Hypnotizability and spatial attentional functions

Many theories of hypnotic responding have proposed that differences in hypnotic trait rely on differences in frontal attentional functions. Evidence of hypnotizability-related attentional abilities are, however, very scant. This study was designed to investigate the relationship between hypnotizability and executive control components of attention in the spatial domain. We chose the Attention Network Test that enables to analyze alerting, orienting and executive control functions by measuring reaction times (RTs) to targets cued for different locations in space. According to Posner theory, alerting, orienting and executive control effects were found in both groups. No differences between highly susceptible (Highs) and low susceptible individuals (Lows) on executive control functions were found. However, in Highs alerting was significantly smaller than in Lows and Highs were significantly faster than Lows in the no and central cue conditions. These findings suggest that Highs would be endowed with a basal higher efficiency in achieving and maintaining their readiness to respond to incoming stimuli. This relation between hypnotizability and alerting, is discussed in terms of a possible more efficient noradrenergic activity driven by frontal attentional systems.     

Congruence between morphological and molecular markers inferred from the analysis of the intra-morphotype genetic diversity and the spatial structure of Oxalis tuberosa Mol.

Oxalis tuberosa is an important crop cultivated in the highest Andean zones. A germplasm collection is maintained ex situ by CIP, which has developed a morphological markers system to classify the accessions into morphotypes, i.e. groups of morphologically identical accessions. However, their genetic uniformity is currently unknown. The ISSR technique was used in two experiments to determine the relationships between both morphological and molecular markers systems. The intra-morphotype genetic diversity, the spatial structures of the diversity and the congruence between both markers systems were determined. In the first experience, 44 accessions representing five morphotypes, clearly distinct from each other, were analyzed. At the molecular level, the accessions exactly clustered according to their morphotypes. However, a genetic variability was observed inside each morphotype. In the second experiment, 34 accessions gradually differing from each other on morphological base were analyzed. The morphological clustering showed no geographical structure. On the opposite, the molecular analysis showed that the genetic structure was slightly related to the collection site. The correlation between both markers systems was weak but significant. The lack of perfect congruence between morphological and molecular data suggests that the morphological system may be useful for the morphotypes management but is not appropriate to study the genetic structure of the oca. The spatial structure of the genetic diversity can be related to the evolution of the species and the discordance between the morphological and molecular structures may result from similar selection pressures at different places leading to similar forms with a different genetic background.     

Population bottlenecks and Pleistocene human evolution

We review the anatomical and archaeological evidence for anearly population bottleneck in humans and bracket the time whenit could have occurred. We outline the subsequent demographicchanges that the archaeological evidence of range expansionsand contractions address, and we examine how inbreeding effectivepopulation size provides an alternative view of past populationsize change. This addresses the question of other, more recent,population size bottlenecks, and we review nonrecombining andrecombining genetic systems that may reflect them. We examinehow these genetic data constrain the possibility of significantpopulation size bottlenecks (i.e., of sufficiently small sizeand/or long duration to minimize genetic variation in autosomaland haploid systems) at several different critical times inhuman history. Different constraints appear in nonrecombiningand recombining systems, and among the autosomal loci most areincompatible with any Pleistocene population size expansions.Microsatellite data seem to show Pleistocene population sizeexpansions, but in aggregate they are difficult to interpretbecause different microsatellite studies do not show the sameexpansion. The archaeological data are only compatible witha few of these analyses, most prominently with data from Aluelements, and we use these facts to question whether the viewof the past from analysis of inbreeding effective populationsize is valid. Finally, we examine the issue of whether inbreedingeffective population size provides any reasonable measure ofthe actual past size of the human species. We contend that ifthe evidence of a population size bottleneck early in the evolutionof our lineage is accepted, most genetic data either lack theresolution to address subsequent changes in the human populationor do not meet the assumptions required to do so validly. Itis our conclusion that, at the moment, genetic data cannot disprovea simple model of exponential population growth following abottleneck 2 MYA at the origin of our lineage and extendingthrough the Pleistocene. Archaeological and paleontologicaldata indicate that this model is too oversimplified to be anaccurate reflection of detailed population history, and thereforewe find that genetic data lack the resolution to validly reflectmany details of Pleistocene human population change. However,there is one detail that these data are sufficient to address.Both genetic and anthropological data are incompatible withthe hypothesis of a recent population size bottleneck. Suchan event would be expected to leave a significant mark acrossnumerous genetic loci and observable anatomical traits, butwhile some subsets of data are compatible with a recent populationsize bottleneck, there is no consistently expressed effect thatcan be found across the range where it should appear, and thisabsence disproves the hypothesis.     

