作物遗传育种系
2014 – 至今 中国农业大学 农学院，作物遗传育种系，国家玉米改良中心，教授（博士生导师）
2010 – 2014 美国亚利桑那大学，农业与生命科学学院，助理教授
2008 – 2010 美国哈佛大学，公共健康学院，博士后
2007 – 2008 美国耶鲁大学，分子细胞发育生物学系，博士后
2002 – 2007 北京大学，生命科学学院，生物信息学 博士
1998 – 2002 中国农业大学，生物学院，生物科学 学士
植物基因组学
王向峰课题组主要应用人工智能与机器学习技术开发玉米智能设计育种决策模型、全基因组选择模型、基因型与环境互作模型；开发玉米育种信息管理系统、育种大数据分析软件；开发玉米多组学数据关联分析算法、种质资源挖掘工具、各类生物信息软件。研究方向主要利用组学大数据从事玉米杂交育种理论、玉米杂种优势遗传互作机制、玉米基因组驯化、玉米适应性演化机制等方面的工作。在Genome Biology, Science Bulletin, Plant Cell, PNAS, Trends in Plant Sciences, Molecular Plants, Plant Journal等国际知名期刊发表论文60余篇。
团队主页：http://ibreeding.org/
生物信息工具及育种软件
1. 王向峰教授课题组主页
2. CropGBM: Genomic Breeding Machines for Crops
(https://ibreeding.github.io/)
3. MODAS: Multi-Omics Data Association Studies
(https://modas-bio.github.io/)
4. GOVS: Genome Optimization via Virtual Simulation
(https://govs-pack.github.io/)
5. MRBIGR: Mendelian Randomization-Based Inference of Genetic Regulation
(https://github.com/liusy-jz/MRBIGR)
6. SR4R database: SNP Ready for Rice
7. iFLAS: Integrative Full Length Alternative Splicing analysis
(http://github.com/CrazyHsu/iFLAS_toolkit)
8. mlDNA: Machine learning-based Differential Network Analysis
(https://cran.r-project.org/src/contrib/Archive/mlDNA/)
发表文章（# 通讯作者，* 第一作者）
1. Liu S, Xu F, Xu Y, Wang Q, Yan J, Wang J, Wang X, Wang X#. MODAS: exploring maize germplasm with multi-omics data association studies. Science Bulletin. 2022. 67(9), 903-906.
2. Cheng Q, Jiang S, Xu F, Wang Q, Xiao Y, Zhang R, Zhao J, Yan J, Ma C#, Wang X#. Genome Optimization via Virtual Simulation to Accelerate Maize Hybrid Breeding. Briefings in Bioinformatics. 2022 Jan 17;23(1): bbab447.
3. Yan J, Xu Y, Cheng Q, Jiang S, Wang Q, Xiao Y, Ma C, Yan J#, Wang X#. LightGBM: accelerated genomically designed crop breeding through ensemble learning. Genome Biology. 2021 Sep 20;22(1):271.
4. Liang X, Liu S, Wang T, Li F, Cheng J, Lai J, Qin F, Li Z#, Wang X#, Jiang C#. Metabolomics-driven gene mining and genetic improvement of tolerance to salt-induced osmotic stress in maize. New Phytol. 2021;230 (6):2355-2370.
5. Xu Y, Laurie J, Wang X#. CropGBM: An ultra-efficient machine learning toolbox for genomic selection-assisted breeding in crops. 2021 Oct, In: Bilichak A., Laurie J.D. (eds) Accelerated Breeding of Cereal Crops. Springer Protocols Handbooks. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1526-3_5
6. McGowan M, Wang J, Dong H, Liu X, Jia Y, Wang X, Iwata H, Li Y, Lipka A.E, Zhang Z. Ideas in Genomic Selection with the Potential to Transform Plant Molecular Breeding: A Review. 2021. A chapter for the book Plant Breeding Reviews. Volume 45. John Wiley & Sons, Inc.
7. Yang C, Yan J, Jiang S, Li X, Min H, Wang X#, Hao D#. Resequencing 250 soybean accessions: new insights into genes associated with agronomic traits and genetic networks. Genomics Proteomics Bioinformatics. 2021. July 24; S1672- 0229 (21) 00160-1.
8. Cui F, Taier G, Wang X, Wang K. Genome-Wide Analysis of the HSP20 Gene Family and Expression Patterns of HSP20 Genes in Response to Abiotic Stresses in Cynodon transvaalensis. Frontiers in Genetics. 2021. 12:732812.
9. CNCB-NGDC Members and Partners. Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2021. Nucleic Acids Res. 2021 Jan 8;49(D1): D18-D28
10. Cui F, Taier G, Li M, Dai X, Hang N, Zhang X, Wang X#, Wang K#. The genome of the warm-season turfgrass African bermudagrass (Cynodon transvaalensis). Horticulture Research. 2021 May 1;8(1):93
11. Xiao Y, Jiang S, Cheng Q, Wang X, Yan J, Zhang R, Qiao F, Ma C, Luo J, Li W, Liu H, Yang W, Song W, Meng Y, Warburton ML, Zhao J#, Wang X#, Yan J#. The genetic mechanism of heterosis utilization in maize improvement. Genome Biology. 2021. 10;22(1):148.
