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23 results for “Pinus taeda”
Supplementary dataset Pinus Taeda for Cappa et al. (2015)
<p>Trial information and family numbers of the <em>Pinus Taeda L</em>. trial.</p> <p>Diameter at breast height of the <em>Pinus taeda </em>L. data set will be available upon request.</p>
Data from: Association genetics of growth and adaptive traits in loblolly pine (Pinus taeda L.) using whole-exome-discovered polymorphisms
In the United States, forest genetics research began over 100 years ago and loblolly pine breeding programs were established in the 1950s. However, the genetics underlying complex traits of loblolly pine remains to be discovered. To address this, adaptive and growth traits were measured and analyzed in a clonally tested loblolly pine (Pinus taeda L.) population. Over 2.8 million single nucleotide polymorphism (SNP) markers detected from exome sequencing were used to test for single locus associations, SNP-SNP interactions and correlation of individual heterozygosity with phenotypic traits. A total of 36 SNP-trait associations were found for specific leaf area (5 SNPs), branch angle (2), crown width (3), stem diameter (4), total height (9), carbon isotope discrimination (4), nitrogen concentration (2), and pitch canker resistance traits (7). Eleven SNP-SNP interactions were found to be associated with branch angle (1 SNP-SNP interaction), crown width (2), total height (2), carbon isotope discrimination (2), nitrogen concentration (1), and pitch canker resistance (3). Non-additive effects imposed by dominance and epistasis account for a large fraction of the genetic variance for the quantitative traits. Genes that contain the identified SNPs have a wide spectrum of functions. Individual heterozygosity positively correlated with water use efficiency and nitrogen concentration. In conclusion, multiple effects identified in this study influence the performance of loblolly pines, provide resources for understanding the genetic control of complex traits, and have potential value for assessing with breeding through marker assisted selection and genomic selection.
Pinus taeda (Pinaceae) - cone - female - receptive
Image of Pinus taeda (Pinaceae) - cone - female - receptive
Pinus taeda (Pinaceae) - cone - male
Image of Pinus taeda (Pinaceae) - cone - male
Pinus taeda (Pinaceae) - twig - showing attachment of needles
Image of Pinus taeda (Pinaceae) - twig - showing attachment of needles
Pinus taeda (Pinaceae) - leaf - showing orientation on twig
Image of Pinus taeda (Pinaceae) - leaf - showing orientation on twig
Pinus taeda (Pinaceae) - cone - female - mature open
Image of Pinus taeda (Pinaceae) - cone - female - mature open
Pinus taeda (Pinaceae) - whole tree - general
Image of Pinus taeda (Pinaceae) - whole tree - general
Pinus taeda (Pinaceae) - bark - of a large tree
Image of Pinus taeda (Pinaceae) - bark - of a large tree
Pinus taeda (Pinaceae) - leaf - entire needle
Image of Pinus taeda (Pinaceae) - leaf - entire needle
Pinus taeda (Pinaceae) - cone - male
Image of Pinus taeda (Pinaceae) - cone - male
Data from: AgMate: an optimal mating software versus other mate pair designing methods on long-term breeding of Pinus taeda L
<p>Breeding objectives aim to optimize two crucial but contrasting goals of maximizing genetic gain while managing genetic diversity. In advanced generations, this becomes a challenge in monoecious conifer tree species breeding programs because they suffer from inbreeding. Developing an algorithm that maximizes genetic gain while maintaining genetic diversity for monoecious species is imperative. While methods and algorithms for animal breeding are well-established, an efficient algorithm suited to monoecious species remains elusive. Towards this goal, we have adopted an evolutionary genetic algorithm, the Differential Evolution algorithm, to optimize mate pair designing in <em>Pinus taeda</em> (loblolly pine), a widely planted pine species in the southern USA. AgMate, an optimal mating for monoecious species software, is a multi-functional, completely automated optimization software. It utilizes genetic relationships and breeding values as input to create an optimal mating list. AgMate maximizes the genetic gain and minimizes the increase in average coancestry and inbreeding in the proposed progeny. AgMate was more effective in optimizing mating lists than positive assortative mating and random mating in short-term and long-term settings. AgMate mating list resulted in an average 93% genetic gain each cycle for ten cycles while simultaneously minimizing the increase in coancestry to 0.086. The framework and methods adapted for Pinus taeda are also relevant to the breeding of other monoecious species.</p>
Pinus taeda L. (BR0000025053739)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Data from: Association genetics of growth and adaptive traits in loblolly pine (Pinus taeda L.) using whole-exome-discovered polymorphisms
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Variant discovery in full-sibling families of Pinus taeda L
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Data from: AgMate: an optimal mating software versus other mate pair designing methods on long-term breeding of Pinus taeda L
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Data from: Optimal mating of Pinus taeda L. under different scenarios using differential evolution algorithm
<p>A newly developed software, AgMate, was used to perform optimized mating for monoecious <em>Pinus taeda L.</em> breeding. Using a computational optimization procedure called differential evolution (DE), AgMate was applied under different breeding population sizes scenarios (50, 100, 150, 200, 250) and candidate contribution scenarios (max use of each candidate was set to 1 or 8), to assess its efficiency in maximizing the genetic gain while controlling inbreeding. Real pedigree data set from North Carolina State University Tree Improvement Co-op with 962 Pinus taeda were used to optimize objective functions accounting for coancestry of parents and expected genetic gain and inbreeding of the future progeny. AgMate results were compared with those from another widely used mating software called MateSel (Kinghorn, 1999). For the proposed mating list for 200 progenies, AgMate resulted in an 83.7% increase in genetic gain compared with the candidate population. There was evidence that AgMate performed similarly to MateSel in managing coancestry and expected genetic gain, but MateSel was superior in avoiding inbreeding in proposed mate pairs. The developed algorithm was computationally efficient in maximizing the objective functions and flexible for practical application in monoecious diploid conifer breeding.</p>
PacBio IsoSeq reference transcriptomes for Pinus taeda L.
<p>Fusiform rust disease, caused by the endemic fungus <i>Cronartium quercuum</i> f. sp. <i>fusiforme</i>, is the most damaging disease affecting economically important pine species in the southeast United States. In this report, we detail the genomic localization and sequence-level discovery of candidate race-nonspecific broad-spectrum fusiform rust resistance genes in <i>Pinus taeda </i>L. Two full-sib families, each with ~1000 progeny, were challenged with a complex inoculum consisting of over 150 pathogen isolates. High-density linkage mapping revealed three QTL distributed on two linkage groups. The two QTL on linkage group 2 were additive with respect to their effects on the probability of disease outcome. All three QTL were validated using a population of 2057 cloned pine genotypes in a six-year-old multi-environmental field trial. As a complement to the QTL mapping approach, bulked segregant RNAseq analysis revealed a small number of candidate nucleotide binding leucine rich repeat genes harboring SNP significantly associated with disease resistance. The results of this study demonstrate that single qualitative resistance genes can confer effective resistance against genetically diverse mixtures of an endemic pathogen.</p>
PacBio IsoSeq reference transcriptomes for Pinus taeda L.
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Data from: Optimal mating of Pinus taeda L. under different scenarios using differential evolution algorithm
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