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Xiaoyuan Wu

Bio: Xiaoyuan Wu is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Sorghum & Sweet sorghum. The author has an hindex of 5, co-authored 12 publications receiving 125 citations.
Topics: Sorghum, Sweet sorghum, Senescence, Medicine, Biology

Papers
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Journal ArticleDOI
TL;DR: In this paper, a pan-genome of 44,079 gene families with 222.6 mb of new sequence identified was generated for the sorghum primary gene pool, and the distribution of these variations was influenced by variation of recombination rate and transposable element content across the genome.
Abstract: Sorghum is a drought-tolerant staple crop for half a billion people in Africa and Asia, an important source of animal feed throughout the world and a biofuel feedstock of growing importance. Cultivated sorghum and its inter-fertile wild relatives constitute the primary gene pool for sorghum. Understanding and characterizing the diversity within this valuable resource is fundamental for its effective utilization in crop improvement. Here, we report analysis of a sorghum pan-genome to explore genetic diversity within the sorghum primary gene pool. We assembled 13 genomes representing cultivated sorghum and its wild relatives, and integrated them with 3 other published genomes to generate a pan-genome of 44,079 gene families with 222.6 Mb of new sequence identified. The pan-genome displays substantial gene-content variation, with 64% of gene families showing presence/absence variation among genomes. Comparisons between core genes and dispensable genes suggest that dispensable genes are important for sorghum adaptation. Extensive genetic variation was uncovered within the pan-genome, and the distribution of these variations was influenced by variation of recombination rate and transposable element content across the genome. We identified presence/absence variants that were under selection during sorghum domestication and improvement, and demonstrated that such variation had important phenotypic outcomes that could contribute to crop improvement. The constructed sorghum pan-genome represents an important resource for sorghum improvement and gene discovery.

56 citations

Journal ArticleDOI
TL;DR: The results imply that selection for Dry gene mutations was a major step leading to the origin of sweet sorghum, and fine-tuning its regulatory network could provide a molecular tool to control crop stem texture.
Abstract: Sorghum (Sorghum bicolor) is the fifth most popular crop worldwide and a C4 model plant. Domesticated sorghum comes in many forms, including sweet cultivars with juicy stems and grain sorghum with dry, pithy stems at maturity. The Dry locus, which controls the pithy/juicy stem trait, was discovered over a century ago. Here, we found that Dry gene encodes a plant-specific NAC transcription factor. Dry was either deleted or acquired loss-of-function mutations in sweet sorghum, resulting in cell collapse and altered secondary cell wall composition in the stem. Twenty-three Dry ancestral haplotypes, all with dry, pithy stems, were found among wild sorghum and wild sorghum relatives. Two of the haplotypes were detected in domesticated landraces, with four additional dry haplotypes with juicy stems detected in improved lines. These results imply that selection for Dry gene mutations was a major step leading to the origin of sweet sorghum. The Dry gene is conserved in major cereals; fine-tuning its regulatory network could provide a molecular tool to control crop stem texture.

51 citations

Journal ArticleDOI
TL;DR: SorGSD is a comprehensive web-portal providing a database of large-scale genome variation across all racial types of cultivated sorghum and wild relatives and can serve as a bioinformatics platform for a range of genomics and molecular breeding activities for sorghums and for other C4 grasses.
Abstract: Background Sorghum (Sorghum bicolor) is one of the most important cereal crops globally and a potential energy plant for biofuel production. In order to explore genetic gain for a range of important quantitative traits, such as drought and heat tolerance, grain yield, stem sugar accumulation, and biomass production, via the use of molecular breeding and genomic selection strategies, knowledge of the available genetic variation and the underlying sequence polymorphisms, is required.

