969 resultados para Quantitative Trait, Heritable
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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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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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 42Â days of age after fasted for 6Â 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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To better understand agronomic and end-use quality in wheat (Triticum aestivum L.) we developed a population containing 154 F6:8 recombinant inbred lines (RILs) from the cross TAM107-R7/Arlin. The parental lines and RILs were phenotyped at six environments in Nebraska and differed for resistance to Wheat soilborne mosaic virus (WSBMV), morphological, agronomic, and end-use quality traits. Additionally, a 2300 cM genome-wide linkage map was created for quantitative trait loci (QTL) analysis. Based on our results across multiple environments, the best RILs could be used for cultivar improvement. The population and marker data are publicly available for interested researchers for future research. The population was used to determine the effect of WSBMV on agronomic and end-use quality and for the mapping of a resistance locus. Results from two infected environments showed that all but two agronomic traits were significantly affected by the disease. Specifically, the disease reduced grain yield by 30% of susceptible RILs and they flowered 5 d later and were 11 cm shorter. End-use quality traits were not negatively affected but flour protein content was increased in susceptible RILs. The resistance locus SbmTmr1 mapped to 27.1 cM near marker wPt-5870 on chromosome 5DL using ELISA data. Finally, we investigated how WSBMV affected QTL detection in the population. QTLs were mapped at two WSBMV infected environments, four uninfected environments, and in the resistant and susceptible RIL subpopulations in the infected environments. Fifty-two significant (LOD≥3) QTLs were mapped in RILs at uninfected environments. Many of the QTLs were pleiotropic or closely linked at 6 chromosomal regions. Forty-seven QTLs were mapped in RILs at WSBMV infected environments. Comparisons between uninfected and infected environments identified 20 common QTLs and 21 environmentally specific QTLs. Finally, 24 QTLs were determined to be affected by WSBMV by comparing the subpopulations in QTL analyses within the same environment. The comparisons were statistically validated using marker by disease interactions. These results showed that QTLs can be affected by WSBMV and careful interpretation of QTL results is needed where biotic stresses are present. Finally, beneficial QTLs not affected by WSBMV or the environment are candidates for marker-assisted selection.
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Sweet sorghum, a botanical variety of sorghum is a potential source of bioenergy because high sugar levels accumulate in its stalks. The objectives of this study were to explore the global diversity of sweet sorghum germplasm, and map the genomic regions that are associated with bioenergy traits. In assessing diversity, 142 sweet sorghum accessions were evaluated with three marker types (SSR, SRAP, and morphological markers) to determine the degree of relatedness among the accessions. The traits measured (anthesis date [AD], plant height [PH], biomass yield [BY], and moisture content [MC]) were all significantly different (P<0.05) among accessions. Morphological marker clustered the accessions into five groups based on PH, MC and AD. The three traits accounted for 92.5% of the variation. There were four and five groups based on SRAP and SSR data respectively classifying accessions mainly on their origin or breeding history. The observed difference between SSR and SRAP based clusters could be attributed to the difference in marker type. SSRs amplify any region of the genome whereas SRAP amplify the open reading frames and promoter regions. Comparing the three marker-type clusters, the markers complimented each other in grouping accessions and would be valuable in assisting breeders to select appropriate lines for crossing. In evaluating QTLs that are associated with bioenergy traits, 165 recombinant inbred lines (RILs) were planted at four environments in Nebraska. A genetic linkage map constructed spanned a length of 1541.3 cM, and generated 18 linkage groups that aligned to the 10 sorghum chromosomes. Fourteen QTLs (6 for brix, 3 for BY, 2 each for AD and MC, and 1 for PH) were mapped. QTLs for the traits that were significantly correlated, colocalized in two clusters on linkage group Sbi01b. Both parents contributed beneficial alleles for most of traits measured, supporting the transgressive segregation in this population. Additional work is needed on exploiting the usefulness of chromosome 1 in breeding sorghum for bioenergy.
