Distinct genetic architectures for male and female inflorescence traits of maize

We compared the genetic architecture of thirteen maize morphological traits in a large population of recombinant inbred lines. Four traits from the male inflorescence (tassel) and three traits from the female inflorescence (ear) were measured and studied using linkage and genome-wide association analyses and compared to three flowering and three leaf traits previously studied in the same population. Inflorescence loci have larger effects than flowering and leaf loci, and ear effects are larger than tassel effects. Ear trait models also have lower predictive ability than tassel, flowering, or leaf trait models. Pleiotropic loci were identified that control elongation of ear and tassel, consistent with their common developmental origin. For these pleiotropic loci, the ear effects are larger than tassel effects even though the same causal polymorphisms are likely involved. This implies that the observed differences in genetic architecture are not due to distinct features of the underlying polymorphisms. Our results support the hypothesis that genetic architecture is a function of trait stability over evolutionary time, since the traits that changed most during the relatively recent domestication of maize have the largest effects.     

Divergence of mate recognition behavior and its consequences for genetic architectures of speciation

The divergence of premating behavior and morphology plays a primary role in speciation, and an understanding of the genetic architectures of these phenotypes is essential for the evaluation of models of the speciation process. However, our empirical knowledge of the genetics underlying speciation-related traits remains limited. In this article, we argue that a dissection of specific aspects of the genetic architecture of such traits in a comparative context can allow us to rule out some mechanisms of divergence. We discuss these ideas with reference to our investigation of intersexual communication behaviors involved in mate recognition in the Hawaiian cricket genus Laupala. Different species of Laupala sing distinctively and show species-specific acoustic preferences. We focus on the sister species Laupala paranigra and Laupala kohalensis, characterized by differences in these classic courtship phenotypes. We discuss our preliminary results on the directionality of effect of substituted alleles underlying these species differences. We then discuss these results in the context of historical inference, a necessary perspective for testing the genomic predictions made by theories of speciation that focus on evolution of mate recognition systems.     

The evolution of genetic architectures underlying quantitative traits

In the classic view introduced by R. A. Fisher, a quantitative trait is encoded by many loci with small, additive effects. Recent advances in quantitative trait loci mapping have begun to elucidate the genetic architectures underlying vast numbers of phenotypes across diverse taxa, producing observations that sometimes contrast with Fisher''s blueprint. Despite these considerable empirical efforts to map the genetic determinants of traits, it remains poorly understood how the genetic architecture of a trait should evolve, or how it depends on the selection pressures on the trait. Here, we develop a simple, population-genetic model for the evolution of genetic architectures. Our model predicts that traits under moderate selection should be encoded by many loci with highly variable effects, whereas traits under either weak or strong selection should be encoded by relatively few loci. We compare these theoretical predictions with qualitative trends in the genetics of human traits, and with systematic data on the genetics of gene expression levels in yeast. Our analysis provides an evolutionary explanation for broad empirical patterns in the genetic basis for traits, and it introduces a single framework that unifies the diversity of observed genetic architectures, ranging from Mendelian to Fisherian.     

A performance comparison of data and memory allocation strategies for sequence aligners on NUMA architectures

Over the last several years, many sequence alignment tools have appeared and become popular for the fast evolution of next generation sequencing technologies. Obviously, researchers that use such tools are interested in getting maximum performance when they execute them in modern infrastructures. Today’s NUMA (Non-uniform memory access) architectures present major challenges in getting such applications to achieve good scalability as more processors/cores are used. The memory system in NUMA systems shows a high complexity and may be the main cause for the loss of an application’s performance. The existence of several memory banks in NUMA systems implies a logical increase in latency associated with the accesses of a given processor to a remote bank. This phenomenon is usually attenuated by the application of strategies that tend to increase the locality of memory accesses. However, NUMA systems may also suffer from contention problems that can occur when concurrent accesses are concentrated on a reduced number of banks. Sequence alignment tools use large data structures to contain reference genomes to which all reads are aligned. Therefore, these tools are very sensitive to performance problems related to the memory system. The main goal of this study is to explore the trade-offs between data locality and data dispersion in NUMA systems. We have performed experiments with several popular sequence alignment tools on two widely available NUMA systems to assess the performance of different memory allocation policies and data partitioning strategies. We find that there is not one method that is best in all cases. However, we conclude that memory interleaving is the memory allocation strategy that provides the best performance when a large number of processors and memory banks are used. In the case of data partitioning, the best results are usually obtained when the number of partitions used is greater, sometimes combined with an interleave policy.     