43 citations

Journal ArticleDOI
TL;DR: The importance and potential of the multi-purpose crop sorghum in global food security have not yet been fully exploited, and the integration of the state-of-the-art genomics and high-throughput technologies into breeding practice is required as discussed by the authors.
Abstract: The importance and potential of the multi-purpose crop sorghum in global food security have not yet been fully exploited, and the integration of the state-of-art genomics and high-throughput technologies into breeding practice is required. Sorghum, a historically vital staple food source and currently the fifth most important major cereal, is emerging as a crop with diverse end-uses as food, feed, fuel and forage and a model for functional genetics and genomics of tropical grasses. Rapid development in high-throughput experimental and data processing technologies has significantly speeded up sorghum genomic researches in the past few years. The genomes of three sorghum lines are available, thousands of genetic stocks accessible and various genetic populations, including NAM, MAGIC, and mutagenised populations released. Functional and comparative genomics have elucidated key genetic loci and genes controlling agronomical and adaptive traits. However, the knowledge gained has far away from being translated into real breeding practices. We argue that the way forward is to take a genome-based approach for tailored designing of sorghum as a multi-functional crop combining excellent agricultural traits for various end uses. In this review, we update the new concepts and innovation systems in crop breeding and summarise recent advances in sorghum genomic researches, especially the genome-wide dissection of variations in genes and alleles for agronomically important traits. Future directions and opportunities for sorghum breeding are highlighted to stimulate discussion amongst sorghum academic and industrial communities.

30 citations

Journal ArticleDOI
TL;DR: The monocot C4 model crop Sorghum bicolor is explored for a holistic picture of SAG profiles by RNA-seq, and the candidate orthologues of the known important senescence transcription factors showed “SAG” expression patterns, implicating their possible roles in regulating sorghum leafsenescence.
Abstract: This piece of the submission is being sent via mail. Leaf senescence is essential for the nutrient economy of crops and is executed by so-called senescence-associated genes (SAGs). Here we explored the monocot C4 model crop Sorghum bicolor for a holistic picture of SAG profiles by RNA-seq. Leaf samples were collected at four stages during developmental senescence, and in total, 3396 SAGs were identified, predominantly enriched in GO categories of metabolic processes and catalytic activities. These genes were enriched in 13 KEGG pathways, wherein flavonoid and phenylpropanoid biosynthesis and phenylalanine metabolism were overrepresented. Seven regions on Chromosomes 1, 4, 5 and 7 contained SAG ‘hotspots’ of duplicated genes or members of cupin superfamily involved in manganese ion binding and nutrient reservoir activity. Forty-eight expression clusters were identified, and the candidate orthologues of the known important senescence transcription factors such as ORE1, EIN3 and WRKY53 showed “SAG” expression patterns, implicating their possible roles in regulating sorghum leaf senescence. Comparison of developmental senescence with salt- and dark- induced senescence allowed for the identification of 507 common SAGs, 1996 developmental specific SAGs as well as 176 potential markers for monitoring senescence in sorghum. Taken together, these data provide valuable resources for comparative genomics analyses of leaf senescence and potential targets for the manipulation of genetic improvement of Sorghum bicolor.

29 citations


Cited by
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19 Oct 2016
TL;DR: The BIG Data Center, established at Beijing Institute of Genomics (BIG), Chinese Academy of Sciences, provides a suite of database resources, providing freely open access to a variety of data resources in support of worldwide research activities in both academia and industry.
Abstract: Biological data are generated at unprecedentedly exponential rates, posing considerable challenges in big data deposition, integration and translation. The BIG Data Center, established at Beijing Institute of Genomics (BIG), Chinese Academy of Sciences, provides a suite of database resources, including (i) Genome Sequence Archive, a data repository specialized for archiving raw sequence reads, (ii) Gene Expression Nebulas, a data portal of gene expression profiles based entirely on RNA-Seq data, (iii) Genome Variation Map, a comprehensive collection of genome variations for featured species, (iv) Genome Warehouse, a centralized resource housing genome-scale data with particular focus on economically important animals and plants, (v) Methylation Bank, an integrated database of whole-genome single-base resolution methylomes and (vi) Science Wikis, a central access point for biological wikis developed for community annotations. The BIG Data Center is dedicated to constructing and maintaining biological databases through big data integration and value-added curation, conducting basic research to translate big data into big knowledge and providing freely open access to a variety of data resources in support of worldwide research activities in both academia and industry. All of these resources are publicly available and can be found at http://bigd.big.ac.cn.

