@article{cainzos_loss_2026,
	title = {Loss of {qE} {Does} {Not} {Necessarily} {Lead} to {Photoinhibition}: {Sustained} {Non}-{Photochemical} {Quenching} in the {Absence} of {PsbS} and {Zeaxanthin}},
	volume = {49},
	copyright = {© 2026 The Author(s). Plant, Cell \& Environment published by John Wiley \& Sons Ltd.},
	issn = {1365-3040},
	shorttitle = {Loss of {qE} {Does} {Not} {Necessarily} {Lead} to {Photoinhibition}},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/pce.70477},
	doi = {10.1111/pce.70477},
	abstract = {Photosynthetic light-harvesting complexes mediate light absorption and energy dissipation. By modulating the photosystems' absorption cross-section, they affect both photosynthetic activity and non-photochemical quenching (NPQ). These processes are often studied by spectrally integrated chlorophyll fluorescence, masking their associated spectral information. We explore in Aspen and Arabidopsis npq mutants how qE affects the development of NPQ spectra under two contrasting conditions: in the absence and the presence of photoinhibition. We introduce a new parameter, the development of new emitting species (NESD), during time- and spectrally resolved NPQ inductions, and develop a pipeline to resolve PSII energy-partitioning heterogeneity. LHCII, PsbS, and zeaxanthin are required for NESD. Combining gas exchange, P700 oxidation, and spectrally resolved kinetics, we show that under photoinhibitory conditions, NES can develop even without PsbS or zeaxanthin, producing sustained quenching independent of photoinhibition of PSII or PSI. Furthermore, the absence of LHCII and CURVATURE THYLAKOID 1 leads to increased photoinhibition, indicating that long-term photoprotection relies on LHCII and thylakoid plasticity, whereas PsbS and zeaxanthin mainly facilitate LHCII-dependent quenching. Finally, we show the limitations of traditional parameters in discriminating between photoinhibition and photoprotective sustained quenching and propose time-resolved monitoring of CO₂ assimilation and Y(II) for their accurate assessment.},
	language = {en},
	number = {6},
	urldate = {2026-05-15},
	journal = {Plant, Cell \& Environment},
	author = {Cainzos, Maximiliano and Hu, Chen and Pissolato, Maria Dolores and Fataftah, Nazeer and Nanda, Sanchali and Jansson, Stefan},
	year = {2026},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/pce.70477},
	keywords = {NPQ, high light, new emitting species development, photoinhibition, photosynthesis: carbon reactions, photosynthesis: electron transport, sustained quenching},
	pages = {3405--3425},
}

Photosynthetic light-harvesting complexes mediate light absorption and energy dissipation. By modulating the photosystems' absorption cross-section, they affect both photosynthetic activity and non-photochemical quenching (NPQ). These processes are often studied by spectrally integrated chlorophyll fluorescence, masking their associated spectral information. We explore in Aspen and Arabidopsis npq mutants how qE affects the development of NPQ spectra under two contrasting conditions: in the absence and the presence of photoinhibition. We introduce a new parameter, the development of new emitting species (NESD), during time- and spectrally resolved NPQ inductions, and develop a pipeline to resolve PSII energy-partitioning heterogeneity. LHCII, PsbS, and zeaxanthin are required for NESD. Combining gas exchange, P700 oxidation, and spectrally resolved kinetics, we show that under photoinhibitory conditions, NES can develop even without PsbS or zeaxanthin, producing sustained quenching independent of photoinhibition of PSII or PSI. Furthermore, the absence of LHCII and CURVATURE THYLAKOID 1 leads to increased photoinhibition, indicating that long-term photoprotection relies on LHCII and thylakoid plasticity, whereas PsbS and zeaxanthin mainly facilitate LHCII-dependent quenching. Finally, we show the limitations of traditional parameters in discriminating between photoinhibition and photoprotective sustained quenching and propose time-resolved monitoring of CO₂ assimilation and Y(II) for their accurate assessment.

