatment strategies are consequently only of limited efficiency. Fusing modern dynamic graph network theory techniques and modeling strategies at different time scales with pinning observability of complex brain networks will lay the foundation for a transformational paradigm in neurodegnerative diseases research regarding disease evolution at the patient level, treatment response evaluation and revealing some central mechanism in a network that drives alterations in these diseases. We model and analyze brain networks as two-time scale sparse dynamic graph networks with hubs (clusters) representing the fast sub-system and the interconnections between hubs the slow sub-system. Alterations in brain function as seen in dementia can be dynamically modeled by determining the clusters in which disturbance inputs have entered and the impact they have on the large-scale dementia dynamic system. Observing a small fraction of specific nodes in dementia networks such that the others can be recovered is accomplished by the novel concept of pinning observability. In addition, how to control this complex network seems to be crucial in understanding the progressive abnormal neural circuits in many neurodegenerative diseases. Detecting the controlling regions in the networks, which serve as key nodes to control the aberrant dynamics of the networks to a desired state and thus influence the progressive abnormal behavior, will have a huge impact in understanding and developing therapeutic solutions and also will provide useful information about the trajectory of the disease. In this paper, we present the theoretical framework and derive the necessary conditions for (1) area aggregation and time-scale modeling in brain networks and for (2) pinning observability of nodes in dynamic graph networks. Simulation examples are given to illustrate the theoretical concepts.

Using the low-resolution properties of correlated images to improve the computational efficiency of eigenspace decomposition.

Eigendecomposition is a common technique that is performed on sets of correlated images in a number of computer vision and robotics applications. Unfortunately, the computation of an eigendecomposition can become prohibitively expensive when dealing with very high-resolution images. While reducing the resolution of the images will reduce the computational expense, it is not known a priori how this will affect the quality of the resulting eigendecomposition. The work presented here provides an analysis of how different resolution reduction techniques affect the eigendecomposition. A computationally efficient algorithm for calculating the eigendecomposition based on this analysis is proposed. Examples show that this algorithm performs well on arbitrary video sequences.

Alternaria yaliinficiens sp. nov. on Ya Li Pear Fruit: From Interception to Identification.

In 2001, numerous Ya Li pear fruit from China with a disease apparently caused by an Alternaria sp. were intercepted at U.S. ports, raising concern because the disease was unknown in the United States. To identify the etiologic agent of the disease, single-spore cultures were established from intercepted fruit and were characterized by pathogenicity to wounded fruit, morphology, and sporulation pattern on three agar media, random amplified polymorphic DNA fragment pattern analysis, and species-specific polymerase chain reaction (PCR). These data indicated that the disease likely was caused by more than one species of Alternaria, and that none of the isolates from intercepted Ya Li fruit was A. alternata or A. gaisen. A species-specific PCR assay for A. gaisen demonstrated that no isolate from Ya Li was A. gaisen. A PCR assay for the AMT gene demonstrated that no isolate from Ya Li was A. 'mali'. Because of these data and the absence of a description to accommodate at least one of the taxa involved, A. yaliinficiens R. G. Roberts sp. nov. is described, and the disease caused by this and other species of Alternaria on Ya Li pear from China is referred to as "chocolate spot of Ya Li pear" to distinguish it from black spot of Japanese pear.

Fast eigenspace decomposition of images of objects with variation in illumination and pose.

Many appearance-based classification problems such as principal component analysis, linear discriminant analysis, and locally preserving projections involve computing the principal components (eigenspace) of a large set of images. Although the online expense associated with appearance-based techniques is small, the offline computational burden becomes prohibitive for practical applications. This paper presents a method to reduce the expense of computing the eigenspace decomposition of a set of images when variations in both illumination and pose are present. In particular, it is shown that the set of images of an object under a wide range of illumination conditions and a fixed pose can be significantly reduced by projecting these data onto a few low-frequency spherical harmonics, producing a set of "harmonic images." It is then shown that the dimensionality of the set of harmonic images at different poses can be further reduced by utilizing the fast Fourier transform. An eigenspace decomposition is then applied in the spectral domain at a much lower dimension, thereby significantly reducing the computational expense. An analysis is also provided, showing that the principal eigenimages computed assuming a single illumination source are capable of recovering a significant amount of information from images of objects when multiple illumination sources exist.

