@article{feng_genetic_2026,
	title = {Genetic structure and diversity of four {Chinese} fir breeding populations over 60 years},
	volume = {22},
	issn = {1614-2950},
	url = {https://doi.org/10.1007/s11295-026-01750-z},
	doi = {10.1007/s11295-026-01750-z},
	abstract = {Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) is the most commercially important conifer species in southern China. Since 2015, the Fujian Province has launched its fourth cycle of genetic improvement, yet the impact of intensive artificial selection for growth and wood quality traits on the genetic diversity of advanced-cycle populations remains unclear. In this study, genotyping-by-sequencing (GBS) was used to genotype 310 individuals sampled from four consecutive breeding populations (first to fourth cycle). Across cycles, diversity indices remained relatively stable, with the fourth-cycle population showing slightly higher values (Ho = 0.325, He = 0.272). The broadening of breeding objectives to include wood quality and resistance traits, together with the introduction of external elite germplasm from the second cycle onward, may have contributed to this balance. Consequently, genetic differentiation among the populations from different breeding cycles was minimal (Fst {\textless} 0.01). Comparison of the genomic and pedigree-based relationship matrices revealed discrepancies for some pairs, indicating that genomic estimates provide complementary information for characterizing relatedness. Overall, genetic diversity was maintained across the four breeding cycles. These results provide a genomic basis for managing genetic diversity and relatedness in advanced-cycle Chinese fir breeding.},
	language = {en},
	number = {5},
	urldate = {2026-09-02},
	journal = {Tree Genetics \& Genomes},
	author = {Feng, Qihang and Chen, Zhi-Qiang and Zhao, Benwen and Zhang, Long and Su, Shunde and Zhang, Xie and Chen, Yu and El-Kassaby, Yousry A. and Wu, Harry X. and Bian, Liming},
	month = aug,
	year = {2026},
	keywords = {Breeding population, Chinese fir, Genetic diversity, Genomic kinship},
	pages = {29},
}

Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) is the most commercially important conifer species in southern China. Since 2015, the Fujian Province has launched its fourth cycle of genetic improvement, yet the impact of intensive artificial selection for growth and wood quality traits on the genetic diversity of advanced-cycle populations remains unclear. In this study, genotyping-by-sequencing (GBS) was used to genotype 310 individuals sampled from four consecutive breeding populations (first to fourth cycle). Across cycles, diversity indices remained relatively stable, with the fourth-cycle population showing slightly higher values (Ho = 0.325, He = 0.272). The broadening of breeding objectives to include wood quality and resistance traits, together with the introduction of external elite germplasm from the second cycle onward, may have contributed to this balance. Consequently, genetic differentiation among the populations from different breeding cycles was minimal (Fst \textless 0.01). Comparison of the genomic and pedigree-based relationship matrices revealed discrepancies for some pairs, indicating that genomic estimates provide complementary information for characterizing relatedness. Overall, genetic diversity was maintained across the four breeding cycles. These results provide a genomic basis for managing genetic diversity and relatedness in advanced-cycle Chinese fir breeding.

@article{rodriguez_comparative_2026,
	title = {Comparative regulomics of wood formation across dicot and conifer trees},
	volume = {17},
	copyright = {2026 The Author(s)},
	issn = {2041-1723},
	url = {https://www.nature.com/articles/s41467-026-75624-2},
	doi = {10.1038/s41467-026-75624-2},
	abstract = {Understanding the regulatory program underlying wood formation is key to improving biomass production and carbon sequestration in trees. However, how wood formation evolved and how these programs have been rewired across lineages remains unclear. Here, we present the first high-spatial-resolution evo-devo resource for wood transcriptomes spanning multiple dicots and conifers, representing the two major tree-containing lineages separated by more than 300 million years of evolution. Using orthology-aware co-expression network analysis, we identified genes with conserved and lineage-specific expression patterns. By integrating chromatin accessibility data and transcription factor motif analysis, we further inferred candidate regulatory networks for xylem differentiation and secondary cell wall formation. We demonstrate how this dataset can be used to answer long standing questions in wood biology related to differences in acetylation of cell wall polymers and master regulators of xylem specification across dicot and conifer tree species. The data offer a resource for the tree biology and evo-devo communities, and are publicly available at PlantGenIE.org.},
	language = {en},
	number = {1},
	urldate = {2026-09-02},
	journal = {Nature Communications},
	publisher = {Nature Publishing Group},
	author = {Rodriguez, Eduardo and Birkeland, Siri and Chapple, Ellen Dimmen and Fredriksson, Samuel and Carracedo Lorenzo, Zulema and Ahlgren Kalman, Teitur and Kumar, Vikash and Mccann, Jamie and Hill, Jason and Soundiramourtty, Sivagamy and Voxeur, Aline and Røhr, Åsmund Kjendseth and Tuominen, Hannele and Mellerowicz, Ewa J. and Street, Nathaniel R. and Hvidsten, Torgeir R.},
	month = jul,
	year = {2026},
	keywords = {Comparative genomics, Gene regulatory networks, Plant evolution, Plant genetics},
	pages = {8916},
}