@article{forsman_structure_2026,
	title = {The structure of intact and active {Photosystem} {II} from {Arabidopsis} thaliana at 2.44 Å resolution},
	volume = {250},
	copyright = {© 2026 The Author(s). New Phytologist © 2026 New Phytologist Foundation.},
	issn = {1469-8137},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/nph.71085},
	doi = {10.1111/nph.71085},
	abstract = {Photosystem II (PS II) is a large membrane-bound protein complex that catalyses light-driven water oxidation in plants and cyanobacteria. The structure of PS II is well studied in cyanobacteria; however, there are very few PS II structures from plants. The currently available plant PS II structures are comparatively low resolution and are frequently incomplete, that is, missing subunits or cofactors. We optimized the procedure for isolating PS II from Arabidopsis thaliana and employed cryo-electron microscopy to generate a high-resolution structure of an intact and oxygen-evolving PS II from Arabidopsis thaliana at 2.44 Å resolution, which to date represents the highest resolution structure of PS II from higher plants. At this resolution, many water molecules within the PS II structure can be detected, including waters around the water-splitting manganese cluster, the nonheme iron, and within the water/proton channels connecting these active sites to the protein exterior, allowing for the first detailed description of the water networks in Arabidopsis thaliana and comparison with the highly resolved cyanobacterial PS II. Our findings further the understanding of design principles of protein–water–cofactor interactions in photosynthetic water splitting, quinone reduction/exchange, and about the role of lipids at the interface between PS II and the light-harvesting proteins.},
	language = {en},
	number = {5},
	urldate = {2026-05-15},
	journal = {New Phytologist},
	author = {Forsman, Jack and Graça, André T. and Aydin, Abuzer Orkun and Hall, Michael and Hussein, Rana and Schröder, Wolfgang P. and Messinger, Johannes},
	year = {2026},
	note = {\_eprint: https://nph.onlinelibrary.wiley.com/doi/pdf/10.1111/nph.71085},
	keywords = {Arabidopsis thaliana, Cryo-EM, Photosystem II structure, manganese cluster, photosynthesis, protein–water–cofactor interactions, water channels},
	pages = {3014--3025},
}

Photosystem II (PS II) is a large membrane-bound protein complex that catalyses light-driven water oxidation in plants and cyanobacteria. The structure of PS II is well studied in cyanobacteria; however, there are very few PS II structures from plants. The currently available plant PS II structures are comparatively low resolution and are frequently incomplete, that is, missing subunits or cofactors. We optimized the procedure for isolating PS II from Arabidopsis thaliana and employed cryo-electron microscopy to generate a high-resolution structure of an intact and oxygen-evolving PS II from Arabidopsis thaliana at 2.44 Å resolution, which to date represents the highest resolution structure of PS II from higher plants. At this resolution, many water molecules within the PS II structure can be detected, including waters around the water-splitting manganese cluster, the nonheme iron, and within the water/proton channels connecting these active sites to the protein exterior, allowing for the first detailed description of the water networks in Arabidopsis thaliana and comparison with the highly resolved cyanobacterial PS II. Our findings further the understanding of design principles of protein–water–cofactor interactions in photosynthetic water splitting, quinone reduction/exchange, and about the role of lipids at the interface between PS II and the light-harvesting proteins.

@article{zhu_mmgs_2026,
	title = {{MMGS}: a novel genomic prediction framework to integrate genotype, environment and their interactions for multi-environment breeding trials},
	volume = {13},
	issn = {2662-6810},
	shorttitle = {{MMGS}},
	url = {https://doi.org/10.1093/hr/uhag035},
	doi = {10.1093/hr/uhag035},
	abstract = {Accurately predicting the performance of trees and crops across diverse and changing climates is essential for matching genotypes to both current and future environments. Yet modelling the complex interplay among genotype, environment, and phenotype in multi-environment trials remains a major challenge. Here, we introduce a unified framework, polygenic environmental interaction (PEI), directly models genotype-by-environment interactions through integrating genotypes and environmental covariates. We implemented an ensemble of 15 estimators spanning parametric, non-parametric, and machine-learning approaches. We then benchmarked our framework against the classical reaction norm (RN) using three genetically distinct populations and three traits with variable genetic architectures. Furthermore, we released an open-source R package, Multiple-environments genomic selection (MMGS), on GitHub. Together, our study offers a flexible and computationally efficient approach for multi-environment genomic prediction, enhancing breeding efficiency, providing deeper insights into modelling the genotype-environment-phenotype continuum.},
	number = {5},
	urldate = {2026-05-15},
	journal = {Horticulture Research},
	author = {Zhu, Mingjia and Zheng, Zeyu and Liu, Wei and Han, Yu and Mou, Wenjie and Yin, Tongming and Dai, Xiaogang and Wu, Huaitong and Yang, Yongzhi and Zan, Yanjun and Liu, Jianquan},
	month = may,
	year = {2026},
	pages = {uhag035},
}