12. Zhang SJ, Liu L, Yang R#, Wang X#. Genome size evolution mediated by Gypsy retrotransposons in Brassicaceae. Genomics Proteomics Bioinformatics. 2020. 18(3):321-332.
13. Jiang S, Cheng Q, Yan J, Fu R, Wang X#. Genome optimization for improvement of maize breeding. Theor Appl Genet. 2020. 133(5):1491-1502.
14. Li H, Jiang S, Li C, Liu L, Lin Z, He H, Deng XW, Zhang Z#, Wang X#. The hybrid protein interactome contributes to rice heterosis as epistatic effects. Plant Journal. 2020. 102(1):116-128
15. Yan J, Zou D, Li C, Zhang Z, Song S#, Wang X#. SR4R: An Integrative SNP Resource for Genomic Breeding and Population Research in Rice. Genomics Proteomics Bioinformatics. 2020. 18(2):173-185
16. Lin Z, Qin P, Zhang X, Fu C, Deng H, Fu X, Huang Z, Jiang S, Li C, Tang X, Wang X, He G, Yang Y, He H, Deng XW. Divergent selection and genetic introgression shape the genome landscape of heterosis in hybrid rice. Proc Natl Acad Sci USA. 2020. 3;117(9):4623-4631
17. Zhang H, Zhang Q, Zhai H, Gao S, Yang L, Wang Z, Xu Y, Huo J, Ren Z, Zhao N, Wang X, Li J, Liu Q, He S. IbBBX24 Promotes the Jasmonic Acid Pathway and Enhances Fusarium Wilt Resistance in Sweet Potato. Plant Cell. 2020 Apr; 32(4):1102-1123.
18. Guo W, Zhu P, Pellegrini M, Zhang MQ, Wang X, Ni Z. CGmapTools improves the precision of heterozygous SNV calls and supports allele-specific methylation detection and visualization in bisulfite-sequencing data. Bioinformatics. 2018. 1;34(3):381-387
19. Liang P, Liu S, Xu F, Jiang S, Yan J, He Q, Liu W, Lin C, Zheng F, Wang X#, Miao W#. Powdery mildews are characterized by contracted carbohydrate metabolism and diverse effectors to adapt to obligate biotrophic lifestyle. Frontiers in Microbiology. 2018. 18;9:3160.
20. Zhang SJ, Meng P, Zhang J, Jia P, Lin J, Wang X, Chen F#, Wei X#. Machine learning models for genetic risk assessment of infants with non-syndromic orofacial cleft. Genomics Proteomics Bioinformatics. 2018. 16(5):354-364.
21. Zhan J, Li G, Ryu CH, Ma C, Zhang S, Lloyd A, Hunter BG, Larkins BA, Drews GN, Wang X, Yadegari R. Opaque-2 regulates a complex gene network associated with cell differentiation and storage functions of maize endosperm. Plant Cell. 2018. 30(10):2425-2446.
22. Zhang SJ, Wang C, Yan S, Fu A, Luan X, Li Y, Sunny Shen Q, Zhong X, Chen JY, Wang X, Chin-Ming Tan B, He A, Li CY. Isoform evolution in primates through independent combination of alternative RNA processing events. Molecular Biology Evolution. 2017. 1;34(10):2453-2468
23. Wang Y, Yu H, Tian C, Sajjad M, Gao C, Tong Y, Wang X#, Jiao Y#. Transcriptome association identifies regulators of wheat spike architecture. Plant Physiology. 2017. 175(2):746-757
24. Zhang H, Zhang Q, Zhai H, Li Y, Wang X, Liu Q, He S, Transcript profile analysis reveals important roles of jasmonic acid signalling pathway in the response of sweet potato to salt stress. Scientific Reports. 2017. 13;7:40819
25. Yan J, Lv S, Hu M, Gao Z, He H, Ma Q, Deng XW, Zhu Z#, Wang X#. Single-Molecule Sequencing Assists Genome Assembly Improvement and Structural Variation Inference. Molecular Plants. 2016. 6;9(7):1085-7
26. IC4R Project Consortium., Hao L, Zhang H, Zhang Z, Hu S, Xue Y, Wang X etc., Information Commons for Rice (IC4R), Nucleic Acids Res. 2016 4;44: D1172-80.
