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1.
The genetic architecture of organ weights is not well understood. In this study, we fine‐mapped quantitative trait loci (QTLs) affecting organ weights by characterizing six intersubspecific subcongenic mouse strains with overlapping and non‐overlapping genomic regions on chromosome 2 derived from wild Mus musculus castaneus. QTLs for heart, lung, spleen and kidney weights were revealed on a 6.38‐Mb genomic region between two microsatellite markers, D2Mit323 and D2Mit472. Effects of the castaneus alleles at the organ weight QTLs were all opposite in direction to a body weight QTL previously mapped to the same genomic region. In addition, new QTLs for lung and kidney weights were revealed on a different 3.57‐Mb region between D2Mit205 and D2Mit182. Their effects were dependent on that of another body weight QTL previously mapped to that genomic region. The organ weight QTLs revealed were all duplicated in independent analyses with F2 intercross populations between subcongenic strains carrying these QTLs and their background strain. The findings suggested that organ weights are not exclusively regulated by genetic loci that commonly influence overall body weight and rather that there are loci contributing to the growth of specific organs only.  相似文献   

2.
四倍体紫花苜蓿是重要的豆科牧草之一,由于其复杂的遗传背景与二倍体作物相比遗传作图与重要性状数量性状位点(quantitative trait locus,QTL)定位研究相对滞后。然而,二倍体苜蓿的相关研究起步较早,已经建立了高密度遗传图谱和物理图谱,这些研究为四倍体苜蓿遗传作图与QTL定位奠定了基础。随着第三代分子标记与测序技术的快速发展,极大地促进了四倍体苜蓿的高密度遗传图谱构建与QTL定位研究,并借助分子标记辅助育种技术对提高苜蓿选育效率,加速育种进程具有重要意义。本文对苜蓿遗传图谱构建与QTL定位研究及发展趋势进行了总结,并对苜蓿关联作图与全基因组选择的研究进展及应用前景加以概述,旨在为读者就相关研究领域有较全面的了解。  相似文献   

3.
The objective of this study was to identify single-nucleotide polymorphisms using a bovine chromosome 14 high-density SNP panel after accounting for the effect of DGAT1. Linkage disequilibrium information and sire heterozygosity were used to select markers for linkage analysis on bovine chromosome 14 for milk production traits in 321 Holstein animals. Results show putative milk peaks at 42 and 61 cM, both at p<0.10, a fat yield peak at 42 and 63 cM, both at p<0.05; a protein yield peak at 42 (p<0.01) and 84 cM (p<0.05); fat per cent peaks at 3 (p<0.01) and 29 cM (p<0.05), and a protein per cent peak at 4 cM (p<0.05). Once quantitative trait loci positions were established, allele substitution effects for all markers were evaluated using the same statistical model. Overlaying information between quantitative trait loci (QTL) and allele effect analysis enabled the identification (p<0.01) of 20 SNPs under the milk yield QTL, 2 under both of the fat yield peaks, 8 and 9 under the protein yield peaks, 2 and 6 for the fat per cent peaks and 5 for the protein per cent peak. One SNP in particular, ss61514555:A>C, showed association with 3 of the 5 traits: milk (p=1.59E-04), fat (p=6.88E-05) and protein yields (p=5.76E-05). Overall, combining information from linkage disequilibrium, sire heterozygosity and genetic knowledge of traits enabled the characterization of additional markers with significant associations with milk production traits.  相似文献   

4.
A directed search for QTL affecting carcass traits was carried out in the region of growth differentiation factor 8 (GDF8, also known as myostatin) on ovine chromosome 2 in seven Texel-sired half-sib families totaling 927 progeny. Weights were recorded at birth, weaning, ultrasound scanning, and slaughter. Ultrasonic measures of LM cross-sectional dimensions and s.c. fat above the LM were made, with the same measurements made on the LM after slaughter. Following slaughter, linear measurements of carcass length and width were made on all carcasses, and legs and loins from 540 lambs were dissected. Genotyping was carried out using eight microsatellite markers from FCB128 to RM356 on OAR 2 and analyzed using Haley-Knott regression. There was no evidence for QTL for growth rates or linear carcass traits. There was some evidence for QTL affecting LM dimensions segregating in some sire families, although it was not consistent between ultrasound and carcass measures of the same traits. There was strong and consistent evidence for a QTL affecting muscle and fat traits in the leg that mapped between markers BM81124 and BULGE20 for the four sires that were heterozygous in this region, but not for the three sires that were homozygous. The size of the effect varied across the four sires, ranging from 0.5 to 0.9 of an adjusted SD for weight-adjusted leg muscle traits, and ranging from 0.6 to 1.2 of an adjusted SD for weight-adjusted leg fat traits. The clearest effect shown was for multivariate analysis combining all leg muscle and fat traits analyzed across sires, where the -log(10) probability was 14. Animals carrying the favorable haplotype had 3.3% more muscle and 9.9% less fat in the leg relative to animals carrying other haplotypes. There was evidence for a second peak in the region of marker TEXAN2 for one sire group. It seems that a QTL affecting muscle and fat traits exists within the New Zealand Texel population, and it maps to the region of GDF8 on OAR2.  相似文献   