Accurately predicting the performance of trees and crops across diverse and changing climates is essential for matching genotypes to both current and future environments. Yet modelling the complex interplay among genotype, environment, and phenotype in multi-environment trials remains a major challenge. Here, we introduce a unified framework, polygenic environmental interaction (PEI), directly models genotype-by-environment interactions through integrating genotypes and environmental covariates. We implemented an ensemble of 15 estimators spanning parametric, non-parametric, and machine-learning approaches. We then benchmarked our framework against the classical reaction norm (RN) using three genetically distinct populations and three traits with variable genetic architectures. Furthermore, we released an open-source R package, Multiple-environments genomic selection (MMGS), on GitHub. Together, our study offers a flexible and computationally efficient approach for multi-environment genomic prediction, enhancing breeding efficiency, providing deeper insights into modelling the genotype-environment-phenotype continuum.

@article{soro_minimum_2026,
	title = {Minimum marker densities for accurate genomic predictions and heritability estimates in three major {North} {American} and {European} spruce species},
	copyright = {2026 His Majesty the King in Right of Canada, as represented by the Minister of Natural Resources and the Authors},
	issn = {1365-2540},
	url = {https://www.nature.com/articles/s41437-026-00836-7},
	doi = {10.1038/s41437-026-00836-7},
	abstract = {Genomic selection (GS) is being increasingly used in tree breeding with the aim to accelerate genetic gains by shortening the long breeding cycles. However, high genotyping costs remain a challenge. This study aimed to determine the optimal marker density in genome coverage to maximize GS accuracy and precision of heritability estimates for growth and wood quality traits. Thousands of SNPs representative of the exome of three major spruce species were used: 18,275 SNPs for black spruce (representing 10,894 distinct gene loci), 11,328 SNPs for white spruce (8647 gene loci), and 116,765 SNPs for Norway spruce (20,695 gene loci). For each species, a similar experimental design was used with related full-sib families replicated on two sites, and GBLUP prediction models were developed. The effect of varying the number of SNPs was examined by resampling subsets from 500 to 100,000 SNPs. Results indicated that plateaus in heritability estimates were reached as the marker density increased, stabilizing between 4000 and 8000 SNPs for a spruce genome size of around 2000 centimorgans, a trend consistent across all traits and species. Predictive ability and prediction accuracy both increased with the number of SNPs up to a similar level, beyond which further improvements were marginal. Such minimum marker densities should be financially affordable for most spruce breeding programs, striking a balance between the need for maximizing GS accuracy and that for minimizing genotyping costs. These findings should support the further deployment of GS in conifer breeding programs, with high selection precision and by reducing the financial burden of very high-density SNP coverage, even for conifers characterized by large giga-genomes.},
	language = {en},
	urldate = {2026-05-15},
	journal = {Heredity},
	publisher = {Nature Publishing Group},
	author = {Soro, André and Lenz, Patrick and Beaulieu, Jean and Laverdière, Jean-Philippe and Nadeau, Simon and Gagnon, France and Ogut, Funda and Wu, Harry X. and Perron, Martin and Bousquet, Jean},
	month = may,
	year = {2026},
	keywords = {Comparative genomics, Ecological genetics, Forestry},
	pages = {1--16},
}

Genomic selection (GS) is being increasingly used in tree breeding with the aim to accelerate genetic gains by shortening the long breeding cycles. However, high genotyping costs remain a challenge. This study aimed to determine the optimal marker density in genome coverage to maximize GS accuracy and precision of heritability estimates for growth and wood quality traits. Thousands of SNPs representative of the exome of three major spruce species were used: 18,275 SNPs for black spruce (representing 10,894 distinct gene loci), 11,328 SNPs for white spruce (8647 gene loci), and 116,765 SNPs for Norway spruce (20,695 gene loci). For each species, a similar experimental design was used with related full-sib families replicated on two sites, and GBLUP prediction models were developed. The effect of varying the number of SNPs was examined by resampling subsets from 500 to 100,000 SNPs. Results indicated that plateaus in heritability estimates were reached as the marker density increased, stabilizing between 4000 and 8000 SNPs for a spruce genome size of around 2000 centimorgans, a trend consistent across all traits and species. Predictive ability and prediction accuracy both increased with the number of SNPs up to a similar level, beyond which further improvements were marginal. Such minimum marker densities should be financially affordable for most spruce breeding programs, striking a balance between the need for maximizing GS accuracy and that for minimizing genotyping costs. These findings should support the further deployment of GS in conifer breeding programs, with high selection precision and by reducing the financial burden of very high-density SNP coverage, even for conifers characterized by large giga-genomes.