Understanding the regulatory program underlying wood formation is key to improving biomass production and carbon sequestration in trees. However, how wood formation evolved and how these programs have been rewired across lineages remains unclear. Here, we present the first high-spatial-resolution evo-devo resource for wood transcriptomes spanning multiple dicots and conifers, representing the two major tree-containing lineages separated by more than 300 million years of evolution. Using orthology-aware co-expression network analysis, we identified genes with conserved and lineage-specific expression patterns. By integrating chromatin accessibility data and transcription factor motif analysis, we further inferred candidate regulatory networks for xylem differentiation and secondary cell wall formation. We demonstrate how this dataset can be used to answer long standing questions in wood biology related to differences in acetylation of cell wall polymers and master regulators of xylem specification across dicot and conifer tree species. The data offer a resource for the tree biology and evo-devo communities, and are publicly available at PlantGenIE.org.

@article{liu_loss_2026,
	title = {Loss of function of the {AP2}/{ERF} transcription factor {StGAME9} abolishes activation and induction of steroidal glycoalkaloid biosynthesis in potato plants},
	volume = {237},
	issn = {0981-9428},
	url = {https://www.sciencedirect.com/science/article/pii/S0981942826005474},
	doi = {10.1016/j.plaphy.2026.111561},
	abstract = {Steroidal glycoalkaloids (SGAs) are toxic defense substances present in certain species of the Solanaceae, including major crops such as eggplant, tomato, and potato. GLYCOALKALOID METABOLISM 9 (GAME9) was first identified in tomato and potato as an APETALA 2/ETHYLENE RESPONSE FACTOR (AP2/ERF) transcription factor regulating key genes in SGA biosynthesis. However, the spatial effects of endogenous GAME9 in potato remain largely unexplored, particularly in tubers, highlighting a knowledge gap in understanding activation and induction of SGA biosynthesis in this important staple food crop. Here, we generated StGAME9 knockout mutants in potato via DNA-free CRISPR/Cas9. Compared to the wild type, knockout mutants contained significantly reduced SGA levels in leaves, and were almost free of SGAs in tubers. Notably, SGA accumulation remained minimal in the mutant tubers even under two SGA-inducing conditions; wounding and light exposure, indicating a loss of inducible SGA biosynthesis. Integrated transcriptomic and metabolomic characterization of knockout mutants (Stgame9) revealed extensive reprogramming of gene expression and metabolism, affecting not only SGA and sterol pathways but also a broader range of metabolic processes, with stress-related metabolic responses being attenuated in Stgame9 tubers. Despite these changes, Stgame9 plants displayed a normal growth phenotype under both greenhouse and field conditions. Our findings substantiate a pivotal role of GAME9 in potato for the regulation of basal and induced SGA biosynthesis. The results further indicate that StGAME9 is involved in the regulation of a broader, complex, and interconnected network along biosynthetic pathways, where potato metabolism exhibits substantial robustness and compensatory capacity to buffer the loss of StGAME9.},
	urldate = {2026-09-02},
	journal = {Plant Physiology and Biochemistry},
	author = {Liu, Ying and Merino, Irene and Potgieter, Lizel and Flöhr, Adam and Johansson, Annika I. and Andersson, Mariette and Sitbon, Folke and Hofvander, Per},
	month = aug,
	year = {2026},
	keywords = {AP2/ERF transcription factor, Abiotic stress, Glycoalkaloids, Metabolomics, Potato (), Transcriptomics},
	pages = {111561},
}

