@article{larsson_litter_2026,
	title = {Litter properties influence decomposition more than local soil environment in a boreal tree species common garden experiment},
	volume = {619},
	issn = {0378-1127},
	url = {https://www.sciencedirect.com/science/article/pii/S037811272600592X},
	doi = {10.1016/j.foreco.2026.124094},
	abstract = {Boreal forests store significant quantities of carbon (C), particularly in their soils. Thus, selecting tree species that promote slow decomposition, due to either their inherent litter properties or soil microbial communities, may be a suitable tool to enhance C uptake in boreal forests. In this study we used two common garden experiments and employed a reciprocal litter transplant decomposition experiment using four common Swedish tree species (Betula pendula, Larix sp., Picea abies and Pinus sylvestris), with varying plant economics strategies. We aimed to partition the relative effects of litter quality and soil environment on litter and humus decomposition rates. Our results showed that litter mass loss was much more dependent on tree species than soil environment, a result further reinforced by the lack of tree species differences in the soil microbial community. The rates of decomposition did however appear to converge over time, as humus mass loss was not responsive to either tree species or soil environment. Our result therefore suggests that tree species selection, as a forest management tool, should be based on each species site-specific growth potential, instead of initial differences in decomposition rate, which could serve to maximize the ecosystem C stock and in turn increase the climate benefits of boreal forest.},
	urldate = {2026-07-31},
	journal = {Forest Ecology and Management},
	author = {Larsson, Marcus and Gundale, Michael J. and Bizjak-Johansson, Tinkara and Spitzer, Clydecia M. and Nordin, Annika},
	month = nov,
	year = {2026},
	keywords = {Boreal forest, Decomposition, Leaf litter, Litter quality, Soil carbon, Soil microbial community, Tree species},
	pages = {124094},
}

Boreal forests store significant quantities of carbon (C), particularly in their soils. Thus, selecting tree species that promote slow decomposition, due to either their inherent litter properties or soil microbial communities, may be a suitable tool to enhance C uptake in boreal forests. In this study we used two common garden experiments and employed a reciprocal litter transplant decomposition experiment using four common Swedish tree species (Betula pendula, Larix sp., Picea abies and Pinus sylvestris), with varying plant economics strategies. We aimed to partition the relative effects of litter quality and soil environment on litter and humus decomposition rates. Our results showed that litter mass loss was much more dependent on tree species than soil environment, a result further reinforced by the lack of tree species differences in the soil microbial community. The rates of decomposition did however appear to converge over time, as humus mass loss was not responsive to either tree species or soil environment. Our result therefore suggests that tree species selection, as a forest management tool, should be based on each species site-specific growth potential, instead of initial differences in decomposition rate, which could serve to maximize the ecosystem C stock and in turn increase the climate benefits of boreal forest.

@article{zhou_early_2026,
	title = {{EARLY} {ABORTION} 1 is an evolutionarily conserved gene required for plant reproduction},
	issn = {0022-0957},
	url = {https://doi.org/10.1093/jxb/erag142},
	doi = {10.1093/jxb/erag142},
	abstract = {The functions of approximately one-third of the proteins in the model plant Arabidopsis remain unknown. It is likely that some of the genes encoding these proteins are essential, and thus indispensable for the survival of the plant; furthermore, these genes would be included in the minimum viable set required for plant life. Evolutionarily conserved single copy genes in flowering plants are enriched in essential housekeeping functions. Building on this observation, we designed a reverse genetic screen that focuses on evolutionarily conserved single copy Arabidopsis genes of unknown function with predominant expression in meristematic cells. This approach identified a previously uncharacterized essential Arabidopsis gene, named as EARLY ABORTION 1 (EBO1). Mutation of the EBO1 locus disrupts gametophyte and/or early embryo development, resulting in defective ovule or seed development. A functional fluorescent EBO1 fusion protein was found to localize to the nucleus, and co-immunoprecipitation experiments detected an interaction between EBO1 and Nucleolar Protein 58 (NOP58) and proteins involved in RNA metabolism, chromatin modification, and transcription. The presented results open a new line of investigation into an evolutionarily conserved mechanism involved in the development of both male and female gametophytes as well as seeds.},
	urldate = {2026-04-24},
	journal = {Journal of Experimental Botany},
	author = {Zhou, Jingjing and Wang, Wei and Zhang, Li and Bruce, Ylva and Zhu, Shaochun and Mateus, André and Niittylä, Totte},
	month = mar,
	year = {2026},
	pages = {erag142},
}

