Comparative transcriptomic analysis and identification of candidate genes related to Verticillium wilt resistance in Gossypium barbadense and Gossypium hirsutum by Jieyin Zhao, Xingui Hu, Yuxiang Wang, Jiaxin Lu, Wenju Gao, Xuening Su, Quanjia Chen, Yanying Qu

“…Here, we report a transcriptomic study for phenotypic evaluation of Verticillium wilt resistance in G. hirsutum (TM-1) and G. barbadense (Hai7124) and a comparison of the transcriptomes at 7 time points after Verticillium dahliae inoculation. …”
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A single-cell transcriptomic map of the murine and human multiple myeloma immune microenvironment across disease stages by Emma Verheye, Daliya Kancheva, Hatice Satilmis, Niels Vandewalle, Rong Fan, Pauline M. R. Bardet, Emile J. Clappaert, Kevin Verstaen, Ann De Becker, Karin Vanderkerken, Kim De Veirman, Damya Laoui

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Automated integration of multi-slice spatial transcriptomics data in 2D and 3D using VR-Omics by Denis Bienroth, Natalie Charitakis, Dillon Wong, Yunhan C. Zhang, Sabrina Jaeger-Honz, Jialin Ding, Kevin I. Watt, Julian Stolper, Hazel Chambers-Smith, Duncan MacGregor, Bronwyn Christiansen, Celine Vivien, Adam T. Piers, Lisa N. Waylen, Lucas B. Hoffmann, Jessica Tang, Hue M. La, Mei R. M. Du, Monika Mohenska, Jose M. Polo, Sean Grimmond, Ethan Scott, Fernando J. Rossello, Enzo R. Porrello, Karsten Klein, Hieu T. Nim, David A. Elliott, Falk Schreiber, Mirana Ramialison

“…Abstract The field of spatial transcriptomics is rapidly evolving, with increasing sample complexity, resolution, and tissue size. …”
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Integrative Genomic and Transcriptomic Analysis of Anorexia Nervosa: A Multi-omics Approach to Identify Genetic and Molecular Pathways by Usha Adiga, Sampara Vasishta, Alfred J. Augustine

“…Conclusion: The study provides comprehensive insights into the multifactorial nature of AN, identifying genetic and molecular pathways that converge on neuropsychiatric and metabolic processes.…”
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Identification of LecRLK gene family in Cerasus humilis through genomic-transcriptomic data mining and expression analyses. by Hongyan Han, Xiaopeng Mu, Pengfei Wang, Zewen Wang, Hongbo Fu, Yu Gary Gao, Junjie Du

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Selection and evaluation of new reference genes for RT-qPCR analysis in Epinephelus akaara based on transcriptome data. by Huan Wang, Xiang Zhang, Qiaohong Liu, Xiaochun Liu, Shaoxiong Ding

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In Silico identification and annotation of non-coding RNAs by RNA-seq and De Novo assembly of the transcriptome of Tomato Fruits. by Daria Scarano, Rosa Rao, Giandomenico Corrado

“…Moreover, our work demonstrates the usefulness of strand specific RNA-seq approach for the transcriptome-based genome annotation and provides a resource valuable for further functional studies.…”
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Single-nucleus and spatial transcriptomics identify brain landscape of gene regulatory networks associated with behavioral maturation in honeybees by Xiaohuan Mu, Zijing Zhang, Qun Liu, Jie Ma, Yating Qin, Haoyu Lang, Yingying Zhang, Nannan Zhang, Qunfei Guo, Pei Zhang, Denghui Li, Ruihua Zhang, Qianyue Ji, Aijun Jiang, Yang Wang, Shanshan Pan, Xiawei Liu, Xuemei Liu, Jiahui Sun, Yan Liu, Hao Chen, Li Zheng, Liang Meng, Haorong Lu, He Zhang, Yifan Zhai, Qiye Li, Junnian Liu, Huanming Yang, Jian Wang, Xiaosong Hu, Xun Xu, Shanshan Liu, Hao Zheng

“…Eusocial honeybees, with their natural behavioral plasticity, provide an excellent model for exploring the connection between brain activity and behavior. …”
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Large-scale transcriptomic analyses of major depressive disorder reveal convergent dysregulation of synaptic pathways in excitatory neurons by Fernando S. Goes, Leonardo Collado-Torres, Peter P. Zandi, Louise Huuki-Myers, Ran Tao, Andrew E. Jaffe, Geo Pertea, Joo Heon Shin, Daniel R. Weinberger, Joel E. Kleinman, Thomas M. Hyde

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Comparative Transcriptome Analysis of Gene Responses of Salt-Tolerant and Salt-Sensitive Watermelon Cultivars’ Roots to Salt Stress by Peng Liu, Chao Gao, Shuai Li, Xudong Wang, Yumei Dong, Chongqi Wang, Zigao Jiao, Jianlei Sun

