@article{zeng_mutations_2025,
	title = {Mutations in the floral regulator gene {HUA2} restore flowering to the {Arabidopsis} trehalose 6-phosphate synthase1 (tps1) mutant},
	volume = {198},
	issn = {0032-0889},
	url = {https://doi.org/10.1093/plphys/kiaf225},
	doi = {10.1093/plphys/kiaf225},
	abstract = {Plant growth and development are regulated by many factors, including carbohydrate availability and signaling. Trehalose 6-phosphate (T6P), which is synthesized by TREHALOSE-6-PHOSPHATE SYNTHASE 1 (TPS1), is positively associated with and functions as a signal that informs the cell about the carbohydrate status. Mutations in TPS1 negatively affect the growth and development of Arabidopsis (Arabidopsis thaliana), and complete loss-of-function alleles are embryo-lethal, which can be overcome using inducible expression of TPS1 (GVG::TPS1) during embryogenesis. Using ethyl methane sulfonate mutagenesis in combination with genome re-sequencing, we have identified several alleles in the floral regulator gene HUA2 that restore flowering in tps1-2 GVG::TPS1. Genetic analyses using an HUA2 T-DNA insertion allele, hua2-4, confirmed this finding. RNA-seq analyses demonstrated that hua2-4 has widespread effects on the tps1-2 GVG::TPS1 transcriptome, including key genes and pathways involved in regulating flowering. Higher order mutants combining tps1-2 GVG::TPS1 and hua2-4 with alleles in the key flowering time regulators FLOWERING LOCUS T (FT), SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1 (SOC1), and FLOWERING LOCUS C (FLC) were constructed to analyze the role of HUA2 during floral transition in tps1-2 in more detail. Our findings demonstrate that loss of HUA2 can restore flowering in tps1-2 GVG::TPS1, in part through activation of FT, with contributions from the upstream regulators SOC1 and FLC. Interestingly, we found that mutation of FLC is sufficient to induce flowering in tps1-2 GVG::TPS1. Furthermore, we observed that mutations in HUA2 modulate carbohydrate signaling and that this regulation might contribute to flowering in hua2-4 tps1-2 GVG::TPS1.},
	number = {2},
	urldate = {2025-06-27},
	journal = {Plant Physiology},
	author = {Zeng, Liping and Zacharaki, Vasiliki and van Es, Sam W and Wang, Yanwei and Schmid, Markus},
	month = jun,
	year = {2025},
	pages = {kiaf225},
}

Plant growth and development are regulated by many factors, including carbohydrate availability and signaling. Trehalose 6-phosphate (T6P), which is synthesized by TREHALOSE-6-PHOSPHATE SYNTHASE 1 (TPS1), is positively associated with and functions as a signal that informs the cell about the carbohydrate status. Mutations in TPS1 negatively affect the growth and development of Arabidopsis (Arabidopsis thaliana), and complete loss-of-function alleles are embryo-lethal, which can be overcome using inducible expression of TPS1 (GVG::TPS1) during embryogenesis. Using ethyl methane sulfonate mutagenesis in combination with genome re-sequencing, we have identified several alleles in the floral regulator gene HUA2 that restore flowering in tps1-2 GVG::TPS1. Genetic analyses using an HUA2 T-DNA insertion allele, hua2-4, confirmed this finding. RNA-seq analyses demonstrated that hua2-4 has widespread effects on the tps1-2 GVG::TPS1 transcriptome, including key genes and pathways involved in regulating flowering. Higher order mutants combining tps1-2 GVG::TPS1 and hua2-4 with alleles in the key flowering time regulators FLOWERING LOCUS T (FT), SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1 (SOC1), and FLOWERING LOCUS C (FLC) were constructed to analyze the role of HUA2 during floral transition in tps1-2 in more detail. Our findings demonstrate that loss of HUA2 can restore flowering in tps1-2 GVG::TPS1, in part through activation of FT, with contributions from the upstream regulators SOC1 and FLC. Interestingly, we found that mutation of FLC is sufficient to induce flowering in tps1-2 GVG::TPS1. Furthermore, we observed that mutations in HUA2 modulate carbohydrate signaling and that this regulation might contribute to flowering in hua2-4 tps1-2 GVG::TPS1.