The functions of approximately one-third of the proteins in the model plant Arabidopsis remain unknown. It is likely that some of the genes encoding these proteins are essential, and thus indispensable for the survival of the plant; furthermore, these genes would be included in the minimum viable set required for plant life. Evolutionarily conserved single copy genes in flowering plants are enriched in essential housekeeping functions. Building on this observation, we designed a reverse genetic screen that focuses on evolutionarily conserved single copy Arabidopsis genes of unknown function with predominant expression in meristematic cells. This approach identified a previously uncharacterized essential Arabidopsis gene, named as EARLY ABORTION 1 (EBO1). Mutation of the EBO1 locus disrupts gametophyte and/or early embryo development, resulting in defective ovule or seed development. A functional fluorescent EBO1 fusion protein was found to localize to the nucleus, and co-immunoprecipitation experiments detected an interaction between EBO1 and Nucleolar Protein 58 (NOP58) and proteins involved in RNA metabolism, chromatin modification, and transcription. The presented results open a new line of investigation into an evolutionarily conserved mechanism involved in the development of both male and female gametophytes as well as seeds.

@article{vallebueno-estrada_unified_2026,
	title = {Unified {Multi}-{Caller} {Ensemble} ({UME}) {Generates} an {Unbiased} {Maize} {Haplotype} {Map} for {Variable} {Coverage} {Whole} {Genome} {Data}},
	volume = {26},
	copyright = {© 2026 The Author(s). Molecular Ecology Resources published by John Wiley \& Sons Ltd.},
	issn = {1755-0998},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/1755-0998.70150},
	doi = {10.1111/1755-0998.70150},
	abstract = {We present a novel diversity-focused haplotype map (HapMap) that characterizes over 64.5 million maize (Zea mays ssp. mays) single nucleotide polymorphisms (SNPs) genotyped across 818 individuals from diverse backgrounds. This HapMap aims to balance the variation obtained from domesticated landraces and inbred lines, outgroup Zea spp. and more distant Tripsacum spp. in order to minimize ascertainment bias for diversity studies. Included individuals derive from public data from various experimental setups and coverages, which is challenging for standard SNP callers to accommodate. We provide evidence of coverage biases associated with standard callers that influence resulting variation and introduce a novel approach called Unified Multi-Caller Ensemble (UME), which enhances variant calling accuracy in low-coverage and mixed-coverage genomic datasets. UME corrects for coverage bias resulting from inter-sample coverage heterogeneity by leveraging evidence from variant callers with orthogonal strategies, re-calibrating the error probabilities across callers to minimize the impact of error biases inherent to a given caller. It outperforms individual strategies and excels in de novo variant calling, taking advantage of instances of higher depth reads, even in low coverage individuals, while preserving biologically informative variant relationships across coverage levels. An important feature of UME is the independence from population allele frequencies in the discovery panel, thus avoiding ascertainment bias resulting from unbalanced input genetic diversity. Discovered variants are less affected by ascertainment bias because no population filtering is used, and the full diversity of SNPs is retained in the final variant call set to maximize the utility of the dataset for production calling newly sequenced samples. We present a strategy for filtering the recalibrated error profiles that relies on maximizing demographic signals to retain genetic relationships within the population while reducing sequencing error. After the variant discovery phase, we employ the UME production stage, which enriches genotype calling across all coverage levels, benefiting low-coverage samples. Error introduced in this process is removed through subsequent filtering. Using this approach, we generated a coverage bias-controlled maize HapMap database, providing a comprehensive representation of maize accessions and emphasizing landrace diversity. This diverse panel of domesticated maize and outgroups from across the Americas enables accurate genotyping in low-coverage samples while offering crucial context for interpreting diversity, particularly for natural diversity and paleogenomic analyses.},
	language = {en},
	number = {5},
	urldate = {2026-07-31},
	journal = {Molecular Ecology Resources},
	author = {Vallebueno-Estrada, Miguel and Swarts, Kelly},
	year = {2026},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/1755-0998.70150},
	keywords = {HapMap, coverage bias, ensemble approaches, maize, variant calling},
	pages = {e70150},
}