@article{bizjak-johansson_norway_2026,
	title = {Norway {Spruce} and {Scots} {Pine} {Fungal} and {Bacterial} {Microbiomes} in a {Boreal} {Forest} {Common} {Garden} {Experiment}},
	volume = {17},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {1999-4907},
	url = {https://www.mdpi.com/1999-4907/17/4/446},
	doi = {10.3390/f17040446},
	abstract = {Soil- and plant-associated fungi and bacteria are an important part of many ecosystems as they can affect plant health, growth and stress tolerance. However, it remains poorly understood whether the microbiomes differ between conifer species growing in the same site conditions and between tree ecosystem compartments. The main aim of the study was to describe and compare the microbiomes of Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) H. Karst.), growing in a boreal forest common garden experiment on adjacent forest plots, to analyse the tree species effect on the composition of the needle and surface soil organic-mineral horizon microbiomes. The needle and surface soil organic-mineral horizon bacterial and fungal microbiomes were simultaneously analysed by full-length 16S and ITS sequencing on a long-read sequencing platform; however, the bacterial analysis was restricted to soil samples. The highly abundant bacterial phyla in both pine and spruce soil were Actinomycetota, Pseudomonadota, Planctomycetota and Acidobacteriota. The dominant fungal phyla in pine and spruce surface organic-mineral soil was Basidiomycota, while the needles were dominated by Ascomycota. The results showed an effect of tree species on the soil bacterial and fungal microbiomes and needle fungal microbiomes based on alpha diversity, which was higher for Norway spruce compared to Scots pine. The results indicated that Norway spruce might be able to support higher microbial diversity, which could potentially be due to differences in needle longevity, root exudates, litter input and its degradation, between pine and spruce. Furthermore, the results indicated distinct microbiomes between the soil and needle compartments.},
	language = {en},
	number = {4},
	urldate = {2026-05-06},
	journal = {Forests},
	publisher = {Multidisciplinary Digital Publishing Institute},
	author = {Bizjak-Johansson, Tinkara and Larsson, Marcus and Gundale, Michael J. and Nordin, Annika},
	month = apr,
	year = {2026},
	keywords = {Norway spruce, Scots pine, bacteria, boreal forest, fungi, microbiome},
	pages = {446},
}

Soil- and plant-associated fungi and bacteria are an important part of many ecosystems as they can affect plant health, growth and stress tolerance. However, it remains poorly understood whether the microbiomes differ between conifer species growing in the same site conditions and between tree ecosystem compartments. The main aim of the study was to describe and compare the microbiomes of Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) H. Karst.), growing in a boreal forest common garden experiment on adjacent forest plots, to analyse the tree species effect on the composition of the needle and surface soil organic-mineral horizon microbiomes. The needle and surface soil organic-mineral horizon bacterial and fungal microbiomes were simultaneously analysed by full-length 16S and ITS sequencing on a long-read sequencing platform; however, the bacterial analysis was restricted to soil samples. The highly abundant bacterial phyla in both pine and spruce soil were Actinomycetota, Pseudomonadota, Planctomycetota and Acidobacteriota. The dominant fungal phyla in pine and spruce surface organic-mineral soil was Basidiomycota, while the needles were dominated by Ascomycota. The results showed an effect of tree species on the soil bacterial and fungal microbiomes and needle fungal microbiomes based on alpha diversity, which was higher for Norway spruce compared to Scots pine. The results indicated that Norway spruce might be able to support higher microbial diversity, which could potentially be due to differences in needle longevity, root exudates, litter input and its degradation, between pine and spruce. Furthermore, the results indicated distinct microbiomes between the soil and needle compartments.