An analysis of the spectra of genetic activity produced by known or suspected human carcinogens

For 24 agents classified by the International Agency for Research on Cancer as known or suspected human carcinogens, we previously catalogued the qualitative genetic bioassay data available in the literature. In the present analysis, dose information, where available, was added to this data base: either the lowest effective dose (LED) or the highest ineffective dose (HID) was recorded for each agent and bioassay system. Bioassay systems were organized according to classes of genetic activity and subdivided by the phylogenetic level of the test organism. For each compound, the quantitative results in the test systems were represented by computer-generated bar graphs ('genetic activity spectra'). The x-axis unit values corresponded to the 100 different test systems, and the y-axis values were the logarithmically transformed LED or HID values. Statistical methods and pattern-recognition techniques were used to evaluate the genetic activity spectra. Spectra were compared among agents grouped according to target-organ specificity. In addition, the spectra of all possible pairs of compounds were compared to identify compounds displaying qualitatively or quantitatively similar genetic activity. Chemically similar compounds frequently produced similar spectra of genetic activity, and it was possible to identify the most appropriate test systems for some classes of compounds. As the data base for human carcinogens is enlarged, analysis of genetic activity spectra may contribute to our understanding of the structure-activity relationships and mechanisms of action of these agents.     

Polyploidy: Pitfalls and paths to a paradigm

Investigators have long searched for a polyploidy paradigm—rules or principles that might be common following polyploidization (whole‐genome duplication, WGD). Here we attempt to integrate what is known across the more thoroughly investigated polyploid systems on topics ranging from genetics to ecology. We found that while certain rules may govern gene retention and loss, systems vary in the prevalence of gene silencing vs. homeolog loss, chromosomal change, the presence of a dominant genome (in allopolyploids), and the relative importance of hybridization vs. genome doubling per se. In some lineages, aspects of polyploidization are repeated across multiple origins, but in other species multiple origins behave more stochastically in terms of genetic and phenotypic change. Our investigation also reveals that the path to synthesis is hindered by numerous gaps in our knowledge of even the best‐known systems. Particularly concerning is the absence of linkage between genotype and phenotype. Moreover, most recent studies have focused on the genetic and genomic attributes of polyploidy, but rarely is there an ecological or physiological context. To promote a path to a polyploidy paradigm (or paradigms), we propose a major community goal over the next 10–20 yr to fill the gaps in our knowledge of well‐studied polyploids. Before a meaningful synthesis is possible, more complete data sets are needed for comparison—systems that include comparable genetic, genomic, chromosomal, proteomic, as well as morphological, physiological, and ecological data. Also needed are more natural evolutionary model systems, as most of what we know about polyploidy continues to come from a few crop and genetic models, systems that often lack the ecological context inherent in natural systems and necessary for understanding the drivers of biodiversity.     

Integration of biological networks and pathways with genetic association studies

Millions of genetic variants have been assessed for their effects on the trait of interest in genome-wide association studies (GWAS). The complex traits are affected by a set of inter-related genes. However, the typical GWAS only examine the association of a single genetic variant at a time. The individual effects of a complex trait are usually small, and the simple sum of these individual effects may not reflect the holistic effect of the genetic system. High-throughput methods enable genomic studies to produce a large amount of data to expand the knowledge base of the biological systems. Biological networks and pathways are built to represent the functional or physical connectivity among genes. Integrated with GWAS data, the network- and pathway-based methods complement the approach of single genetic variant analysis, and may improve the power to identify trait-associated genes. Taking advantage of the biological knowledge, these approaches are valuable to interpret the functional role of the genetic variants, and to further understand the molecular mechanism influencing the traits. The network- and pathway-based methods have demonstrated their utilities, and will be increasingly important to address a number of challenges facing the mainstream GWAS.     

