Dataset Information

A comparison of genomic selection models across time in interior spruce (Picea engelmannii × glauca) using unordered SNP imputation methods.

ABSTRACT: Genomic selection (GS) potentially offers an unparalleled advantage over traditional pedigree-based selection (TS) methods by reducing the time commitment required to carry out a single cycle of tree improvement. This quality is particularly appealing to tree breeders, where lengthy improvement cycles are the norm. We explored the prospect of implementing GS for interior spruce (Picea engelmannii × glauca) utilizing a genotyped population of 769 trees belonging to 25 open-pollinated families. A series of repeated tree height measurements through ages 3-40 years permitted the testing of GS methods temporally. The genotyping-by-sequencing (GBS) platform was used for single nucleotide polymorphism (SNP) discovery in conjunction with three unordered imputation methods applied to a data set with 60% missing information. Further, three diverse GS models were evaluated based on predictive accuracy (PA), and their marker effects. Moderate levels of PA (0.31-0.55) were observed and were of sufficient capacity to deliver improved selection response over TS. Additionally, PA varied substantially through time accordingly with spatial competition among trees. As expected, temporal PA was well correlated with age-age genetic correlation (r=0.99), and decreased substantially with increasing difference in age between the training and validation populations (0.04-0.47). Moreover, our imputation comparisons indicate that k-nearest neighbor and singular value decomposition yielded a greater number of SNPs and gave higher predictive accuracies than imputing with the mean. Furthermore, the ridge regression (rrBLUP) and BayesC? (BC?) models both yielded equal, and better PA than the generalized ridge regression heteroscedastic effect model for the traits evaluated.

SUBMITTER: Ratcliffe B

PROVIDER: S-EPMC4806902 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Publications

A comparison of genomic selection models across time in interior spruce (Picea engelmannii × glauca) using unordered SNP imputation methods.

Ratcliffe B B El-Dien O G OG Klápště J J Porth I I Chen C C Jaquish B B El-Kassaby Y A YA

Heredity 20150701 6

Genomic selection (GS) potentially offers an unparalleled advantage over traditional pedigree-based selection (TS) methods by reducing the time commitment required to carry out a single cycle of tree improvement. This quality is particularly appealing to tree breeders, where lengthy improvement cycles are the norm. We explored the prospect of implementing GS for interior spruce (Picea engelmannii × glauca) utilizing a genotyped population of 769 trees belonging to 25 open-pollinated families. A ...[more]

PMID: 26126540

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Project description:Inferring the heritability of gene expression is one of the main areas of the field of genetical genomics. With the possibility to treat the abundances of gene transcripts as a suite of quantitative traits, genetical genomics can make an extensive use of the microarray technology. Here we extended a major method for estimating the heritability of a quantitative trait, single parent-offspring regression, to assess the heritability of the expression of genes with two-channel microarrays. In a series of maternal parent-offspring pairs of Interior spruce (Picea glauca x engelmannii, our focus in the outer stem tissues is the expression of defense-related genes, the heritability of which can affect fitness and necessary for evolution by natural selection. Parent-offspring pairs of Interior spruce planted as a part of Tree Breeding and Improvement Program of the Forest Genetics Section, British Columbia Ministry of Forests and Range, Prince George, BC, Canada (http://www.for.gov.bc.ca/hre/forgen/interior/spruce.htm#1) were used. A total of 30 trees, comprising 15 parent-offpsring pairs were sampled. These include15 offsprings and 15 maternal parents (grafts), which were planted within ~ 1Km range west (122º 42’ 43’’W, 53º 45’41’’N) of the offsprings, hence grown in a relatively similar environment. The bark and the attached phloem were separated from inner layers in the mid-morning hours of June 25, 2008, flash-frozen in liquid nitrogen, and transferred into separate containers. A chain design was decided for gene expression profiling (a total of 45 slides) using the Treenomix third generation cDNA microarray platform (GEO accession #: GPL5423). Array350 kit (Genisphere, Hatfield, USA) was chosen for the microarray hybridizations. The slides were scanned with a ProScanArray scanner (PerkinElmer, Downers Grove, IL, USA), and the scanned TIF images were processed by ImaGene software (BioDiscovery, Inc., El Segundo, CA, USA) to quantify spot signals. Normalization was done between arrays using variance stabilizing (VSN) method for ratio based analysis of the expression data.

Dataset Information

A comparison of genomic selection models across time in interior spruce (Picea engelmannii × glauca) using unordered SNP imputation methods.

Publications

A comparison of genomic selection models across time in interior spruce (Picea engelmannii × glauca) using unordered SNP imputation methods.

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