564 research outputs found

    Additions to a revision of the shark genus Carcharhinus: Synonymy of Aprionodon and Hypoprion, and description of a new species of Carcharhinus (Carcharhinidae)

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    Features of the valid nominal species of Aprionodon Gill (isodon Valenciennes) and Hypoprion Muller and Henle (hemiodon Valenciennes, macloti Muller and Henle, and signatus Poey), plus those of a previously unrecognized species here described as Carcharhinus leiodon n.sp., are examined and compared with those of Carcharhinus Blainville. Features studied include morphometrics, vertebral numbers and other vertebral characteristics, tooth numbers, color pattern, and some other aspects of external morphology. It is concluded that on these features C. leiodon n.sp. is entirely encompassed within the parameters of Carcharhinus, and that, although A. isodon, H. hemiodon, H. macloti, and H. signatus each extend the range of diversity of Carcharhinus in one or more features, A. isodon is not uniquely different from Carcharhinus, and there is no common pattern of difference between the three species of Hypoprion and Carcharhinus. Accordingly, and because the nature of the teeth of Aprionodon and Hypoprion has been found insufficient to warrant generic distinction from Carcharhinus, the genera Aprionodon and Hypoprion are synonymised with Carcharhinus. A diagnosis and description are given for each of the above species. The descriptions include measurements, counts, and line illustrations that show the whole shark in lateral view, underside of head, nostril, and teeth. The geographic distribution is summarized, as are also the meager biological data available on number of embryos, size at birth, size at sexual maturity, and maximum size. (PDF file contains 32 pages.

    Isolated Gust Generation for the Investigation of Airfoil-Gust Interaction

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    As part of an effort to examine the impact of vortical gusts on airfoils, a simple gust generator has been built and investigated. This consists of a heaving at plate capable of following a specifed transverse trajectory across a water tunnel. The relationship between the trajectory and the properties of the gusts that are shed downstream is characterized for non-periodic heaving motion described by Eldredge's smooth motion equation. PIV experiments show that the circulation of the vortical gust is proportional to the heaving speed of the plate. Tests with a downstream NACA 0018 airfoil demonstrate repeatable forces in response to the produced gusts

    The accuracies of DNA-based estimates of genetic merit derived from Angus or multibreed beef cattle training populations

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    Several organizations have developed prediction models for molecular breeding values (MBV) for quantitative growth and carcass traits in beef cattle using Bovine SNP50 genotypes and phenotypic or EBV data. Molecular breeding values for Angus cattle have been developed by IGENITY, Pfi zer Animal Genetics, and a collaboration between researchers from Iowa State University and the University of Missouri-Columbia (ISU/UMC). The U.S. Meat Animal Research Center (USMARC; Clay Center, NE) has also developed MBV for 16 cattle breeds using 2 multibreed populations, the Germplasm Evaluation (GPE) Program and the 2,000 Bull Project (2KALL), and 2 single breed subpopulations of the 2,000 Bull Project, Angus (2KAN) and Hereford (2KHH). In this study, these MBV were assessed relative to commercial ranch EBV estimated from the progeny phenotypes of Angus bulls naturally mated in multisire breeding pastures to commercial cows: 121 for USMARC MBV, 99 for ISU/UMC MBV, and 29 for IGENITY and Pfizer MBV (selected based on number of progeny carcass records). Five traits were analyzed: weaning weight (WW), HCW, marbling score (MS), rib-eye muscle area (RE), and, for IGENITY and Pfi zer only, feedlot ADG. The average accuracies of MBV across traits were 0.38 ± 0.05 for IGENITY, 0.61 ± 0.12 for Pfizer, 0.46 ± 0.12 for ISU/UMC, 0.16 ± 0.04 for GPE, 0.26 ± 0.05 for 2KALL, 0.24 ± 0.04 for 2KAN, and 0.02 ± 0.12 for 2KHH. Angus-based MBV (IGENITY, Pfizer, ISU/UMC, and 2KAN) explained larger proportions of genetic variance in this population than GPE, 2KALL, or 2KHH MBV for the same traits. In this data set, IGENITY, Pfizer, and ISU/UMC MBV were predictive of realized performance of progeny, and incorporation of that information into national genetic evaluations would be expected to improve EPD accuracy, particularly for young animals

    Accuracy of Genomic Selection Methods in a Standard Data Set of Loblolly Pine (Pinus taeda L.)

