854 research outputs found
Introduction: Indigenous Creolization, Amerindian Hybridity and the Invention of Authenticity
From Silence to a Whisper to Active Participation: Using Literature Circles with ELL Students
This article discusses benefits of using literature circles with ELL students to strengthen literacy skills and student confidence. Highlighting one teacher\u27s implementation of literature circles, the authors present a candid examination of areas of initial weakness and describe strategies used for improvements in subsequent rounds. A discussion of specific student growth in oral communication, attitude toward reading and improved reading comprehension is included as well as lists of resources and strategies supporting effective literature circles
Genotype imputation accuracy in a F2 pig population using high density and low density SNP panels
Background: F2 resource populations have been used extensively to map QTL segregating between pig breeds. A limitation associated with the use of these resource populations for fine mapping of QTL is the reduced number of founding individuals and recombinations of founding haplotypes occurring in the population. These limitations, however, become advantageous when attempting to impute unobserved genotypes using within family segregation information. A trade-off would be to re-type F2 populations using high density SNP panels for founding individuals and low density panels (tagSNP) in F2 individuals followed by imputation. Subsequently a combined meta-analysis of several populations would provide adequate power and resolution for QTL mapping, and could be achieved at relatively low cost. Such a strategy allows the wealth of phenotypic information that has previously been obtained on experimental resource populations to be further mined for QTL identification. In this study we used experimental and simulated high density genotypes (HD-60K) from an F2 cross to estimate imputation accuracy under several genotyping scenarios. Results: Selection of tagSNP using physical distance or linkage disequilibrium information produced similar imputation accuracies. In particular, tagSNP sets averaging 1 SNP every 2.1 Mb (1,200 SNP genome-wide) yielded imputation accuracies (IA) close to 0.97. If instead of using custom panels, the commercially available 9K chip is used in the F2, IA reaches 0.99. In order to attain such high imputation accuracy the F0 and F1 generations should be genotyped at high density. Alternatively, when only the F0 is genotyped at HD, while F1 and F2 are genotyped with a 9K panel, IA drops to 0.90. Conclusions: Combining 60K and 9K panels with imputation in F2 populations is an appealing strategy to re-genotype existing populations at a fraction of the cost.Fil: Gualdron Duarte, Jose Luis. Michigan State University; Estados Unidos. Universidad de Buenos Aires. Facultad de Agronomia. Departamento de Producción Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Bates, Ronald O.. Michigan State University; Estados UnidosFil: Ernst, Catherine W.. Michigan State University; Estados UnidosFil: Raney, Nancy E.. Michigan State University; Estados UnidosFil: Cantet, Rodolfo Juan Carlos. Universidad de Buenos Aires. Facultad de Agronomia. Departamento de Producción Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Steibel, Juan P.. Michigan State University; Estados Unido
Rapid Communication: Myogenin (MYOG) Physically Maps to Porcine Chromosome 9q2.1-q2.6
Species and Locus. Pig Myogenin (MYOG). Source and Description of Primers. Oligonucleotide primers designed from pig cDNA sequence (GenBank accession no. U14331) were used to amplify a 1,644-bp fragment of the porcine MYOG gene. Primer Sequences. Forward primer: 5¢-TCT ATG ACG GGG AAA ACT AC-3¢; reverse primer: 5¢-TGG AGC CAG AGT GGT GTA TC-3¢
Estimation of linkage disequilibrium in four US pig breeds
