Inhibitory effects of ghrelin on sexual behavior: role of the peptide in the receptivity reduction induced by food restriction in mice

Ghrelin (Ghr) is a gut/hypothalamus peptide with inhibitory actions on reproductive physiology; however, there are no previous reports of its role on estrous behavior. Under the hypothesis that the increase of plasma Ghr during food restriction (FR) is responsible for receptivity reduction, we intended to evaluate the receptivity percentage of female mice subjected to: exp. 1) acute and chronic FR and Ghr administration (3?nmol/animal/day, s.?c.) and exp. 2) the co-administration of a ghrelin antagonist [ant=(d-Lys3)-GHRP-6; 6?nmol/animal/day s.?c.]. All females were ovariectomized, primed with steroids, trained, and randomly subjected every week to each one of several protocols, followed by a behavioral test. Experiment 1 (n=8): basal, no treatment; acute FR (aFR), 24-h fasting; chronic FR (cFR), 50% FR for 5 days; acute ghrelin (aGhr), Ghr 30?min before test and chronic ghrelin (cGhr), Ghr for 5 days. Except for cGhr, all treatments significantly decreased the percentage of receptivity (mean±SEM): basal 61.9±6.0, aFR 33.1±8.1, cFR 18.8±7.7, aGhr 45.6±10.6, p<0.05 vs. basal. In exp. 2 (n=11), except for cFR+ant (55.0±6.4) the co-administration of the antagonist reversed the deleterious effects detected in exp. 1: basal 70.9±5.4; aFR+ant 72.3±7.6; aGhr+ant 73.6±4.7. As expected, the administration of vehicle or antagonist alone did not modify receptivity. Besides, we found a significant correlation between percentage of body weight loss and percentage of receptivity reduction (r=0.62, p=0.0004). This is the first study demonstrating that ghrelin is able to inhibit female mice sexual behavior and that is involved, at least in part, in receptivity reduction after food scarcity.     

Beyond missing heritability: prediction of complex traits

Despite rapid advances in genomic technology, our ability to account for phenotypic variation using genetic information remains limited for many traits. This has unfortunately resulted in limited application of genetic data towards preventive and personalized medicine, one of the primary impetuses of genome-wide association studies. Recently, a large proportion of the "missing heritability" for human height was statistically explained by modeling thousands of single nucleotide polymorphisms concurrently. However, it is currently unclear how gains in explained genetic variance will translate to the prediction of yet-to-be observed phenotypes. Using data from the Framingham Heart Study, we explore the genomic prediction of human height in training and validation samples while varying the statistical approach used, the number of SNPs included in the model, the validation scheme, and the number of subjects used to train the model. In our training datasets, we are able to explain a large proportion of the variation in height (h(2) up to 0.83, R(2) up to 0.96). However, the proportion of variance accounted for in validation samples is much smaller (ranging from 0.15 to 0.36 depending on the degree of familial information used in the training dataset). While such R(2) values vastly exceed what has been previously reported using a reduced number of pre-selected markers (<0.10), given the heritability of the trait (～ 0.80), substantial room for improvement remains.     

Non-linear models based on simple topological indices to identify RNase III protein members

Alignment-free classifiers are especially useful in the functional classification of protein classes with variable homology and different domain structures. Thus, the Topological Indices to BioPolymers (TI2BioP) methodology (Agüero-Chapin et al., 2010) inspired in both the TOPS-MODE and the MARCH-INSIDE methodologies allows the calculation of simple topological indices (TIs) as alignment-free classifiers. These indices were derived from the clustering of the amino acids into four classes of hydrophobicity and polarity revealing higher sequence-order information beyond the amino acid composition level. The predictability power of such TIs was evaluated for the first time on the RNase III family, due to the high diversity of its members (primary sequence and domain organization). Three non-linear models were developed for RNase III class prediction: Decision Tree Model (DTM), Artificial Neural Networks (ANN)-model and Hidden Markov Model (HMM). The first two are alignment-free approaches, using TIs as input predictors. Their performances were compared with a non-classical HMM, modified according to our amino acid clustering strategy. The alignment-free models showed similar performances on the training and the test sets reaching values above 90% in the overall classification. The non-classical HMM showed the highest rate in the classification with values above 95% in training and 100% in test. Although the higher accuracy of the HMM, the DTM showed simplicity for the RNase III classification with low computational cost. Such simplicity was evaluated in respect to HMM and ANN models for the functional annotation of a new bacterial RNase III class member, isolated and annotated by our group.     

