Correspondence between Breeding Values of the Same Pinus taeda L. Genotypes from Clonal Trials and Half-Sib Seedling Progeny Trials

Shalizi, Mohammad Nasir; Gezan, Salvador A.; McKeand, Steven E.; Sherrill, J. R.; Cumbie, W. Patrick; Whetten, Ross; Isik, Fikret

doi:10.1093/forsci/fxaa016

Cited by 10 publications

(7 citation statements)

References 19 publications

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“…The narrow-sense heritability estimates for SV in LP vary considerably depending on the statistical strategies used and are substantially higher for more complex models (Schmidt et al 2019; Shalizi and Isik 2019). We found heritability values for SV ranging from 0.17 to 0.32 among the seven sites analyzed, indicating that there are different trends of heritability at each site, but similar to those found by other authors (Xiang et al 2003; Shalizi et al 2020). In general, SV heritability values increase over time and present correlations with plant age.…”

Section: Discussionsupporting

confidence: 89%

“…The narrow-sense heritability estimates for SV in LP vary considerably depending on the statistical strategies used and are substantially greater for more complex models [20,64]. We found heritability values for SV ranging from 0.17 to 0.32 among the seven sites analyzed, indicating that there are different trends of heritability at each site, but these trends are similar to those found by other authors [66,67].…”

Section: Discussionsupporting

confidence: 86%

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Genome-wide association reveals novel insights into the molecular mechanisms regulating stem volume inPinus taeda

Bajay¹,

Aono²,

Francisco³

et al. 2022

Preprint

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Pinus taeda(loblolly pine [LP]), a long-lived tree species, is one of the world's most economically important forest trees. Genetic improvement programs for loblolly and otherPinusspecies have focused on survival, biomass growth, resistance to diseases and pests, and stem shape. Among the growth traits, volume is the most widely considered in tree improvement programs. Despite the great interest in increasing volume growth, there are significant challenges to unraveling the molecular mechanisms behind this quantitative trait since it is presumably influenced by the action of large numbers of genes that may interact epistatically through unknown molecular mechanisms. The challenge of uncovering the genetic variants involved in variation for growth traits and their interaction is even greater in conifers such as LP because of the extremely large size and high complexity ofPinusgenomes. Here we present a comprehensive genetic analysis of LP involving genetic markers in association with volume (via genome-wide association studies [GWAS] and machine learning [ML]) to uncover pathways involved with good phenotypes for volume. The objective of this data integration was to provide a functional characterization of the genetic marker regions selected by GWAS and ML. We used a population of LP in the 2nd cycle of breeding and testing composed of full-sib progenies established at seven sites by the Cooperative Forest Genetics Research Program at the University of Florida. A total of 1,692 individuals were phenotyped and genotyped using sequence capture probes targeting putative genes. Probes were developed based on an elite germplasm transcriptome from LP. A total of 31,589 SNPs were identified and used to perform a GWAS through a multilocus mixed model. A precision core marker set with 7,864 SNPs selected through ML, i.e., feature selection (FS), was used for genomic selection (GS), providing a predictive accuracy (R Pearson coefficient) of approximately 0.79. For genome annotation and the construction of gene coexpression networks, three transcriptomes were assembled based on data from different pine species (Pinus taeda,Pinus elliottiiandPinus radiata). We selected genes associated with the target trait and assessed the cascade of related molecular mechanisms within coexpression networks. These results advance our understanding of the genetics influencing wood traits and reveal candidate genes for future functional studies as well as increase our understanding of quantitative genetics and the genomics of complex phenotypic variations in LP.

