Long and short range multi-locus QTL interactions in a complex trait of yeast

We analyse interactions of Quantitative Trait Loci (QTL) in heat selected yeast by comparing them to an unselected pool of random individuals. Here we re-examine data on individual F12 progeny selected for heat tolerance, which have been genotyped at 25 locations identified by sequencing a selected pool [Parts, L., Cubillos, F. A., Warringer, J., Jain, K., Salinas, F., Bumpstead, S. J., Molin, M., Zia, A., Simpson, J. T., Quail, M. A., Moses, A., Louis, E. J., Durbin, R., and Liti, G. (2011). Genome research, 21(7), 1131-1138]. 960 individuals were genotyped at these locations and multi-locus genotype frequencies were compared to 172 sequenced individuals from the original unselected pool (a control group). Various non-random associations were found across the genome, both within chromosomes and between chromosomes. Some of the non-random associations are likely due to retention of linkage disequilibrium in the F12 population, however many, including the inter-chromosomal interactions, must be due to genetic interactions in heat tolerance. One region of particular interest involves 3 linked loci on chromosome IV where the central variant responsible for heat tolerance is antagonistic, coming from the heat sensitive parent and the flanking ones are from the more heat tolerant parent. The 3-locus haplotypes in the selected individuals represent a highly biased sample of the population haplotypes with rare double recombinants in high frequency. These were missed in the original analysis and would never be seen without the multigenerational approach. We show that a statistical analysis of entropy and information gain in genotypes of a selected population can reveal further interactions than previously seen. Importantly this must be done in comparison to the unselected population's genotypes to account for inherent biases in the original population

The Correspondence of Fr Matthew Gaughren OMI (1888-1890)

Em meados de 1888, o padre Matthew Gaughren (1843-1914) foi enviado à Argentina por seu superior, o O.M.I. provincial da Grã-Bretanha, a uma “expedição de mendicância”, que visava arrecadar dinheiro entre os colonos irlandeses para diminuir a dívida da igreja de Nossa Senhora da Graça em Tower Hill. No entanto, Gaughren mudou as prioridades de sua missão na América do Sul e apelou à comunidade de língua inglesa para apoiar os imigrantes irlandeses vindos de Cork, em fevereiro de 1889, no navio a vapor Dresden, e enviados a uma malfadada colônia irlandesa em Napostá, próxima ao porto de Bahía Blanca. Seu pensamento e sua luta são revelados nas cartas a seguir, coletadas de diversos arquivos, que agora estão sendo publicadas, a maioria delas pela primeira vez, em sua forma completa.In mid-1888, Fr Matthew Gaughren (1843-1914) was sent to Argentina by his superior, the O.M.I. provincial in Great Britain, on a “begging expedition”, which aimed at collecting money among the Irish settlers to lessen the debt upon the church of Our Lady of Grace at Tower Hill. However, Gaughren changed the priorities of his mission in South America and appealed to the English-speaking community to support the Irish immigrants who arrived in Buenos Aires in February 1889 on the Dresden steamer ship from Cork and were sent to an ill-fated Irish Colony in Napostá, near the port of Bahía Blanca. His thinking and his struggle are revealed in the following letters, collected from various archival sources, which are now being published, most of them for the first time, in their complete form

Discrimination of Individual Tigers (\u3cem\u3ePanthera tigris\u3c/em\u3e) from Long Distance Roars

This paper investigates the extent of tiger (Panthera tigris) vocal individuality through both qualitative and quantitative approaches using long distance roars from six individual tigers at Omaha\u27s Henry Doorly Zoo in Omaha, NE. The framework for comparison across individuals includes statistical and discriminant function analysis across whole vocalization measures and statistical pattern classification using a hidden Markov model (HMM) with frame-based spectral features comprised of Greenwood frequency cepstral coefficients. Individual discrimination accuracy is evaluated as a function of spectral model complexity, represented by the number of mixtures in the underlying Gaussian mixture model (GMM), and temporal model complexity, represented by the number of sequential states in the HMM. Results indicate that the temporal pattern of the vocalization is the most significant factor in accurate discrimination. Overall baseline discrimination accuracy for this data set is about 70% using high level features without complex spectral or temporal models. Accuracy increases to about 80% when more complex spectral models (multiple mixture GMMs) are incorporated, and increases to a final accuracy of 90% when more detailed temporal models (10-state HMMs) are used. Classification accuracy is stable across a relatively wide range of configurations in terms of spectral and temporal model resolution