Chromosome Banding and 18S rDNA in situ Hybridization Analysis of Seven Species of the Family Achiridae (Teleostei: Pleuronectiformes)

Achiridae is an important family of the order Pleuronectiformes widely distributed in North, Central, and South America with freshwater and marine species. In the present study cytogenetic analyses comprising conventional and molecular techniques were carried out in seven species of this family. The following diploid numbers (2n) and fundamental numbers (FN) were obtained: Achirus declivis 2n = 34, FN = 52; Achirus lineatus 2n = 40, FN = 66; Catathyridium jenynsi 2n = 40 and FN = 50; Gymnachirus nudus 2n = 36 and FN = 50; Hypoclinemus mentalis 2n = 38 and FN = 54; Trinectes paulistanus 2n = 42 and FN = 52; and Trinectes sp. 2n = 38 and FN = 54. All species presented a single nucleolar organizer region (NOR) bearing chromosome pair and C-band positive segments mainly distributed at the pericentromeric position. The wide variation observed in chromosome number and FN suggests the occurrence of larger chromosome rearrangements in the family Achiridae if compared with other families of the same order.     

Cell population indexes of spermatogenic yield and testicular sperm reserves in adult jaguars (Panthera onca)

The intrinsic yield of spermatogenesis and supporting capacity of Sertoli cells are the desirable indicators of sperm production in a species. The objective of the present study was to quantify intrinsic yield and the Sertoli cell index in the spermatogenic process and estimate testicular sperm reserves by histological assessment of fragments obtained by testicular biopsy of five adult jaguars in captivity. The testicular fragments were fixed in 4% glutaric aldehyde, dehydrated at increasing alcohol concentrations, included into hydroxyethyl methacrylate, and were cut into 4 μm thickness. In the seminiferous epithelium of the jaguar, 9.2 primary spermatocytes in pre-leptotene were produced by “A” spermatogonia. During the meiotic divisions only 3.2 spermatids were produced by a primary spermatocyte. The general spermatogenic yield of the jaguar was about 23.4 cells and each Sertoli cell was able to maintain about 19.2 germ cells, 11 of them were round spermatids. In each seminiferous epithelium cycle about 166 million spermatozoa were produced by each gram of testicular tissue. In adult jaguars, the general spermatogenic yield was similar to the yield observed in pumas, greater than that observed for the domestic cat, but less compared to most domestic animals.     

Prediction of Genetic Values of Quantitative Traits in Plant Breeding Using Pedigree and Molecular Markers