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Section: Discussionsupporting

confidence: 89%

Section: Discussionsupporting

confidence: 86%

Genome-wide association reveals novel insights into the molecular mechanisms regulating stem volume inPinus taeda

Bajay¹,

Aono²,

Francisco³

et al. 2022

Preprint

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“…Low overall fusiform rust disease incidence (10%) was another caveat of the study. Low incidence of fusiform rust disease is not surprising and has been widely reported from cloned progeny tests ( Foster and Anderson 1989 ; Frampton et al 2000 ; Isik et al 2003 ; Shalizi et al 2020 ). Compared with seedling progeny, vegetative propagules of P. taeda are resistant to fusiform rust disease in field trials ( Frampton et al 2000 ).…”

Section: Discussionmentioning

confidence: 94%

Genomic prediction for fusiform rust disease incidence in a large cloned population of Pinus taeda

Shalizi

Cumbie

Isik

2021

G3 Genes|Genomes|Genetics

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In this study, 723 Pinus taeda L. (loblolly pine) clonal varieties genotyped with 16920 SNP markers were used to evaluate genomic selection for fusiform rust disease caused by the fungus Cronartium quercuum f. sp. fusiforme. The 723 clonal varieties were from five full-sib families. They were a subset of a larger population (1831 clonal varieties), field-tested across 26 locations in the southeast US. Ridge regression, Bayes B and Bayes Cπ models were implemented to study marker-trait associations and estimate predictive ability for selection. A cross-validation scenario based on random sampling of 80% of the clonal varieties for model building had higher (0.71- 0.76) prediction accuracies of genomic estimated breeding values compared with family and within-family cross-validation scenarios. Random sampling within families for model training to predict genomic estimated breeding values of the remaining progenies within each family produced accuracies between 0.38 to 0.66. Using four families out of five for model training was not successful. The results showed the importance of genetic relatedness between the training and validation sets. Bayesian whole genome regression models detected three QTL with large effects on the disease outcome, explaining 54% of the genetic variation in the trait. The significance of QTL was validated with GWAS while accounting for the population structure and polygenic effect. The odds of disease incidence for heterozygous AB genotypes were 10.7 and 12.1 times greater than the homozygous AA genotypes for SNP11965 and SNP6347 loci, respectively. Genomic selection for fusiform rust disease incidence could be effective in P. taeda breeding. Markers with large effects could be fit as fixed covariates to increase the prediction accuracies, provided that their effects are validated further.

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“…Row-column designs have been strongly implemented for annual and perennial crops [20,21] and forestry [22][23][24], in which breeding feld trials typically occupy large areas. Concerning grapevines, fully replicated designs are useful for evaluating intravarietal genetic variability and for performing genetic selection [4].…”

Section: Introductionmentioning

confidence: 99%

Fully and Partially Replicated Experimental Designs for Evaluating Intravarietal Variability in Grapevine

Gonçalves

Carrasquinho

Martins

2022

Australian Journal of Grape and Wine Research

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Background and Aims. In ancient grapevine varieties, the experimental design of field trials is crucial to providing a reliable evaluation of quantitative traits. The main purposes of this study are to demonstrate the benefits of the resolvable row-column design (RCD) for quantifying intravarietal variability and performing polyclonal selection and to compare the efficiency of fully and partially replicated designs for quantifying intravarietal variability to implement the latter designs for a preliminary analysis of that variability. Methods and Results. Linear mixed models were fitted to yield data obtained in field trials with fully and partially replicated designs. The results pointed out the importance of the RCD in controlling the spatial variability present in large field trials. Although less precise, a partially replicated design proved to be useful in evaluating intravarietal variability when the average of years was used. Conclusions. The results reinforced the importance of the RCD in increasing the efficiency of intravarietal variability quantification and polyclonal selection. The partially replicated design proved to be useful when the only objective was to perform a preliminary analysis of intravarietal variability. Significance of the Study. Understanding the role of experimental design in grapevine selection field trials will help grapevine breeders enhance their knowledge about variability within ancient varieties and implement more successful polyclonal selection.

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Correspondence between Breeding Values of the Same Pinus taeda L. Genotypes from Clonal Trials and Half-Sib Seedling Progeny Trials

Cited by 10 publications

References 19 publications

Genome-wide association reveals novel insights into the molecular mechanisms regulating stem volume inPinus taeda

Genome-wide association reveals novel insights into the molecular mechanisms regulating stem volume inPinus taeda

Genomic prediction for fusiform rust disease incidence in a large cloned population of Pinus taeda

Fully and Partially Replicated Experimental Designs for Evaluating Intravarietal Variability in Grapevine

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