University of Madeira

About: University of Madeira is a education organization based out in Funchal, Portugal. It is known for research contribution in the topics: Population & Dendrimer. The organization has 1014 authors who have published 2759 publications receiving 59457 citations.

DAZ gene copies: evidence of Y chromosome evolution

Abstract: The DAZ gene, a contributing factor in infertility, lies on the human Y chromosome's AZFc region, whose deletion is a common cause of spermatogenic failure. Y chromosome binary polymorphisms on the non-recombining Y (NRY) region, believed to be a single occurrence on an evolutionary scale, were typed in a sample of fertile and infertile men with known DAZ backgrounds. The Y single-nucleotide polymorphisms (Y-SNPs) with low mutation rates are currently well characterized and permit the construction of a unique phylogeny of haplogroups. DAZ haplotypes were defined using single-nucleotide variant (SNV)/sequence tagged-site (STS) markers to distinguish between the four copies of the gene. The variation of 10 Y chromosome short tandem repeat (STRs) was used to determine the coalescence age of DAZ haplotypes in a comparable time frame similar to that of SNP haplogroups. An association between DAZ haplotypes and Y chromosome haplogroups was found, and our data show that the DAZ gene is not under selective constraints and its evolution depends only on the mutation rate. The same variants were common to fertile and infertile men, although partial DAZ deletions occurred only in infertile men, suggesting that those should only be used as a tool for infertility diagnosis when analysed in combination with haplogroup determinations.

Estimation of regional richness in marine benthic communities: quantifying the error

Abstract: Species richness is the most widely used measure of biodiversity. It is considered crucial for testing numerous ecological theories. While local species richness is easily determined by sampling, the quantification of regional richness relies on more or less complete species inventories, expert estimation, or mathematical extrapolation from a number of replicated local samplings. However the accuracy of such extrapolations is rarely known. In this study, we compare the common estimators MM (Michaelis-Menten), Chao1, Chao2, ACE (Abundance-based Coverage Estimator), and the first and second order Jackknifes against the asymptote of the species accumulation curve, which we use as an estimate of true regional richness. Subsequently, we quantified the role of sample size, i.e., number of replicates, for precision, accuracy, and bias of the estimation. These replicates were sub-sets of three large data sets of benthic assemblages from the NE Atlantic: (i) soft-bottom sediment communities in the Western Baltic (n = 70); (ii) hard-bottom communities from emergent rock on the Island of Helgoland, North Sea (n = 52), and (iii) hardbottom assemblages grown on artificial substrata in Madeira Island, Portugal (n = 56). For all community types, Jack2 showed a better performance in terms of bias and accuracy while MM exhibited the highest precision. However, in virtually all cases and across all sampling efforts, the estimators underestimated the regional species richness, regardless of habitat type, or selected estimator. Generally, the amount of underestimation decreased with sampling effort. A logarithmic function was applied to quantify the bias caused by low replication using the best estimator, Jack2. The bias was more obvious in the soft-bottom environment, followed by the natural hard-bottom and the artificial hard-bottom habitats, respectively. If a weaker estimator in terms of performance is chosen for this quantification, more replicates are required to obtain a reliable estimation of regional richness.