“…The transcriptome analysis identified differentially expressed genes (DEGs) between the two cultivars under salt stress, with T23 showing the highest number of DEGs at 6 h, while B2 exhibited a significant increase in DEGs at 168 h. …”
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CellFM: a large-scale foundation model pre-trained on transcriptomics of 100 million human cells by Yuansong Zeng, Jiancong Xie, Ningyuan Shangguan, Zhuoyi Wei, Wenbing Li, Yun Su, Shuangyu Yang, Chengyang Zhang, Jinbo Zhang, Nan Fang, Hongyu Zhang, Yutong Lu, Huiying Zhao, Jue Fan, Weijiang Yu, Yuedong Yang

“…Abstract Single-cell sequencing provides transcriptomic profiling at single-cell resolution, uncovering cellular heterogeneity with unprecedented precision. …”
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Comparative genomics and transcriptomic response to root exudates of six rice root-associated Burkholderia sensu lato species by Wallner, Adrian, Klonowska, Agnieszka, Guigard, Ludivine, King, Eoghan, Rimbault, Isabelle, Ngonkeu, Eddy, Nguyen, Phuong, Béna, Gilles, Moulin, Lionel

“…Beyond being a reliable nutrient provider, some bacteria will perceive the plant as a potential host and undertake root colonization leading to mutualistic or parasitic interactions. …”
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Deciphering the miRNA transcriptome of granulosa cells from dominant and subordinate follicles at first follicular wave in goat by Jinzhu Meng, Yuanyuan Zhao, Xingchao Song, Qingming An, Zhenyang Wu

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The Scarlet Alchemy of Survival: Integrated Transcriptomic and Metabolomic Analysis of Leaf Coloration in Endangered <i>Parrotia subaequalis</i> by Lifang Zhang, Aya Hafsi, Xianting Wang, Chenyun Zhang, Zedong Lang, Mingjian Yu, Yanming Fang

“…Here, we combined transcriptomic, metabolomic, and physiological analyses to investigate pigment changes within the yellow leaf phenotype of <i>P. subaequalis</i>. …”
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Integrated transcriptomic and single-cell analysis reveals key immune-related genes and cellular crosstalk in the myocarditis microenvironment by Yuanqing Li, Shangfei He, Jun Wu, Shenrong Liu, Ruiming Liu, Yipeng Du, Dunzheng Han, Wenjie Luo, Zheng Huang, Pingzhen Yang

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Comprehensive RNA-Seq Profiling to Evaluate the Sheep Mammary Gland Transcriptome in Response to Experimental Mycoplasma agalactiae Infection. by Rohini Chopra-Dewasthaly, Melanie Korb, René Brunthaler, Reinhard Ertl

“…To our knowledge this is the first study that describes host transcriptomics of M. agalactiae infection and the related immune-inflammatory responses. …”
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Reverse engineering neuron-type-specific and type-orthogonal splicing-regulatory networks using diverse cellular transcriptomes by Daniel F. Moakley, Melissa Campbell, Miquel Anglada-Girotto, Huijuan Feng, Andrea Califano, Edmund Au, Chaolin Zhang

“…We also identify a module of exons and candidate regulators specific to long- and short-projection neurons across multiple neuronal classes. This study provides a resource for elucidating splicing-regulatory programs that drive neuronal molecular diversity, including those that do not align with gene-expression-based classifications.…”
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Transcriptome and Proteome Analyses Revealed Differences in JEV-Infected PK-15 Cells in Response to Ferroptosis Agonists and Antagonists by Xiaolong Zhou, Yiwei Chen, Xinyao Kang, Ayong Zhao, Songbai Yang

“…Our results provide a better understanding of the molecular mechanisms through which ferroptosis affects the proliferation of JEV.…”
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Analysis of differential gene expression in the brain tissue transcriptome of Jiangkou radish piglets infected with porcine pseudorabies virus by Wei Sun, Shan-Shan Liu, Yu Fan, Sheng-Qing Deng, Hua-Qi Zhang, Fengzhao Zhu, Shi-He Long, Tao-Hua Ren, Ling Bai

“…Results: Infected piglets showed increased oligodendrocyte counts and pseudorabies virus-positive signals. Transcriptomic analysis revealed 269 differentially expressed genes, with 149 up-regulated and 120 down-regulated. …”
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A spatial imaging-transcriptomics paradigm for deciphering the molecular basis of microscopic MRI in the normal brain and Alzheimer’s disease by Yiqi Shen, Yao Shen, Menglei Wang, Kaiyu Jin, Penghui Yang, Zuozhen Cao, Qinfeng Zhu, Zhiyong Zhao, Haotian Li, Lei Han, Shiping Liu, Jie Liao, Jing Zhang, Xiaohui Fan, Dan Wu

“…The spatial imaging-transcriptomics paradigm provides an unprecedented high-resolution bridge between neuroimaging and transcriptomics, benefitting the decipherment of complex molecular events in brain disorders.…”
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