Perspectives for artificial insemination and genomics to improve global swine populations

Civilizations throughout the world continue to depend on pig meat as an important food source. Approximately 40% of the red meat consumed annually worldwide (94 million metric tons) is pig meat. Pig numbers (940 million) and consumption have increased consistent with the increasing world population (FAO 2002). In the past 50 years, research guided genetic selection and nutrition programs have had a major impact on improving carcass composition and efficiency of production in swine. The use of artificial insemination (AI) in Europe has also had a major impact on pig improvement in the past 35 years and more recently in the USA. Several scientific advances in gamete physiology and/or manipulation have been successfully utilized while others are just beginning to be applied at the production level. Semen extenders that permit the use of fresh semen for more than 5 days post-collection are largely responsible for the success of AI in pigs worldwide. Transfer of the best genetics has been enabled by use of AI with fresh semen, and to some extent, by use of AI with frozen semen over the past 25 years. Sexed semen, now a reality, has the potential for increasing the rate of genetic progress in AI programs when used in conjunction with newly developed low sperm number insemination technology. Embryo cryopreservation provides opportunities for international transport of maternal germplasm worldwide; non-surgical transfer of viable embryos in practice is nearing reality. While production of transgenic animals has been successful, the low level of efficiency in producing these animals and lack of information on multigene interactions limit the use of the technology in applied production systems. Technologies based on research in functional genomics, proteomics and cloning have significant potential, but considerable research effort will be required before they can be utilized for AI in pig production. In the past 15 years, there has been a coordinated worldwide scientific effort to develop the genetic linkage map of the pig with the goal of identifying pigs with genetic alleles that result in improved growth rate, carcass quality, and reproductive performance. Molecular genetic tests have been developed to select pigs with improved traits such as removal of the porcine stress (RYR1) syndrome, and selection for specific estrogen receptor (ESR) alleles. Less progress has been made in developing routine tests related to diseases. Major research in genomics is being pursued to improve the efficiency of selection for healthier pigs with disease resistance properties. The sequencing of the genome of the pig to identify new genes and unique regulatory elements holds great promise to provide new information that can be used in pig production. AI, in vitro embryo production and embryo transfer will be the preferred means of implementing these new technologies to enhance efficiency of pig production in the future.     

The autonomy of biological individuals and artificial models

This paper aims to offer an overview of the meaning of autonomy for biological individuals and artificial models rooted in a specific perspective that pays attention to the historical and structural aspects of its origins and evolution. Taking autopoiesis and the recursivity characteristic of its circular logic as a starting point, we depart from some of its consequences to claim that the theory of autonomy should also take into account historical and structural features. Autonomy should not be considered only in internal or constitutive terms, the largely neglected interactive aspects stemming from it should be equally addressed. Artificial models contribute to get a better understanding of the role of autonomy for life and the varieties of its organization and phenomenological diversity.     

Processing local signals into global patterns

Perceptual organization or grouping is one of the central issues in vision research. Recent reports in the neuroimaging literature suggest that perceptual organization is mediated by distributed visual areas that range from the primary visual cortex (V1) to higher visual areas, depending on the availability of grouping cues and on the weight of contribution of each visual area. Evidence suggests that grouping by proximity and collinearity, and also perhaps filling-in, involve V1, whereas grouping by similarity and symmetry seems to depend on activation of higher visual areas. Further studies should include deliberate controls for confounding factors such as attentional artifacts and radial orientation bias, to clarify how spatiotemporal information in visual areas is integrated to give rise to perceptual organization.     

MEG responses to the perception of global structure within glass patterns

Background

The perception of global form requires integration of local visual cues across space and is the foundation for object recognition. Here we used magnetoencephalography (MEG) to study the location and time course of neuronal activity associated with the perception of global structure from local image features. To minimize neuronal activity to low-level stimulus properties, such as luminance and contrast, the local image features were held constant during all phases of the MEG recording. This allowed us to assess the relative importance of striate (V1) versus extrastriate cortex in global form perception.

