Integrative analysis of 115 transcriptomic studies decodes the molecular landscape of neurodevelopmental disorders by Jarno Koetsier, Lars M. T. Eijssen, Leon J. Schurgers, Leopold M. G. Curfs, Chris P. Reutelingsperger, Nasim Bahram Sangani

“…Abstract Due to the low disease prevalence, transcriptomic studies of neurodevelopmental disorders (NDDs) often face limited statistical power, constraining the depth of insights they can provide. …”
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Transcriptome sequencing of Codonopsis pilosula and identification of candidate genes involved in polysaccharide biosynthesis. by Jian Ping Gao, Dong Wang, Ling Ya Cao, Hai Feng Sun

“…<h4>Significance</h4>To our knowledge, this is the first study to provide a public transcriptome dataset prepared from C. pilosula and an outline of the biosynthetic pathway of polysaccharides in a medicinal plant. …”
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Combined metabolome and transcriptome analysis reveal the mechanism of water stress in Ophiocordyceps sinensis by Li He, ChuanYong Li, ZhaoHe Chen, YanLi Huo, Bo Zhou, Fang Xie

“…Conclusions Overall, our findings provide important information for further exploration of the mechanism underlying the water stress tolerance of O. sinensis for the industrialization of artificial cultivation of Chinese cordyceps.…”
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Transcriptome profiling and co-expression network analysis of 96 Haematococcus pluvialis samples by Bin Hu, Kai Liu, Feichao Du, Hailiang Xing, Xiaoyuan Su, Tao Hu, Feng Chen, Yujie Qin, Zhaozhen Dong, Xue Sun, Liuquan Zhang, Jagroop Pandhal, Nianjun Xu, Chaoyang Hu

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Decoding hippocampal subfield and glial responses in ischemia using single-cell transcriptomics by Donghee Kwak, Ji Hyun Park, Yun Hak Kim, Hong Il Yoo

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Transcriptomic analysis of maize leaves under different irrigation treatments in field conditions by Yuan-Xin Li, Ru-Zhi Li, Jing Yang, Zhi-Wei Wang, Xiao-Guang Li, Hou-Zhen Yi, Xin-Ping Guo, Hang Zhou, Kai-Hua Jia, Peng-Fei Chu

“…This not only deepens our understanding of maize’s response to water stress but also provides valuable genetic resources and theoretical insights for future genetic improvement. …”
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Comparative phenotypic, physiological, and transcriptomic responses to drought and recovery in two Fraxinus species by Tae-Lim Kim, Hyemin Lim, Kyungmi Lee, Michael Immanuel Jesse Denison, Sathishkumar Natarajan, Changyoung Oh

“…This study aimed to compare the phenotypic, physiological, and transcriptomic characteristics of drought-stressed and recovered rewatered plants in a time-course experiment. …”
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Effects of supplementary light treatment on saffron: integrated physiological, metabolomic, and transcriptome analyses by Li Li, Yujie Zhou, Jingting Wang, Xiwu Qi, Hailing Fang, Yang Bai, Zequn Chen, Xu Yu, Dongmei Liu, Qun Liu, Chengyuan Liang

“…Expression analysis of key genes and their correlations with crocin-related metabolites may provide useful information for screening functional genes involved in crocin synthesis. …”
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spVelo: RNA velocity inference for multi-batch spatial transcriptomics data by Wenxin Long, Tianyu Liu, Lingzhou Xue, Hongyu Zhao

“…Here, we introduce spVelo, a scalable framework for RNA velocity inference of multi-batch spatial transcriptomics data. spVelo supports several downstream applications, including uncertainty quantification, complex trajectory pattern discovery, driver marker identification, gene regulatory network inference, and temporal cell-cell communication inference. spVelo has the potential to provide deeper insights into complex tissue organization and underscore biological mechanisms based on spatially resolved patterns.…”
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Seasonal transcriptomic shifts reveal metabolic flexibility of chemosynthetic symbionts in an upwelling region by Isidora Morel-Letelier, Benedict Yuen, Luis H. Orellana, A. Carlotta Kück, Yolanda E. Camacho-García, Minor Lara, Matthieu Leray, Laetitia G. E. Wilkins

“…These conditions serve as a natural experiment that provides a unique opportunity to study how marine animals and their associated microorganisms respond in the face of environmental change. …”
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Protocol for single-cell RNA sequencing and spatial transcriptomics of bladder Ewing sarcoma by Weipu Mao, Houliang Zhang, Jie Ji, Jianpung Wu, Ming Chen, Chao Sun