Human implicit memory for irrelevant dimension values is similar to rats' incidental memory in simultaneous discrimination tasks

Participants completed a category-learning task in which they needed to discover which of three stimulus dimensions (shape, color or size) was relevant. After meeting a learning criterion (nine of 10 consecutive correct responses), participants continued making categorization choices and response latencies associated with these trials were examined. In both Experiments 1 and 2, people responded reliably faster when correct responses matched the previous responses with respect to irrelevant dimension values. Thus, they demonstrated a form of incidental short-term memory analogous to that we previously reported in studies of rats. In Experiment 2, participants' explicit memory for irrelevant dimension values was assessed after category learning was complete. The results indicated that people were unaware of the irrelevant dimension values encountered on trials preceding surprise probe trials. This indicates that memory for the irrelevant dimension values was implicit (i.e. unconscious). The findings are discussed with respect to both human and non-human studies of hippocampus-independent memory and implicit memory.     

Intrusion of stereotyped responding in pigeon spatial memory tasks

Pigeons appear predisposed to respond in stereotyped manners in multi-item spatial memory tasks in which the items are simultaneously presented. We discovered this when we attempted to study primacy and recency serial position effects using a delayed matching of key location task (Experiment 1) and when we attempted to develop a keypack analog of the radial-arm maze task (Experiment 4). In Experiment 1 matching accuracy for first-pecked sample was above chance, approximately chance for the second-pecked sample, and below chance for the third-pecked sample. Experiments 2 and 3 showed that the results of Experiment 1 were due to “superstitious” stereotyped responding: When pigeons were allowed to respond to two or three keys in any order and then respond to the same keys again, they responded in the same order on the second occasion. In Experiment 4, the pigeons successfully avoided pecking previously-pecked keys but did so by pecking the keys in a fixed sequence.     

Next generation modeling in GWAS: comparing different genetic architectures

The continuous advancement in genotyping technology has not been accompanied by the application of innovative statistical methods, such as multi-marker methods (MMM), to unravel genetic associations with complex traits. Although the performance of MMM has been widely explored in a prediction context, little is known on their behavior in the quantitative trait loci (QTL) detection under complex genetic architectures. We shed light on this still open question by applying Bayes A (BA) and Bayesian LASSO (BL) to simulated and real data. Both methods were compared to the single marker regression (SMR). Simulated data were generated in the context of six scenarios differing on effect size, minor allele frequency (MAF) and linkage disequilibrium (LD) between QTLs. These were based on real SNP genotypes in chromosome 21 from the Spanish Bladder Cancer Study. We show how the genetic architecture dramatically affects the behavior of the methods in terms of power, type I error and accuracy of estimates. Markers with high MAF are easier to detect by all methods, especially if they have a large effect on the phenotypic trait. A high LD between QTLs with either large or small effects differently affects the power of the methods: it impairs QTL detection with BA, irrespectively of the effect size, although boosts that of small effects with BL and SMR. We demonstrate the convenience of applying MMM rather than SMR because of their larger power and smaller type I error. Results from real data when applying MMM suggest novel associations not detected by SMR.     

A note on a quantitative genetic approach for modelling of differentiation tasks

Learning capacities and cognitive abilities of farm animals will become more important and they will have an impact on animal welfare and productivity. Scientific examinations of these aspects presuppose genetic models. This paper presents an approach for modelling differentiation tasks in animal learning on a quantitative genetic basis. The approach links the likelihood function, to make a correct decision, with the two-dimensional density function, capable to be to decide right. The proposed model is able to depict several situations in learning processes of populations. Its parameters characterize the theoretical course of the learning process and also the stage of learning which a population has reached. The approach can be used to estimate parameters of a learning process and of the genetic disposition to learn, to estimate breeding values of learning capacity and to fit models on population's learning capability under selection.     

