The impact of learning on sexual selection and speciation

Learning is widespread in nature, occurring in most animal taxa and in several different ecological contexts and, thus, might play a key role in evolutionary processes. Here, we review the accumulating empirical evidence for the involvement of learning in mate choice and the consequences for sexual selection and reproductive isolation. We distinguish two broad categories: learned mate preferences and learned traits under mate selection (such as bird song). We point out that the context of learning, namely how and when learning takes place, often makes a crucial difference to the predicted evolutionary outcome. Factors causing biases in learning and when one should expect the evolution of learning itself are also explored.     

The impact of epistatic selection on the genomic traces of selection

The rapid accumulation of genomic data has led to an explosion of studies searching for signals of past selection left within DNA sequences. Yet the majority of theoretical studies investigating the traces of selection have assumed a simple form of selection, without interactions among selectively fixed sites. Fitness interactions—‘epistasis’—are commonplace, however, and take on a myriad of forms ( Whitlock et al. 1995 ; Segrèet al. 2005 ; Phillips 2008 ). It is thus important to determine how such epistasis would influence selective sweeps. On p. 5018 of this issue, Takahasi (2009) explores the effect of epistasis on genetic variation neighbouring two sites that interact in determining fitness, finding that such epistasis has a dramatic impact on the genetic variability in regions surrounding the interacting sites.     

The geneis and mechanism of human error in accidents resulting latent danger.

Six accidental cases caused by overlooking latent environmental danger were analyzed and the geneses and mechanism of the human error involved were discussed. In all cases detection of the danger was easy or indications by some warning were distinct. In a typical case, a lineman, after cleaning the insulators of a suspended line, proceeded toward the danger zone of another line charged with current on reaching the ground. He disregarded the warning flag, and received a shock and fell to the ground. It was also common in all the other cases that victims were conducting relatively easy or habitual activities and responded, being almost unaware of the unusual physical characteristics of the environment, to its more apparent aspects. These errors were relevant to experimental results by the author that subjects had great difficulty in identifying the rule of presentation of signal figures if the key item and the rule, either serial or positional, were different from foregoing trials. It is suggested that an individual fails to see an external object that has little function value in regard to the content of the current behavior under influence of personal habitual experiences and the theories of human error need to be reconstruct as the basis of ecological knowledge about them.     

The galactosaminoglycan-containing decorin and its impact on diseases

1. Download : Download high-res image (281KB)
2. Download : Download full-size image

Highlights? Mutation in the decorin gene causes opacity. ? Gene involved in the synthesis of CS/DS of decorin leads to defects in dermal collagen fibrils. ? Genes involved in the sulfation of CS/DS also lead to altered dermal collagen fibrils. ? Lack of decorin and changes in CS/DS structures might lead to an altered cell signaling.     

The impact of imprinting: Prader-Willi syndrome resulting from chromosome translocation, recombination, and nondisjunction.

Prader-Willi syndrome (PWS) is most often the result of a deletion of bands q11.2-q13 of the paternally derived chromosome 15, but it also occurs either because of maternal uniparental disomy (UPD) of this region or, rarely, from a methylation imprinting defect. A significant number of cases are due to structural rearrangements of the pericentromeric region of chromosome 15. We report two cases of PWS with UPD in which there was a meiosis I nondisjunction error involving an altered chromosome 15 produced by both a translocation event between the heteromorphic satellite regions of chromosomes 14 and 15 and recombination. In both cases, high-resolution banding of the long arm was normal, and FISH of probes D15S11, SNRPN, D15S10, and GABRB3 indicated no loss of this material. Chromosome heteromorphism analysis showed that each patient had maternal heterodisomy of the chromosome 15 short arm, whereas PCR of microsatellites demonstrated allele-specific maternal isodisomy and heterodisomy of the long arm. SNRPN gene methylation analysis revealed only a maternal imprint in both patients. We suggest that the chromosome structural rearrangements, combined with recombination in these patients, disrupted normal segregation of an imprinted region, resulting in uniparental disomy and PWS.     

Gene selection based on multi-class support vector machines and genetic algorithms

Microarrays are a new technology that allows biologists to better understand the interactions between diverse pathologic state at the gene level. However, the amount of data generated by these tools becomes problematic, even though data are supposed to be automatically analyzed (e.g., for diagnostic purposes). The issue becomes more complex when the expression data involve multiple states. We present a novel approach to the gene selection problem in multi-class gene expression-based cancer classification, which combines support vector machines and genetic algorithms. This new method is able to select small subsets and still improve the classification accuracy.     