“…Spatial transcriptomics, meanwhile, delivers spatial visualization and quantitative analysis of tissue sections. …”
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Analysis of differential gene expression and novel transcript units of ovine muscle transcriptomes. by Chunlan Zhang, Guizhi Wang, Jianmin Wang, Zhibin Ji, Fei Dong, Tianle Chao

“…In this study, we characterized differentially expressed genes (DEGs) between the muscle transcriptomes of Small-tailed Han sheep and Dorper sheep and predicted novel transcript units using high-throughput RNA sequencing technology. …”
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STModule: identifying tissue modules to uncover spatial components and characteristics of transcriptomic landscapes by Ran Wang, Yan Qian, Xiaojing Guo, Fangda Song, Zhiqiang Xiong, Shirong Cai, Xiuwu Bian, Man Hon Wong, Qin Cao, Lixin Cheng, Gang Lu, Kwong Sak Leung

“…STModule uncovers diverse expression signals in transcriptomic landscapes such as cancer, intraepithelial neoplasia, immune infiltration, outcome-related molecular features and various cell types, which facilitate downstream analysis and provide insights into tumor microenvironments, disease mechanisms, treatment development, and histological organization of tissues. …”
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Transcriptome analysis reveals defense responses of alfalfa seedling roots to Sclerotium rolfsii by Shizhen Jia, Shizhen Jia, Zhencuo Dan, Zhencuo Dan, He Li, He Li, Yuhan Guo, Yuhan Guo, Lei Jia, Lei Jia, Ailing Yu, Ailing Yu, Huitong Zhan, Huitong Zhan, Xiangjun Liu, Xiangjun Liu, Teng Gao, Teng Gao, Yun Shi, Yun Shi, Zeng-Yu Wang, Zeng-Yu Wang, Lili Cong, Lili Cong, Lili Cong

“…This study aims to explore the interaction mechanisms between alfalfa and S. rolfsii, identify key regulatory factors involved in disease resistance, and provide insights for improving alfalfa's resistance to root rot. …”
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Transcriptome Analysis of Low-Temperature-Induced Breaking of Garlic Aerial Bulb Dormancy by Yuhui Dong, Mengjiao Guan, Lixia Wang, Lei Yuan, Xiudong Sun, Shiqi Liu

“…The high-throughput transcriptome sequencing results showed that 6,675 DEGs were upregulated and 36,596 DEGs were downregulated in the aerial bulbs given low-temperature treatment. …”
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Transcriptome Analysis of Dimethyl Fumarate Inhibiting the Growth of <i>Aspergillus carbonarius</i> by Siruo Wang, Bowen Tai, Xifan Yu, Erfeng Li, Gang Wang, Jing Jin, Fuguo Xing

“…To further explore its antifungal mechanism, this study elucidated the functions of key pathway-related genes through a transcriptomics analysis. A total of 1402 differentially expressed genes (DEGs) were identified, including 987 up-regulated and 415 down-regulated genes. …”
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Transcriptomics and metabolomics profiling of Paris polyphylla var. yunnanensis with different growth years by Xiaoye Zhang, Jia Chen, Ping Xu, Xuan Zhang, Shuiyi Yang, Jie Zhang, Xiheng Wan, Yingsi Gao, Guowei Zheng

“…In this study, we collected samples of P. polyphylla aged 3 to 8 years for metabolome and transcriptome sequencing analysis. The total saponin content was found to be significantly higher in 8-year-old P. polyphylla compared to younger plants. …”
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Single-cell and spatial transcriptomic insights into glioma cellular heterogeneity and metabolic adaptations by Yixin Fu, Yong Yi, Yongxiang Shao, Jingcheng Jiang, Qingshan Deng

“…This review integrates recent advancements in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics to elucidate glioblastoma’s cellular heterogeneity and metabolic reprogramming. …”
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Comparative transcriptome analyses indicate molecular homology of zebrafish swimbladder and mammalian lung. by Weiling Zheng, Zhengyuan Wang, John E Collins, Robert M Andrews, Derek Stemple, Zhiyuan Gong

“…Our comparative analyses also provide molecular evidence of the relatedness of the fish swimbladder and mammalian lung.…”
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Evaluation and Interpretation of Transcriptome Data Underlying Heterogeneous Chronic Obstructive Pulmonary Disease by Seokjin Ham, Yeon-Mok Oh, Tae-Young Roh

“…Our extensive evaluation of COPD transcriptome data could provide guidelines for analyzing heterogeneous gene expression profiles and classifying potential candidate genes that are responsible for the pathogenesis of COPD.…”
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