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Rice-wheat comparative genomics:Gains and gaps

The Crop Journal 2024年第3期12卷 656-669页

作者： Akila Wijerathna-Yapa Ruchi Bishnoi Buddhini Ranawaka Manu Maya Magar Hafeez Ur Rehman Swati G.Bharad Michal T.Lorenc Vinita Ramtekey Sasha Gohar Charu Lata Md.Harun-Or-Rashid Maryam Razzaq Muhammad Sajjad Bhoja *** School of Agriculture and Food Sustainability The University of QueenslandSt LuciaQLD 4072Australia ARC Centre of Excellence for Plant Success in Nature and Agriculture The University of QueenslandSt LuciaQLD 4072Australia Department of Genetics and Plant Breeding College of AgricultureUmmedganj-KotaAgriculture UniversityKotaRajasthan 324001India Centre for Agriculture and the Bioeconomy Queensland University of Technology(QUT)2 George StreetBrisbaneQLD 4000Australia UWA School of Agriculture and Environment The University of Western Australia35 Stirling HighwayCrawleyWA 6009Australia Nepal Agriculture Research Council KhumaltarLalitpurNepal Department of Agronomy University of AgricultureFaisalabad 38040Pakistan Department of Agricultural Botany Dr Panjabrao Deshmukh Krishi VidyapeethAkola 444104MaharashtraIndia ICAR-Indian Institute of Seed Science MauUttar Pradesh 275103India School of Natural Sciences Macquarie UniversityMacquarie ParkNSW 2109Australia ICAR-Indian Institute of Wheat and Barley Research Flowrdale 54642ShimlaIndia International Maize and Wheat Improvement Center(CIMMYT)Bangladesh Office Gulshan-2Dhaka 1212Bangladesh Center for Seed Science University of AgricultureFaisalabad 38000Pakistan Department of Biosciences COMSATS University IslamabadPark RoadTarlai KalanIslamabad 45550Pakistan CGIAR’s Excellence in Breeding(EiB)Platform/Accelerated Breeding Initiative International Maize and Wheat Improvement Center(CIMMYT)El Batán 56237Mexico

Rice and wheat provide nearly 40%of human calorie and protein *** share a common ancestor and belong to the Poaceae(grass)*** their genetic homology is crucial for developing new cultivars with enhanced *** wheat genes and gene families have been characterized based on their rice ***–wheat orthology can identify genetic regions that regulate similar traits in both ***–wheat comparative genomics can identify candidate wheat genes in a genomic region identified by association or QTL mapping,deduce their putative functions and biochemical pathways,and develop molecular markers for marker-assisted breeding.A knowledge of gene homology facilitates the transfer between crops of genes or genomic regions associated with desirable traits by genetic engineering,gene editing,or wide crossing.

关键词： Comparative genomics orthologs Genes Synteny Genetic engineering Molecular breeding

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Construction of a Rice Glycosyltransferase Phylogenomic Database and Identification of Rice-Diverged Glycosyltransferases

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Molecular Plant 2008年第5期1卷 858-877页

作者： Pei-Jian Cao Laura E. Bartley Ki-Hong Jung Pamela C. Ronald Department of Plant Pathology University of California Davis CA 95616 and the Joint BioEnergy Institute Emeryville CA 94710 USA Institute of Bioinformatics Zhejiang University Hangzhou Zhejiang 310029 China

Glycosyltransferases （GTs; EC 2.4.x.y） constitute a large group of enzymes that form glycosidic bonds through transfer of sugars from activated donor molecules to acceptor molecules. GTs are critical to the biosynthesis of plant cell walls, among other diverse functions. Based on the Carbohydrate-Active enZymes （CAZy） database and sequence ***, we have identified 609 potential GT genes （loci） corresponding to 769 transcripts （gene models） in rice （Oryza sativa）, the reference monocotyledonous species. Using domain composition and sequence similarity, these rice GTs were classified into 40 CAZy families plus an additional unknown class. We found that two Pfam domains of unknown function, PF04577 and PF04646, are associated with GT families GT61 and GT31, respectively. To facilitate functional analysis of this important and large gene family, we created a phylogenomic Rice GT Database （http：//ricephylogenomics. ***/cellwalls/gtJ）. Through the database, several classes of functional genomic data, including mutant lines and gene expression data, can be displayed for each rice GT in the context of a phylogenetic tree, allowing for comparative analysis both within and between GT families. Comprehensive digital expression analysis of public gene expression data revealed that most （-80%） rice GTs are expressed. Based on analysis with Inparanoid, we identified 282 ‘rice-diverged＇ GTs that lack orthologs in sequenced dicots （Arabidopsis thaliana, Populus tricocarpa, Medicago truncatula, and Ricinus communis）. Combining these analyses, we identified 33 rice-diverged GT genes （45 gene models） that are highly expressed in above-ground, vegetative tissues. From the literature and this analysis, 21 of these loci are excellent targets for functional examination toward understanding and manipulating grass cell wall qualities. Study of the remainder may reveal aspects of hormone and protein metabolism that are critical for rice biology. This list of 33 genes a