@article{gil-munoz_implications_2025,
	title = {Implications of {Breeding} for {Growth} on {Drought} {Tolerance} in {Scots} {Pine} ({Pinus} sylvestris {L}.)—{Insights} {From} {Metabolomics} and {High}-{Throughput} {Plant} {Architecture} {Analysis}},
	volume = {18},
	copyright = {© 2025 The Author(s). Evolutionary Applications published by John Wiley \& Sons Ltd.},
	issn = {1752-4571},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/eva.70122},
	doi = {10.1111/eva.70122},
	abstract = {Drought has been identified as one of the important environmental factors in the context of climate change due to its interaction with other biotic and abiotic stresses. However, only a few studies have reported the effect of breeding on forest adaptability to climate change. Using a common garden experiment with seedlings from families of Scots pine (Pinus sylvestris L.) from northern Sweden, we have found differences in drought tolerance between seedlings from breeding stands and those from natural forests. We performed a genetic analysis including high-throughput image-based phenotyping of seedling canopy and root traits and conducted metabolomic and hormone analyses with the aerial parts of the seedlings. Our results indicate that root architecture traits associated with drought tolerance exhibit moderate to high heritability. Analyses of seedling architecture reveal that families from breeding stands have higher drought resistance but lower genetic variation than the ones from natural forests, especially in the case of canopy traits. Metabolomic and hormone analyses of the aerial parts of the seedlings also support that the breeding stands may have a higher capacity to withstand or deal with drought conditions as compared to the natural forests. For example, increase in abscisic acid along with increase in tryptophan and auxin conjugates in the breeding stands compared to the natural forests under drought conditions may contribute to alleviation of drought response in the breeding stands. The methodology employed to evaluate drought tolerance and plant architecture in this study might be useful for future research and forest management focused on climate change adaptability.},
	language = {en},
	number = {6},
	urldate = {2025-06-27},
	journal = {Evolutionary Applications},
	author = {Gil-Muñoz, Francisco and Ranade, Sonali Sachin and Hayatgheibi, Haleh and Niemi, Juha and Östlund, Lars and García-Gil, María Rosario},
	year = {2025},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/eva.70122},
	keywords = {abscisic acid, drought, metabolomics, root architecture, scots pine},
	pages = {e70122},
}

Drought has been identified as one of the important environmental factors in the context of climate change due to its interaction with other biotic and abiotic stresses. However, only a few studies have reported the effect of breeding on forest adaptability to climate change. Using a common garden experiment with seedlings from families of Scots pine (Pinus sylvestris L.) from northern Sweden, we have found differences in drought tolerance between seedlings from breeding stands and those from natural forests. We performed a genetic analysis including high-throughput image-based phenotyping of seedling canopy and root traits and conducted metabolomic and hormone analyses with the aerial parts of the seedlings. Our results indicate that root architecture traits associated with drought tolerance exhibit moderate to high heritability. Analyses of seedling architecture reveal that families from breeding stands have higher drought resistance but lower genetic variation than the ones from natural forests, especially in the case of canopy traits. Metabolomic and hormone analyses of the aerial parts of the seedlings also support that the breeding stands may have a higher capacity to withstand or deal with drought conditions as compared to the natural forests. For example, increase in abscisic acid along with increase in tryptophan and auxin conjugates in the breeding stands compared to the natural forests under drought conditions may contribute to alleviation of drought response in the breeding stands. The methodology employed to evaluate drought tolerance and plant architecture in this study might be useful for future research and forest management focused on climate change adaptability.

@article{zhong_maize_2025,
	title = {A maize near-isogenic line population designed for gene discovery and characterization of allelic effects},
	volume = {122},
	copyright = {© 2025 The Author(s). The Plant Journal published by Society for Experimental Biology and John Wiley \& Sons Ltd.},
	issn = {1365-313X},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/tpj.70228},
	doi = {10.1111/tpj.70228},
	abstract = {In this study, we characterized a panel of 1264 maize near-isogenic lines (NILs), developed from crosses between 18 diverse inbred lines and the recurrent parent B73, referred to as nested NILs (nNILs). In this study, 888 of the nNILs were genotyped using genotyping-by-sequencing (GBS). Subsequently, 24 of these nNILs, and all the parental lines, were re-genotyped using a high-density single nucleotide polymorphism (SNP) chip. A novel pipeline for calling introgressions, which does not rely on knowing the donor parent of each nNIL, was developed based on a hidden Markov model (HMM) algorithm. By comparing the introgressions detected using GBS data with those identified using chip data, we optimized the HMM parameters for analyzing the entire nNIL population. A total of 2969 introgressions were identified across the 888 nNILs. Individual introgression blocks ranged from 21 bp to 204 Mbp, with an average size of 17 Mbp. By comparing SNP genotypes within introgressed segments to the known genotypes of the donor lines, we determined that in about one third of the lines, the identity of the donors did not match expectation based on their pedigrees. We characterized the entire nNIL population for three foliar diseases. Using these data, we mapped a number of quantitative trait loci (QTL) for disease resistance in the nNIL population and observed extensive variation in effects among the alleles from different donor parents at most QTL identified. This population will be of significant utility for dissecting complex agronomic traits and allelic series in maize.},
	language = {en},
	number = {5},
	urldate = {2025-07-07},
	journal = {The Plant Journal},
	author = {Zhong, Tao and Mullens, Alex and Morales, Laura and Swarts, Kelly L. and Stafstrom, William C. and He, Yijian and Sermons, Shannon M and Yang, Qin and Lopez-Zuniga, Luis O. and Rucker, Elizabeth and Thomason, Wade E. and Nelson, Rebecca J. and Jamann, Tiffany and Balint-Kurti, Peter J. and Holland, James B.},
	year = {2025},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/tpj.70228},
	keywords = {allelic series, disease resistance, maize, near isogenic line},
	pages = {e70228},
}