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Abstract Background In tropical countries, losses caused by bovine tick Rhipicephalus (Boophilus) microplus infestation have a tremendous economic impact on cattle production systems. Genetic variation between Bos taurus and Bos indicus to tick resistance and molecular biology tools might allow for the identification of molecular markers linked to resistance traits that could be used as an auxiliary tool in selection programs. The objective of this work was to identify QTL associated with tick resistance/susceptibility in a bovine F2 population derived from the Gyr (Bos indicus) × Holstein (Bos taurus) cross. Results Through a whole genome scan with microsatellite markers, we were able to map six genomic regions associated with bovine tick resistance. For most QTL, we have found that depending on the tick evaluation season (dry and rainy) different sets of genes could be involved in the resistance mechanism. We identified dry season specific QTL on BTA 2 and 10, rainy season specific QTL on BTA 5, 11 and 27. We also found a highly significant genome wide QTL for both dry and rainy seasons in the central region of BTA 23. Conclusions The experimental F2 population derived from Gyr × Holstein cross successfully allowed the identification of six highly significant QTL associated with tick resistance in cattle. QTL located on BTA 23 might be related with the bovine histocompatibility complex. Further investigation of these QTL will help to isolate candidate genes involved with tick resistance in cattle.
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In a previous study on maize (Zea mays, L.) several quantitative trait loci (QTL) showing high dominance-additive ratio for agronomic traits were identified in a population of recombinant inbred lines derived from B73 × H99. For four of these mapped QTL, namely 3.05, 4.10, 7.03 and 10.03 according to their chromosome and bin position, families of near-isogenic lines (NILs) were developed, i.e., couples of homozygous lines nearly identical except for the QTL region that is homozygote either for the allele provided by B73 or by H99. For two of these QTL (3.05 and 4.10) the NILs families were produced in two different genetic backgrounds. The present research was conducted in order to: (i) characterize these QTL by estimating additive and dominance effects; (ii) investigate if these effects can be affected by genetic background, inbreeding level and environmental growing conditions (low vs. high plant density). The six NILs’ families were tested across three years and in three Experiments at different inbreeding levels as NILs per se and their reciprocal crosses (Experiment 1), NILs crossed to related inbreds B73 and H99 (Experiment 2) and NILs crossed to four unrelated inbreds (Experiment 3). Experiment 2 was conducted at two plant densities (4.5 and 9.0 plants m-2). Results of Experiments 1 and 2 confirmed previous findings as to QTL effects, with dominance-additive ratio superior to 1 for several traits, especially for grain yield per plant and its component traits; as a tendency, dominance effects were more pronounced in Experiment 1. The QTL effects were also confirmed in Experiment 3. The interactions involving QTL effects, families and plant density were generally negligible, suggesting a certain stability of the QTL. Results emphasize the importance of dominance effects for these QTL, suggesting that they might deserve further studies, using NILs’ families and their crosses as base materials.
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The progress in molecular genetics in animal breeding is moderately effective as compared to traditional animal breeding using quantitative genetic approaches. There is an extensive disparity between the number of reported quantitative trait loci (QTLs) and their linked genetic variations in cattle, pig, and chicken. The identification of causative mutations affecting quantitative traits is still very challenging and hampered by the cloudy relationship between genotype and phenotype. There are relatively few reports in which a successful identification of a causative mutation for an animal production trait was demonstrated. The examples that have attracted considerable attention from the animal breeding community are briefly summarized and presented in a table. In this mini-review, the recent progress in mapping quantitative trait nucleotides (QTNs) are reviewed, including the ABCG2 gene mutation that underlies a QTL for fat and protein content and the ovine MSTN gene mutation that causes muscular hypertrophy in Texel sheep. It is concluded that the progress in molecular genetics might facilitate the elucidation of the genetic architecture of QTLs, so that also the high-hanging fruits can be harvested in order to contribute to efficient and sustainable animal production.
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We report the identification of quantitative trait loci (QTL) affecting carcass composition, carcass length, fat deposition and lean meat content using a genome scan across 462 animals from a combined intercross and backcross between Hampshire and Landrace pigs. Data were analysed using multiple linear regression fitting additive and dominance effects. This model was compared with a model including a parent-of-origin effect to spot evidence of imprinting. Several precisely defined muscle phenotypes were measured in order to dissect body composition in more detail. Three significant QTL were detected in the study at the 1% genome-wide level, and twelve significant QTL were detected at the 5% genome-wide level. These QTL comprise loci affecting fat deposition and lean meat content on SSC1, 4, 9, 10, 13 and 16, a locus on SSC2 affecting the ratio between weight of meat and bone in back and weight of meat and bone in ham and two loci affecting carcass length on SSC12 and 17. The well-defined phenotypes in this study enabled us to detect QTL for sizes of individual muscles and to obtain information of relevance for the description of the complexity underlying other carcass traits.
