@article{shi_alleleauto_2026,
	title = {Alleleauto: a pipeline for allele identification and analysis of allele-specific gene expression with haplotype-resolved diploid genome assemblies},
	volume = {7},
	issn = {2662-1738},
	shorttitle = {Alleleauto},
	url = {https://www.sciencedirect.com/science/article/pii/S2662173826000706},
	doi = {10.1016/j.abiote.2026.100056},
	abstract = {Advanced sequencing now enables haplotype resolution of genomes from non-model diploid plant species, facilitating allele identification and the use of allele-specific expression (ASE) analysis to uncover the relationships between genes and phenotypes in heterozygous genomes. However, identification of true allelic pairs remains challenging due to the presence of paralogous genes from ancient genome duplications, and existing methods lack systematic, reproducible filtering criteria. In this study, we developed Alleleauto, a workflow integrating the parametric 3σ rule and the non-parametric Tukey's method as two complementary outlier detection methods to precisely identify alleles and perform ASE analysis from haplotype-resolved assemblies. Alleleauto first searches for homologous genes across homologous chromosomes, then applies statistical filtering criteria based on synonymous substitution rates (Ks) and synteny to systematically remove false alleles (paralogs). This dual-method framework offers flexible filtering strategies with adjustable parameters, enabling optimization for diverse genomes. We validated the workflow on tea plant (Camellia sinensis), ginger (Zingiber officinale), and lychee (Litchi chinensis), three plant species with distinct genomic features, demonstrating that statistical filtering significantly improves accuracy over the use of sequence similarity alone. Using the alleles identified by Alleleauto, we performed ASE analysis and calculated sequence divergence parameters to investigate ASE and heterosis mechanisms. Our open-source, and easy-to-use pipeline provides significant value for reproducible, scalable investigation of ASE and heterosis with haplotype-resolved genome assemblies.},
	number = {3},
	urldate = {2026-06-12},
	journal = {aBIOTECH},
	author = {Shi, Tian-Le and Nie, Shuai and Bao, Yu-Tao and Li, Zhi-Chao and Chen, Zhao-Yang and Zhao, Shi-Wei and Yan, Xue-Mei and Ma, Hai-Yao and Tian, Xue-Chan and Jia, Kai-Hua and Guo, Jing-Fang and Zhang, Jun-Ke and Mao, Jian-Feng},
	month = sep,
	year = {2026},
	keywords = {Allele identification, Allele-specific expression, Haplotype-resolved, Non-model diploid plant genome, Sequence similarity},
	pages = {100056},
}

Advanced sequencing now enables haplotype resolution of genomes from non-model diploid plant species, facilitating allele identification and the use of allele-specific expression (ASE) analysis to uncover the relationships between genes and phenotypes in heterozygous genomes. However, identification of true allelic pairs remains challenging due to the presence of paralogous genes from ancient genome duplications, and existing methods lack systematic, reproducible filtering criteria. In this study, we developed Alleleauto, a workflow integrating the parametric 3σ rule and the non-parametric Tukey's method as two complementary outlier detection methods to precisely identify alleles and perform ASE analysis from haplotype-resolved assemblies. Alleleauto first searches for homologous genes across homologous chromosomes, then applies statistical filtering criteria based on synonymous substitution rates (Ks) and synteny to systematically remove false alleles (paralogs). This dual-method framework offers flexible filtering strategies with adjustable parameters, enabling optimization for diverse genomes. We validated the workflow on tea plant (Camellia sinensis), ginger (Zingiber officinale), and lychee (Litchi chinensis), three plant species with distinct genomic features, demonstrating that statistical filtering significantly improves accuracy over the use of sequence similarity alone. Using the alleles identified by Alleleauto, we performed ASE analysis and calculated sequence divergence parameters to investigate ASE and heterosis mechanisms. Our open-source, and easy-to-use pipeline provides significant value for reproducible, scalable investigation of ASE and heterosis with haplotype-resolved genome assemblies.

@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}.)},
	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},
	urldate = {2026-06-05},
	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},
}

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.

