Genetic parameter estimates and GxE interaction in a large cloned population of Pinus taeda L.

Shalizi, Mohammad Nasir; Isik, Fikret

doi:10.1007/s11295-019-1352-7

Cited by 20 publications

(24 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The population used for model training, Atlantic Coastal Elite (ACE), is a clonally replicated collection of full-sib families established across eight environments in the early 2000s ( Shalizi and Isik 2019 ). A total of 24 parents was intermated in three disconnected eight-parent diallels, producing 76 full-sib families.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Prediction ability of genome-wide markers in Pinus taeda L. within and between population is affected by relatedness to the training population and trait genetic architecture

Lauer

Holland

Isik

2021

G3 Genes|Genomes|Genetics

Self Cite

View full text Add to dashboard Cite

Genomic prediction has the potential to significantly increase the rate of genetic gain in tree breeding programs. In this study, a clonally replicated population (n = 2063) was used to train a genomic prediction model. The model was validated both within the training population and in a separate population (n = 451). The prediction abilities from random (20% vs. 80%) cross validation within the training population were 0.56 and 0.78 for height and stem form, respectively. Removal of all full-sib relatives within the training population resulted in ∼50% reduction in their genomic prediction ability for both traits. The average prediction ability for all 451 individual trees was 0.29 for height and 0.57 for stem form. The degree of genetic linkage (full sib family, half sib family, unrelated) between the training and validation sets had a strong impact on prediction ability for stem form but not for height. A dominant dwarfing allele, the first to be reported in a conifer species, was discovered via GWAS on linkage group 5 that conferred a 0.33 m mean height reduction. However, the QTL was family specific. The rapid decay of LD, large genome size, and inconsistencies in marker-QTL linkage phase suggest that large, diverse training populations are needed for genomic selection in Pinus taeda L.

show abstract

Section: Methodsmentioning

confidence: 99%

“…From each progeny, eight rooted cuttings (ramets) were produced. These ramets were established in eight environments across the southeast United States ( Shalizi and Isik 2019 ). Each environment featured an alpha-cyclic row–column incomplete block design with a single replication.…”

Section: Methodsmentioning

confidence: 99%

Prediction ability of genome-wide markers in Pinus taeda L. within and between population is affected by relatedness to the training population and trait genetic architecture

Lauer

Holland

Isik

2021

G3 Genes|Genomes|Genetics

Self Cite

View full text Add to dashboard Cite

show abstract

“…Two key questions for forest breeders are which phenotypes to measure and which trees to select (Matallana-Ramirez et al, 2021). Although the answer to this question depends on the location of the populations evaluated and the level of diversity involved, volume growth, a trait evaluated in this work, is one of the traits that forest breeders most often focus on for the evaluation and selection of phenotypes (Zobel and Talbert, 1984; Shalizi and Isik, 2019; Shalizi et al, 2022). Since the 1960s and early 1970s, breeders have been able to produce 7-12% more volume per hectare at harvest than trees grown from wild seeds (Li et al, 1999).…”

Section: Discussionmentioning

confidence: 99%

“…The targeting of genetic breeding programs to produce varieties with high SV is prioritized for most cultivated tree species, including LP (Lu et al, 2018;Shalizi and Isik, 2019).…”

Section: Introductionmentioning

confidence: 99%

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

Bajay¹,

Aono²,

Francisco³

et al. 2022

Preprint

View full text Add to dashboard Cite

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.

show abstract

“…The mixed linear models could be used to describe longitudinal data, choosing different matrices for covariance structures associated with random factors of the model that explain the dependence between measurements (Shalizi and Isik, 2019). The simplest repeatability model assumes the independent residual effect and considers environmental and genetic correlations constant among different registers of repeated measurements.…”

Section: Introductionmentioning

confidence: 99%

Repeatability estimates in longitudinal data on guava trees

Silva

Viana

Corrêa

et al. 2023

Sci. agric. (Piracicaba, Braz.)

View full text Add to dashboard Cite

The use of longitudinal measurements is an essential practice both in Psidium guajava L. breeding and in other perennial crops in which covariance structures can be introduced to explain the form of dependence between measurements. Hence, this study aimed to analyze six covariance structures to identify one that best described the correlation between the repeated measurements in time in traits of guava full-sib families. The repeatability coefficient for each trait was estimated and the minimum number of evaluations required for estimates representing the population was determined. The work was performed based on average data of three yield-related variables from nine harvests of a guava tree population evaluated from 2011 to 2018. The best model was chosen based on the Akaike and Schwarz Bayesian information criterion. The autoregressive covariance structure best represented the dependencies among families between crops for all traits. The number of variables of fruits and total yield per plant presented repeatability estimates higher than 0.5 and may be essential traits for indirect selection of others, such as fruit mass, which had an estimated repeatability of 0.24, proving low regularity in the repetition of the character from one cycle to another. It was also possible to define four harvests as the minimum acceptable number of observations necessary on the same individual for these traits; therefore, the repetitions represented the individuals.

show abstract

Genetic parameter estimates and GxE interaction in a large cloned population of Pinus taeda L.

Cited by 20 publications

References 26 publications

Prediction ability of genome-wide markers in Pinus taeda L. within and between population is affected by relatedness to the training population and trait genetic architecture

Prediction ability of genome-wide markers in Pinus taeda L. within and between population is affected by relatedness to the training population and trait genetic architecture

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

Repeatability estimates in longitudinal data on guava trees

Contact Info

Product

Resources

About