In this study, we characterized a panel of 1264 maize near-isogenic lines (NILs), developed from crosses between 18 diverse inbred lines and the recurrent parent B73, referred to as nested NILs (nNILs). In this study, 888 of the nNILs were genotyped using genotyping-by-sequencing (GBS). Subsequently, 24 of these nNILs, and all the parental lines, were re-genotyped using a high-density single nucleotide polymorphism (SNP) chip. A novel pipeline for calling introgressions, which does not rely on knowing the donor parent of each nNIL, was developed based on a hidden Markov model (HMM) algorithm. By comparing the introgressions detected using GBS data with those identified using chip data, we optimized the HMM parameters for analyzing the entire nNIL population. A total of 2969 introgressions were identified across the 888 nNILs. Individual introgression blocks ranged from 21 bp to 204 Mbp, with an average size of 17 Mbp. By comparing SNP genotypes within introgressed segments to the known genotypes of the donor lines, we determined that in about one third of the lines, the identity of the donors did not match expectation based on their pedigrees. We characterized the entire nNIL population for three foliar diseases. Using these data, we mapped a number of quantitative trait loci (QTL) for disease resistance in the nNIL population and observed extensive variation in effects among the alleles from different donor parents at most QTL identified. This population will be of significant utility for dissecting complex agronomic traits and allelic series in maize.

@article{chubanava_nad_2025,
	title = {{NAD} depletion in skeletal muscle does not compromise muscle function or accelerate aging},
	issn = {1550-4131},
	url = {https://www.sciencedirect.com/science/article/pii/S1550413125002128},
	doi = {10.1016/j.cmet.2025.04.002},
	abstract = {Nicotinamide adenine dinucleotide (NAD) is a ubiquitous electron carrier essential for energy metabolism and post-translational modification of numerous regulatory proteins. Dysregulations of NAD metabolism are widely regarded as detrimental to health, with NAD depletion commonly implicated in aging. However, the extent to which cellular NAD concentration can decline without adverse consequences remains unclear. To investigate this, we generated a mouse model in which nicotinamide phosphoribosyltransferase (NAMPT)-mediated NAD+ biosynthesis was disrupted in adult skeletal muscle. The intervention resulted in an 85\% reduction in muscle NAD+ abundance while maintaining tissue integrity and functionality, as demonstrated by preserved muscle morphology, contractility, and exercise tolerance. This absence of functional impairments was further supported by intact mitochondrial respiratory capacity and unaltered muscle transcriptomic and proteomic profiles. Furthermore, lifelong NAD depletion did not accelerate muscle aging or impair whole-body metabolism. Collectively, these findings suggest that NAD depletion does not contribute to age-related decline in skeletal muscle function.},
	urldate = {2025-05-09},
	journal = {Cell Metabolism},
	author = {Chubanava, Sabina and Karavaeva, Iuliia and Ehrlich, Amy M. and Justicia, Roger M. and Basse, Astrid L. and Kulik, Ivan and Dalbram, Emilie and Ahwazi, Danial and Heaselgrave, Samuel R. and Trošt, Kajetan and Stocks, Ben and Hodek, Ondřej and Rodrigues, Raissa N. and Havelund, Jesper F. and Schlabs, Farina L. and Larsen, Steen and Yonamine, Caio Y. and Henriquez-Olguín, Carlos and Giustarini, Daniela and Rossi, Ranieri and Gerhart-Hines, Zachary and Moritz, Thomas and Zierath, Juleen R. and Sakamoto, Kei and Jensen, Thomas E. and Færgeman, Nils J. and Lavery, Gareth G. and Deshmukh, Atul S. and Treebak, Jonas T.},
	month = apr,
	year = {2025},
	keywords = {NAD biosynthesis, NAD metabolism, NAMPT, aging, epigenetic clock, exercise, mitochondrial supercomplexes, nicotinamide, reactive oxygen species, skeletal muscle},
}