The availability of dense molecular markers has made possible the use of genomic selection (GS) for plant breeding. However, the evaluation of models for GS in real plant populations is very limited. This article evaluates the performance of parametric and semiparametric models for GS using wheat (Triticum aestivum L.) and maize (Zea mays) data in which different traits were measured in several environmental conditions. The findings, based on extensive cross-validations, indicate that models including marker information had higher predictive ability than pedigree-based models. In the wheat data set, and relative to a pedigree model, gains in predictive ability due to inclusion of markers ranged from 7.7 to 35.7%. Correlation between observed and predictive values in the maize data set achieved values up to 0.79. Estimates of marker effects were different across environmental conditions, indicating that genotype × environment interaction is an important component of genetic variability. These results indicate that GS in plant breeding can be an effective strategy for selecting among lines whose phenotypes have yet to be observed.PEDIGREE-BASED prediction of genetic values based on the additive infinitesimal model (Fisher 1918) has played a central role in genetic improvement of complex traits in plants and animals. Animal breeders have used this model for predicting breeding values either in a mixed model (best linear unbiased prediction, BLUP) (Henderson 1984) or in a Bayesian framework (Gianola and Fernando 1986). More recently, plant breeders have incorporated pedigree information into linear mixed models for predicting breeding values (Crossa et al. 2006, 2007; Oakey et al. 2006; Burgueño et al. 2007; Piepho et al. 2007).The availability of thousands of genome-wide molecular markers has made possible the use of genomic selection (GS) for prediction of genetic values (Meuwissen et al. 2001) in plants (e.g., Bernardo and Yu 2007; Piepho 2009; Jannink et al. 2010) and animals (Gonzalez-Recio et al. 2008; VanRaden et al. 2008; Hayes et al. 2009; de los Campos et al. 2009a). Implementing GS poses several statistical and computational challenges, such as how models can cope with the curse of dimensionality, colinearity between markers, or the complexity of quantitative traits. Parametric (e.g., Meuwissen et al. 2001) and semiparametric (e.g., Gianola et al. 2006; Gianola and van Kaam 2008) methods address these problems differently.In standard genetic models, phenotypic outcomes, , are viewed as the sum of a genetic value, , and a model residual, ; that is, . In parametric models for GS, is described as a regression on marker covariates (j = 1,  …  , p molecular markers) of the form , such that(or , in matrix notation), where is the regression of on the jth marker covariate .Estimation of via multiple regression by ordinary least squares (OLS) is not feasible when p > n. A commonly used alternative is to estimate marker effects jointly using penalized methods such as ridge regression (Hoerl and Kennard 1970) or the Least Absolute Shrinkage and Selection Operator (LASSO) (Tibshirani 1996) or their Bayesian counterpart. This approach yields greater accuracy of estimated genetic values and can be coupled with geostatistical techniques commonly used in plant breeding to model multienvironments trials (Piepho 2009).In ridge regression (or its Bayesian counterpart) the extent of shrinkage is homogeneous across markers, which may not be appropriate if some markers are located in regions that are not associated with genetic variance, while markers in other regions may be linked to QTL (Goddard and Hayes 2007). To overcome this limitation, many authors have proposed methods that use marker-specific shrinkage. In a Bayesian setting, this can be implemented using priors of marker effects that are mixtures of scaled-normal densities. Examples of this are methods Bayes A and Bayes B of Meuwissen et al. (2001) and the Bayesian LASSO of Park and Casella (2008).An alternative to parametric regressions is to use semiparametric methods such as reproducing kernel Hilbert spaces (RKHS) regression (Gianola and van Kaam 2008). The Bayesian RKHS regression regards genetic values as random variables coming from a Gaussian process centered at zero and with a (co)variance structure that is proportional to a kernel matrix K (de los Campos et al. 2009b); that is, , where , are vectors of marker genotypes for the ith and jth individuals, respectively, and is a positive definite function evaluated in marker genotypes. In a finite-dimensional setting this amounts to modeling the vector of genetic values, , as multivariate normal; that is, where is a variance parameter. One of the most attractive features of RKHS regression is that the methodology can be used with almost any information set (e.g., covariates, strings, images, graphs). A second advantage is that with RKHS the model is represented in terms of n unknowns, which gives RKHS a great computational advantage relative to some parametric methods, especially when p ≫ n.This study presents an evaluation of several methods for GS, using two extensive data sets. One contains phenotypic records of a series of wheat trials and recently generated genomic data. The other data set pertains to international maize trials in which different traits were measured in maize lines evaluated under severe drought and well-watered conditions.     

Expression of clock genes in human subcutaneous and visceral adipose tissues

Disrupted circadian rhythms are associated with obesity and metabolic alterations, but little is known about the participation of peripheral circadian clock machinery in these processes. The aim of the present study was to analyze RNA expression of clock genes in subcutaneous (SAT) and visceral (VAT) adipose tissues of male and female subjects in AM (morning) and PM (afternoon) periods, and its interactions with body mass index (BMI). Ninety-one subjects (41 ± 11 yrs of age) presenting a wide range of BMI (21.4 to 48.6 kg/m(2)) were included. SAT and VAT biopsies were obtained from patients undergoing abdominal surgeries. Clock genes expressions were evaluated by qRT-PCR. The only clock gene that showed higher expression (p 相似文献   