Methodology/Principal Findings

Stimuli were horizontal, rotational and radial Glass patterns. Glass patterns without coherent structure were viewed during the baseline period to ensure neuronal responses reflected perception of structure and not changes in local image features. The spatial distribution of task-related changes in source power was mapped using Synthetic Aperture Magnetometry (SAM), and the time course of activity within areas of maximal power change was determined by calculating time-frequency plots using a Hilbert transform. For six out of eight observers, passive viewing of global structure was associated with a reduction in 10–20 Hz cortical oscillatory power within extrastriate occipital cortex. The location of greatest power change was the same for each pattern type, being close to or within visual area V3a. No peaks of activity were observed in area V1. Time-frequency analyses indicated that neural activity was least for horizontal patterns.

Conclusions

We conclude: (i) visual area V3a is involved in the analysis of global form; (ii) the neural signature for perception of structure, as assessed using MEG, is a reduction in 10–20 Hz oscillatory power; (iii) different neural processes may underlie the perception of horizontal as opposed to radial or rotational structure; and (iv) area V1 is not strongly activated by global form in Glass patterns.     

Vertical stratification influences global patterns of biodiversity

Species distributions in terrestrial ecosystems are three‐dimensional, spanning both the horizontal landscape and the vertical space provided by the physical environment. Classical hypotheses suggest that communities become more vertically stratified with increasing species richness, owing to reduced competition or finer niche subdivision. However, this assertion remains untested in the context of the broader realm of biogeography. Here, integrating traits and distribution data for amphibians globally, we show how vertical strategies interact with the physical and climatic environments to govern global patterns of species richness and community composition. Our results reveal a marked latitudinal shift in strategies of vertical habitat use, from highly arboreal assemblages in the tropics to highly fossorial assemblages in sub‐tropical and temperate regions. Arboreality is strongly associated with precipitation, vegetation structure and climatic stability, whereas fossoriality is more common in dry environments with high diurnal temperature range and low vegetation structure. These analyses shed light on the importance of vertical stratification for species coexistence in species‐rich regions. As certain tropical habitats become drier from climate change, the rich biological diversity that is emblematic of the tropics may transition from vertically stratified to ‘flattened’, with future communities living mostly on or beneath the ground.     

Race and global patterns of phenotypic variation

Phenotypic traits have been used for centuries for the purpose of racial classification. Developments in quantitative population genetics have allowed global comparison of patterns of phenotypic variation with patterns of variation in classical genetic markers and DNA markers. Human skin color shows a high degree of variation among geographic regions, typical of traits that show extensive natural selection. Even given this high level of geographic differentiation, skin color variation is clinal and is not well described by discrete racial categories. Craniometric traits show a level of among-region differentiation comparable to genetic markers, with high levels of variation within populations as well as a correlation between phenotypic and geographic distance. Craniometric variation is geographically structured, allowing high levels of classification accuracy when comparing crania from different parts of the world. Nonetheless, the boundaries in global variation are not abrupt and do not fit a strict view of the race concept; the number of races and the cutoffs used to define them are arbitrary. The race concept is at best a crude first-order approximation to the geographically structured phenotypic variation in the human species. Am J Phys Anthropol 2009. © 2009 Wiley-Liss, Inc.     

Self-similar patterns of nature: insect diversity at local to global scales

The insects are probably the most hyperdiverse and economically important metazoans on the planet, but there is no consensus on the best way to model the dimensions of their diversity at multiple spatial scales, and the huge amount of information involved hinders data synthesis and the revelation of 'patterns of nature'. Using a sample of more than 600k insect species in the size range 1-100mm, we analysed insect body sizes and revealed self-similar patterns persisting across spatial scales from several hectares to the World. The same patterns were found in both Northern and Southern Hemispheres. The patterns include: parallel rank-abundance distributions; flatter species-area curves in smaller insects-indicating their wider geographical distribution; the recurrence of the same species-rich family in the same body-size class at all spatial scales-which generates self-similar size-frequency distributions (SFDs)-and the discovery that with decreasing mean body size, local species richness represents an increasing fraction of global species richness. We describe how these 'rationalizing' patterns can be translated into methods for monitoring and predicting species diversity and community structure at all spatial scales.     