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The aim of many genetic studies is to locate the genomic regions (called quantitative trait loci, QTLs) that contribute to variation in a quantitative trait (such as body weight). Confidence intervals for the locations of QTLs are particularly important for the design of further experiments to identify the gene or genes responsible for the effect. Likelihood support intervals are the most widely used method to obtain confidence intervals for QTL location, but the non-parametric bootstrap has also been recommended. Through extensive computer simulation, we show that bootstrap confidence intervals are poorly behaved and so should not be used in this context. The profile likelihood (or LOD curve) for QTL location has a tendency to peak at genetic markers, and so the distribution of the maximum likelihood estimate (MLE) of QTL location has the unusual feature of point masses at genetic markers; this contributes to the poor behavior of the bootstrap. Likelihood support intervals and approximate Bayes credible intervals, on the other hand, are shown to behave appropriately.
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The etiology of complex diseases is heterogeneous. The presence of risk alleles in one or more genetic loci affects the function of a variety of intermediate biological pathways, resulting in the overt expression of disease. Hence, there is an increasing focus on identifying the genetic basis of disease by sytematically studying phenotypic traits pertaining to the underlying biological functions. In this paper we focus on identifying genetic loci linked to quantitative phenotypic traits in experimental crosses. Such genetic mapping methods often use a one stage design by genotyping all the markers of interest on the available subjects. A genome scan based on single locus or multi-locus models is used to identify the putative loci. Since the number of quantitative trait loci (QTLs) is very likely to be small relative to the number of markers genotyped, a one-stage selective genotyping approach is commonly used to reduce the genotyping burden, whereby markers are genotyped solely on individuals with extreme trait values. This approach is powerful in the presence of a single quantitative trait locus (QTL) but may result in substantial loss of information in the presence of multiple QTLs. Here we investigate the efficiency of sequential two stage designs to identify QTLs in experimental populations. Our investigations for backcross and F2 crosses suggest that genotyping all the markers on 60% of the subjects in Stage 1 and genotyping the chromosomes significant at 20% level using additional subjects in Stage 2 and testing using all the subjects provides an efficient approach to identify the QTLs and utilizes only 70% of the genotyping burden relative to a one stage design, regardless of the heritability and genotyping density. Complex traits are a consequence of multiple QTLs conferring main effects as well as epistatic interactions. We propose a two-stage analytic approach where a single-locus genome scan is conducted in Stage 1 to identify promising chromosomes, and interactions are examined using the loci on these chromosomes in Stage 2. We examine settings under which the two-stage analytic approach provides sufficient power to detect the putative QTLs.
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The aim of this study was to identify quantitative trait loci (QTL) for osteochondrosis (OC) and palmar/plantar osseous fragments (POF) in fetlock joints in a whole-genome scan of 219 South German Coldblood horses. Symptoms of OC and POF were checked by radiography in 117 South German Coldblood horses at a mean age of 17 months. The radiographic examination comprised the fetlock and hock joints of all limbs. The genome scan included 157 polymorphic microsatellite markers. All microsatellite markers were equally spaced over the 31 autosomes and the X chromosome, with an average distance of 17.7 cM and a mean polymorphism information content (PIC) of 63%. Sixteen chromosomes harbouring putative QTL regions were further investigated by genotyping the animals with 93 additional markers. QTL that had chromosome-wide significance by non-parametric Z-means and LOD scores were found on 10 chromosomes. This included seven QTL for fetlock OC and one QTL on ECA18 associated with hock OC and fetlock OC. Significant QTL for POF in fetlock joints were located on equine chromosomes 1, 4, 8, 12 and 18. This genome scan is an important step towards the identification of genes responsible for OC in horses.