Errors in CGAP xProfiler and cDNA DGED: the importance of library parsing and gene selection algorithms

Background  

The Cancer Genome Anatomy Project (CGAP) xProfiler and cDNA Digital Gene Expression Displayer (DGED) have been made available to the scientific community over a decade ago and since then were used widely to find genes which are differentially expressed between cancer and normal tissues. The tissue types are usually chosen according to the ontology hierarchy developed by NCBI. The xProfiler uses an internally available flat file database to determine the presence or absence of genes in the chosen libraries, while cDNA DGED uses the publicly available UniGene Expression and Gene relational databases to count the sequences found for each gene in the presented libraries.     

The effects of alignment error and alignment filtering on the sitewise detection of positive selection

When detecting positive selection in proteins, the prevalence of errors resulting from misalignment and the ability of alignment filters to mitigate such errors are not well understood, but filters are commonly applied to try to avoid false positive results. Focusing on the sitewise detection of positive selection across a wide range of divergence levels and indel rates, we performed simulation experiments to quantify the false positives and false negatives introduced by alignment error and the ability of alignment filters to improve performance. We found that some aligners led to many false positives, whereas others resulted in very few. False negatives were a problem for all aligners, increasing with sequence divergence. Of the aligners tested, PRANK's codon-based alignments consistently performed the best and ClustalW performed the worst. Of the filters tested, GUIDANCE performed the best and Gblocks performed the worst. Although some filters showed good ability to reduce the error rates from ClustalW and MAFFT alignments, none were found to substantially improve the performance of PRANK alignments under most conditions. Our results revealed distinct trends in error rates and power levels for aligners and filters within a biologically plausible parameter space. With the best aligner, a low false positive rate was maintained even with extremely divergent indel-prone sequences. Controls using the true alignment and an optimal filtering method suggested that performance improvements could be gained by improving aligners or filters to reduce the prevalence of false negatives, especially at higher divergence levels and indel rates.     

The impact of climatic variation on the opportunity for sexual selection

Many studies have demonstrated influences of climatic variation on a variety of ecological processes, however, its impact on the potent evolutionary force of sexual selection has largely been ignored. The intensity of sexual selection is a fundamental parameter in animal populations, which depends upon the degree of polygamy and will probably be influenced by the impact of local climatic variation upon 'environmental potential for polygamy'. Here, we provide evidence of a direct effect of local climatic variation on the intensity of sexual selection, by showing a clear correlation between local weather conditions and inter-annual changes in the degree of polygamy in a long-term study of colonially breeding grey seals (Halichoerus grypus). Our results show that changes in local weather conditions alter the annual proportion of males contributing to the effective population size (Ne) by up to 61%. Consequently, over the 'lifetime' of a cohort, a broader range of individuals will contribute genetically to the next generation if local weather conditions are variable. In the context of predicted future changes in climatic variation, these findings have broad implications for population genetics of socially structured animal systems through the major influence that the degree of polygamy has upon Ne.     

Estimating genotyping error rates from Mendelian errors in SNP array genotypes and their impact on inference

A simple method of inferring the genotyping error rate of SNP arrays and similar high-throughput genotyping methods from Mendelian errors is described. Application to genotypes from small families using the Affymetrix GeneChip Human Mapping 50 k Array indicates an error rate of about 0.1%, and this rate can be reduced by increasing the quality criterion for calls, though at the cost of a reduced genotype call rate, which limits the benefit available. Simulated data are used to show that the number of SNPs on this array is sufficient for such a low error rate to have little impact on identical by descent-based inference for disease linkage in sib-pair studies.     

The impact of errors in copy number variation detection algorithms on association results

The inaccuracy of copy number variation (CNV) detection on single nucleotide polymorphism (SNP) arrays has recently been brought to attention. Such high error rates will undoubtedly have ramifications on downstream association testing. We examined this effect for a wide range of scenarios and found a noticeable decrease in power for error rates typical of CNV calling algorithms. We compared power using CNV calls to the log relative ratio and found the latter to be superior when error rates are moderate to large or when the CNV size is small. It is our recommendation that CNV researchers use intensity measurements as an alternative to CNV calls in these scenarios.