66 resultados para quantitative trait locus mapping

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


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Differences in domestication and selection processes have contributed to considerable phenotypic and genotypic differences between Bos taurus and Bos indicus cattle breeds. of particular interest in tropical and subtropical production environments are those genetic differences between subspecies that underlie the phenotypic extremes in tolerance and susceptibility to parasite infection. In general, B. taurus cattle are more susceptible to ectoparasites than B. indicus cattle in tropical environments, and much of this difference is under genetic control. To identify genomic regions involved in tick resistance, we developed a B. taurus x B. indicus F-2 experimental population to map quantitative trait loci (QTL) for resistance to the Riphicephalus (Boophilus) microplus tick. About 300 individuals were measured for parasite load in two seasons (rainy and dry) and genotyped for 23 microsatellite markers covering chromosomes 5, 7 and 14. We mapped a suggestive chromosome-wide QTL for tick load in the rainy season (P < 0.05) on chromosome 5. For the dry season, suggestive (P < 0.10) chromosome-wide QTL were mapped on chromosomes 7 and 14. The additive effect of the QTL on chromosome 14 corresponds to 3.18% of the total observed phenotypic variance. Our QTL-mapping study has identified different genomic regions controlling tick resistance; these QTL were dependent upon the season in which the ticks were counted, suggesting that the QTL in question may depend on environmental factors.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Rapid growth in broilers is associated with susceptibility to metabolic disorders such as pulmonary hypertension syndrome (ascites) and sudden death. This study describes a genome search for QTL associated with relative weight of cardio respiratory and metabolically important organs (heart, lungs, liver and gizzard), and hematocrit value in a Brazilian broiler-layer cross. QTL with similar or different effects across sexes were investigated. At 42 days of age after fasted for 6 h, the F2 chickens were weighed and slaughtered. Weights and percentages of the weight relative to BW42 of gizzard, heart, lungs, liver and hematocrit were used in the QTL search. Parental, F1 and F2 individuals were genotyped with 128 genetic markers (127 microsatellites and 1 SNP) covering 22 linkage groups. QTL mapping analyses were carried out using mixed models. A total of 11 genome-wide significant QTL and five suggestive linkages were mapped. Thus, genome-wide significant QTL with similar effects across sexes were mapped to GGA2, 4 and 14 for heart weight, and to GGA2, 8 and 12 for gizzard %. Additionally, five genome-wide significant QTL with different effects across sexes were mapped to GGA 8, 19 and 26 for heart weight; GGA26 for heart % and GGA3 for hematocrit value. Five QTL were detected in chromosomal regions where QTL for similar traits were previously mapped in other F2 chicken populations. Seven novel genome-wide significant QTL are reported here, and 21 positional candidate genes in QTL regions were identified.

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A genome-wide scan for quantitative trait loci (QTL) affecting gastrointestinal nematode resistance in sheep was completed using a double backcross population derived from Red Maasai and Dorper ewes bred to F1 rams. This design provided an opportunity to map potentially unique genetic variation associated with a parasite-tolerant breed like Red Maasai, a breed developed to survive East African grazing conditions. Parasite indicator phenotypes (blood packed cell volume PCV and faecal egg count FEC) were collected on a weekly basis from 1064 lambs during a single 3-month post-weaning grazing challenge on infected pastures. The averages of last measurements for FEC (AVFEC) and PCV (AVPCV), along with decline in PCV from challenge start to end (PCVD), were used to select lambs (N = 371) for genotyping that represented the tails (10% threshold) of the phenotypic distributions. Marker genotypes for 172 microsatellite loci covering 25 of 26 autosomes (1560.7 cm) were scored and corrected by Genoprob prior to qxpak analysis that included BoxCox transformed AVFEC and arcsine transformed PCV statistics. Significant QTL for AVFEC and AVPCV were detected on four chromosomes, and this included a novel AVFEC QTL on chromosome 6 that would have remained undetected without BoxCox transformation methods. The most significant P-values for AVFEC, AVPCV and PCVD overlapped the same marker interval on chromosome 22, suggesting the potential for a single causative mutation, which remains unknown. In all cases, the favourable QTL allele was always contributed from Red Maasai, providing support for the idea that future marker-assisted selection for genetic improvement of production in East Africa will rely on markers in linkage disequilibrium with these QTL.

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The advent of molecular markers has created opportunities for a better understanding of quantitative inheritance and for developing novel strategies for genetic improvement of agricultural species, using information on quantitative trait loci (QTL). A QTL analysis relies on accurate genetic marker maps. At present, most statistical methods used for map construction ignore the fact that molecular data may be read with error. Often, however, there is ambiguity about some marker genotypes. A Bayesian MCMC approach for inferences about a genetic marker map when random miscoding of genotypes occurs is presented, and simulated and real data sets are analyzed. The results suggest that unless there is strong reason to believe that genotypes are ascertained without error, the proposed approach provides more reliable inference on the genetic map.