Steroidal glycoalkaloids (SGAs) are toxic defense substances present in certain species of the Solanaceae, including major crops such as eggplant, tomato, and potato. GLYCOALKALOID METABOLISM 9 (GAME9) was first identified in tomato and potato as an APETALA 2/ETHYLENE RESPONSE FACTOR (AP2/ERF) transcription factor regulating key genes in SGA biosynthesis. However, the spatial effects of endogenous GAME9 in potato remain largely unexplored, particularly in tubers, highlighting a knowledge gap in understanding activation and induction of SGA biosynthesis in this important staple food crop. Here, we generated StGAME9 knockout mutants in potato via DNA-free CRISPR/Cas9. Compared to the wild type, knockout mutants contained significantly reduced SGA levels in leaves, and were almost free of SGAs in tubers. Notably, SGA accumulation remained minimal in the mutant tubers even under two SGA-inducing conditions; wounding and light exposure, indicating a loss of inducible SGA biosynthesis. Integrated transcriptomic and metabolomic characterization of knockout mutants (Stgame9) revealed extensive reprogramming of gene expression and metabolism, affecting not only SGA and sterol pathways but also a broader range of metabolic processes, with stress-related metabolic responses being attenuated in Stgame9 tubers. Despite these changes, Stgame9 plants displayed a normal growth phenotype under both greenhouse and field conditions. Our findings substantiate a pivotal role of GAME9 in potato for the regulation of basal and induced SGA biosynthesis. The results further indicate that StGAME9 is involved in the regulation of a broader, complex, and interconnected network along biosynthetic pathways, where potato metabolism exhibits substantial robustness and compensatory capacity to buffer the loss of StGAME9.

@article{bhowmick_additional_2026,
	title = {An additional water is introduced into the manganese cluster during the formation of the {S3} state of photosystem {II}},
	volume = {17},
	copyright = {2026 The Author(s)},
	issn = {2041-1723},
	url = {https://www.nature.com/articles/s41467-026-76805-9},
	doi = {10.1038/s41467-026-76805-9},
	abstract = {During photosynthetic water oxidation, the Mn4Ca cluster in Photosystem II progresses through five intermediate Si (i = 0–4) states. X-ray crystallography studies have reported the insertion of one new O ligand during the formation of the S3 state, but recent studies question the presence of this additional ligand based on cryo-EM and earlier room-temperature crystallography data. There is also controversy about whether the O-O bond interaction already occurs in the S3 state or in the subsequent S3 to S0 transition. Here we report conventional high-resolution data for the S1, S2, and S3 states to a resolution of {\textasciitilde}1.9 Å, and anomalous diffraction data at two energies (9.5 keV and 7 keV), that was used to model the Mn positions, followed by determination of oxygen positions using the high-resolution maps. We show that the new oxygen atom, OX (or O6), in the S3 state is observable as a distinct peak without any restraints, confirming its ligation to Mn1 and Ca. The OX-O5 distance is {\textasciitilde}2.1 Å, supporting no strong interaction between them in the S3 state, suggesting that if this is the O-O bond formation site, it is formed during the S3 to S0 transition initiated by the final oxidation of the cluster.},
	language = {en},
	number = {1},
	urldate = {2026-09-02},
	journal = {Nature Communications},
	publisher = {Nature Publishing Group},
	author = {Bhowmick, Asmit and Zhang, Miao and Simon, Philipp S. and Makita, Hiroki and Nangca, Isabela I. and Szilagyi, Erzsi and Kretzschmar, Moritz and Doyle, Margaret D. and Minnetian, Natalie M. and Hussein, Rana and Hart, Olli and Chatterjee, Kuntal and Aydin, A. Orkun and Shevela, Dmitry and Cheah, Mun Hon and Croy, Nicholas and Chernev, Petko and Fransson, Thomas and Tiwari, Vandana and Sanchez, Humberto and Schleissner, Pamela and Lemons, Randy and Gate, Greg and Henstridge, Meredith and Glownia, James M. and Poitevin, Frédéric and Rosenberg, Daniel J. and Dehe, Sebastian and Gee, Leland B. and Tono, Kensuke and Owada, Shigeki and Oggenfuss, Roland and Ozerov, Dmitry and Sander, Mathias and Mankowsky, Roman and Lemke, Henrik T. and Young, Iris D. and Holton, James M. and Mittan-Moreau, David W. and Paley, Daniel W. and Afonine, Pavel V. and Moriarty, Nigel W. and Adams, Paul D. and Mamedov, Fikret and Dobbek, Holger and Zouni, Athina and Alonso-Mori, Roberto and Bergmann, Uwe and Brewster, Aaron S. and Sauter, Nicholas K. and Messinger, Johannes and Kern, Jan F. and Yachandra, Vittal K. and Yano, Junko},
	month = aug,
	year = {2026},
	keywords = {Bioenergetics, Physical chemistry, Structural biology},
	pages = {8818},
}

