Effects of pre-adult and adult experience on host acceptance in choice and non-choice tests in two strains ofTrichogramma

The effect of adult learning through an oviposition experience, and pre-adult learning through development inside a host was investigated in two strains of an Australian egg parasitoid,Trichogramma nrivelae (Hymenoptera: Trichogrammatidae). Host response was measured in two types of laboratory preference tests. In single host tests, females reared on three lepidopteran hosts (Heliothis punctigera (Noctuidae),Papilio aegeus (Papilionidae), andHypolimnas bolina (Nymphalinae)) were presented host eggs individually, and allowed two ovipositions. Pre-adult experience affected host preference in only one strain, while acceptance of a host was increased in both strains when they had previously oviposited in this host species. An oviposition experience had a stronger effect on host preference than pre-adult experience. In choice tests, pairwise combinations of hosts were arranged in an alternating grid. The ratio of host acceptances to host contacts was computed for the whole test and up to the first oviposition. These indicated that effects of rearing host were weak or absent, but the host chosen initially had a strong effect on host preference. Relative size of the hosts had a strong effect on choice of the first host. The implications of learning inTrichogramma are discussed in relation to host preference testing procedures and the selection of candidate strains for mass rearing and inundative release.     

Tight clustering: a resampling-based approach for identifying stable and tight patterns in data

In this article, we propose a method for clustering that produces tight and stable clusters without forcing all points into clusters. The methodology is general but was initially motivated from cluster analysis of microarray experiments. Most current algorithms aim to assign all genes into clusters. For many biological studies, however, we are mainly interested in identifying the most informative, tight, and stable clusters of sizes, say, 20-60 genes for further investigation. We want to avoid the contamination of tightly regulated expression patterns of biologically relevant genes due to other genes whose expressions are only loosely compatible with these patterns. "Tight clustering" has been developed specifically to address this problem. It applies K-means clustering as an intermediate clustering engine. Early truncation of a hierarchical clustering tree is used to overcome the local minimum problem in K-means clustering. The tightest and most stable clusters are identified in a sequential manner through an analysis of the tendency of genes to be grouped together under repeated resampling. We validated this method in a simulated example and applied it to analyze a set of expression profiles in the study of embryonic stem cells.     

He hears,she hears: Are there sex differences in auditory processing?

Songbirds learn individually unique songs through vocal imitation and use them in courtship and territorial displays. Previous work has identified a forebrain auditory area, the caudomedial nidopallium (NCM), that appears specialized for discriminating and remembering conspecific vocalizations. In zebra finches (ZFs), only males produce learned vocalizations, but both sexes process these and other signals. This study assessed sex differences in auditory processing by recording extracellular multiunit activity at multiple sites within NCM. Juvenile female ZFs (n = 46) were reared in individual isolation and artificially tutored with song. In adulthood, songs were played back to assess auditory responses, stimulus‐specific adaptation, neural bias for conspecific song, and memory for the tutor's song, as well as recently heard songs. In a subset of females (n = 36), estradiol (E2) levels were manipulated to test the contribution of E2, known to be synthesized in the brain, to auditory responses. Untreated females (n = 10) showed significant differences in response magnitude and stimulus‐specific adaptation compared to males reared in the same paradigm (n = 9). In hormone‐manipulated females, E2 augmentation facilitated the memory for recently heard songs in adulthood, but neither E2 augmentation (n = 15) nor E2 synthesis blockade (n = 9) affected tutor song memory or the neural bias for conspecific song. The results demonstrate subtle sex differences in processing communication signals, and show that E2 levels in female songbirds can affect the memory for songs of potential suitors, thus contributing to the process of mate selection. The results also have potential relevance to clinical interventions that manipulate E2 in human patients. © 2014 Wiley Periodicals, Inc. Develop Neurobiol 75: 302–314, 2015     

State-dependency in C. elegans

Memory and the expression of learned behaviors by an organism are often triggered by contextual cues that resemble those that were present when the initial learning occurred. In state-dependent learning, the cue eliciting a learned behavior is a neuroactive drug; behaviors initially learned during exposure to centrally acting compounds such as ethanol are subsequently recalled better if the drug stimulus is again present during testing. Although state-dependent learning is well documented in many vertebrate systems, the molecular mechanisms underlying state-dependent learning and other forms of contextual learning are not understood. Here we demonstrate and present a genetic analysis of state- dependent adaptation in Caenorhabditis elegans. C. elegans normally exhibits adaptation, or reduced behavioral response, to an olfactory stimulus after prior exposure to the stimulus. If the adaptation to the olfactory stimulus is acquired during ethanol administration, the adaptation is subsequently displayed only if the ethanol stimulus is again present. cat-1 and cat-2 mutant animals are defective in dopaminergic neuron signaling and are impaired in state dependency, indicating that dopamine functions in state-dependent adaptation in C. elegans.     