Hybrid FMS control architectures based on holonic principles

The escalation in processor technologies and the corresponding reduction in costs have enabled alternative FMS control architectures to be developed without the restrictions of “fixed machine controller boundaries”. These new architectures can be based upon the use of intelligent servo axes, which are desccribed in this article, as flexible numerical control (FNC). In current parlance, the FNC is a “part movement holon” within a manufacturing cell. The control architectures that can be derived from the FNC concept are referred to as hybrid architectures and share the emerging attributes of holonics. This article details the problems that arise in the scheduling and control of FMSs in the light of hybrid control architectures. A number of traditional scheduling approaches have been devised to cope with the scheduling of parts to discrete machines, but the problem here is to ascribe the processing (machining) of part features to axis groups. This article documents how two research programs, undertaken at the CIM Centre at Swinburne University of Technology in Hawthorn, Victoria, Australia, have endeavored to address the problem of hybrid architectures and their associated scheduling.     

Multimodal sensory integration in insects--towards insect brain control architectures

Although a variety of basic insect behaviours have inspired successful robot implementations, more complex capabilities in these 'simple' animals are often overlooked. By reviewing the general architecture of their nervous systems, we gain insight into how they are able to integrate behaviours, perform pattern recognition, context-dependent learning, and combine many sensory inputs in tasks such as navigation. We review in particular what is known about two specific 'higher' areas in the insect brain, the mushroom bodies and the central complex, and how they are involved in controlling an insect's behaviour. While much of the functional interpretation of this information is still speculative, it nevertheless suggests some promising new approaches to obtaining adaptive behaviour in robots.     

Modelling relative recency discrimination tasks using a stochastic working memory model

Relative recency discrimination (RD) task is typically used to assess the temporal organization function of the prefrontal cortex (PFC). Subjects look at a series of cards (with words or drawings on them) and on seeing a test card determine which of the two items was seen more recently. Results show that patients with damage to the prefrontal cortex are severely impaired on this task. We propose a memory trace-priming mechanism, based on automatic time-marking process hypothesis (Schacter, D.L., 1987. Memory, amnesia, and frontal lobe dysfunction: a critique and interpretation. Psychobiology 15, 21-36), to offer a computational account of the results. In this model, successive words seen by subjects leave decaying memory traces in PFC, which subsequently prime the representations in higher sensory areas such as inferior temporal Cortex (IT) during discrimination judgements. The paper focuses on the evaluation of a probabilistic pre-frontal trace mechanism using a pool of clusters of neurons with self-sustained firing that ends at a random time. The results show that the probabilistic behavior of subjects can be accounted for by the stochasticity of the trace model. A good fit to experimental data is obtained with a PFC memory persistence probability with a decay time constant of tau = approximately 30 s. The model allows for a distributed representation in IT and PFC, but the best fit suggests a sparse representation. It is concluded that further data are needed on representations in IT and PFC, on the connectivity between these two areas, and on the statistical and dynamic properties of memory neurons in PFC.     

The current status and outlook for molecular genetic methods in solving the tasks of medical microbiology

The article deals with modern methods, viz. PCR, molecular display and genotherapy, which permit the new approach to the solution of problems connected with the identification of infective agents, the study of the mechanisms of the pathogenesis of infectious diseases and their treatment. In this article concrete examples, clearly demonstrating how each of the above-mentioned technologies makes it possible to broaden the circle of problems solved in infectious pathology of man, are presented.     

Long-term response to genomic selection: effects of estimation method and reference population structure for different genetic architectures

Background

Genomic selection has become an important tool in the genetic improvement of animals and plants. The objective of this study was to investigate the impacts of breeding value estimation method, reference population structure, and trait genetic architecture, on long-term response to genomic selection without updating marker effects.

Methods

Three methods were used to estimate genomic breeding values: a BLUP method with relationships estimated from genome-wide markers (GBLUP), a Bayesian method, and a partial least squares regression method (PLSR). A shallow (individuals from one generation) or deep reference population (individuals from five generations) was used with each method. The effects of the different selection approaches were compared under four different genetic architectures for the trait under selection. Selection was based on one of the three genomic breeding values, on pedigree BLUP breeding values, or performed at random. Selection continued for ten generations.