Nicotinamide adenine dinucleotide (NAD) is a ubiquitous electron carrier essential for energy metabolism and post-translational modification of numerous regulatory proteins. Dysregulations of NAD metabolism are widely regarded as detrimental to health, with NAD depletion commonly implicated in aging. However, the extent to which cellular NAD concentration can decline without adverse consequences remains unclear. To investigate this, we generated a mouse model in which nicotinamide phosphoribosyltransferase (NAMPT)-mediated NAD+ biosynthesis was disrupted in adult skeletal muscle. The intervention resulted in an 85% reduction in muscle NAD+ abundance while maintaining tissue integrity and functionality, as demonstrated by preserved muscle morphology, contractility, and exercise tolerance. This absence of functional impairments was further supported by intact mitochondrial respiratory capacity and unaltered muscle transcriptomic and proteomic profiles. Furthermore, lifelong NAD depletion did not accelerate muscle aging or impair whole-body metabolism. Collectively, these findings suggest that NAD depletion does not contribute to age-related decline in skeletal muscle function.

@article{tian_plantlncboost_2025,
	title = {{PlantLncBoost}: key features for plant {lncRNA} identification and significant improvement in accuracy and generalization},
	copyright = {© 2025 The Author(s). New Phytologist © 2025 New Phytologist Foundation.},
	issn = {1469-8137},
	shorttitle = {{PlantLncBoost}},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/nph.70211},
	doi = {10.1111/nph.70211},
	abstract = {Long noncoding RNAs (lncRNAs) are critical regulators of numerous biological processes in plants. Nevertheless, their identification is challenging due to the low sequence conservation across various species. Existing computational methods for lncRNA identification often face difficulties in generalizing across diverse plant species, highlighting the need for more robust and versatile identification models. Here, we present PlantLncBoost, a novel computational tool designed to improve the generalization in plant lncRNA identification. By integrating advanced gradient boosting algorithms with comprehensive feature selection, our approach achieves both high accuracy and generalizability. We conducted an extensive analysis of 1662 features and identified three key features – ORF coverage, complex Fourier average, and atomic Fourier amplitude – that effectively distinguish lncRNAs from mRNAs. We assessed the performance of PlantLncBoost using comprehensive datasets from 20 plant species. The model exhibited exceptional performance, with an accuracy of 96.63\%, a sensitivity of 98.42\%, and a specificity of 94.93\%, significantly outperforming existing tools. Further analysis revealed that the features we selected effectively capture the differences between lncRNAs and mRNAs across a variety of plant species. PlantLncBoost represents a significant advancement in plant lncRNA identification. It is freely accessible on GitHub (https://github.com/xuechantian/PlantLncBoost) and has been integrated into a comprehensive analysis pipeline, Plant-LncRNA-pipeline v.2 (https://github.com/xuechantian/Plant-LncRNA-pipeline-v2).},
	language = {en},
	urldate = {2025-05-30},
	journal = {New Phytologist},
	author = {Tian, Xue-Chan and Nie, Shuai and Domingues, Douglas and Rossi Paschoal, Alexandre and Jiang, Li-Bo and Mao, Jian-Feng},
	month = may,
	year = {2025},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/nph.70211},
	keywords = {Fourier transform, ORF coverage, feature selection, gradient boosting algorithms, long noncoding RNAs (lncRNAs), model selection},
}

Long noncoding RNAs (lncRNAs) are critical regulators of numerous biological processes in plants. Nevertheless, their identification is challenging due to the low sequence conservation across various species. Existing computational methods for lncRNA identification often face difficulties in generalizing across diverse plant species, highlighting the need for more robust and versatile identification models. Here, we present PlantLncBoost, a novel computational tool designed to improve the generalization in plant lncRNA identification. By integrating advanced gradient boosting algorithms with comprehensive feature selection, our approach achieves both high accuracy and generalizability. We conducted an extensive analysis of 1662 features and identified three key features – ORF coverage, complex Fourier average, and atomic Fourier amplitude – that effectively distinguish lncRNAs from mRNAs. We assessed the performance of PlantLncBoost using comprehensive datasets from 20 plant species. The model exhibited exceptional performance, with an accuracy of 96.63%, a sensitivity of 98.42%, and a specificity of 94.93%, significantly outperforming existing tools. Further analysis revealed that the features we selected effectively capture the differences between lncRNAs and mRNAs across a variety of plant species. PlantLncBoost represents a significant advancement in plant lncRNA identification. It is freely accessible on GitHub (https://github.com/xuechantian/PlantLncBoost) and has been integrated into a comprehensive analysis pipeline, Plant-LncRNA-pipeline v.2 (https://github.com/xuechantian/Plant-LncRNA-pipeline-v2).