@article{turco_comparative_2026,
	title = {Comparative {Metabarcoding} of {ITS1}, {ITS2}, and {Full}-{Length} {ITS} {Reveals} {Marker}- and {Tissue}-{Specific} {Variation} in {Fungal} {Community} {Profiling} in {Potato}},
	volume = {7},
	copyright = {© 2026 The Author(s). Plant-Environment Interactions published by John Wiley \& Sons Ltd and New Phytologist Foundation.},
	issn = {2575-6265},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/pei3.70168},
	doi = {10.1002/pei3.70168},
	abstract = {Accurate profiling of plant-associated fungal and oomycete communities depends critically on the choice of ITS marker. Using Illumina sequencing for ITS1/ITS2 and PacBio HiFi sequencing for full-length ITS (ITSf), we compared read recovery, taxonomic assignment depth, and diversity patterns across potato leaf and root tissues. ITS2 generally recovered more diverse and even community profiles in leaves, whereas ITSf recovered comparatively more even and taxonomically broad profiles in roots. In contrast, ITS1 showed high read recovery but produced strongly skewed compositional profiles and was frequently dominated by host-derived sequences. Beta-diversity analyses indicated that ITS marker choice was associated with substantial variation in observed community composition, while functional annotation highlighted communities composed of taxa associated with multiple ecological guilds, including endophytes and opportunistic pathogens such as Cladosporium and Ilyonectria. Overall, the results demonstrate that ITS marker choice strongly influences the observed structure and diversity of plant-associated communities. ITS2 was generally more suitable for phyllosphere-associated communities, whereas ITSf provided broader recovery of root-associated taxa. Combining complementary markers therefore offers a more comprehensive representation of potato-associated microbial eukaryotic communities than single-marker approaches alone.},
	language = {en},
	number = {3},
	urldate = {2026-06-05},
	journal = {Plant-Environment Interactions},
	author = {Turco, Silvia and Giubilei, Irene and Mahawar, Lovely and Mazzaglia, Angelo and Albrectsen, Benedicte Riber},
	year = {2026},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/pei3.70168},
	keywords = {ITS markers, Solanum tuberosum L., amplicon sequencing, metabarcoding, mycobiome},
	pages = {e70168},
}

Accurate profiling of plant-associated fungal and oomycete communities depends critically on the choice of ITS marker. Using Illumina sequencing for ITS1/ITS2 and PacBio HiFi sequencing for full-length ITS (ITSf), we compared read recovery, taxonomic assignment depth, and diversity patterns across potato leaf and root tissues. ITS2 generally recovered more diverse and even community profiles in leaves, whereas ITSf recovered comparatively more even and taxonomically broad profiles in roots. In contrast, ITS1 showed high read recovery but produced strongly skewed compositional profiles and was frequently dominated by host-derived sequences. Beta-diversity analyses indicated that ITS marker choice was associated with substantial variation in observed community composition, while functional annotation highlighted communities composed of taxa associated with multiple ecological guilds, including endophytes and opportunistic pathogens such as Cladosporium and Ilyonectria. Overall, the results demonstrate that ITS marker choice strongly influences the observed structure and diversity of plant-associated communities. ITS2 was generally more suitable for phyllosphere-associated communities, whereas ITSf provided broader recovery of root-associated taxa. Combining complementary markers therefore offers a more comprehensive representation of potato-associated microbial eukaryotic communities than single-marker approaches alone.

@article{anjam_single-cell_2026,
	title = {Single-cell laser ablation uncovers the blueprint of plant development},
	issn = {1360-1385},
	url = {https://www.sciencedirect.com/science/article/pii/S1360138526001329},
	doi = {10.1016/j.tplants.2026.04.029},
	abstract = {Understanding how positional information within plant tissues shapes developmental programs in real time has long remained a challenge due to technical limitations in precisely accessing and manipulating defined cellular domains within complex tissues. Recent advances in single-cell laser ablation, particularly when combined with confocal microscopy, now allow precise spatiotemporal perturbation of selected cells. This technology has enabled researchers to dissect cellular functions, communication dynamics, and mechanical responses with unprecedented accuracy. Here, we review how laser ablation has emerged as a transformative approach in plant biology, from unraveling the signaling networks governing meristem maintenance and root patterning to modeling wound responses and immune activation.},
	urldate = {2026-05-29},
	journal = {Trends in Plant Science},
	author = {Anjam, Muhammad S. and Di Fino, Luciano Martín and Ma, Xuemin and Marhavý, Peter},
	month = may,
	year = {2026},
	keywords = {mechanobiology, phytohormone crosstalk, single-cell ablation, tissue regeneration, wound signaling},
}