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    Genomic selection can increase genetic gain per generation through early selection. Genomic selection is expected to be particularly valuable for traits that are costly to phenotype and expressed late in the life cycle of long-lived species. Alternative approaches to genomic selection prediction models may perform differently for traits with distinct genetic properties. Here the performance of four different original methods of genomic selection that differ with respect to assumptions regarding distribution of marker effects, including (i) ridge regression–best linear unbiased prediction (RR–BLUP), (ii) Bayes A, (iii) Bayes Cπ, and (iv) Bayesian LASSO are presented. In addition, a modified RR–BLUP (RR–BLUP B) that utilizes a selected subset of markers was evaluated. The accuracy of these methods was compared across 17 traits with distinct heritabilities and genetic architectures, including growth, development, and disease-resistance properties, measured in a Pinus taeda (loblolly pine) training population of 951 individuals genotyped with 4853 SNPs. The predictive ability of the methods was evaluated using a 10-fold, cross-validation approach, and differed only marginally for most method/trait combinations. Interestingly, for fusiform rust disease-resistance traits, Bayes Cπ, Bayes A, and RR–BLUB B had higher predictive ability than RR–BLUP and Bayesian LASSO. Fusiform rust is controlled by few genes of large effect. A limitation of RR–BLUP is the assumption of equal contribution of all markers to the observed variation. However, RR-BLUP B performed equally well as the Bayesian approaches.The genotypic and phenotypic data used in this study are publically available for comparative analysis of genomic selection prediction models

    Detection of potential genetic variants affecting gene function in Guzerat cattle.

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    Guzerat is a dual-purpose breed recognized for important traits to its adaptation to adverse tropical environments such as resistance to parasites, heat tolerance and ability to intake forage with low nutritional value. Once genetic variation responsible for this traits has so far not been well characterized, the aim of this study was to identity single nucleotide variants (SNVs) and insertion/deletions (Indels) in Guzerat cattle breed from whole genome re-sequencing in order to characterize loss-of-function variants which could be associated with complex traits in this cattle breed.X-meeting 2016

    Comparison of variant calling methods for whole genome sequencing data in dairy cattle

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    Accurate identification of SNPs from next-generation sequencing data is crucial for high-quality downstream analysis. Whole genome sequence data of 65 key ancestors of genotyped Swiss dairy populations were available for investigation (24 billion reads, 96.8% mapped to UMD31, 12x coverage). Four publically available variant calling programmes were assessed and different levels of pre-calling handling for each method were tested and compared. SNP concordance was examined with Illumina’s BovineHD Genotyping BeadChip®. Depending on variant calling software used, between 16,894,054 and 22,048,382 SNP were identified (multi-sample calling). A total of 14,644,310 SNP were identified by all four variant callers (multi-sample calling). InDel counts ranged from 1,997,791 to 2,857,754; 1,708,649 InDels were identified by all four variant callers. A minimum of pre-calling data handling resulted in the highest non-reference sensitivity and the lowest non-reference discrepancy rates

    Integration of GWAS, CNV and sele ction signature reveals candidate genes for abdominal fat regulation in chickens.