We present a novel diversity-focused haplotype map (HapMap) that characterizes over 64.5 million maize (Zea mays ssp. mays) single nucleotide polymorphisms (SNPs) genotyped across 818 individuals from diverse backgrounds. This HapMap aims to balance the variation obtained from domesticated landraces and inbred lines, outgroup Zea spp. and more distant Tripsacum spp. in order to minimize ascertainment bias for diversity studies. Included individuals derive from public data from various experimental setups and coverages, which is challenging for standard SNP callers to accommodate. We provide evidence of coverage biases associated with standard callers that influence resulting variation and introduce a novel approach called Unified Multi-Caller Ensemble (UME), which enhances variant calling accuracy in low-coverage and mixed-coverage genomic datasets. UME corrects for coverage bias resulting from inter-sample coverage heterogeneity by leveraging evidence from variant callers with orthogonal strategies, re-calibrating the error probabilities across callers to minimize the impact of error biases inherent to a given caller. It outperforms individual strategies and excels in de novo variant calling, taking advantage of instances of higher depth reads, even in low coverage individuals, while preserving biologically informative variant relationships across coverage levels. An important feature of UME is the independence from population allele frequencies in the discovery panel, thus avoiding ascertainment bias resulting from unbalanced input genetic diversity. Discovered variants are less affected by ascertainment bias because no population filtering is used, and the full diversity of SNPs is retained in the final variant call set to maximize the utility of the dataset for production calling newly sequenced samples. We present a strategy for filtering the recalibrated error profiles that relies on maximizing demographic signals to retain genetic relationships within the population while reducing sequencing error. After the variant discovery phase, we employ the UME production stage, which enriches genotype calling across all coverage levels, benefiting low-coverage samples. Error introduced in this process is removed through subsequent filtering. Using this approach, we generated a coverage bias-controlled maize HapMap database, providing a comprehensive representation of maize accessions and emphasizing landrace diversity. This diverse panel of domesticated maize and outgroups from across the Americas enables accurate genotyping in low-coverage samples while offering crucial context for interpreting diversity, particularly for natural diversity and paleogenomic analyses.

@article{hussain_progression_2026,
	title = {The progression of leaf senescence is gated by the cytosolic arginine pool},
	volume = {12},
	copyright = {2026 The Author(s)},
	issn = {2055-0278},
	url = {https://www.nature.com/articles/s41477-026-02328-2},
	doi = {10.1038/s41477-026-02328-2},
	abstract = {Leaf senescence aims to degrade cellular components to recover valuable nutrients and reallocate them to other organs1. Once this remobilization is complete, cells undergo a vacuolar-type of programmed cell death2, ultimately leading to the death of the entire organ. But how do cells from a senescing leaf ‘know’ when to die? If the cell death process per se is initiated too early, remobilization may not be completed, rendering it futile. This suggests the presence of a ‘sensing’ mechanism that coordinates the remobilization phase with the onset of cell death during leaf senescence. Here, using Arabidopsis thaliana functional stay-green mutants, we show that senescing cells are wired to metabolically dissipate the cytosolic arginine pool, which otherwise represses the progression of leaf senescence. We propose a model in which a senescing cell uses this pool as a proxy for the completion of nitrogen remobilization and to accurately time the subsequent induction of cell death.},
	language = {en},
	number = {7},
	urldate = {2026-07-24},
	journal = {Nature Plants},
	publisher = {Nature Publishing Group},
	author = {Hussain, Shah and Boussardon, Clément and Keech, Olivier},
	month = jul,
	year = {2026},
	keywords = {Abiotic, Cell fate},
	pages = {1325--1333},
}