The finite number of global motion patterns available to symmetric protein complexes

In PDB, more than half of the entries are structure complexes and of these complexes, most are symmetric, composed of identical subunits. Complex formation is the way through which larger structures and even molecular machines are assembled and built in nature. In this work, we apply group theory and carry out a comprehensive study of the global motion patterns of protein complexes of various symmetries. The work presents for the first time a comprehensive list of all the symmetric, aesthetically pleasing, global motion patterns available to complexes of cyclic, dihedral, tetrahedral, or octahedral symmetry. Our results clearly demonstrate that complexes with the same symmetry will have the same global motion patterns and thus may function in a similar way, and that there are only a finite number of global motion patterns available to symmetric complexes as the number of protein symmetry groups is effectively finite. The work complements our current understanding of the principle of complex formation that has been mostly structure‐based by providing novel dynamics‐based insights. Furthermore, as dynamics is closely tied to function, these motion patterns can provide global insights into the general functional mechanisms of protein complexes.     

Historical and contemporary factors govern global biodiversity patterns

A novel hierarchical framework integrates the effects of time, area, productivity, and temperature at their respective relevant scales and successfully predicts the latitudinal gradient in global vertebrate diversity.     

Probability of matching RFLP patterns from unrelated individuals.

RFLP patterns from more than 3,700 individuals, collected by several southeastern laboratories, were compared using a series of mathematical match criteria to determine the probability of randomly matching two samples from different individuals. Data from five loci (D1S7, D2S44, D4S139, D10S28, and D17S79) were compared in all possible combinations. The probability of declaring a false match under any of the match criteria decreased by at least one order of magnitude for each locus added to the comparison. No false matches were declared across four or more loci when match criteria approximately equivalent to that of forensic laboratories were used.     

A comprehensive framework for global patterns in biodiversity

The present study proposes to reconcile the different spatial and temporal scales of regional species production and local constraint on species richness. Although interactions between populations rapidly achieve equilibrium and limit membership in ecological communities locally, these interactions occur over heterogeneous environments within large regions, where the populations of species are stably regulated through competition and habitat selection. Consequently, exclusion of species from a region depends on long‐term regional‐scale environmental change or evolutionary change among interacting populations, bringing species production and extinction onto the same scale and establishing a link between local and regional processes.     

The mathematical influence on global patterns of biodiversity

Although we understand how species evolve, we do not appreciate how this process has filled an empty world to create current patterns of biodiversity. Here, we conduct a numerical experiment to determine why biodiversity varies spatially on our planet. We show that spatial patterns of biodiversity are mathematically constrained and arise from the interaction between the species’ ecological niches and environmental variability that propagates to the community level. Our results allow us to explain key biological observations such as (a) latitudinal biodiversity gradients (LBGs) and especially why oceanic LBGs primarily peak at midlatitudes while terrestrial LBGs generally exhibit a maximum at the equator, (b) the greater biodiversity on land even though life first evolved in the sea, (c) the greater species richness at the seabed than at the sea surface, and (d) the higher neritic (i.e., species occurring in areas with a bathymetry lower than 200 m) than oceanic (i.e., species occurring in areas with a bathymetry higher than 200 m) biodiversity. Our results suggest that a mathematical constraint originating from a fundamental ecological interaction, that is, the niche–environment interaction, fixes the number of species that can establish regionally by speciation or migration.     

Hierarchical patterns of global human Y-chromosome diversity.

We examined 43 biallelic polymorphisms on the nonrecombining portion of the Y chromosome (NRY) in 50 human populations encompassing a total of 2,858 males to study the geographic structure of Y-chromosome variation. Patterns of NRY diversity varied according to geographic region and method/level of comparison. For example, populations from Central Asia had the highest levels of heterozygosity, while African populations exhibited a higher level of mean pairwise differences among haplotypes. At the global level, 36% of the total variance of NRY haplotypes was attributable to differences among populations (i.e., Phi(ST) = 0.36). When a series of AMOVA analyses was performed on different groupings of the 50 populations, high levels of among-groups variance (Phi(CT)) were found between Africans, Native Americans, and a single group containing all 36 remaining populations. The same three population groupings formed distinct clusters in multidimensional scaling plots. A nested cladistic analysis (NCA) demonstrated that both population structure processes (recurrent gene flow restricted by isolation by distance and long-distance dispersals) and population history events (contiguous range expansions and long-distance colonizations) were instrumental in explaining this tripartite division of global NRY diversity. As in our previous analyses of smaller NRY data sets, the NCA detected a global contiguous range expansion out of Africa at the level of the total cladogram. Our new results support a general scenario in which, after an early out-of-Africa range expansion, global-scale patterns of NRY variation were mainly influenced by migrations out of Asia. Two other notable findings of the NCA were (1) Europe as a "receiver" of intercontinental signals primarily from Asia, and (2) the large number of intracontinental signals within Africa. Our AMOVA analyses also supported the hypothesis that patrilocality effects are evident at local and regional scales, rather than at intercontinental and global levels. Finally, our results underscore the importance of subdivision of the human paternal gene pool and imply that caution should be exercised when using models and experimental strategies based on the assumption of panmixia.     

