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Genome-wide identification and gene expression pattern reveal dominant digestive enzyme genes contributing to major enzyme activities during the molting cycle of the Chinese mitten crab, Eriocheir sinensis

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AQUACULTURE 2025年 597卷

作者： Zhu, Boxiang Zhang, Min Li, Mingjie Pan, Kewu Yao, Ping Zhang, Xin Wu, Xugan Shanghai Ocean Univ Key Lab Explorat & Utilizat Aquat Genet Resources Minist Educ Shanghai 201306 Peoples R China Chinese Acad Sci South China Sea Inst Oceanol Key Lab Breeding Biotechnol & Sustainable Aquacult Key Lab Trop Marine Bioresources & EcolGuangdong Guangzhou 510301 Peoples R China Shanghai Ocean Univ Shanghai Collaborat Innovat Aquat Anim Genet & Bre Shanghai 201306 Peoples R China Shanghai Ocean Univ Ctr Res Environm Ecol & Fish Nutr Minist Agr Shanghai 201306 Peoples R China

Chinese mitten crab Eriocheir sinensis is an important economic species, but it largely remains unknown for the genome-wide identification of digestive enzyme genes, gene expression pattern and their activities during the molting cycle of E. sinensis. Therefore, this study was conducted to investigate the diversity of major digestive enzyme genes, their dynamic expression patterns as well as the digestive enzyme activities during the molting cycle;the binding sites and affinities of major digestive enzyme-substrate were also predicted using molecular docking analysis. The results revealed that there were 4 alpha-amylase genes, 14 trypsin genes, and 7 lipase genes identified in E. sinensis. Among them, Es-Amylase4, Es-Trypsin11-I7, and Es-Lipase1 exhibited the highest transcriptional expression levels respectively, with Es-Amylase4 and Es-Lipase1 peaking in stage C and Es-Trypsin11-I7 in stage D. The alpha-amylase and lipase activities peak in stage C, while trypsin activity was highest in stage A/B. During molting process, the transcriptional expression levels of 4 alpha-amylase isoforms and 3 lipase isoforms positively correlated with enzyme activity changes, and the expression of Es-lipase1-mRNA was significantly higher than the other lipase transcripts (P < 0.05). As lipase is one of most important digestive enzymes during food digestion and there are two transcription isoforms with significantly higher expression levels than the others. There were 1 and 3 hydrogen bonds for Es-lipase1- triglyceride and Es-lipase7- triglyceride complexes, respectively, while the binding affinities of Es-lipase1- triglyceride and Es-lipase7- triglyceride were- 8.0 kcal/ mol and- 7.1 kcal/mol, respectively. In conclusion, crustaceans have numerous digestive enzymes with a high degree of polymorphism, but there are 3, 2, and 1 highly expressed gene in E. sinensis contributed to the major enzyme activities of alpha-amylase, trypsin, and lipase, respectively. For alpha-amylase and lip

关键词： Crustacean genetic diversity of digestive enzyme Genome-wide identification gene expression pattern Molecular docking

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Drosophila gene expression pattern Annotation through Multi-Instance Multi-Label Learning

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2012年第1期9卷 98-112页

作者： Li, Ying-Xin Ji, Shuiwang Kumar, Sudhir Ye, Jieping Zhou, Zhi-Hua Nanjing Univ Natl Key Lab Novel Software Technol Nanjing 210093 Peoples R China Old Dominion Univ Dept Comp Sci Norfolk VA 23529 USA Arizona State Univ Biodesign Inst Ctr Evolutionary Med & Informat Tempe AZ 85287 USA

In the studies of Drosophila embryogenesis, a large number of two-dimensional digital images of gene expression patterns have been produced to build an atlas of spatio-temporal gene expression dynamics across developmental time. gene expressions captured in these images have been manually annotated with anatomical and developmental ontology terms using a controlled vocabulary (CV), which are useful in research aimed at understanding gene functions, interactions, and networks. With the rapid accumulation of images, the process of manual annotation has become increasingly cumbersome, and computational methods to automate this task are urgently needed. However, the automated annotation of embryo images is challenging. This is because the annotation terms spatially correspond to local expression patterns of images, yet they are assigned collectively to groups of images and it is unknown which term corresponds to which region of which image in the group. In this paper, we address this problem using a new machine learning framework, Multi-Instance Multi-Label (MIML) learning. We first show that the underlying nature of the annotation task is a typical MIML learning problem. Then, we propose two support vector machine algorithms under the MIML framework for the task. Experimental results on the FlyExpress database (a digital library of standardized Drosophila gene expression pattern images) reveal that the exploitation of MIML framework leads to significant performance improvement over state-of-the-art approaches.