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    Abstract: Carcass fat content is an economically important trait in commercial chickens. The use of genome-wide high density SNPs may improve the power and resolution to identify QTLs, putative candidate genes and copy number variations (CNVs), for selection programs. The main goal of this study was to identify genomic windows and putative candidate genes for carcass fat content. We checked the overlap of QTL with regions demonstrating signatures of selection and inherited CNVs identified in the same population. A total of 497 42 day-old chickens from the EMBRAPA F2 Chicken Resource Population developed for QTL studies were genotyped with the 600K SNP genotyping array (Affymetrix®), and phenotyped for carcass fat content weight (CFCW) and carcass fat content on a dry matter basis (CFCDM). After quality control, a total of 480 samples and 371,557 SNPs annotated in autosomal chromosomes (GGA1-28) based on Gallus_gallus-5.0 (NCBI) were kept for further analysis. GWAS analyses were performed with GenSel software using BayesB method (π=0.9988) to identify genomic windows associated with CFCW or CFC%. We identified 15 genomic windows associated with CFC% on GGA1, 7, 15, 20 and 28, and from those, we identified two adjacent windows on GGA7 considered as the same QTL explaining 1.31 and 2.18% of the genetic variance for CFCW and CFC%, respectively. This QTL overlapped with one regions previsiouly know to regulate abdominal fat in chickens and the QTL region encompassed two putative candidate genes overlapping with signatures of selection and inherited CNVs. Our findings are helpful to better understand the genetic regulation of fatness in chickens. Resumo: O teor de gordura na carcaça Ă© uma caracterĂ­stica economicamente importante em frangos comerciais. O uso de SNPs de alta densidade em todo o genoma pode melhorar o poder e a resolução para identificar QTLs, genes candidatos putativos e variações no nĂşmero de cĂłpias (CNVs), para programas de seleção. O principal objetivo deste estudo foi identificar janelas genĂ´micas e possĂ­veis genes candidatos para o conteĂşdo de gordura na carcaça. Verificamos a sobreposição de QTL com regiões demonstrando assinaturas de seleção e CNVs herdadas identificadas na mesma população. Um total de 497 galinhas com 42 dias de idade da EMBRAPA F2 Chicken Resource Population desenvolvidas para estudos QTL foram genotipadas com o arranjo de genĂłtipos SNP 600K (Affymetrix®) e fenotipadas para peso de gordura na carcaça (CFCW) e teor de gordura na carcaça seca. matĂ©ria básica (CFCDM). ApĂłs o controle de qualidade, um total de 480 amostras e 371.557 SNPs anotados em cromossomos autossĂ´micos (GGA1-28) baseados em Gallus_gallus-5.0 (NCBI) foram mantidos para análise posterior. As análises de GWAS foram realizadas com o software GenSel usando o mĂ©todo de BayesB (π = 0,9988) para identificar janelas genĂ´micas associadas ao CFCW ou CFC%. Foram identificadas 15 janelas genĂ´micas associadas a% CFC em GGA1, 7, 15, 20 e 28 e, a partir delas, identificamos duas janelas adjacentes em GGA7 consideradas como os mesmos QTLs explicando 1,31 e 2,18% da variância genĂ©tica para CFCW e CFC% , respectivamente. Este QTL se sobrepunha a uma das regiões previsamente conhecidas para regular a gordura abdominal em frangos e a regiĂŁo QTL englobava dois supostos genes candidatos que se sobrepunham com assinaturas de seleção e CNVs herdadas. Nossas descobertas sĂŁo Ăşteis para entender melhor a regulação genĂ©tica da gordura em frangos

    Results of survey of stakeholders regarding knowledge of and attitudes towards feed intake, efficiency and genetic improvement concepts

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    Individual animal feed efficiency plays a key role in the profitability and sustainability of the US beef industry. During the growing and finishing phase of production, a 10% improvement in feed efficiency has a two-fold greater impact on profit than a 10% increase in rate of gain (Fox et al., 2001). The traits that beef producers routinely record are outputs which determine the value of product sold and not the inputs defining the cost of beef production. The inability to routinely measure feed intake and feed efficiency on large numbers of cattle has precluded the efficient application of selection despite moderate heritabilities (h2 = 0.16-0.46; Archer et al., 1999). Feed costs in calf feeding and yearling finishing systems account for approximately 66% and 77% of costs, respectively (Anderson et al., 2005).Feed costs account for approximately 65% of total beef production costs. Of the metabolizable energy required from conception to consumption of a beef animal, 72% is utilized during the cow-calf segment of production while 28% of calories are utilized in the calf growing and finishing phases of production (Ferrell and Jenkins, 1982). Of the calories consumed in the cow-calf segment, more than half are used for maintenance which presents a large selection target
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