THE GENETIC BASIS OF ZEBRA FINCH VOCALIZATIONS

Animal vocalizations play an important role in individual recognition, kin recognition, species recognition, and sexual selection. Despite much work in these fields done on birds virtually nothing is known about the heritability of vocal traits in birds. Here, we study a captive population of more than 800 zebra finches ( Taeniopygia guttata ) with regard to the quantitative genetics of call and song characteristics. We find very high heritabilities in nonlearned female call traits and considerably lower heritabilities in male call and song traits, which are learned from a tutor and hence show much greater environmental variance than innate vocalizations. In both sexes, we found significant heritabilities in several traits such as mean frequency and measures of timbre, which reflect morphological characteristics of the vocal tract. These traits also showed significant genetic correlations with body size, as well as positive genetic correlations between the sexes, supporting a scenario of honest signaling of body size through genetic pleiotropy ("index signal"). In contrast to such morphology-related voice characteristics, classical song features such as repertoire size or song length showed very low heritabilities. Hence, these traits that are often suspected to be sexually selected would hardly respond to current directional selection.     

The effect of trauma on Neanderthal culture: A mathematical analysis

Traumatic lesions are often observed in ancient skeletal remains. Since ancient medical technology was immature, severely traumatized individuals may have frequently lost the physical ability for cultural skills that demand complex body movements. I develop a mathematical model to analyze the effect of trauma on cultural transmission and apply it to Neanderthal culture using Neanderthal fossil data. I estimate from the data that the proportion of adult individuals who suffered traumatic injuries before death was approximately 0.79–0.94, in which 0.37–0.52 were injured severely and 0.13–0.19 were injured before adulthood. Assuming that every severely traumatized individual and a quarter to a half of the other traumatized individuals lost the capacity for a cultural skill that demands complex control of the traumatized body part, I estimate that if an upper limb is associated with a cultural skill, each individual had to communicate closely with at least 1.5–2.6 individuals during adulthood to maintain the skill in Neanderthal society, and if a whole body is associated, at least 3.1–11.5 individuals were necessary. If cultural transmissions between experts and novices were inaccurate, or if low frequency skills easily disappeared from the population due to random drift, more communicable individuals were necessary. Since the community size of Neanderthals was very small, their high risk of injury may have inhibited the spread of technically difficult cultural skills in their society. It may be important to take this inhibition into consideration when we study Neanderthal culture and the replacement of Neanderthals by modern humans.     

Integrating multi-platform genomic data using hierarchical Bayesian relevance vector machines

Background

Recent advances in genome technologies and the subsequent collection of genomic information at various molecular resolutions hold promise to accelerate the discovery of new therapeutic targets. A critical step in achieving these goals is to develop efficient clinical prediction models that integrate these diverse sources of high-throughput data. This step is challenging due to the presence of high-dimensionality and complex interactions in the data. For predicting relevant clinical outcomes, we propose a flexible statistical machine learning approach that acknowledges and models the interaction between platform-specific measurements through nonlinear kernel machines and borrows information within and between platforms through a hierarchical Bayesian framework. Our model has parameters with direct interpretations in terms of the effects of platforms and data interactions within and across platforms. The parameter estimation algorithm in our model uses a computationally efficient variational Bayes approach that scales well to large high-throughput datasets.

Results

We apply our methods of integrating gene/mRNA expression and microRNA profiles for predicting patient survival times to The Cancer Genome Atlas (TCGA) based glioblastoma multiforme (GBM) dataset. In terms of prediction accuracy, we show that our non-linear and interaction-based integrative methods perform better than linear alternatives and non-integrative methods that do not account for interactions between the platforms. We also find several prognostic mRNAs and microRNAs that are related to tumor invasion and are known to drive tumor metastasis and severe inflammatory response in GBM. In addition, our analysis reveals several interesting mRNA and microRNA interactions that have known implications in the etiology of GBM.

Conclusions

Our approach gains its flexibility and power by modeling the non-linear interaction structures between and within the platforms. Our framework is a useful tool for biomedical researchers, since clinical prediction using multi-platform genomic information is an important step towards personalized treatment of many cancers. We have a freely available software at: http://odin.mdacc.tmc.edu/~vbaladan.

     

A review of the generalization of auditory learning

The ability to detect and discriminate attributes of sounds improves with practice. Determining how such auditory learning generalizes to stimuli and tasks that are not encountered during training can guide the development of training regimens used to improve hearing abilities in particular populations as well as provide insight into the neural mechanisms mediating auditory performance. Here we review the newly emerging literature on the generalization of auditory learning, focusing on behavioural investigations of generalization on basic auditory tasks in human listeners. The review reveals a variety of generalization patterns across different trained tasks that can not be summarized with a simple rule, and a diversity of views about the definition, evaluation and interpretation of generalization.