Conservation genetics: beyond the maintenance of marker diversity

One of the major problems faced by conservation biologists is the allocation of scarce resources to an overwhelmingly large number of species in need of preservation efforts. Both demographic and genetic information have been brought to bear on this problem; however, the role of information obtained from genetic markers has largely been limited to the characterization of gene frequencies and patterns of diversity. While the genetic consequences of rarity may be a contributing factor to endangerment, it is widely recognized that demographic factors often may be more important. Because patterns of genetic marker variation are influenced by the same demographic factors of interest to the conservation biologist, it is possible to extract useful demographic information from genetic marker data. Such an approach may be productive for determining plant mating systems, inbreeding depression, effective population size, and metapopulation structure. In many cases, however, data consisting only of marker frequencies are inadequate for these purposes. Development of genealogical based analytical methods coupled with studies of DNA sequence variation within and among populations is likely to yield the most information on demographic processes from genetic marker data. Indeed, in some cases it may be the only means of obtaining information on the long-term demographic properties that may be most useful for determining the future prospects of a species of interest.     

Sex-specific demographic behaviours that shape human genomic variation

In the human species, the two uniparental genetic systems (mitochondrial DNA and Y chromosome) exhibit contrasting diversity patterns. It has been proposed that sex-specific behaviours, and in particular differences in migration rate between men and women, may explain these differences. The availability of high-density genomic data and the comparison of genetic patterns on autosomal and sex chromosomes at global and local scales allow a reassessment of the extent to which sex-specific behaviours shape our genome. In this article, we first review studies comparing the genetic patterns at uniparental and biparental genetic systems and assess the extent to which sex-specific migration processes explain the differences between these genetic systems. We show that differences between male and female migration rates matter, but that they are certainly not the only contributing factor. In particular, differences in effective population size between men and women are also likely to account for these differences. Then, we present and discuss three anthropological processes that may explain sex-specific differences in effective population size and thus human genomic variation: (i) variance in reproductive success arising from, for example, polygyny; (ii) descent rules; and (iii) transmission of reproductive success.     

Mating systems and sexual selection in male-pregnant pipefishes and seahorses: insights from microsatellite-based studies of maternity

In pipefishes and seahorses (family Syngnathidae), the males provide all postzygotic care of offspring by brooding embryos on their ventral surfaces. In some species, this phenomenon of male "pregnancy" results in a reversal of the usual direction of sexual selection, such that females compete more than males for access to mates, and secondary sexual characteristics evolve in females. Thus the syngnathids can provide critical tests of theories related to the evolution of sex differences and sexual selection. Microsatellite-based studies of the genetic mating systems of several species of pipefishes and seahorses have provided insights into important aspects of the natural history and evolution of these fishes. First, males of species with completely enclosed pouches have complete confidence of paternity, as might be predicted from parental investment theory for species in which males invest so heavily in offspring. Second, a wide range of genetic mating systems have been documented in nature, including genetic monogamy in a seahorse, polygynandry in two species of pipefish, and polyandry in a third pipefish species. The genetic mating systems appear to be causally related to the intensity of sexual selection, with secondary sex characters evolving most often in females of the more polyandrous species. Third, genetic studies of captive-breeding pipefish suggest that the sexual selection gradient (or Bateman gradient) may be a substantially better method for characterizing the mating system than previously available techniques. Finally, these genetic studies of syngnathid mating systems have led to some general insights into the occurrence of clustered mutations at microsatellite loci, the utility of linked loci in studies of parentage, and the use of parentage data for direct estimation of adult population size.     

Structural systems identification of genetic regulatory networks

MOTIVATION: Reverse engineering of genetic regulatory networks from experimental data is the first step toward the modeling of genetic networks. Linear state-space models, also known as linear dynamical models, have been applied to model genetic networks from gene expression time series data, but existing works have not taken into account available structural information. Without structural constraints, estimated models may contradict biological knowledge and estimation methods may over-fit. RESULTS: In this report, we extended expectation-maximization (EM) algorithms to incorporate prior network structure and to estimate genetic regulatory networks that can track and predict gene expression profiles. We applied our method to synthetic data and to SOS data and showed that our method significantly outperforms the regular EM without structural constraints. AVAILABILITY: The Matlab code is available upon request and the SOS data can be downloaded from http://www.weizmann.ac.il/mcb/UriAlon/Papers/SOSData/, courtesy of Uri Alon. Zak's data is available from his website, http://www.che.udel.edu/systems/people/zak.