322 citations

Journal ArticleDOI
TL;DR: The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support global research in both academia and industry.
Abstract: The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support global research in both academia and industry. With the explosively accumulated multi-omics data at ever-faster rates, CNCB-NGDC is constantly scaling up and updating its core database resources through big data archive, curation, integration and analysis. In the past year, efforts have been made to synthesize the growing data and knowledge, particularly in single-cell omics and precision medicine research, and a series of resources have been newly developed, updated and enhanced. Moreover, CNCB-NGDC has continued to daily update SARS-CoV-2 genome sequences, variants, haplotypes and literature. Particularly, OpenLB, an open library of bioscience, has been established by providing easy and open access to a substantial number of abstract texts from PubMed, bioRxiv and medRxiv. In addition, Database Commons is significantly updated by cataloguing a full list of global databases, and BLAST tools are newly deployed to provide online sequence search services. All these resources along with their services are publicly accessible at https://ngdc.cncb.ac.cn.

186 citations

Journal ArticleDOI
TL;DR: BI Search, a scalable, one-stop, cross-database search engine, has been significantly updated by providing easy access to a large number of internal and external biological resources from CNCB-NGDC, its partners, EBI and NCBI.
Abstract: The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a suite of database resources to support worldwide research activities in both academia and industry. With the explosive growth of multi-omics data, CNCB-NGDC is continually expanding, updating and enriching its core database resources through big data deposition, integration and translation. In the past year, considerable efforts have been devoted to 2019nCoVR, a newly established resource providing a global landscape of SARS-CoV-2 genomic sequences, variants, and haplotypes, as well as Aging Atlas, BrainBase, GTDB (Glycosyltransferases Database), LncExpDB, and TransCirc (Translation potential for circular RNAs). Meanwhile, a series of resources have been updated and improved, including BioProject, BioSample, GWH (Genome Warehouse), GVM (Genome Variation Map), GEN (Gene Expression Nebulas) as well as several biodiversity and plant resources. Particularly, BIG Search, a scalable, one-stop, cross-database search engine, has been significantly updated by providing easy access to a large number of internal and external biological resources from CNCB-NGDC, our partners, EBI and NCBI. All of these resources along with their services are publicly accessible at https://bigd.big.ac.cn.

168 citations

Journal ArticleDOI
TL;DR: In this article, a suite of new approaches that fast-track targeted manipulation of allelic variation for creating novel diversity and facilitate their rapid and efficient incorporation in crop improvement programs is presented.

163 citations

Journal ArticleDOI
TL;DR: Various attributes of sweet sorghum that make it an ideal candidate for biofuel feedstock are discussed, and an overview of genetic diversity, tools, and resources available for engineering and/or marker-assisting breeding of sweet Sorghum are provided.
Abstract: Sweet sorghum is a promising target for biofuel production. It is a C4 crop with low input requirements and accumulates high levels of sugars in its stalks. However, large-scale planting on marginal lands would require improved varieties with optimized biofuel-related traits and tolerance to biotic and abiotic stresses. Considering this, many studies have been carried out to generate genetic and genomic resources for sweet sorghum. In this review, we discuss various attributes of sweet sorghum that make it an ideal candidate for biofuel feedstock, and provide an overview of genetic diversity, tools, and resources available for engineering and/or marker-assisting breeding of sweet sorghum. Finally, the progress made so far, in identification of genes/quantitative trait loci (QTLs) important for agronomic traits and ongoing molecular breeding efforts to generate improved varieties, has been discussed.

162 citations