Chlorophyll <Emphasis Type="Italic">a</Emphasis> fluorescence study revealing effects of flooding in canola hybrids

By generating stress conditions soil flooding can induce alterations in the cell metabolism and thus is detrimental to plant growth. This study was done under the greenhouse conditions to determine the effect of soil flooding on the chlorophyll fluorescence of some hybrids of canola (Brassica napus L.). Fifty five days old plants were subjected to flooding for six days. There was no difference in the parameters modulate chlorophyll fluorescence, in contrast, some the parameters related to the energy flux in photosystem II varied due to flooding stress. At the end of the six days, the performance indexes (PI_total and PI_ABS) decreased, in all hybrids except in ‘Hyola 420’. The difference kinetics of the chlorophyll a fluorescence transient showed different effects on different sites of the photosynthetic machinery. It could be concluded that compared to the other hybrids, ‘Hyola 420’ was less sensitive to flooding.     

Effects of swimming training on tissue glycogen content in experimental thyrotoxic rats

Thyrotoxicosis, a condition in which there is an excessive amount of circulating thyroid hormones, leads to reduced glycogen content in different tissues. In this study we analyzed the effects of aerobic swimming training on liver, heart, and skeletal muscle glycogen content in experimentally induced thyrotoxicosis. Wistar male rats were divided into euthyroid sedentary (ES, n = 12), euthyroid trained (ET, n = 11), thyrotoxic sedentary (TS, n = 12), and thyrotoxic trained (TT, n = 10) groups. Thyrotoxic groups received daily i.p. doses of T4 (sodium levothyroxine, 25 μg/100 g body mass) through the experimental period, and trained groups swam for 1 h at 80% of the aerobic-anaerobic transition intensity, 5 days/week for 4 weeks. Heart and liver glycogen stores were ～30% lower in T4 treated compared with nontreated groups, but were not changed by training status. On the other hand, glycogen content in mixed fiber type gastrocnemius of TT was 1.5- to 2.3-fold greater than those in other groups, whereas no significant differences were found for the slow soleus muscle. Increased gastrocnemius but not soleus, liver, or heart glycogen indicates that in mild long-term thyrotoxicosis chronic swimming affects glycogen stores in a tissue-specific manner.     

Molecular dynamics simulation of GTPase activity in polymers of the cell division protein FtsZ

FtsZ, the prokaryotic ortholog of tubulin, assembles into polymers in the bacterial division ring. The interfaces between monomers contain a GTP molecule, but the relationship between polymerization and GTPase activity is not unequivocally proven. A set of short FtsZ polymers were modelled and the formation of active GTPase structures was monitored using molecular dynamics. Only the interfaces nearest the polymer ends exhibited an adequate geometry for GTP hydrolysis. Simulated conversion of interfaces from close-to-end to internal position and vice versa resulted in their spontaneous rearrangement between active and inactive conformations. This predicted behavior of FtsZ polymer ends was supported by in vitro experiments.     

Natural polymer-based magnetic hydrogels: Potential vectors for remote-controlled drug release

The preparation and characterization of natural polymer-based hydrogels that contain 50-nm diameter magnetite (i.e., FeO:Fe(2)O(3)) nanoparticles are described herein. Fourier-transform infrared spectroscopy (FTIR) analysis confirmed the efficiency of the polysaccharide-modifying process. Thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and compressive moduli demostrate that the presence of magnetite improves thermal and mechanical resistance. Transient diffusion of water in magnetic hydrogels was analyzed via boundary layer mass transfer across an expaning interface, and the degree of swelling of these polysaccharide hydrogels decreases in the presence of magnetite, with no variation in the binary diffusion mechanism. The absence of hysteresis loops and coercivity observed via magnetometry suggests that magnetic hydrogels are useful for remote-controlled drug release, as demonstrated by magnetic-field-induced release of curcumin. Experiments reveal that magnetic hydrogels with greater magnetic susceptibility have the potential to release larger concentrations of drugs from the hydrogel network.