Leaf senescence aims to degrade cellular components to recover valuable nutrients and reallocate them to other organs1. Once this remobilization is complete, cells undergo a vacuolar-type of programmed cell death2, ultimately leading to the death of the entire organ. But how do cells from a senescing leaf ‘know’ when to die? If the cell death process per se is initiated too early, remobilization may not be completed, rendering it futile. This suggests the presence of a ‘sensing’ mechanism that coordinates the remobilization phase with the onset of cell death during leaf senescence. Here, using Arabidopsis thaliana functional stay-green mutants, we show that senescing cells are wired to metabolically dissipate the cytosolic arginine pool, which otherwise represses the progression of leaf senescence. We propose a model in which a senescing cell uses this pool as a proxy for the completion of nitrogen remobilization and to accurately time the subsequent induction of cell death.

@article{collani_soppis_2026,
	title = {{SoPPIs}: a highly parallelized protein–protein-interaction screening method in prokaryotic and eukaryotic hosts},
	volume = {54},
	issn = {1362-4962},
	shorttitle = {{SoPPIs}},
	url = {https://doi.org/10.1093/nar/gkag716},
	doi = {10.1093/nar/gkag716},
	abstract = {Protein–protein interactions (PPIs) are at the heart of most cellular processes but despite recent progress, their genome-wide analysis remains challenging. With this in mind, we have developed SoPPIs (sequencing of PPIs), a powerful method that facilitates parallelized PPI analyses using an innovative combination of the split-Cre/loxP system and high-throughput DNA sequencing. Sequential recombination of plasmids encodes information about pairs of interacting proteins in recombined DNA, facilitating their easy and cost-efficient identification by next-generation sequencing. Importantly, SoPPIs works with most soluble proteins, can be implemented in any cell type that can be transformed with episomal plasmids, and is in principle capable of interrogating all possible PPIs in an organism in a single experiment. To demonstrate the power of SoPPIs, we analyzed the composition of the Arabidopsis thaliana LSm/Sm ring, an evolutionarily highly conserved core component of the spliceosome and performed parallelized library screens to identify LSm/Sm-interacting proteins. Given its versatility and usability, we expect SoPPIs to quickly gain popularity and help provide insights into the PPI networks underlying complex biological systems.},
	number = {14},
	urldate = {2026-07-24},
	journal = {Nucleic Acids Research},
	author = {Collani, Silvio and Nardeli, Sarah Muniz and Chowdary, K V S K Arjun and Goretti, Daniela and Schmid, Markus},
	month = aug,
	year = {2026},
	pages = {gkag716},
}

Protein–protein interactions (PPIs) are at the heart of most cellular processes but despite recent progress, their genome-wide analysis remains challenging. With this in mind, we have developed SoPPIs (sequencing of PPIs), a powerful method that facilitates parallelized PPI analyses using an innovative combination of the split-Cre/loxP system and high-throughput DNA sequencing. Sequential recombination of plasmids encodes information about pairs of interacting proteins in recombined DNA, facilitating their easy and cost-efficient identification by next-generation sequencing. Importantly, SoPPIs works with most soluble proteins, can be implemented in any cell type that can be transformed with episomal plasmids, and is in principle capable of interrogating all possible PPIs in an organism in a single experiment. To demonstrate the power of SoPPIs, we analyzed the composition of the Arabidopsis thaliana LSm/Sm ring, an evolutionarily highly conserved core component of the spliceosome and performed parallelized library screens to identify LSm/Sm-interacting proteins. Given its versatility and usability, we expect SoPPIs to quickly gain popularity and help provide insights into the PPI networks underlying complex biological systems.