关键词： glycosyltransferases GT phylogenetic tree orthologs expression pattern mutant lines phylogenomic database rice cell wall.

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Rice In Vivo RNA Structurome Reveals RNA Secondary Structure Conservation and Divergence in Plants

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Molecular Plant 2018年第4期11卷 607-622页

作者： Hongjing Deng Jitender Cheema Hang Zhang Hugh Woolfenden Matthew Norris Zhenshan Liu Qi Liu Xiaofei Yang Minglei Yang Xian Deng Xiaofeng Cao Yiliang Ding State Key Laboratory of Plant Genomics and National Center for Plant Gene Research CAS Center for Excellence in Molecular Plant Sciences Institute of Genetics and Developmental Biology Chinese Academy of Sciences Beijing 100101 China Department of Cell and Developmental Biology John Innes Centre Norwich Research Park Norwich NR4 7UH UK Department of Computational and Systems Biology John Innes Centre Norwich Research Park Norwich NR4 7UH UK College of Life Sciences University of Chinese Academy of Sciences 100049 Beijing China CAS-JIC Centre of Excellence for Plant and Microbial Science (CEPAMS) John Innes Centre Norwich Research Park Norwich NR4 7UH UK

RNA secondary structure plays a critical role in gene regulation. Rice （Oryza sativa） is one of the most important food crops in the world. However, RNA structure in rice has scarcely been studied. Here, we have successfully generated in vivo Structure-seq libraries in rice. We found that the structural flexibility of mRNAs might associate with the dynamics of biological function. Higher N6-methyladenosine （mSA） modification tends to have less RNA structure in 3＇ UTR, whereas GC content does not significantly affect in vivo mRNA structure to maintain efficient biological processes such as translation. Comparative analysis of RNA structurome between rice and Arabidopsis revealed that higher GC content does not lead to stronger structure and less RNA structural flexibility. Moreover, we found a weak correlation between sequence and structure conservation of the orthologs between rice and Arabidopsis. The conservation and divergence of both sequence and in vivo RNA structure corresponds to diverse and specific biological processes. Our results indicate that RNA secondary structure might offer a separate layer of selection to the sequence between monocot and dicot. Therefore, our study implies that RNA structure evolves differently in various biological processes to maintain robustness in development and adaptational flexibility during angiosperm evolution.

关键词： RNA secondary structure Structure-seq Oryza sativa GC content orthologs

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ortholog——概念、生物信息预测方法和数据库

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生物物理学报 2004年第2期20卷 137-142页

作者：陈作舟朱晟薛成海陈良标浙江大学生命科学院杭州310029 中国科学院遗传与发育生物学研究所北京100080 中国科学院自动化研究所复杂系统与智能科学国家重点实验室北京100080

orthologs指起源于不同物种的最近的共同祖先的一些基因。orthologous的基因,具有相近甚至相同的功能,由相似的途径调控,在不同的物种中扮演相似甚至相同的角色,因此在基因组序列的注释中,是最可靠的选择。orthologs的生物信息预测方法... 详细信息

orthologs指起源于不同物种的最近的共同祖先的一些基因。orthologous的基因,具有相近甚至相同的功能,由相似的途径调控,在不同的物种中扮演相似甚至相同的角色,因此在基因组序列的注释中,是最可靠的选择。orthologs的生物信息预测方法主要有两类:系统发生方法和序列比对方法。这两类方法都是基于序列的相似性,但又各有特点。系统发生方法通过重建系统发生树来预测orthologs,因此在概念上比较精确,但难于自动化,运算量也很大。序列比对方法在概念上比较粗糙,但简单实用,运算量相对较小,因此得到了较广泛的应用。

关键词：基因生物信息学 orthologs 数据库物种生物信息预测方法系统发生序列比对

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