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Descriptive herd variables (DVHE) were used to explain genotype by environment interactions (G x E) for milk yield (MY) in Brazilian and Colombian production environments and to develop a herd-cluster model to estimate covariance components and genetic parameters for each herd environment group. Data consisted of 180,522 lactation records of 94,558 Holstein cows from 937 Brazilian and 400 Colombian herds. Herds in both countries were jointly grouped in thirds according to 8 DVHE: production level, phenotypic variability, age at first calving, calving interval, percentage of imported semen, lactation length, and herd size. For each DVHE, REML bivariate animal model analyses were used to estimate genetic correlations for MY between upper and lower thirds of the data. Based on estimates of genetic correlations, weights were assigned to each DVHE to group herds in a cluster analysis using the FASTCLUS procedure in SAS. Three clusters were defined, and genetic and residual variance components were heterogeneous among herd clusters. Estimates of heritability in clusters 1 and 3 were 0.28 and 0.29, respectively, but the estimate was larger (0.39) in Cluster 2. The genetic correlations of MY from different clusters ranged from 0.89 to 0.97. The herd-cluster model based on DVHE properly takes into account G x E by grouping similar environments accordingly and seems to be an alternative to simply considering country borders to distinguish between environments.

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Background: Birth weight (BW) is an economically important trait in beef cattle, and is associated with growth- and stature-related traits and calving difficulty. One region of the cattle genome, located on Bos primigenius taurus chromosome 14 (BTA14), has been previously shown to be associated with stature by multiple independent studies, and contains orthologous genes affecting human height. A genome-wide association study (GWAS) for BW in Brazilian Nellore cattle (Bos primigenius indicus) was performed using estimated breeding values (EBVs) of 654 progeny-tested bulls genotyped for over 777,000 single nucleotide polymorphisms (SNPs).Results: The most significant SNP (rs133012258, PGC = 1.34 × 10-9), located at BTA14:25376827, explained 4.62% of the variance in BW EBVs. The surrounding 1 Mb region presented high identity with human, pig and mouse autosomes 8, 4 and 4, respectively, and contains the orthologous height genes PLAG1, CHCHD7, MOS, RPS20, LYN, RDHE2 (SDR16C5) and PENK. The region also overlapped 28 quantitative trait loci (QTLs) previously reported in literature by linkage mapping studies in cattle, including QTLs for birth weight, mature height, carcass weight, stature, pre-weaning average daily gain, calving ease, and gestation length.Conclusions: This study presents the first GWAS applying a high-density SNP panel to identify putative chromosome regions affecting birth weight in Nellore cattle. These results suggest that the QTLs on BTA14 associated with body size in taurine cattle (Bos primigenius taurus) also affect birth weight and size in zebu cattle (Bos primigenius indicus). © 2013 Utsunomiya et al.; licensee BioMed Central Ltd.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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In the past, the focus of broiler breeding programs on yield and carcass traits improvement led to problems related to meat quality. Awareness of public concern for quality resulted in inclusion of meat quality traits in the evaluation process. Nevertheless, few genes associated with meat quality attributes are known. Previous studies mapped quantitative trait loci for weight at 35 and 42 days in a region of GGA4 flanked by the microsatellite markers, MCW0240 and LEI0063. In this region, there are 2 fibroblast growth factor binding protein (FGFBP) genes that play an important role in embryogenesis, cellulardifferentiation, and proliferation in chickens. The objective of this study was to identify and associate single nucleotide polymorphisms (SNPs) in FGFBP1 and FGFBP2 with performance, carcass, and meat quality in experimental and commercial chicken populations. In the commercial population, SNP g.2014G>A in FGFBP1 was associated with decreased carcass weight (P < 0.05), and SNP g.651G>A in FGFBP2 was associated with thawing loss and meat redness content (P < 0.05). Four haplotypes were constructed based on 2 SNPs and were associated with breast weight, thawing loss, and meat redness content. The diplotypes were associated with thawing loss, lightness, and redness content. The SNPs evaluated in the present study may be used as markers in poultry breeding programs to aid in improving growth and meat quality traits. © FUNPEC-RP.

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Two functional and positional candidate genes were selected in a region of chicken chromosome 1 (GGA1), based on their biological roles, and also where several quantitative trait loci (QTL) have been mapped and associated with performance, fatness and carcass traits in chickens. The insulin-like growth factor 1 (IGF1) gene has been associated with several physiological functions related to growth. The lysine (K)-specific demethylase 5A (KDM5A) gene participates in the epigenetic regulation of genes involved with the cell cycle. Our objective was to find associations of selected single-nucleotide polymorphisms (SNPs) in these genes with performance, fatness and carcass traits in 165 F2 chickens from a resource population. In the IGF1 gene, 17 SNPs were detected, and in the KDM5A gene, nine SNPs were detected. IGF1 SNP c. 47673G > A was associated with body weight and haematocrit percentage, and also with feed intake and percentages of abdominal fat and gizzard genotype × sex interactions. KDM5A SNP c. 34208C > T genotype × sex interaction affected body weight, feed intake, percentages of abdominal fat (p = 0. 0001), carcass, gizzard and haematocrit. A strong association of the diplotype × sex interaction (p < 0. 0001) with abdominal fat was observed, and also associations with body weight, feed intake, percentages of carcass, drums and thighs, gizzard and haematocrit. Our findings suggest that the KDM5A gene might play an important role in the abdominal fat deposition in chickens. The IGF1 and KDM5A genes are strong candidates to explain the QTL mapped in this region of GGA1. © 2012 Institute of Plant Genetics, Polish Academy of Sciences, Poznan.