Distribution and location of genetic effects for dairy traits
TL;DR: A high-density scan using 38,416 single nucleotide polymorphism markers for 5,285 bulls confirmed 2 previously known major genes on Bos taurus autosomes (BTA) 6 and 14 but revealed few other large effects as discussed by the authors.
About: This article is published in Journal of Dairy Science.The article was published on 2009-06-01 and is currently open access. It has received 224 citations till now. The article focuses on the topics: Quantitative trait locus & Allele.
Citations
More filters
01 Jan 2010
3 citations
Dissertation•
01 Jul 2010
TL;DR: This dissertation presents a meta-anatomy of the immune system and its role in the response to infectious disease and shows clear patterns in response to antibiotics and its applications in the environment.
Abstract: University of Minnesota Ph.D. dissertation. July 2010. Major: Animal Science. Advisor: Yang Da. 1 computer file (PDF); viii, 148 pages, appendices A-E. Ill. (some col.)
3 citations
TL;DR: A posteriori and modified granddaughter designs were applied to determine haplotype effects for Holstein bulls and cows with BovineSNP50 and although the results can be used to determine causative polymorphisms for most of the analyzed traits, complete DNA sequencing of most ofThe analyzed sires probably will be required.
3 citations
11 Jan 2019
TL;DR: Progress is being made with ‘synthetic approaches’ in genetics and animal sciences, providing exciting opportunities to modulate, genome design and fi nally synthesis animal for favorite traits.
Abstract: Synthetic biology is an interdisciplinary branch of biology and engineering. The subject combines various disciplines from within these domains, such as biotechnology, evolutionary biology, molecular biology, systems biology, biophysics, computer engineering, and genetic engineering. Synthetic biology aims to understand whole biological systems working as a unit, rather than investigating their individual components and design new genome. Signifi cant advances have been made using systems biology and synthetic biology approaches, especially in the fi eld of bacterial and eukaryotic cells. Similarly, progress is being made with ‘synthetic approaches’ in genetics and animal sciences, providing exciting opportunities to modulate, genome design and fi nally synthesis animal for favorite traits. Review Article Synthetic Animal: Trends in Animal Breeding and Genetics Abolfazl Bahrami1* and Ali Najafi 2 1Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran 2Molecular Biology Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran *Address for Correspondence: A Bahrami, Department of Animal Science, Tehran University, Karaj, I.R. Iran, Tel/Fax: +98 9199300065; Email: a.bahrami@ut.ac.ir Submitted: 31 December 2018 Approved: 10 January 2019 Published: 11 January 2019 Copyright: © 2018 Bahrami A, et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
3 citations
Dissertation•
24 Feb 2011
TL;DR: A new Bayesian approach for detecting differentiated loci based on FST was developed and applied to a set of geographically separated populations with identical or diverse breeding goals and revealed the potential of FST analysis in detecting selection signals by testing some candidate major genes in the authors' data set.
Abstract: The knowledge of the extent and pattern of linkage disequilibrium (LD) is necessary for estimating the number of SNPs required for implementing association mapping studies as well as describing genomic structure of the bovine genome as a whole. In the first work of this study we used Illumina Bovine SNP50K BeadChip genotypes in a sample of German Holstein¨CFriesian cattle and developed a second generation of LD map statistics which has four times higher resolution compared to the maps available so far. These results revealed a lower level of LD for SNP pairs at distances iU100 Kb than previously thought. The level of LD obtained in this study indicated that a denser SNP map would be beneficial to capture the LD information required for whole-genome fine mapping and genomic selection and to completely assess the pattern of LD across the genome. Effective population size (Ne) was estimated based on the direct estimates of recombination rates from haplotype data and showed a persistent decline in about 100 individuals at the current generations. The impact of allele frequency in analyzing genome-wide LD was also explored in this part. Our observation revealed that minimizing the allele frequency difference between SNPs, reduces the influence of frequency on r2 estimates and provides a useful metric for analyzing LD. The larger block size in Holstein cattle observed in this study indicates substantially greater LD in cattle than in human populations. The second task of this thesis involved our attempts to find traces of decades of intensive artificial selection for traits of economically importance in modern cattle. In the first experiment we employed the recently described Extended Haplotype Homozygosity (EHH) test for tagging the genome wide footprints of positive selection in Holstein-Friesian cattle. This test uses the characteristics of haplotypes to detect selection by measuring the decay of haplotype homozygosity within a single population. To formally assess the significance of these results, we compared the combination of frequency and the Relative Extended Haplotype Homozygosity (REHH) value of each core haplotype with equally frequent haplotypes across the genome. A subset of the putative regions showing the highest significance genome-wide was mapped. Regarding the fact that problems arising from multiple testing may have affected the results we performed a further validation by aligning the 12 regions of extreme REHH to the bovine genome (Btau 4.0) to verify any coincidence of the preliminary signals observed with important genomic regions. We found co-location of a panel of genes such as FABP3, CLPN3, SPERT, HTR2A5, ABCE1, BMP4 and PTGER2 and some others with putative regions. This panel represents a broad range of economically important traits such as milk yield and composition as well as reproductive and behavioral traits. We also reported high values of LD and a slower decay of haplotype homozygosity for some candidate regions harboring major genes related to dairy quality. The results of this study provided a genome wide map of selection footprints in Holstein genome. In further experiments we exploited the variation among populations to explore the signatures of past selection. In this sense, we developed a new Bayesian approach for detecting differentiated loci based on FST and applied it to a set of geographically