Results

Differences in long-term selection response were small. For a genetic architecture with a very small number of three to four quantitative trait loci (QTL), the Bayesian method achieved a response that was 0.05 to 0.1 genetic standard deviation higher than other methods in generation 10. For genetic architectures with approximately 30 to 300 QTL, PLSR (shallow reference) or GBLUP (deep reference) had an average advantage of 0.2 genetic standard deviation over the Bayesian method in generation 10. GBLUP resulted in 0.6% and 0.9% less inbreeding than PLSR and BM and on average a one third smaller reduction of genetic variance. Responses in early generations were greater with the shallow reference population while long-term response was not affected by reference population structure.

Conclusions

The ranking of estimation methods was different with than without selection. Under selection, applying GBLUP led to lower inbreeding and a smaller reduction of genetic variance while a similar response to selection was achieved. The reference population structure had a limited effect on long-term accuracy and response. Use of a shallow reference population, most closely related to the selection candidates, gave early benefits while in later generations, when marker effects were not updated, the estimation of marker effects based on a deeper reference population did not pay off.     

Voluntary control of cardiovascular reactions to demanding tasks

Three groups of 10 normotensives participated in a study exploring voluntary control of cardiovascular reactions to cognitive tasks. Pulse transit time (TT), interbeat interval (IBI), skin conductance level, and respiratory variables were monitored throughout one introductory and four experimental sessions. The groups were matched on the basis of initial TT and IBI responses to the taxing arithmetic and reasoning tasks. During experimental sessions, one group (FB) was provided with visual analogue TT feedback, while the REL group was given detailed relaxation instructions. A third group (CON) performed the same sequence of tasks but was not instructed to modify cardiovascular reactions at any point. Training in voluntary control was carried out in resting (no-task) conditions, and during task administration. Both treatment groups showed lower cardiovascular reactions than controls in task trials. Only REL subjects lengthened TT in no-task conditions, while both FB and REL groups showed smaller cardiovascular reactions than CON during the tasks. Effects were confined to cardiovascular variables, since respiratory and electrodermal reactions during task administration were similar in all groups. The effects of treatments were especially marked among the most reactive subjects.This work was supported by the Medical Research Council, U.K. We are grateful to Derek Johnston for his comments on an earlier draft of this paper.     

Voluntary control of cardiovascular reactions to demanding tasks

Three groups of 10 normotensives participated in a study exploring voluntary control of cardiovascular reactions to cognitive tasks. Pulse transit time (TT), interbeat interval (IBI), skin conductance level, and respiratory variables were monitored throughout one introductory and four experimental sessions. The groups were matched on the basis of initial TT and IBI responses to the taxing arithmetic and reasoning tasks. During experimental sessions, one group (FB) was provided with visual analogue TT feedback, while the REL group was given detailed relaxation instructions. A third group (CON) performed the same sequence of tasks but was not instructed to modify cardiovascular reactions at any point. Training in voluntary control was carried out in resting (no-task) conditions, and during task administration. Both treatment groups showed lower cardiovascular reactions than controls in task trials. Only REL subjects lengthened TT in no-task conditions, while both FB and REL groups showed smaller cardiovascular reactions than CON during the tasks. Effects were confined to cardiovascular variables, since respiratory and electrodermal reactions during task administration were similar in all groups. The effects of treatments were especially marked among the most reactive subjects.     

Quantifying dynamic stability of genetic memory circuits

Bistability/Multistability has been found in many biological systems including genetic memory circuits. Proper characterization of system stability helps to understand biological functions and has potential applications in fields such as synthetic biology. Existing methods of analyzing bistability are either qualitative or in a static way. Assuming the circuit is in a steady state, the latter can only reveal the susceptibility of the stability to injected DC noises. However, this can be inappropriate and inadequate as dynamics are crucial for many biological networks. In this paper, we quantitatively characterize the dynamic stability of a genetic conditional memory circuit by developing new dynamic noise margin (DNM) concepts and associated algorithms based on system theory. Taking into account the duration of the noisy perturbation, the DNMs are more general cases of their static counterparts. Using our techniques, we analyze the noise immunity of the memory circuit and derive insights on dynamic hold and write operations. Considering cell-to-cell variations, our parametric analysis reveals that the dynamic stability of the memory circuit has significantly varying sensitivities to underlying biochemical reactions attributable to differences in structure, time scales, and nonlinear interactions between reactions. With proper extensions, our techniques are broadly applicable to other multistable biological systems.