Conservation of Genetic Diversity of Scots Pine (Pinus sylvestris L.) in a Central European National Park Based on cpDNA Studies

Przybylski, Paweł; Tereba, Anna; Meger, Joanna; Szyp-Borowska, Iwona; Tyburski, Łukasz

doi:10.3390/d14020093

Cited by 6 publications

(2 citation statements)

References 37 publications

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“…However, no further efforts were made for stone pine. Other pines have been the target of such studies and efforts more recently (from 2014 to 2022), as is the case of P. cembra [82], P. sylvestris [83], and P. contorta [84].…”

Section: Stone Pine and Other Related Speciesmentioning

confidence: 99%

Stone Pine (Pinus pinea L.) High-Added-Value Genetics: An Overview

Simões,

Borges,

Grazina

et al. 2024

Genes

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Stone pine (Pinus pinea L.) has received limited attention in terms of genetic research. However, genomic techniques hold promise for decoding the stone pine genome and contributing to developing a more resilient bioeconomy. Retrotransposon and specific genetic markers are effective tools for determining population-specific genomic diversity. Studies on the transcriptome and proteome have identified differentially expressed genes PAS1, CLV1, ATAF1, and ACBF involved in shoot bud formation. The stone pine proteome shows variation among populations and shows the industrial potential of the enzyme pinosylvin. Microsatellite studies have revealed low levels of polymorphism and a unique genetic diversity in stone pine, which may contribute to its environmental adaptation. Transcriptomic and proteomic analyses uncover the genetic and molecular responses of stone pine to fungal infections and nematode infestations, elucidating the defense activation, gene regulation, and the potential role of terpenes in pathogen resistance. Transcriptomics associated with carbohydrate metabolism, dehydrins, and transcription factors show promise as targets for improving stone pine’s drought stress response and water retention capabilities. Stone pine presents itself as an important model tree for studying climate change adaptation due to its characteristics. While knowledge gaps exist, stone pine’s genetic resources hold significant potential, and ongoing advancements in techniques offer prospects for future exploration.

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Section: Stone Pine and Other Related Speciesmentioning

confidence: 99%

Stone Pine (Pinus pinea L.) High-Added-Value Genetics: An Overview

Simões,

Borges,

Grazina

et al. 2024

Genes

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show abstract

“…Breeders conduct targeted breeding work based on the characteristics of phenotypic variations in various germplasm resources, for identifying high-quality genetic trait breeding materials and genetic improvement [ 9 ]. Various research methods have been employed to study the genetic variation of trees, including phenotypic trait measurement, cytological markers, biochemical markers, and molecular markers [ 10 , 11 , 12 ]. Among these methods, the study of phenotypic trait measurement has the advantages of quickness and simplicity.…”

Section: Introductionmentioning

confidence: 99%

Phenotypic Variation Analysis and Excellent Clone Selection of Alnus cremastogyne from Different Provenances

Zheng,

Feng,

et al. 2023

Plants

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Alnus cremastogyne is a rapidly growing broad-leaved tree species that is widely distributed in southwest China. It has a significant economic and ecological value. However, with the expansion of the planting area, the influence of phenotypic variation and differentiation on Alnus cremastogyne has increased, resulting in a continuous decline in its genetic quality. Therefore, it is crucial to investigate the phenotypic variation of Alnus cremastogyne and select excellent breeding materials for genetic improvement. Herein, four growth-related phenotypic traits (diameter at breast height, the height of trees, volume, height under the branches) and twelve reproductive-related phenotypic traits (fresh weight of single cone, dry weight of single cone, seed weight per plant, thousand kernel weight, cone length, cone width, cone length × cone width, fruit shape index, seed rate, germination rate, germination potential, germination index) of 40 clones from four provenances were measured and analyzed. The phenotypic variation was comprehensively evaluated by correlation analysis, principal component analysis and cluster analysis, and excellent clones were selected as breeding materials. The results revealed that there were abundant phenotypic traits variations among and within provenances. Most of the phenotypic traits were highly significant differences (p < 0.01) among provenances. The phenotypic variation among provenances (26.36%) was greater than that of within provenances clones (24.80%). The average phenotypic differentiation coefficient was accounted for 52.61% among provenances, indicating that the phenotypic variation mainly came from among provenances. The coefficient of variation ranged from 9.41% (fruit shape index) to 97.19% (seed weight per plant), and the repeatability ranged from 0.36 (volume) to 0.77 (cone width). Correlation analysis revealed a significantly positive correlation among most phenotypic traits. In principal component analysis, the cumulative contribution rate of the first three principal components was 79.18%, representing the main information on the measured phenotypic traits. The cluster analysis revealed four groups for the 40 clones. Group I and group II exhibited better performance phenotypic traits as compared with group III and group IV. In addition, the four groups are not clearly clustered following the distance from the provenance. Employing the multi-trait comprehensive evaluation method, 12 excellent clones were selected, and the average genetic gain for each phenotypic trait ranged from 4.78% (diameter at breast height) to 32.05% (dry weight of single cone). These selected excellent clones can serve as candidate materials for the improvement and transformation of Alnus cremastogyne seed orchards. In addition, this study can also provide a theoretical foundation for the genetic improvement, breeding, and clone selection of Alnus cremastogyne.

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Design and Optimizing of Precision Seeder of Pinus sylvestris var. mongolica L. Bud-Seeds for Containerized Nursery Production

Miao,

2024

j biobased mat bioenergy

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Mongolian pine holds immense ecological and economic values as a vital biobased material. Its wood fiber, rosin and turpentine are important raw materials suitable for multiple industrial applications, it also exhibited soil and water conservation capabilities. To improve its seeding efficiency, this study designed a precision seeding machine for Mongolian pine (Pinus sylvestris var. mongolica L.) bud-seeds, and optimized the technical seeding parameters, which utilized a combined vibration-air blowing fluidization device to overcome seed flowability limitations and facilitate accurate seed selection. A particle model was established based on the seeds’ physical characteristics, and EDEM software was utilized to simulate the spatial distribution of seed particles under various seeding parameters through seeding experiments. The optimal air pressure for the combined seed supply was approximately 0.24 kPa, with a frequency of 20 Hz and an amplitude of 5 mm, to obtain an optimal spatial distribution of the seed particles. The most effective seeding area for seed adhesion was determined to be 5–15 mm from the bottom of the seeding plate. When the seed suction negative pressure is set to 6.7 kPa, with an upper hole diameter of 0.9 mm, a lower hole diameter of 3 mm, and a hole depth of 1.5 mm, the seedling emergence rate reached 89.06%, and the fastest emergence time was 2 days. One month after sowing, the seedlings exhibited a height growth rate of 16.1%, and a ground diameter growth rate of 20.9%. This study demonstrates the effectiveness of the precision seeding machine and optimized parameters in achieving efficient and accurate sowing of Mongolian pine bud-seeds. This work provides basic technical and data support for advancing the development and sustainable utilization of Mongolian pine as a vital biobased material resource.

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Conservation of Genetic Diversity of Scots Pine (Pinus sylvestris L.) in a Central European National Park Based on cpDNA Studies

Cited by 6 publications

References 37 publications

Stone Pine (Pinus pinea L.) High-Added-Value Genetics: An Overview

Stone Pine (Pinus pinea L.) High-Added-Value Genetics: An Overview

Phenotypic Variation Analysis and Excellent Clone Selection of Alnus cremastogyne from Different Provenances

Design and Optimizing of Precision Seeder of Pinus sylvestris var. mongolica L. Bud-Seeds for Containerized Nursery Production

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