关键词： gene expression pattern image annotation machine learning multi-instance multi-label (MIML) learning support vector machine Drosophila

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Clustering gene expression pattern and extracting relationship in gene network based on artificial neural networks

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JOURNAL OF BIOSCIENCE AND BIOENGINEERING 2003年第5期96卷 421-428页

作者： Huang, JH Shimizu, H Shioya, S Osaka Univ Dept Biotechnol Grad Sch Engn Suita Osaka 5650871 Japan Osaka Univ Dept Bioinformat Engn Grad Sch Informat Sci & Technol Suita Osaka 5650871 Japan

Massive datasets such as gene expression profiles are accumulating along with the development of DNA microarray technologies. In this paper, we focus on mining biological relevant information such as typical expression patterns and the interconnections of gene networks from massive datasets. At first, the algorithm of a self-organizing map (SOM) was used to cluster gene expression data. Then, for the typical patterns extracted by the SOM, a three-layer artificial neural network (ANN) model was used to extract the relationships between the expression patterns. In order to evaluate the clustering analysis based on the SOM, biological and statistical indices were introduced. To validate the efficiency of the scheme proposed for extracting the relationships between the expression patterns with the ANN, a test dataset was created and used for the test. Finally, the interconnections of a typical pattern of early G1, late G1, S, G2, and M phases in a yeast cell cycle were extracted and visualized.

关键词： clustering gene expression pattern self-organizing map artificial neural network

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Relationship between 5′ UTR length and gene expression pattern in chicken

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geneTICA 2013年第7-9期141卷 311-318页

作者： Rao, You S. Wang, Zhang F. Chai, Xue W. Nie, Qing H. Zhang, Xi Q. Nanchang Normal Univ Dept Biol Technol Nanchang Jiangxi Peoples R China South China Agr Univ Guangdong Prov Key Lab Agroanim Genom & Mol Breed Guangzhou Guangdong Peoples R China

The chicken (Gallus gallus) is an important model organism that bridges the evolutionary gap between mammals and non-amniote vertebrates. Here, we carried out a systematic study of the relationship between 5' UTR length and gene expression pattern in the chicken genome. We found that gene 5' UTRs lengths show a negative correlation with gene expression levels and gene expression breadths significantly. The relevance of 5' UTR length to expression pattern can not be a consequence of transcription-associated mutations. We also found that gene 5' UTR length shows a weakly positive correlation with gene tissue specificity. Another intriguing finding is that genes with 5' UTR length < 30 bp have highest expression level, highest expression breadth, and lowest tissue specificity in chicken. We argued that selection is likely involved in shaping 5' UTR length in the chicken genome.

关键词： Gallus gallus 5' UTR length gene expression pattern Selection

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Isolation of developmentally regulated novel genes based on sequence identity and gene expression pattern

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MOLECULES AND CELLS 1999年第2期9卷 207-218页

作者： Kim, SJ Shin, JH Kim, J Kim, SH Chae, JH Park, EJ Seong, RH Hong, SH Park, SD Jeong, S Kim, CG Hanyang Univ Coll Nat Sci Dept Life Sci Seoul 133791 South Korea Seoul Natl Univ Inst Mol Biol & Genet Seoul 151742 South Korea Seoul Natl Univ Dept Mol Biol Seoul 151742 South Korea Seoul Natl Univ Res Ctr Cell Differentiat Seoul 151742 South Korea Dankook Univ Dept Mol Biol Seoul 140714 South Korea

