Orbital signatures in a late Miocene dinoflagellate record from Crete (Greece)

A high-resolution palynological study of the cyclically bedded Faneromeni section (upper Tortonian-lower Messinian) on Crete (Greece) is presented. This study aims to recognize orbitally-driven variations in the palynological record and to validate the age model based on the astronomical calibration of the sedimentary cycles. Four palynology-based environmental proxies were utilised using interpretations of fossil dinoflagellate associations based on modern ecological characteristics. Cross-spectral analysis between the proxy records and astronomical target curve, the 65°N summer insolation, yielded in most cases significant spectral power and coherence in the precession and/or obliquity frequency bands. Precession-controlled variations in the proxy records are related to lithology and indicate that maxima in continental input and minima in sea surface salinity coincide with sapropel formation. The influence of obliquity is most clearly reflected in the index of continental versus marine palynomorphs (S-D). The absence of a distinct time lag relative to obliquity indicates that the 41-kyr component in continental input is controlled by oscillations in regional Mediterranean climate rather than by glacial cyclicity. Phase relations in the different astronomical frequency bands of the spectrum, as compared with the Mediterranean Pliocene, essentially confirm the validity of the Miocene astronomical time scale. Finally, a major non-cyclic change in the palynological assemblage at 6.68 Ma indicates enhanced salinity and decreased river discharge. This shift coincides with a significant drop in sedimentation rate informally termed the “Early Messinian Sediment starvation Event”.     

Speed congenics: accelerated genome recovery using genetic markers.

Genetic markers throughout the genome can be used to speed up 'recovery' of the recipient genome in the backcrossing phase of the construction of a congenic strain. The prediction of the genomic proportion during backcrossing depends on the assumptions regarding the distribution of chromosome segments, the population structure, the marker spacing and the selection strategy. In this study simulation was used to investigate the rate of recovery of the recipient genome for a mouse, Drosophila and Arabidopsis genome. It was shown that an incorrect assumption of a binomial distribution of chromosome segments, and failing to take account of a reduction in variance in genomic proportion due to selection, can lead to a downward bias of up to two generations in the estimation of the number of generations required for the formation of a congenic strain.     

Genetics of human height

Height is correlated with risk to certain diseases and various socio-economic outcomes. As an easy to observe and measure trait, it has been a classic paradigm in the emergence of fundamental concepts regarding inheritance and genetics. Resemblances in height between relatives suggest that 80% of height variation is under genetic control with the rest controlled by environmental factors such as diet and disease exposure. Nearly a century ago it was recognised that many genes were likely to be involved but it is only with recent advances in technology that it has become possible to comprehensively search the human genome for DNA variants that control height. About 50 genes and regions of the genome have been associated with height to date. These begin to explain the biological basis of height, its links to disease and aid our understanding of the evolution of human height. The genes discovered so far have a very small individual effect and hundreds, maybe thousands, more of even smaller effects are still lost in the genome. Despite a successful start to height gene mapping, there remain considerable theoretical, technological, and statistical hurdles to be overcome in order to unravel its full genetic basis.     

GPS measurement error and resource selection functions in a fragmented landscape

Advances in technology have allowed ecologists to employ remote observations of individual organism's spatial location. These data are used to model species distributions and habitat associations, which inform conservation efforts and management plans. These data are not without error. To illustrate the consequences of not considering measurement error, I introduce measurement error to a habitat selection model, using three different distributions. I show how measurement error can confound inferences made about a hypothetical organism's true habitat selection. By simulating different initial strengths of selection I show the introduction of measurement error results in the largest reduction in habitat selection strength (from truth) for very selective individuals (habitat specialists). Not surprisingly, the inclusion of error in very weakly selective individuals (habitat generalists) can result in a switching from true selection to observed avoidance. Researchers need to be aware that, first, there is measurement error in remotely observed data, and second, a tradeoff occurs between measurement error and landscape fragmentation. Landscapes with a high degree of fragmentation require spatially accurate (low measurement error) data in order to make reliable estimates of habitat selection or species distribution. The results of this study are discussed in light of the conservation of species threatened by habitat fragmentation and the management suggestions arising from selection studies.     

Highly cost-efficient genome-wide association studies using DNA pools and dense SNP arrays

Genome-wide association (GWA) studies to map genes for complex traits are powerful yet costly. DNA-pooling strategies have the potential to dramatically reduce the cost of GWA studies. Pooling using Affymetrix arrays has been proposed and used but the efficiency of these arrays has not been quantified. We compared and contrasted Affymetrix Genechip HindIII and Illumina HumanHap300 arrays on the same DNA pools and showed that the HumanHap300 arrays are substantially more efficient. In terms of effective sample size, HumanHap300-based pooling extracts >80% of the information available with individual genotyping (IG). In contrast, Genechip HindIII-based pooling only extracts ~30% of the available information. With HumanHap300 arrays concordance with IG data is excellent. Guidance is given on best study design and it is shown that even after taking into account pooling error, one stage scans can be performed for >100-fold reduced cost compared with IG. With appropriately designed two stage studies, IG can provide confirmation of pooling results whilst still providing ~20-fold reduction in total cost compared with IG-based alternatives. The large cost savings with Illumina HumanHap300-based pooling imply that future studies need only be limited by the availability of samples and not cost.