5.
The purpose of this study was to map quantitative trait loci (QTL) influencing female fertility estimated by non-return rate (NRR) in the French dairy cattle breeds Prim'Holstein, Normande and Montbeliarde. The first step was a QTL detection study on NRR at 281 days after artificial insemination on 78 half-sib families including 4993 progeny tested bulls. In Prim'Holstein, three QTL were identified on Bos taurus chromosomes BTA01, BTA02 and BTA03 (p < 0.01), whereas one QTL was identified in Normande on BTA01 (p < 0.05). The second step aimed at confirming these three QTL and refining their location by selecting and genotyping additional microsatellite markers on a sub-sample of 41 families from the three breeds using NRR within 56, 90 and 281 days after AI. Only the three QTL initially detected in Prim'Holstein were confirmed. Moreover, the analysis of NRR within 56, 90 and 281 days after AI allowed us to distinguish two FF QTL on BTA02 in Prim'Holstein, one for NRR56 and one for NRR90. Estimated QTL variance was 18%, 14%, 11.5% and 14% of the total genetic variance, respectively, for QTL mapping to BTA01, BTA02 (NRR90 and NRR56) and BTA03.  相似文献   

6.
A primary genomic screen for quantitative trait loci (QTL) affecting carcass and growth traits was performed by genotyping 238 microsatellite markers on 185 out of 300 total progeny from a Bos indicus x Bos taurus sire mated to Bos taurus cows. The following traits were analyzed for QTL effects: birth weight (BWT), weaning weight (WW), yearling weight (YW), hot carcass weight (HCW), dressing percentage (DP), fat thickness (FT), marbling score (MAR), longissimus muscle area (LMA), rib bone (RibB), rib fat (RibF), and rib muscle (RibM), and the predicted whole carcass traits, retail product yield (RPYD), fat trim yield (FATYD), bone yield (BOYD), retail product weight (RPWT), fat weight (FATWT), and bone weight (BOWT). Data were analyzed by generating an F-statistic profile computed at 1-cM intervals for each chromosome by the regression of phenotype on the conditional probability of receiving the Brahman allele from the sire. There was compelling evidence for a QTL allele of Brahman origin affecting an increase in RibB and a decrease in DP on chromosome 5 (BTA5). Putative QTL at or just below the threshold for genome-wide significance were as follows: an increase in RPYD and component traits on BTA2 and BTA13, an increase in LMA on BTA14, and an increase in BWT on BTA1. Results provided represent a portion of our efforts to identify and characterize QTL affecting carcass and growth traits.  相似文献   

7.
Conventional selective genotyping which is using the extreme phenotypes (EP) was compared with alternative criteria to find the most informative animals for genotyping with respects to mapping quantitative trait loci (QTL). Alternative sampling strategies were based on minimizing the sampling error of the estimated QTL effect (MinERR) and maximizing likelihood ratio test (MaxLRT) using both phenotypic and genotypic information. In comparison, animals were randomly genotyped either within or across families. One hundred data sets were simulated each with 30 half-sib families and 120 daughters per family. The strategies were compared in these datasets with respect to estimated effect and position of a QTL within a previously defined genomic region at genotyping 10, 20 or 30% of the animals. Combined linkage disequilibrium linkage analysis (LDLA) was applied in a variance component approach. Power to detect QTL was significantly higher for both MinERR and MaxLRT compared with EP and random genotyping methods (either across or within family), for all the proportions of genotyped animals. Power to detect significant QTL (alpha = 0.01) with 20% genotyping for MinERR and MaxLRT was 80 and 75% of that obtained with complete genotyping compared with 70 and 38% genotyping for EP within and across families respectively. With 30% genotyping, the powers were 78, 83, 78 and 58% respectively. The estimated variance components were unbiased in EP strategies (within and across family), only when at least 30% was genotyped. To decrease the number of genotyped individuals either MinERR or MaxLRT could be considered. With 20% genotyping in MinERR, the estimated QTL variance components were not significant compared with complete genotype information but all studied strategies at 20% genotyping overestimated the QTL effect. Results showed that combining the phenotypic and genotypic information in selective genotyping (e.g. MinERR and MaxLRT) is better than using only the EPs and the combined methods can be considered as alternative approaches to decrease genotyping costs, with unbiased QTL effects, decreased sampling variance of the QTL variance component and also increased the power of QTL detection.  相似文献   