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Arabidopsis thaliana has emerged as a leading model species in plant genetics and functional genomics including research on the genetic causes of heterosis. We applied a triple testcross (TTC) design and a novel biometrical approach to identify and characterize quantitative trait loci (QTL) for heterosis of five biomass-related traits by (i) estimating the number, genomic positions, and genetic effects of heterotic QTL, (ii) characterizing their mode of gene action, and (iii) testing for presence of epistatic effects by a genomewide scan and marker x marker interactions. In total, 234 recombinant inbred lines (RILs) of Arabidopsis hybrid C24 x Col-0 were crossed to both parental lines and their F1 and analyzed with 110 single-nucleotide polymorphism (SNP) markers. QTL analyses were conducted using linear transformations Z1, Z2, and Z3 calculated from the adjusted entry means of TTC progenies. With Z1, we detected 12 QTL displaying augmented additive effects. With Z2, we mapped six QTL for augmented dominance effects. A one-dimensional genome scan with Z3 revealed two genomic regions with significantly negative dominance x additive epistatic effects. Two-way analyses of variance between marker pairs revealed nine digenic epistatic interactions: six reflecting dominance x dominance effects with variable sign and three reflecting additive x additive effects with positive sign. We conclude that heterosis for biomass-related traits in Arabidopsis has a polygenic basis with overdominance and/or epistasis being presumably the main types of gene action.
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Senescence, the decline in survivorship and fertility with increasing age, is a near-universal property of organisms. Senescence and limited lifespan are thought to arise because weak natural selection late in life allows the accumulation of mutations with deleterious late-age effects that are either neutral (the mutation accumulation hypothesis) or beneficial (the antagonistic pleiotropy hypothesis) early in life. Analyses of Drosophila spontaneous mutations, patterns of segregating variation and covariation, and lines selected for late-age fertility have implicated both classes of mutation in the evolution of aging, but neither their relative contributions nor the properties of individual loci that cause aging in nature are known. To begin to dissect the multiple genetic causes of quantitative variation in lifespan, we have conducted a genome-wide screen for quantitative trait loci (QTLs) affecting lifespan that segregate among a panel of recombinant inbred lines using a dense molecular marker map. Five autosomal QTLs were mapped by composite interval mapping and by sequential multiple marker analysis. The QTLs had large sex-specific effects on lifespan and age-specific effects on survivorship and mortality and mapped to the same regions as candidate genes with fertility, cellular aging, stress resistance and male-specific effects. Late age-of-onset QTL effects are consistent with the mutation accumulation hypothesis for the evolution of senescence, and sex-specific QTL effects suggest a novel mechanism for maintaining genetic variation for lifespan.
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A high-resolution physical and genetic map of a major fruit weight quantitative trait locus (QTL), fw2.2, has been constructed for a region of tomato chromosome 2. Using an F2 nearly isogenic line mapping population (3472 individuals) derived from Lycopersicon esculentum (domesticated tomato) × Lycopersicon pennellii (wild tomato), fw2.2 has been placed near TG91 and TG167, which have an interval distance of 0.13 ± 0.03 centimorgan. The physical distance between TG91 and TG167 was estimated to be ≤ 150 kb by pulsed-field gel electrophoresis of tomato DNA. A physical contig composed of six yeast artificial chromosomes (YACs) and encompassing fw2.2 was isolated. No rearrangements or chimerisms were detected within the YAC contig based on restriction fragment length polymorphism analysis using YAC-end sequences and anchored molecular markers from the high-resolution map. Based on genetic recombination events, fw2.2 could be narrowed down to a region less than 150 kb between molecular markers TG91 and HSF24 and included within two YACs: YAC264 (210 kb) and YAC355 (300 kb). This marks the first time, to our knowledge, that a QTL has been mapped with such precision and delimited to a segment of cloned DNA. The fact that the phenotypic effect of the fw2.2 QTL can be mapped to a small interval suggests that the action of this QTL is likely due to a single gene. The development of the high-resolution genetic map, in combination with the physical YAC contig, suggests that the gene responsible for this QTL and other QTLs in plants can be isolated using a positional cloning strategy. The cloning of fw2.2 will likely lead to a better understanding of the molecular biology of fruit development and to the genetic engineering of fruit size characteristics.