During photosynthetic water oxidation, the Mn4Ca cluster in Photosystem II progresses through five intermediate Si (i = 0–4) states. X-ray crystallography studies have reported the insertion of one new O ligand during the formation of the S3 state, but recent studies question the presence of this additional ligand based on cryo-EM and earlier room-temperature crystallography data. There is also controversy about whether the O-O bond interaction already occurs in the S3 state or in the subsequent S3 to S0 transition. Here we report conventional high-resolution data for the S1, S2, and S3 states to a resolution of ~1.9 Å, and anomalous diffraction data at two energies (9.5 keV and 7 keV), that was used to model the Mn positions, followed by determination of oxygen positions using the high-resolution maps. We show that the new oxygen atom, OX (or O6), in the S3 state is observable as a distinct peak without any restraints, confirming its ligation to Mn1 and Ca. The OX-O5 distance is ~2.1 Å, supporting no strong interaction between them in the S3 state, suggesting that if this is the O-O bond formation site, it is formed during the S3 to S0 transition initiated by the final oxidation of the cluster.

@article{wu_integrating_2026,
	title = {Integrating {GWAS}-guided markers preselection with genomic selection enhances prediction of pulpwood-related traits in slash pine ({Pinus} elliottii {Englem}.)},
	volume = {26},
	issn = {1471-2229},
	url = {https://doi.org/10.1186/s12870-026-09114-4},
	doi = {10.1186/s12870-026-09114-4},
	abstract = {This study aimed to enhance the efficiency of genomic prediction for pulpwood-related traits in slash pine (Pinus elliottii Engelm. var. elliottii) by integrating genome-wide association study (GWAS) information with genomic selection (GS). We evaluated 12 traits related to growth, fiber, and wood chemical composition in a population of 340 individuals genotyped with 319,286 high-quality SNPs, comparing the performance of six GS models, including GBLUP and Bayesian methods, under varying training population sizes and marker densities. The results showed that while both GBLUP and Bayesian Lasso performed well, Bayesian Lasso slightly outperformed GBLUP for fiber traits. Predictive ability (PA) plateaued at approximately 100 K SNPs for fiber traits, 60 K for DBH, and 10 K for wood chemical composition traits in all models. Using 100 K random SNPs, PA ranged from 0.05 to 0.23, which expanded to 0.09–0.35 with GWAS-guided SNP preselection (maximum improvement of 16.26\%) and further broadened to 0.01–0.38 by incorporating large-effect QTLs (greatest improvement of 23.54\%). Overall, integrating GWAS information into GS frameworks significantly improved prediction accuracy as assessed by t-test, offering a cost-effective strategy to accelerate genetic improvement. These findings provide practical guidance for enhancing breeding efficiency in slash pine and other conifer breeding programs.},
	language = {en},
	number = {1},
	urldate = {2026-08-17},
	journal = {BMC Plant Biology},
	author = {Wu, Yadi and Ding, Xianyin and Diao, Shu and Huang, Qinyun and Shang, Guiqi and Tan, Zifeng and Wu, Shaoze and Hua, Xiahui and He, Chengbo and Luan, Qifu and Chen, Zhi-Qiang and Wu, Harry X.},
	month = may,
	year = {2026},
	keywords = {Bayesian Lasso, Genomic selection, Pulpwood properties, SNP preselection, Slash pine},
	pages = {1271},
}

This study aimed to enhance the efficiency of genomic prediction for pulpwood-related traits in slash pine (Pinus elliottii Engelm. var. elliottii) by integrating genome-wide association study (GWAS) information with genomic selection (GS). We evaluated 12 traits related to growth, fiber, and wood chemical composition in a population of 340 individuals genotyped with 319,286 high-quality SNPs, comparing the performance of six GS models, including GBLUP and Bayesian methods, under varying training population sizes and marker densities. The results showed that while both GBLUP and Bayesian Lasso performed well, Bayesian Lasso slightly outperformed GBLUP for fiber traits. Predictive ability (PA) plateaued at approximately 100 K SNPs for fiber traits, 60 K for DBH, and 10 K for wood chemical composition traits in all models. Using 100 K random SNPs, PA ranged from 0.05 to 0.23, which expanded to 0.09–0.35 with GWAS-guided SNP preselection (maximum improvement of 16.26%) and further broadened to 0.01–0.38 by incorporating large-effect QTLs (greatest improvement of 23.54%). Overall, integrating GWAS information into GS frameworks significantly improved prediction accuracy as assessed by t-test, offering a cost-effective strategy to accelerate genetic improvement. These findings provide practical guidance for enhancing breeding efficiency in slash pine and other conifer breeding programs.