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Haojing Shao Lab


       邵浩靖,副研究员,深圳市海外高层次人才。2018年博士毕业于澳大利亚昆士兰大学,研究方向为针对DNA测序数据数据的生物信息方法开发和分析,开发了npInv和SOAP-popIndel等算法软件。近年来使用自主研发的方法或现有方法对基因组变异进行研究,其结果作为成果的一部分发表到高水平学术期刊,获得引用共计6000余次并以第一作者在Nucleic Acids Research, Scientific Report, BMC Bioinformatics上发表学术论文3篇。



  2020.8–至今          中国农业科学院深圳农业基因组研究所     副研究员

  2018.9–2020.6      昆士兰大学                                             博士后   

  2009.3–2013.12    华大基因                                                课题组长



  2014.1–2018.8                昆士兰大学        博士 

  2006.9–2010.6                华南理工大学    学士     






      Haojing Shao, Associate Professor, Overseas High-Caliber Personnel. He graduated from The University of Queensland in 2018. His research interest is developing computational methods to analyze DNA sequencing data. He has developed computational methods called npInv and SOAP-popIndel. In recent years, he used his own methods or existing methods to study genomic variation, and the results have been published as part of his work in high-level academic journals, which have been quoted more than 6000 times in total.Besides,he also published three papers as the first author at Nucleic Acids Research, Scientific Report, BMC Bioinformatics.


  Research Experience

        2020-now      Shenzhen agricultural Genome Research Institute, Chinese Academy of Agricultural Sciences      Associate Professor

        2018-2020     The University of Queensland                                                                                                            Australia Postdoctoral Fellow

  2009-2013     Shenzhen-Beijing Genomics Institute                                                                                                Leader of a Bioinformatics group



  2014-2018         The University of Queensland, Australia         Ph.D. of Bioinformatics, Supervised by Bernard Degnan and Sandie Degnan

  2006-2010         South China University of Technology            Bachelor of Computer Science


  Research Interest

       At present, our lab focuses on the study of spatial transcriptomics. We use spatial gene expression solution strategy to measure the total mRNA of the complete tissue sections, and we combine the spatial information of total mRNA with the morphological content to obtain the location of all gene expression and a complex and complete gene expression map. Then, we use the spatial location of different genes and cell populations to explore biological issues such as gene and cell functions, phenotype, tissue microenvironment and development, and constructed the 3D transcriptome model. In addition, our lab also aims to use computational methods to explore the genome. Currently, most animal and plant genomes are assembled at chromosome level, but they are not assembled at 100% complete telomere-to-telomere(T2T) level yet. The majority of the unknown sequences are tandem repeat sequences (centromere and ribosomal DNA array) and large segmental duplications. Our lab develops computational methods for next-generation sequencing, third-generation sequencing or Hi-C data to explore and analyze these unknown genetics regions.


  Selected Publication

  1.  Shao, Haojing, et al. "npInv: accurate detection and genotyping of inversions mediated by non-allelic homologous recombination using long read sub-alignment." BMC bioinformatics 19 (1), 261 (2018).    (First Author)

  2. Shao, Haojing, et al. "Ongoing human chromosome end extension driven by a primate ancestral genomic region revealed by analysis of BioNano genomics data." Scientific reports 8 (1), 16616 (2018)      (First Author)

  3. Shao, Haojing, et al. "A population model for genotyping indels from next -generation sequence data." Nucleic acids research 41.3 (2012): e46-e46.    (First Author)

  4. Li, Yingrui, et al. "Structural variation in two human genomes mapped at single-nucleotide resolution by whole genome de novo assembly." Nature biotechnology 29.8 (2011): 723-730.  (co-author) 

  5. Poznik, G. David, et al. "Punctuated bursts in human male demography inferred from 1,244 worldwide Y-chromosome sequences." Nature genetics 48.6 (2016): 593-599.  (co-author)

  6. 1000 Genomes Project Consortium. "A global reference for human genetic variation." Nature 526.7571 (2015): 68.   (co-author)

  7. Tang, Huayang, et al. "A large-scale screen for coding variants predisposing to psoriasis." Nature genetics 46.1 (2014): 45. (co-author)

  8. Zhou, Fusheng, et al. "Deep sequencing of the MHC region in the Chinese population contributes to studies of complex disease." Nature genetics 48.7 (2016): 740.   (co-author)