separated populations with identical or diverse breeding goals. This algorithm was able to deal with a large battery of marker information. Clustering the genome-wide estimates of FST values between Holstein and Brown Swiss versus Angus and Piedemontese breeds using Akaikei¯s criterion recognized two groups, one representing putatively neutral loci, and the other possibly corresponding the genomic regions affected by selection. We examined the potential of FST analysis in detecting selection signals by testing some candidate major genes in our data set. The results revealed FST values larger than expected (P < 10%) for regions harboring the Casein cluster, GHR, STS, LP and IGF-1 genes which are supposed to be targets for artificial selection. However, we were not able to propose strong candidate genes on the basis of the gene content in the vicinity of extreme signals. As an explanation, we theorized that selection may work on genes that were not considered the primary targets of selection so far. Consistent with the previous reports our results mostly revealed gene deserts in the location of extreme peaks, which may reflect selection acting on uncharacterized regulatory region or simply fixation of non-coding DNA by genetic drift in the absence of any selection. Thus, these results in combination with the observations on human population data suggest that non-coding regions have been an important substrate for adaptive evolution. In a parallel analysis the integrated Haplotype Homozygosity Score (|iHS|) a derivation of EHH test, was applied for tracing on-going sweeps. After estimating |iHS| for each locus, we defined regions of the genome that may contain targets of positive selection as windows in the extreme of empirical distribution. This criterion resulted in 94 significant windows (P iU 0.05). These results revealed significant enrichments for genes such as SPATA17, MGAT1, PGRMC2 and SRD5A2 in the region of clustered signals which belong to the number of functional categories relevant to reproduction including gamete generation, embryo development and spermatogenesis and genes in these categories may provide strong candidates for selection for fertility traits. Another interesting observation is the presence of the genes like Actinin, Collagen and fibroblast activation protein as well as the gene responsible for developing the cartilage rudiments in the positively selected regions of beef cattle. These results suggest that selection for muscle related phenotypes play a major role in the shaping the beef cattle. These results generally are consistent with the previous reports and begin to suggest general themes about the types of genes that have been targets of positive selection in cattle genome. Overall, based on the results of this study we conclude that high-resolution genome scans using dense markers are capable to identify outlier regions that potentially contain genes contributing to within and inter-breed phenotypic variation. Our results may be of future interest for identifying signatures of recent positive artificial selection between the cattle breeds or as additional evidence for any polymorphisms that show associations with beef or milk traits.
2 citations
References
More filters
Book•
01 Jan 1981
TL;DR: The genetic constitution of a population: Hardy-Weinberg equilibrium and changes in gene frequency: migration mutation, changes of variance, and heritability are studied.
Abstract: Part 1 Genetic constitution of a population: Hardy-Weinberg equilibrium. Part 2 Changes in gene frequency: migration mutation. Part 3 Small populations - changes in gene frequency under simplified conditions. Part 4 Small populations - less simplified conditions. Part 5 Small populations - pedigreed populations and close inbreeding. Part 6 Continuous variation. Part 7 Values and means. Part 8 Variance. Part 9 Resemblance between relatives. Part 10 Heritability. Part 11 Selection - the response and its prediction. Part 12 Selection - the results of experiments. Part 13 Selection - information from relatives. Part 14 Inbreeding and crossbreeding - changes of mean value. Part 15 Inbreeding and crossbreeding - changes of variance. Part 16 Inbreeding and crossbreeding - applications. Part 17 Scale. Part 18 Threshold characters. Part 19 Correlated characters. Part 20 Metric characters under natural selection.
20,288 citations
TL;DR: It was concluded that selection on genetic values predicted from markers could substantially increase the rate of genetic gain in animals and plants, especially if combined with reproductive techniques to shorten the generation interval.
Abstract: Recent advances in molecular genetic techniques will make dense marker maps available and genotyping many individuals for these markers feasible. Here we attempted to estimate the effects of ∼50,000 marker haplotypes simultaneously from a limited number of phenotypic records. A genome of 1000 cM was simulated with a marker spacing of 1 cM. The markers surrounding every 1-cM region were combined into marker haplotypes. Due to finite population size (Ne = 100), the marker haplotypes were in linkage disequilibrium with the QTL located between the markers. Using least squares, all haplotype effects could not be estimated simultaneously. When only the biggest effects were included, they were overestimated and the accuracy of predicting genetic values of the offspring of the recorded animals was only 0.32. Best linear unbiased prediction of haplotype effects assumed equal variances associated to each 1-cM chromosomal segment, which yielded an accuracy of 0.73, although this assumption was far from true. Bayesian methods that assumed a prior distribution of the variance associated with each chromosome segment increased this accuracy to 0.85, even when the prior was not correct. It was concluded that selection on genetic values predicted from markers could substantially increase the rate of genetic gain in animals and plants, especially if combined with reproductive techniques to shorten the generation interval.
6,036 citations
TL;DR: Efficient methods for processing genomic data were developed to increase reliability of estimated breeding values and to estimate thousands of marker effects simultaneously, and a blend of first- and second-order Jacobi iteration using 2 separate relaxation factors converged well for allele frequencies and effects.
4,196 citations
TL;DR: Genotypes for 38,416 markers and August 2003 genetic evaluations for 3,576 Holstein bulls born before 1999 were used to predict January 2008 daughter deviations and genomic prediction improves reliability by tracing the inheritance of genes even with small effects.
1,166 citations