Based on the surmise that a variety of genes might play important roles in embryonic development and tissue differentiation, and that some of them are likely to be expressed in undifferentiated ES cells, we attempted to identify new genes from the ES cell cDNA library. The modified method of expressed sequence tags (ESTs) and the examination of the expression patterns in adult tissues and in vitro differentiated ES cells were utilized in this study. We have isolated and identified several novel cDNA clones with interesting developmental expression pattern. Among the 83 clones randomly chosen, 23 clones (27.7%) have no homology to any sequences in public databases. The rest contain limited or complete sequence homology to the previously reported mammalian genes or ESTs, yet some clones have not been previously identified in the mouse. To examine the expression profile of clones during development and differentiation, sets of slot blots were hybridized with developmental stage specific or tissue specific probes. Out of 40 novel clones tested (21 totally unknown clones and 19 unidentified clones in mouse), most of them were up- or down-regulated as differentiation proceeded, and some clones showed differentiation-stage specific expression profiles. Surprisingly, a majority of genes were also expressed in adult tissues, and some clones even revealed tissue specific expression, These results demonstrate that not only was the strategy we employed in this study quite efficient for screening novel genes, but that the information gained by such studies would also be a useful guide for further analysis of these genes. It also suggests the feasibility of this approach to explore the genomewide network of gene expression during complicated biological processes, such as embryonic development and tissue differentiation.

关键词： development and differentiation embryonic stem cells ESTs gene cloning gene expression pattern

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Involvement of TNF-α in differential gene expression pattern of CXCR4 on human marrow-derived mesenchymal stem cells

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MOLECULAR BIOLOGY REPORTS 2014年第2期41卷 1059-1066页

作者： Ziaei, Rozita Ayatollahi, Maryam Yaghobi, Ramin Sahraeian, Zeinab Zarghami, Nosratollah Shiraz Univ Med Sci Transplant Res Ctr Shiraz Iran

Cell therapy and tissue repair are used in a variety of diseases including tissue and organ transplantation, autoimmune diseases and cancers. Now mesenchymal stem cells (MSCs) are an attractive and promising source for cell-based therapy according to their individual characteristics. Soluble factors which are able to induce MSCs migration have a vital role in cell engraftment and tissue regeneration. Tumor necrosis factor alpha (TNF-alpha) is a major cytokine present in damaged tissues. We have investigated the pattern of gene expression of chemokine receptor CXCR4 in nine groups of human bone marrow-derived MSCs stimulated with TNF-alpha in different dose and time manner. Comparison of TNF-alpha treated with untreated MSCs revealed the highest expression level of CXCR4 after treatment with 1, and 10 ng/ml of TNF-alpha in 24 h, and the production of CXCR4 mRNA was regulated up to 216 and 512 fold, respectively. Our results demonstrated the differential gene expression pattern of chemokine receptor CXCR4 in human marrow-derived MSCs stimulated with inflammatory cytokine TNF-alpha. These findings suggest that in vitro control of both dose and time factors may be important in stem cell migration capacity, and perhaps in future-stem cell transplantation therapies.

关键词： Mesenchymal stem cell Chemokine receptor CXCR4 Tumor necrosis factor alpha gene expression pattern Real time PCR

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Identification of an IL-1-induced gene expression pattern in AR⁺ PCa cells that mimics the molecular phenotype of AR^- PCa cells

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PROSTATE 2018年第8期78卷 595-606页

作者： Thomas-Jardin, Shayna E. Kanchwala, Mohammed S. Jacob, Joan Merchant, Sana Meade, Rachel K. Gahnim, Nagham M. Nawas, Afshan F. Xing, Chao Delk, Nikki A. Univ Texas Dallas Dept Biol Sci Richardson TX 75083 USA Univ Texas Southwestern Med Ctr Dallas McDermott Ctr Human Growth & Dev Dallas TX 75390 USA Univ Texas Southwestern Med Ctr Dallas Dept Bioinformat Dallas TX 75390 USA Univ Texas Southwestern Med Ctr Dallas Dept Clin Sci Dallas TX 75390 USA

