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- Abrahamsson, Sara, et al.
(author)
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Maternal heterozygosity and progeny fitness association in an inbred Scots pine population
- 2013
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In: Genetica. - : Springer Netherlands. - 0016-6707 .- 1573-6857. ; 141:1-3, s. 41-50
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Journal article (peer-reviewed)abstract
- Associations between heterozygosity and fitness traits have typically been investigated in populations characterized by low levels of inbreeding. We investigated the associations between standardized multilocus heterozygosity (stMLH) in mother trees (obtained from12 nuclear microsatellite markers) and five fitness traits measured in progenies from an inbred Scots pine population. The traits studied were proportion of sound seed, mean seed weight, germination rate, mean family height of one-year old seedlings under greenhouse conditions (GH) and mean family height of three-year old seedlings under field conditions (FH). The relatively high average inbreeding coefficient (F) in the population under study corresponds to a mixture of trees with different levels of co-ancestry, potentially resulting from a recent bottleneck. We used both frequentist and Bayesian methods of polynomial regression to investigate the presence of linear and non-linear relations between stMLH and each of the fitness traits. No significant associations were found for any of the traits except for GH, which displayed negative linear effect with stMLH. Negative HFC for GH could potentially be explained by the effect of heterosis caused by mating of two inbred mother trees (Lippman and Zamir 2006), or outbreeding depression at the most heterozygote trees and its negative impact on the fitness of the progeny, while their simultaneous action is also possible (Lynch. 1991). However,since this effect wasn’t detected for FH, we cannot either rule out that the greenhouse conditions introduce artificial effects that disappear under more realistic field conditions.
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2. |
- Mészáros, Gábor, et al.
(author)
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A genome wide association study for longevity in cattle
- 2014
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In: Open Journal of Genetics. - : Scientific Research Publishing. - 2162-4453 .- 2162-4461. ; 4:1, s. 46-55
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Journal article (peer-reviewed)abstract
- Longevity is regarded as the most important functional trait in cattle breeding with high economic value yet low heritability. In order to identify genomic regions associated with longevity, a genome wise association study was performed using data from 4887 Fleckvieh bulls and 33,556 SNPs after quality control. Single SNP regression was used for identification of important SNPs including eigenvectors as a means of correction for population structure. SNPs selected with a false discovery rate threshold of 0.05 and with local false discovery rate identified genomic regions associated with longevity which were subsequently cross checked with the National Center for Biotechnology Information (NCBI) database. This, to identify interesting genes in cattle and their homologue forms in other species. The most notable genes were SYT10 located on chromosome 5, ADAMTS3 on chromosome 6, NTRK2 on chromosome 8 and SNTG1 on chromosome 14 of the cattle genome. Several of the genes found have previously been associated with cattle fertility. Poor fertility is an important culling reason and thereby affects longevity in cattle. Several signals were located in regions sparse with described genes, which suggest that there might be several other non-identified genetic pathways for this important trait.
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3. |
- Quilot-Turion, Bénédicte, et al.
(author)
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Genetic changes in flowering and morphology in response to adaptation to a high-latitude environment in Arabidopsis lyrata
- 2013
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In: Annals of Botany. - : Oxford University Press. - 0305-7364 .- 1095-8290. ; 111:5, s. 957-968
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Journal article (peer-reviewed)abstract
- Background and Aims The adaptive plastic reactions of plant populations to changing climatic factors, such as winter temperatures and photoperiod, have changed during range shifts after the last glaciation. Timing of flowering is an adaptive trait regulated by environmental cues. Its genetics has been intensively studied in annual plants, but in perennials it is currently not well characterized. This study examined the genetic basis of differentiation in flowering time, morphology, and their plastic responses to vernalization in two locally adapted populations of the perennial Arabidopsis lyrata: (1) to determine whether the two populations differ in their vernalization responses for flowering phenology and morphology; and (2) to determine the genomic areas governing differentiation and vernalization responses.Methods Two A. lyrata populations, from central Europe and Scandinavia, were grown in growth-chamber conditions with and without cold treatment. A QTL analysis was performed to find genomic regions that interact with vernalization.Key Results The population from central Europe flowered more rapidly and invested more in inflorescence growth than the population from alpine Scandinavia, especially after vernalization. The alpine population had consistently a low number of inflorescences and few flowers, suggesting strong constraints due to a short growing season, but instead had longer leaves and higher leaf rosettes. QTL mapping in the F2 population revealed genomic regions governing differentiation in flowering time and morphology and, in some cases, the allelic effects from the two populations on a trait were influenced by vernalization (QTL × vernalization interactions).Conclusions The results indicate that many potentially adaptive genetic changes have occurred during colonization; the two populations have diverged in their plastic responses to vernalization in traits closely connected to fitness through changes in many genomic areas.