8.
In broiler chickens, bone problems are an important welfare issue that has been linked to genetic selection for rapid growth. The objectives of this study were to identify and fine map quantitative trait loci (QTL) associated with bone traits. The Northeast Agricultural University resource population (NEAURP) being an F(2) population was used in this study, and a total of 17 bone traits were measured. In primary genome scan, the linkage map was constructed with 23 microsatellite markers across the entire chicken chromosome 1. Seventeen QTLs for bone traits were identified and 12 of these were found between LEI0079 and ROS0025 (50.8 cM apart). To fine map the QTLs located between LEI0079 and ROS0025, more markers and more individuals were used and a new partial linkage map was constructed. The confidence intervals for QTLs were sharply narrowed down from 24.5~52.6 to 2.7~17.0 Mb. This study identified chromosome regions harbouring significant QTLs affecting bone traits and showed that the use of more markers and individuals could decrease the confidence interval of QTL effectively. The results provide a useful reference for further candidate gene research and MAS for bone traits.  相似文献   

9.
10.
The primary goal of this study was to detect and confirm QTL on SSC6 for growth and fatness traits in 2 experimental F(2) intercrosses: Iberian x Landrace (IB x LR) and Iberian x Meishan (IB x MS), which were used in this study for the first time in a QTL analysis related to productive traits. For this purpose, single- and joint-population analyses with single and bivariate trait models of both populations were performed. The presence of the SSC6 QTL for backfat thickness previously identified in the IB x LR cross was detected in this population with additional molecular information, but also was confirmed in the IB x MS cross. In addition, a QTL affecting BW was detected in both crosses in a similar position to the QTL detected for backfat thickness. This is the first study in which a QTL affecting BW is detected on SSC6 in the IB x LR cross, as well as in the IB x MS resource population. Furthermore, we analyzed a previously described nonsynonymous leptin receptor (LEPR) SNP located in exon 14 (c.2002C > T) for causality with respect to this QTL within both F(2) populations. Our results supported the previously reported association between LEPR alleles and backfat thickness in the IB x LR cross, and this association was also confirmed within the IB x MS cross. An association not reported before between LEPR alleles and BW was identified in both populations.  相似文献   

11.
A confirmatory scan for the regions of bovine chromosome 1 segregating the quantitative trait loci (QTL) influencing birthweight, weaning weight, yearling weight, and preweaning and postweaning average daily gains was performed by genotyping half‐sib progeny of four Japanese Black sires using microsatellite DNA markers. Data were analyzed by generating an F‐statistic every 1 cM on a linkage map by the regression of phenotype on the probabilities of inheriting an allele from the sire after adjusting for the fixed effects of sire, sex, parity and season of birth as well as age as a covariate. Permutation tests at chromosome‐wide significance thresholds were carried out over 10 000 iterations. A significant QTL for birthweight at 114 cM was detected in the sire 2 family. This identification of a birthweight QTL in Japanese Black cattle may be useful for the implementation of marker‐assisted selection.  相似文献   