<p>Abstract</p> <p>Background</p> <p>The success of marker assisted selection depends on the amount of linkage disequilibrium (LD) across the genome. To implement marker assisted selection in the swine breeding industry, information about extent and degree of LD is essential. The objective of this study is to estimate LD in four US breeds of pigs (Duroc, Hampshire, Landrace, and Yorkshire) and subsequently calculate persistence of phase among them using a 60 k SNP panel. In addition, we report LD when using only a fraction of the available markers, to estimate persistence of LD over distance.</p> <p>Results</p> <p>Average <it>r<sup>2 </sup></it>between adjacent SNP across all chromosomes was 0.36 for Landrace, 0.39 for Yorkshire, 0.44 for Hampshire and 0.46 for Duroc. For markers 1 Mb apart, <it>r<sup>2 </sup></it>ranged from 0.15 for Landrace to 0.20 for Hampshire. Reducing the marker panel to 10% of its original density, average <it>r<sup>2 </sup></it>ranged between 0.20 for Landrace to 0.25 for Duroc. We also estimated persistence of phase as a measure of prediction reliability of markers in one breed by those in another and found that markers less than 10 kb apart could be predicted with a maximal accuracy of 0.92 for Landrace with Yorkshire.</p> <p>Conclusions</p> <p>Our estimates of LD, although in good agreement with previous reports, are more comprehensive and based on a larger panel of markers. Our estimates also confirmed earlier findings reporting higher LD in pigs than in American Holstein cattle, especially at increasing marker distances (> 1 Mb). High average LD (<it>r<sup>2 </sup></it>> 0.4) between adjacent SNP found in this study is an important precursor for the implementation of marker assisted selection within a livestock species.</p> <p>Results of this study are relevant to the US purebred pig industry and critical for the design of programs of whole genome marker assisted evaluation and selection. In addition, results indicate that a more cost efficient implementation of marker assisted selection using low density panels with genotype imputation, would be feasible for these breeds.</p
Anchoring of a dye precursor on NiO(001) studied by non-contact atomic force microscopy
The properties of metal oxides, such as charge transport mechanisms or optoelectronic characteristics, can be modified by functionalization with organic molecules. This kind of organic/inorganic surface is nowadays highly regarded, in particular, for the design of hybrid devices such as dye sensitized solar cells. However, a key parameter for optimized interfaces is not only the choice of the compounds but also the properties of adsorption. Here, we investigated the deposition of an organic dye precursor molecule on a NiO(001) single crystal surface by means of non-contact atomic force microscopy at room temperature. Depending on the coverage, single molecules, groups of adsorbates with random or recognizable shapes, or islands of closely packed molecules were identified. Single molecules and self assemblies are resolved with sub-molecular resolution showing that they are lying flat on the surface in a trans-conformation. Within the limits of our Kelvin probe microscopy setup a charge transfer from NiO to the molecular layer of 0.3 electrons per molecules was observed only in the areas, where the molecules are closed packed
Application of alternative models to identify QTL for growth traits in an F2 Duroc x Pietrain pig resource population
<p>Abstract</p> <p>Background</p> <p>A variety of analysis approaches have been applied to detect quantitative trait loci (QTL) in experimental populations. The initial genome scan of our Duroc x Pietrain F<sub>2 </sub>resource population included 510 F<sub>2 </sub>animals genotyped with 124 microsatellite markers and analyzed using a line-cross model. For the second scan, 20 additional markers on 9 chromosomes were genotyped for 954 F<sub>2 </sub>animals and 20 markers used in the first scan were genotyped for 444 additional F<sub>2 </sub>animals. Three least-squares Mendelian models for QTL analysis were applied for the second scan: a line-cross model, a half-sib model, and a combined line-cross and half-sib model.</p> <p>Results</p> <p>In total, 26 QTL using the line-cross model, 12 QTL using the half-sib model and 3 additional QTL using the combined line-cross and half-sib model were detected for growth traits with a 5% false discovery rate (FDR) significance level. In the line-cross analysis, highly significant QTL for fat deposition at 10-, 13-, 16-, 19-, and 22-wk of age were detected on SSC6. In the half-sib analysis, a QTL for loin muscle area at 19-wk of age was detected on SSC7 and QTL for 10th-rib backfat at 19- and 22-wk of age were detected on SSC15.</p> <p>Conclusions</p> <p>Additional markers and animals contributed to reduce the confidence intervals and increase the test statistics for QTL detection. Different models allowed detection of new QTL which indicated differing frequencies for alternative alleles in parental breeds.</p
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