BackgroundIn immunosurveillance, bone-derived immune cells infiltrate the tumor and secrete inflammatory cytokines to destroy cancer cells. However, cancer cells have evolved mechanisms to usurp inflammatory cytokines to promote tumor progression. In particular, the inflammatory cytokine, interleukin-1 (IL-1), is elevated in prostate cancer (PCa) patient tissue and serum, and promotes PCa bone metastasis. IL-1 also represses androgen receptor (AR) accumulation and activity in PCa cells, yet the cells remain viable and tumorigenic;suggesting that IL-1 may also contribute to AR-targeted therapy resistance. Furthermore, IL-1 and AR protein levels negatively correlate in PCa tumor cells. Taken together, we hypothesize that IL-1 reprograms AR positive (AR(+)) PCa cells into AR negative (AR(-)) PCa cells that co-opt IL-1 signaling to ensure AR-independent survival and tumor progression in the inflammatory tumor microenvironment. MethodsLNCaP and PC3 PCa cells were treated with IL-1 or HS-5 bone marrow stromal cell (BMSC) conditioned medium and analyzed by RNA sequencing and RT-QPCR. To verify genes identified by RNA sequencing, LNCaP, MDA-PCa-2b, PC3, and DU145 PCa cell lines were treated with the IL-1 family members, IL-1 or IL-1, or exposed to HS-5 BMSC in the presence or absence of Interleukin-1 Receptor Antagonist (IL-1RA). Treated cells were analyzed by western blot and/or RT-QPCR. ResultsComparative analysis of sequencing data from the AR(+) LNCaP PCa cell line versus the AR(-) PC3 PCa cell line reveals an IL-1-conferred gene suite in LNCaP cells that is constitutive in PC3 cells. Bioinformatics analysis of the IL-1 regulated gene suite revealed that inflammatory and immune response pathways are primarily elicited;likely facilitating PCa cell survival and tumorigenicity in an inflammatory tumor microenvironment. ConclusionsOur data supports that IL-1 reprograms AR(+) PCa cells to mimic AR(-) PCa gene expression patterns that favor AR-targeted treatment resistance an

关键词： androgen receptor gene expression pattern interleukin-1 prostate cancer treatment resistance

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AUTOMATED gene expression pattern ANNOTATION IN THE MOUSE BRAIN 20

AUTOMATED GENE EXPRESSION PATTERN ANNOTATION IN THE MOUSE BR...

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20th Pacific Symposium on Biocomputing (PSB)

作者： Yang, Tao Zhao, Xinlin Lin, Binbin Zeng, Tao Ji, Shuiwang Ye, Jieping Arizona State Univ Dept Comp Sci & Engn Tempe AZ 85287 USA Arizona State Univ Biodesign Inst Ctr Evolutionary Med & Informat Tempe AZ 85287 USA Old Dominion Univ Dept Comp Sci Norfolk VA 23529 USA

ISBN: (纸本)9789814644730;9789814644723

Brain tumor is a fatal central nervous system disease that occurs in around 250,000 people each year globally and it is the second cause of cancer in children. It has been widely acknowledged that genetic factor is one of the significant risk factors for brain cancer. Thus, accurate descriptions of the locations of where the relative genes are active and how these genes express are critical for understanding the pathogenesis of brain tumor and for early detection. The Allen Developing Mouse Brain Atlas is a project on gene expression over the course of mouse brain development stages. Utilizing mouse models allows us to use a relatively homogeneous system to reveal the genetic risk factor of brain cancer. In the Allen atlas, about 435,000 high-resolution spatiotemporal in situ hybridization images have been generated for approximately 2,100 genes and currently the expression patterns over specific brain regions are manually annotated by experts, which does not scale with the continuously expanding collection of images. In this paper, we present an efficient computational approach to perform automated gene expression pattern annotation on brain images. First, the gene expression information in the brain images is captured by invariant features extracted from local image patches. Next, we adopt an augmented sparse coding method, called Stochastic Coordinate Coding, to construct high-level representations. Different pooling methods are then applied to generate gene-level features. To discriminate gene expression patterns at specific brain regions, we employ supervised learning methods to build accurate models for both binary-class and multi-class cases. Random undersampling and majority voting strategies are utilized to deal with the inherently imbalanced class distribution within each annotation task in order to further improve predictive performance. In addition, we propose a novel structure-based multi-label classification approach, which makes use of label hierarchy

关键词： gene expression pattern Image Annotation Sparse Learning Imbalanced Learning Multi-label classification Label Hierarchy

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Drosophila gene expression pattern Annotation Using Sparse Features and Term-Term Interactions 09

Drosophila Gene Expression Pattern Annotation Using Sparse F...