Tadpole fingerprinting: Using tail venation patterns to photo-identify tadpole individuals of a threatened frog

Traditional methods for identifying individual amphibians in capture–mark–recapture (CMR) studies have been primarily confined to post-metamorphic stages, using artificial markers that come with a variety of limitations. An alternative that may open CMR studies to earlier life stages involves the use of a species' natural external markers in photo-based identification. In this study, we investigated whether it was possible to distinguish tadpoles of the threatened green and golden bell frog (Litoria aurea) at the individual level based on tail venation patterns. We collected photographs of the tails of captive-raised tadpoles using a smartphone over a 4-week period. This photo-library was used to create an electronic survey where participants were asked to detect matches for query tadpoles from small image pools. We found that most participants agreed on a match for each query, with perfect consensus achieved for most queries (83%). We detected a 14% decline in perfect consensus when participants were asked to match images of tadpoles separated by longer time intervals, suggesting that it is more difficult to visually identify recapture events of L. aurea tadpoles over extended periods due to changes to tail appearance. However, consensus was obtained by participants for all queries, with all matches verified as being correct by the primary researcher. The strength of agreement among participants with no prior experience in matching tadpole tails suggests that there is sufficient inter-individual variation in this feature for individuals to be manually identified. We thus propose that photo-identification is likely to be a valid, non-invasive technique that can be used for short-term studies on tadpole populations that display tail venation. This offers an alternative to artificial markers that may not allow for individual identification, while also opening up tadpole monitoring programmes to citizen scientists who can be recruited online to process image data from home.     

Predictions of patterns of response to artificial selection in lines derived from natural populations

The pattern of response to artificial selection on quantitative traits in laboratory populations can tell us something of the genetic architecture in the natural population from which they were derived. We modeled artificial selection in samples drawn from natural populations in which variation had been maintained by recurrent mutation, with genes having an effect on the trait, which was subject to real stabilizing selection, and a pleitropic effect on fitness (the joint-effect model). Natural selection leads to an inverse correlation between effects and frequencies of genes, such that the frequency distribution of genes increasing the trait has an extreme U-shape. In contrast to the classical infinitesimal model, an early accelerated response and a larger variance of response among replicates were predicted. However, these are reduced if the base population has been maintained in the laboratory for some generations by random sampling prior to artificial selection. When multiple loci and linkage are also taken into account, the gametic disequilibria generated by the Bulmer and Hill-Robertson effects are such that little or no increase in variance and acceleration of response in early generations of artificial selection are predicted; further, the patterns of predicted responses for the joint-effect model now become close to those of the infinitesimal model. Comparison with data from laboratory selection experiments shows that, overall, the analysis did not provide clear support for the joint-effect model or a clear case for rejection.     

A new training algorithm using artificial neural networks to classify gender-specific dynamic gait patterns

The aim of this study was to present a new training algorithm using artificial neural networks called multi-objective least absolute shrinkage and selection operator (MOBJ-LASSO) applied to the classification of dynamic gait patterns. The movement pattern is identified by 20 characteristics from the three components of the ground reaction force which are used as input information for the neural networks in gender-specific gait classification. The classification performance between MOBJ-LASSO (97.4%) and multi-objective algorithm (MOBJ) (97.1%) is similar, but the MOBJ-LASSO algorithm achieved more improved results than the MOBJ because it is able to eliminate the inputs and automatically select the parameters of the neural network. Thus, it is an effective tool for data mining using neural networks. From 20 inputs used for training, MOBJ-LASSO selected the first and second peaks of the vertical force and the force peak in the antero-posterior direction as the variables that classify the gait patterns of the different genders.