Telomere dynamics in parasitic great spotted cuckoos and their magpie hosts

Although little is known on the impact of environment on telomere length dynamics, it has been suggested to be affected by stress, lifestyle and/or life‐history strategies of animals. We here compared telomere dynamics in erythrocytes of hatchlings and fledglings of the brood parasite great spotted cuckoos (Clamator glandarius) and of magpies (Pica pica), their main host in Europe. In magpie chicks, telomere length decreased from hatching to fledging, whereas no significant change in telomere length of great spotted cuckoo chicks was found. Moreover, we found interspecific differences in the association between laying date and telomere shortening. Interspecific differences in telomere shortening were interpreted as a consequence of differences in lifestyle and life‐history characteristics of magpies and great spotted cuckoos. In comparison with magpies, cuckoos experience reduced sibling competition and higher access to resources and, consequently, lower stressful environmental conditions during the nestling phase. These characteristics also explain the associations between telomere attrition and environmental conditions (i.e. laying date) for magpies and the absence of association for great spotted cuckoos. These results therefore fit expectations on telomere dynamics derived from interspecific differences in lifestyle and life history of brood parasites and their bird hosts.     

QTL Mapping of Agronomic Waterlogging Tolerance Using Recombinant Inbred Lines Derived from Tropical Maize (Zea mays L) Germplasm

Waterlogging is an important abiotic stress constraint that causes significant yield losses in maize grown throughout south and south-east Asia due to erratic rainfall patterns. The most economic option to offset the damage caused by waterlogging is to genetically incorporate tolerance in cultivars that are grown widely in the target agro-ecologies. We assessed the genetic variation in a population of recombinant inbred lines (RILs) derived from crossing a waterlogging tolerant line (CAWL-46-3-1) to an elite but sensitive line (CML311-2-1-3) and observed significant range of variation for grain yield (GY) under waterlogging stress along with a number of other secondary traits such as brace roots (BR), chlorophyll content (SPAD), % stem and root lodging (S&RL) among the RILs. Significant positive correlation of GY with BR and SPAD and negative correlation with S&RL indicated the potential use of these secondary traits in selection indices under waterlogged conditions. RILs were genotyped with 331 polymorphic single nucleotide polymorphism (SNP) markers using KASP (Kompetitive Allele Specific PCR) Platform. QTL mapping revealed five QTL on chromosomes 1, 3, 5, 7 and 10, which together explained approximately 30% of phenotypic variance for GY based on evaluation of RIL families under waterlogged conditions, with effects ranging from 520 to 640 kg/ha for individual genomic regions. 13 QTL were identified for various secondary traits associated with waterlogging tolerance, each individually explaining from 3 to 14% of phenotypic variance. Of the 22 candidate genes with known functional domains identified within the physical intervals delimited by the flanking markers of the QTL influencing GY and other secondary traits, six have previously been demonstrated to be associated with anaerobic responses in either maize or other model species. A pair of flanking SNP markers has been identified for each of the QTL and high throughput marker assays were developed to facilitate rapid introgression of waterlogging tolerance in tropical maize breeding programs.     

Segmentation and Tracking of Adherens Junctions in 3D for the Analysis of Epithelial Tissue Morphogenesis

Epithelial morphogenesis generates the shape of tissues, organs and embryos and is fundamental for their proper function. It is a dynamic process that occurs at multiple spatial scales from macromolecular dynamics, to cell deformations, mitosis and apoptosis, to coordinated cell rearrangements that lead to global changes of tissue shape. Using time lapse imaging, it is possible to observe these events at a system level. However, to investigate morphogenetic events it is necessary to develop computational tools to extract quantitative information from the time lapse data. Toward this goal, we developed an image-based computational pipeline to preprocess, segment and track epithelial cells in 4D confocal microscopy data. The computational pipeline we developed, for the first time, detects the adherens junctions of epithelial cells in 3D, without the need to first detect cell nuclei. We accentuate and detect cell outlines in a series of steps, symbolically describe the cells and their connectivity, and employ this information to track the cells. We validated the performance of the pipeline for its ability to detect vertices and cell-cell contacts, track cells, and identify mitosis and apoptosis in surface epithelia of Drosophila imaginal discs. We demonstrate the utility of the pipeline to extract key quantitative features of cell behavior with which to elucidate the dynamics and biomechanical control of epithelial tissue morphogenesis. We have made our methods and data available as an open-source multiplatform software tool called TTT (http://github.com/morganrcu/TTT)