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4. |
- Waldmann, Patrik, 1967-, et al.
(author)
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Evaluation of the lasso and the elastic net in genome-wide association studies
- 2013
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In: Frontiers in Genetics. - : Frontiers Research Foundation. - 1664-8021. ; 4:270
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Journal article (peer-reviewed)abstract
- The number of publications performing genome-wide association studies (GWAS) has increased dramatically. Penalized regression approaches have been developed to overcome the challenges caused by the high dimensional data, but these methods are relatively new in the GWAS field. In this study we have compared the statistical performance of two methods (the least absolute shrinkage and selection operator—lasso and the elastic net) on two simulated data sets and one real data set from a 50 K genome-wide single nucleotide polymorphism (SNP) panel of 5570 Fleckvieh bulls. The first simulated data set displays moderate to high linkage disequilibrium between SNPs, whereas the second simulated data set from the QTLMAS 2010 workshop is biologically more complex. We used cross-validation to find the optimal value of regularization parameter λ with both minimum MSE and minimum MSE + 1SE of minimum MSE. The optimal λ values were used for variable selection. Based on the first simulated data, we found that the minMSE in general picked up too many SNPs. At minMSE + 1SE, the lasso didn't acquire any false positives, but selected too few correct SNPs. The elastic net provided the best compromise between few false positives and many correct selections when the penalty weight α was around 0.1. However, in our simulation setting, this α value didn't result in the lowest minMSE + 1SE. The number of selected SNPs from the QTLMAS 2010 data was after correction for population structure 82 and 161 for the lasso and the elastic net, respectively. In the Fleckvieh data set after population structure correction lasso and the elastic net identified from 1291 to 1966 important SNPs for milk fat content, with major peaks on chromosomes 5, 14, 15, and 20. Hence, we can conclude that it is important to analyze GWAS data with both the lasso and the elastic net and an alternative tuning criterion to minimum MSE is needed for variable selection.
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5. |
- Weinwurm, Stephan, et al.
(author)
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The effect of linkage disequilibrium on Bayesian genome-wide association methods
- 2013
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In: Journal of Biometrics & Biostatistics. - : Omics Publishing Group. - 2155-6180. ; 4:5, s. 180-
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Journal article (peer-reviewed)abstract
- The goal of genome-wide association studies (GWAS) is to identify the best subset of single-nucleotide polymorphisms (SNPs) that strongly influence a certain trait. State of the art GWAS comprise several thousand or even millions of SNPs, scored on a substantially lower number of individuals. Hence, the number of variables greatly exceeds the number of observations, which also is known as the p≫n problem.This problem has been tackled by using Bayesian variable selection methods, for example stochastic search variable selection (SSVS) and Bayesian penalized regression methods (Bayesian lasso; BLA and Bayesian ridge regression; BRR). Even though the above mentioned approaches are capable of dealing with situations where p≫n, it is also known that these methods experience problems when the predictor variables are correlated. The potential problem that linkage disequilibrium (LD) between SNPs can introduce is often ignored.The main contribution of this study is to assess the performance of SSVS, BLA, BRR and a recently introduced method denoted hybrid correlation based search (hCBS) with respect to their ability to identify quantitative trait loci, where SNPs are partially highly correlated. Furthermore, each method’s capability to predict phenotypes based on the selected SNPs and their computational demands are studied. Comparison is based upon three simulated datasets where the simulated phenotypes are assumed to be normally distributed.Results indicate that all methods perform reasonably well with respect to true positive detections but often detect too many false positives on all datasets. As the heritability decreases, the Bayesian penalized regression methods are no longer able to detect any predictors because of shrinkage. Overall, BLA slightly outperformed the other methods and provided superior results in terms of highest true positive/ false positive ratio, but SSVS achieved the best properties on the real LD data.
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