Eigendecomposition of images correlated on S(1), S(2), and SO3 using spectral theory.

Eigendecomposition represents one computationally efficient approach for dealing with object detection and pose estimation, as well as other vision-based problems, and has been applied to sets of correlated images for this purpose. The major drawback in using eigendecomposition is the off line computational expense incurred by computing the desired subspace. This off line expense increases drastically as the number of correlated images becomes large (which is the case when doing fully general 3-D pose estimation). Previous work has shown that for data correlated on S(1), Fourier analysis can help reduce the computational burden of this off line expense. This paper presents a method for extending this technique to data correlated on S(2) as well as SO3 by sampling the sphere appropriately. An algorithm is then developed for reducing the off line computational burden associated with computing the eigenspace by exploiting the spectral information of this spherical data set using spherical harmonics and Wigner-D functions. Experimental results are presented to compare the proposed algorithm to the true eigendecomposition, as well as assess the computational savings.

Cryopreservation of economically valuable marine micro-algae in the classes Bacillariophyceae, Chlorophyceae, Cyanophyceae, Dinophyceae, Haptophyceae, Prasinophyceae, and Rhodophyceae.

The ability to routinely cryopreserve micro-algal species reduces costs associated with maintaining large culture collections and reduces the risks of losing particular strains or species through contamination and genetic drift. Cryopreservation is also a useful adjunct in aquaculture hatcheries for strains of micro-algae where the nutritional status may change as a result of continuous sub-culture. In this study, cryopreservation of isolates from seven micro-algal classes was investigated. Successful candidates included the marine dinoflagellates Amphidinium carterae, Amphidinium trulla, and Gymnodinium simplex, and the haptophytes Chrysochromulina simplex, Prymnesium parvum, Prymnesium parvum f. patelliferum, Isochrysis galbana, and Pavlova lutheri. Also successfully cryopreserved were the planktonic diatoms Chaetoceros calcitrans, Chaetoceros muelleri, Chaetoceros sp., and the benthic Nitzschia ovalis, the chlorophyte Chlamydomonas coccoides, the rhodophyte Porphyridium purpureum, the prasinophytes Tetraselmis chuii, and Tetraselmis suecica, and the cyanophytes Raphidiopsis sp., and Aphanizomenon flos-aquae. All species were successfully cryopreserved using 15% Me2SO.

Shared ITS DNA substitutions in isolates of opposite mating type reveal a recombining history for three presumed asexual species in the filamentous ascomycete genus Alternaria.

About 15,000 species of ascomycete fungi lack a known sexual state. For fungi with asexual states in the anamorph genera Embellisia, Ulocladium, and Alternaria, six species have known sexual states but more than 50 species do not. In sexual filamentous ascomycetes, opposite mating type information at the MAT1 locus regulates mating and the opposite mating type genes each have a clonal, non-recombining phylogenetic history. We used PCR to amplify and sequence fragments of the opposite mating type genes from three supposedly asexual species, A. brassicae, A. brassicicola and A. tenuissima. Each haploid fungal isolate had just one mating type, but both mating types were present in all the three species. We sequenced the ribosomal ITS regions for isolates of opposite mating type, for the three asexual species and four known related sexual species. In a phylogenetic analysis including other ITS sequences from GenBank, the three asexual species were not closely related to any of the known sexual species. Isolates of opposite mating type but the same species had identical ITS sequences. During any period of asexual evolutionary history, lineages of each mating type would have had a separate evolutionary history and any ITS substitutions shared between isolates of opposite mating type would have had to accumulate by convergence. Allowing for varying substitution rates and assuming a Poisson distribution of substitutions, the probability that isolates of opposite mating type shared an ITS substitution through convergence was low. This suggests that isolates of opposite mating type of A. brassicae, A. brassicicola and A. tenuissima were exchanging substitutions through sexual or parasexual reproduction while the ITS was evolving. If sexuality was lost, it was lost after the period of evolutionary history represented by the shared substitutions.