A mixed model QTL analysis for sugarcane multiple-harvest-location trial data

Sugarcane-breeding programs take at least 12 years to develop new commercial cultivars. Molecular markers offer a possibility to study the genetic architecture of quantitative traits in sugarcane, and they may be used in marker-assisted selection to speed up artificial selection. Although the performance of sugarcane progenies in breeding programs are commonly evaluated across a range of locations and harvest years, many of the QTL detection methods ignore two- and three-way interactions between QTL, harvest, and location. In this work, a strategy for QTL detection in multi-harvest-location trial data, based on interval mapping and mixed models, is proposed and applied to map QTL effects on a segregating progeny from a biparental cross of pre-commercial Brazilian cultivars, evaluated at two locations and three consecutive harvest years for cane yield (tonnes per hectare), sugar yield (tonnes per hectare), fiber percent, and sucrose content. In the mixed model, we have included appropriate (co)variance structures for modeling heterogeneity and correlation of genetic effects and non-genetic residual effects. Forty-six QTLs were found: 13 QTLs for cane yield, 14 for sugar yield, 11 for fiber percent, and 8 for sucrose content. In addition, QTL by harvest, QTL by location, and QTL by harvest by location interaction effects were significant for all evaluated traits (30 QTLs showed some interaction, and 16 none). Our results contribute to a better understanding of the genetic architecture of complex traits related to biomass production and sucrose content in sugarcane.

Emergence of sensory selection mechanisms in Artificial Life simulations

Background The evolutionary advantages of selective attention are unclear. Since the study of selective attention began, it has been suggested that the nervous system only processes the most relevant stimuli because of its limited capacity [1]. An alternative proposal is that action planning requires the inhibition of irrelevant stimuli, which forces the nervous system to limit its processing [2]. An evolutionary approach might provide additional clues to clarify the role of selective attention. Methods We developed Artificial Life simulations wherein animals were repeatedly presented two objects, "left" and "right", each of which could be "food" or "non-food." The animals' neural networks (multilayer perceptrons) had two input nodes, one for each object, and two output nodes to determine if the animal ate each of the objects. The neural networks also had a variable number of hidden nodes, which determined whether or not it had enough capacity to process both stimuli (Table 1). The evolutionary relevance of the left and the right food objects could also vary depending on how much the animal's fitness was increased when ingesting them (Table 1). We compared sensory processing in animals with or without limited capacity, which evolved in simulations in which the objects had the same or different relevances. Table 1. Nine sets of simulations were performed, varying the values of food objects and the number of hidden nodes in the neural networks. The values of left and right food were swapped during the second half of the simulations. Non-food objects were always worth -3. The evolution of neural networks was simulated by a simple genetic algorithm. Fitness was a function of the number of food and non-food objects each animal ate and the chromosomes determined the node biases and synaptic weights. During each simulation, 10 populations of 20 individuals each evolved in parallel for 20,000 generations, then the relevance of food objects was swapped and the simulation was run again for another 20,000 generations. The neural networks were evaluated by their ability to identify the two objects correctly. The detectability (d') for the left and the right objects was calculated using Signal Detection Theory [3]. Results and conclusion When both stimuli were equally relevant, networks with two hidden nodes only processed one stimulus and ignored the other. With four or eight hidden nodes, they could correctly identify both stimuli. When the stimuli had different relevances, the d' for the most relevant stimulus was higher than the d' for the least relevant stimulus, even when the networks had four or eight hidden nodes. We conclude that selection mechanisms arose in our simulations depending not only on the size of the neuron networks but also on the stimuli's relevance for action.

Effect of nAellore cows ciclicity on conception and pregnant rates after synchronization protocols for fixed timed artificial insemination

Palhano H.B., Jesus V.L.T., Abidu-Figueiredo M., Baldrighi J.M. & Mello M.R.B. [Effect of nAellore cows ciclicity on conception and pregnant rates after synchronization protocols for fixed timed artificial insemination]. Efeito da ciclicidade de vacas Nelore sobre as taxas de concepcao e de prenhez apos protocolos de sincronizacao para inseminacao artificial em tempo fixo. Revista Brasileira de Medicina Veterinaria, 34(1):63-68, 2012. Departamento de Biologia Animal, Universidade Federal Rural do Rio de Janeiro, BR 465 km 7, Seropedica, RJ 23890-000, Brasil. Email: hbpalhano@gmail.com The present study evaluated the effect on conception and pregnancy rates of Nellore cows selected for Fixed Timed Artificial Insemination (FTAI) program, submitted to four synchronization protocols. Four hundred and ninety lactating females were used and assigned to eight groups: I-OvSynch, n=68, with selection of cycling cows; II-OvSynch + progesterone (P-4), n=67, after selection of non-cycling animals; III-OvSynch, without selection, n=68; IV-OvSynch + P-4, without selection, n=67; V-Co-Synch, n=55, with selection of cycling cows; VI-Co-Synch + P-4, n=55, with selection non-cycling cows; VII- Co-Synch without selection, n=55; VIII- Co-Synch + P-4, without selection, n=55. The conception and pregnancy rates were, respectively, 45.6%, 27.9% and 82.4%, 48.5% for groups I and III; 61.2%, 37.3% and 85.1%, 58.2% for groups II and IV; 43.6%, 25.5% and 80%, 41.8% for groups V and VII; 52.7%, 32.7% and 83.6%, 50.9% for groups VI and VIII. When compared these rates, the results after chi-square test showed significant difference (P < 0.05) among protocols with or without selection. There was no significant difference (P > 0.05) between OvSynch and Co-Synch protocols, with or without P-4 and with selection, considering Co-Synch a viable option for optimization of FTAI. In conclusion, the selection of cows before FTAI program contributed significantly to improve the conception and pregnancy rates.