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15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

作者： Ji, Shuiwang Yuan, Lei Li, Ying-Xin Zhou, Zhi-Hua Kumar, Sudhir Ye, Jieping Arizona State Univ Biodesign Inst Ctr Evolutionary Funct Genom Tempe AZ 85287 USA

ISBN: (纸本)9781605584959

The Drosophila gene expression pattern images document the spatial and temporal dynamics of gene expression and they are valuable tools for explicating the gene functions, interaction, and networks during Drosophila embryogenesis. To provide text-based pattern searching, the images in the Berkeley Drosophila Genome Project (BDGP) study are annotated with ontology terms manually by human curators. We present a systematic approach for automating this task, because the number of images needing text descriptions is now rapidly increasing. We consider both improved feature representation and novel learning formulation to boost the annotation performance. For feature representation, we adapt the bag-of-words scheme commonly used in visual recognition problems so that the image group information in the BDGP study is retained. Moreover, images from multiple views can e integrated naturally in this representation. To reduce the quantization error caused by the bag-of-words representation, we propose an improved feature representation scheme based on the sparse learning technique. In the design of learning formulation, we propose a local regularization framework that can incorporate the correlations among terms explicitly. We further show that the resulting optimization problem admits an analytical solution. Experimental results show that the representation based on sparse learning outperforms the bag-of-words representation significantly. Results also show that incorporation of the term-term correlations improves the annotation performance consistently.

关键词： gene expression pattern image annotation bag-of-words sparse learning regularization

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Whole-body gene expression pattern registration in Platynereis larvae

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EVODEVO 2012年第1期3卷 27-27页

作者： Asadulina, Albina Panzera, Aurora Veraszto, Csaba Liebig, Christian Jekely, Gasper Max Planck Inst Dev Biol D-72076 Tubingen Germany

Background: Digital anatomical atlases are increasingly used in order to depict different gene expression patterns and neuronal morphologies within a standardized reference template. In evo-devo, a discipline in which the comparison of gene expression patterns is a widely used approach, such standardized anatomical atlases would allow a more rigorous assessment of the conservation of and changes in gene expression patterns during micro- and macroevolutionary time scales. Due to its small size and invariant early development, the annelid Platynereis dumerilii is particularly well suited for such studies. Recently a reference template with registered gene expression patterns has been generated for the anterior part (episphere) of the Platynereis trochophore larva and used for the detailed study of neuronal development. Results: Here we introduce and evaluate a method for whole-body gene expression pattern registration for Platynereis trochophore and nectochaete larvae based on whole-mount in situ hybridization, confocal microscopy, and image registration. We achieved high-resolution whole-body scanning using the mounting medium 2,2'-thiodiethanol (TDE), which allows the matching of the refractive index of the sample to that of glass and immersion oil thereby reducing spherical aberration and improving depth penetration. This approach allowed us to scan entire whole-mount larvae stained with nitroblue tetrazolium/5-bromo-4-chloro-3-indolyl phosphate (NBT/BCIP) in situ hybridization and counterstained fluorescently with an acetylated-tubulin antibody and the nuclear stain 4'6-diamidino-2-phenylindole (DAPI). Due to the submicron isotropic voxel size whole-mount larvae could be scanned in any orientation. Based on the whole-body scans, we generated four different reference templates by the iterative registration and averaging of 40 individual image stacks using either the acetylated-tubulin or the nuclear-stain signal for each developmental stage. We then registered to t

关键词： gene expression pattern Image Registration Average Absolute Deviation Reference Marker Ciliary Band

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