Understanding how positional information within plant tissues shapes developmental programs in real time has long remained a challenge due to technical limitations in precisely accessing and manipulating defined cellular domains within complex tissues. Recent advances in single-cell laser ablation, particularly when combined with confocal microscopy, now allow precise spatiotemporal perturbation of selected cells. This technology has enabled researchers to dissect cellular functions, communication dynamics, and mechanical responses with unprecedented accuracy. Here, we review how laser ablation has emerged as a transformative approach in plant biology, from unraveling the signaling networks governing meristem maintenance and root patterning to modeling wound responses and immune activation.

@article{tiziani_deciphering_2026,
	title = {Deciphering underexplored rhizosphere processes: root acquisition of citric acid and its metabolic journey in tomato},
	issn = {0022-0957},
	shorttitle = {Deciphering underexplored rhizosphere processes},
	url = {https://doi.org/10.1093/jxb/erag066},
	doi = {10.1093/jxb/erag066},
	abstract = {Root-exuded organic acids are crucial in mitigating iron (Fe) and phosphorus (P) deficiencies, and their biosynthesis and secretion require significant metabolic investment. Recent studies have shown that roots can also uptake exudates. We hypothesized that citric acid uptake increases under Fe and P deficiencies, declines over time, and contributes to primary metabolism. We investigated citric acid uptake, translocation, and metabolization in Fe- and P-deficient tomato plants grown hydroponically using 13C-labelling with bulk stable-isotope and compound-specific stable-isotope analysis. Physiological parameters, root morphology, and elemental composition were also assessed. Deficient plants showed reduced P and Fe contents, reduced photosynthesis, altered root morphology, and an altered citric acid uptake that could not be attributed to morphological differences. Iron deficiency reduced citric acid uptake, indicating its role in rhizospheric Fe mobilization, while P deficiency increased the uptake, enhancing resource use efficiency. Unexpectedly, citric acid uptake increased with plant development. In Fe deficiency, citric acid-derived carbon was allocated to secondary metabolites, while in P deficiency it supported the tricarboxylic acid and GS-GOGAT cycles. This study is the first to demonstrate that citric acid uptake is a multifunctional process, underscoring its critical role in plant responses to nutrient starvation, especially under P deficiency.},
	urldate = {2026-04-24},
	journal = {Journal of Experimental Botany},
	author = {Tiziani, Raphael and Trevisan, Fabio and Hodek, Ondřej and Jämtgård, Sandra and Moritz, Thomas and Bouaicha, Oussama and Chibesa, Mirriam C and Fracasso, Ilaria and Mimmo, Tanja},
	month = feb,
	year = {2026},
	pages = {erag066},
}

Root-exuded organic acids are crucial in mitigating iron (Fe) and phosphorus (P) deficiencies, and their biosynthesis and secretion require significant metabolic investment. Recent studies have shown that roots can also uptake exudates. We hypothesized that citric acid uptake increases under Fe and P deficiencies, declines over time, and contributes to primary metabolism. We investigated citric acid uptake, translocation, and metabolization in Fe- and P-deficient tomato plants grown hydroponically using 13C-labelling with bulk stable-isotope and compound-specific stable-isotope analysis. Physiological parameters, root morphology, and elemental composition were also assessed. Deficient plants showed reduced P and Fe contents, reduced photosynthesis, altered root morphology, and an altered citric acid uptake that could not be attributed to morphological differences. Iron deficiency reduced citric acid uptake, indicating its role in rhizospheric Fe mobilization, while P deficiency increased the uptake, enhancing resource use efficiency. Unexpectedly, citric acid uptake increased with plant development. In Fe deficiency, citric acid-derived carbon was allocated to secondary metabolites, while in P deficiency it supported the tricarboxylic acid and GS-GOGAT cycles. This study is the first to demonstrate that citric acid uptake is a multifunctional process, underscoring its critical role in plant responses to nutrient starvation, especially under P deficiency.