12.
The objective of this study was to identify quantitative trait loci for economically important traits in two families segregating an inactive copy of the myostatin gene. Two half-sib families were developed from a Belgian Blue x MARC III (n = 246) and a Piedmontese x Angus (n = 209) sire. Traits analyzed were birth, weaning, and yearling weight (kg); preweaning average daily gain (kg/d); postweaning average daily gain (kg/d); hot carcass weight (kg); fat depth (cm); marbling score; longissimus muscle area (cm2); estimated kidney, pelvic, and heart fat (%); USDA yield grade; retail product yield (%); fat yield (%); and wholesale rib-fat yield (%). Meat tenderness was measured as Warner-Bratzler shear force at 3 and 14 d postmortem. The effect of the myostatin gene was removed using phase information from six microsatellite markers flanking the locus. Interactions of the myostatin gene with other loci throughout the genome were also evaluated: The objective was to use markers in each family, scanning the genome approximately every 25 to 30 centimorgans (cM) on 18 autosomal chromosomes, excluding 11 autosomal chromosomes previously analyzed. A total of 89 markers, informative in both families, were used to identify genomic regions potentially associated with each trait. In the family of Belgian Blue inheritance, a significant QTL (expected number of false-positives = 0.025) was identified for marbling score on chromosome 3. Suggestive QTL for the same family (expected number of false-positives = 0.5) were identified for retail product yield on chromosome 3, for hot carcass weight and postweaning average daily gain on chromosome 4, for fat depth and marbling score on chromosome 8, for 14-d Warner-Bratzler shear force on chromosome 9, and for marbling score on chromosome 10. Evidence suggesting the presence of an interaction for 3-d Warner-Bratzler shear force between the myostatin gene and a QTL on chromosome 4 was detected. In the family of Piedmontese and Angus inheritance, evidence indicates the presence of an interaction for fat depth between the myostatin gene and chromosome 8, in a similar position where the evidence suggests the presence of a QTL for fat depth in the family with Belgian Blue inheritance. Regions identified underlying QTL need to be assessed in other populations. Although the myostatin gene has a considerable effect, other loci with more subtle effects are involved in the expression of the phenotype.  相似文献   

13.
We previously mapped a quantitative trait locus (QTL) affecting the trait non-return rate at 56 days in heifers to bovine chromosome 9. The purpose of this study was to confirm and refine the position of the QTL by using a denser marker map and fine mapping methods. Five families that previously showed segregation for the QTL were included in the study. The mapping population consisted of 139 bulls in a granddaughter design. All bulls were genotyped for 25 microsatellite markers surrounding the QTL on chromosome 9. We also analysed the correlated trait number of inseminations per service period in heifers. Both traits describe the heifer's ability to become pregnant after insemination. Linkage analysis, linkage disequilibrium and combined linkage and linkage disequilibrium analysis were used to analyse the data. Analysis of the families jointly by linkage analysis resulted in a significant but broad QTL peak for non-return rate. Results from the combined analysis gave a sharp QTL peak with a well-defined maximum in between markers BMS1724 and BM7209, at the same position as where the highest peak from the linkage disequilibrium analysis was found. One of the sire families segregated clearly at this position and the difference in effects between the two sire haplotypes was 2.9 percentage units in non-return rate. No significant results were found for the number of inseminations in the combined analysis.  相似文献   

14.
The objective of this study was to assess the effect of genotyped bulls with different numbers of phenotyped progenies on quantitative trait loci (QTL) detection and genomic evaluation using a simulated cattle population. Twelve generations (G1–G12) were simulated from the base generation (G0). The recent population had different effective population sizes, heritability, and number of QTL. G0–G4 were used for pedigree information. A total of 300 genotyped bulls from G5–G10 were randomly selected. Their progenies were generated in G6–G11 with different numbers of progeny per bull. Scenarios were considered according to the number of progenies and whether the genotypes were possessed by the bulls or the progenies. A genome‐wide association study and genomic evaluation were performed with a single‐step genomic best linear unbiased prediction method to calculate the power of QTL detection and the genomic estimated breeding value (GEBV). We found that genotyped bulls could be available for QTL detection depending on conditions. Additionally, using a reference population, including genotyped bulls, which had more progeny phenotypes, enabled a more accurate prediction of GEBV. However, it is desirable to have more than 4,500 individuals consisting of both genotypes and phenotypes for practical genomic evaluation.  相似文献   

15.
The small intestine is a vital organ in animal gastrointestinal system, in which a large variety of nutrients are absorbed. To identify quantitative trait loci (QTL) for the length of porcine small intestine, phenotypic values were measured in 1034 individuals at 240 d from a White Duroc × Chinese Erhualian intercross F2 population. The length of small intestine showed strong correlation with growth traits and carcass length in the F2 population. A whole‐genome scan was performed based on 183 microsatellites covering the pig genome in the F2 population. A total of 10 QTL for this trait were identified on 8 pig chromosomes (SSC), including four 1% genome‐wide significant QTL on SSC2, 4, 7 and 8, one 5% genome‐wide significant QTL on SSC12, and five 5% chromosome‐wide significant QTL on SSC5, 7, 13 and 14. The Erhualian alleles were generally associated with shorter length of the small intestine except the alleles on SSC7 and 13. The QTL on SSC4 overlapped with the previously reported QTL for the length of small intestine. Several significant QTL on SSC2, 8, and 12 were consistent with previous reports. The significant QTL detected on SSC7 was reported for the first time. All QTL identified in this study corresponded to the known region significantly associated with growth traits, supporting the important role of the length of small intestine in pig growth.  相似文献   

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