27. Xin M, Yang G, Yao Y, Peng H, Hu Z, Sun Q, Wang X, Ni Z. Temporal small RNA transcriptome profiling unraveled partitioned miRNA expression in developing maize endosperms between reciprocal crosses. Front Plant Sci. 2015. 15;6:744
28. Yao X, Arst HN Jr, Wang X, Xiang X., Discovery of a vezatin-like protein for dynein-mediated early endosome transport. Mol Biol Cell. 2015.1;26(21):3816-27
29. Zhan J, Thakare D, Ma C, Lloyd A, Nixon NM, Arakaki AM, Burnett WJ, Logan KO, Wang D, Wang X, Drews GN, Yadegari R., RNA sequencing of laser-capture microdissected compartments of the maize kernel identifies regulatory modules associated with endosperm cell differentiation. Plant Cell. 2015. 27(3):513-31
30. Ma C, Zhang HH, Wang X. Machine learning for Big Data analytics in plants. Trends in Plant Sciences. 2014. 19(12):798-808.
31. Thakare D, Yang R, Steffen JG, Zhan J, Wang D, Clark RM, Wang X, Yadegari R, RNA-Seq analysis of laser-capture microdissected cells of the developing central starchy endosperm of maize, Genomic Data. 2014 Aug 7;2:242-5
32. Xin M, Yang R, Yao Y, Ma C, Peng H, Sun Q, Wang X, Ni Z., Dynamic parent-of-origin effects on small interfering RNA expression in the developing maize endosperm. BMC Plant Biol. 2014. 24;14:192
33. Yao X, Wang X, Xiang X. FHIP and FTS proteins are critical for dynein mediated transport of early endosomes in Aspergillus. Mol Biol Cell. 2014 Jul 15;25(14):2181-9
34. Li G, Wang D, Yang R, Logan K, Chen H, Zhang S, Skaggs MI, Lloyd A, Burnett WJ, Laurie JD, Hunter BG, Dannenhoffer JM, Larkins BA#, Drews GN, Wang X#, Yadegari R#. Temporal patterns of gene expression in developing maize endosperm identified through transcriptome sequencing. Proc Natl Acad Sci. USA 2014. 27;111(21):7582-7
35. Ma C, Xin M, Feldmann KA, Wang X#. Machine Learning-Based Differential Network Analysis: A Study of Stress-Responsive Transcriptomes in Arabidopsis. Plant Cell. 2014 Feb;26(2):520-37
36. Xin M, Yang R, Li G, Chen H, Laurie J, Ma C, Wang D, Yao Y, Larkins B, Sun Q, Yadegari, R, Wang X# and Ni Z. Dynamic expression of imprinted genes associates with maternally controlled nutrient allocation during maize endosperm development. Plant Cell. 2013. 25(9):3212-27;
37. Zhang Y, Yu N, Huang Q, Yin G, Guo A, Wang X, Xiong Z, Liu Z. Complete genome of Hainan papaya ringspot virus using small RNA deep sequencing. Virus Genes. 2014 Jun;48(3):502-8
38. Chen, H and Wang, X#. CrusView: a Java-based visualization platform for comparative genomics analyses in Brassicaceae species. 2013. Plant Physiology; 163(1):354-62
39. Wei, X and Wang, X#. A computational workflow to identify allele-specific expression and epigenetic modification in maize. 2013. Genomics Proteomics Bioinformatics; 11(4): 247-52
40. Yang R, Chen H, Jarvis D, Beilstein M, Grimwood J, Jenkins J, Shu S, Prochnik S, Xin M, Ma C, Schmutz J, Wing R, Mitchell-Olds T, Schumaker K#, Wang X#. The reference genome of the halophytic plant Eutrema salsugineum. 2013. Frontier in Plant Sciences; 4:46
41. Ma C, Chen H, Yang R, Xin M, Wang X#. KGBassembler: A karyotype-based genome assembler for Brassicaceae species. 2012. Bioinformatics; 28(23):3141-3
42. Yang R and Wang X#. Organ evolution in angiosperms driven by correlated divergences of gene sequences and expression patterns. 2012. The Plant Cell; 25(1):71-82
43. Ma C and Wang X#. Application of the Gini correlation coefficient to infer regulatory relationships in transcriptome analysis. 2012. Plant Physiology; 160(1):192-203
44. Xin M, Wang X, Peng H, Yao Y, Xie C, Han Y, Ni Z, Sun Q. Transcriptome comparison of susceptible and resistant wheat in response to powdery mildew infection. 2012. Genomics, Proteomics Bioinformatics; 10(2):94-106
45. Wang X# and Liu XS#. Systematic curation of miRBase microRNA annotation using integrated deep small RNA sequencing data for C. elegans and Drosophila. 2011. Frontiers in Genetics; 2:25.
46. Wang X#, Laurie J, Liu T, Wentz J, Liu XS#. Computational dissection of Arabidopsis smRNAome leads to discovery of RNA interference machinery associated with transcription start sites. 2011. Genomics; 97(4):235-43.
47. Zhang H, He H, Wang X, Li L and Deng X. Genome-wide identification of Hy5 binding sites in Arabidopsis. 2011. The Plant Journal; 65(3):346-58
48. He H, Zhang H, Wang X, Wu N, Yang X, Chen R, Li Y, Deng XW and Li L. Development of a versatile, target-oriented tiling microarray assay for measuring allele-specific gene expression. 2010. Genomics; 96(5):308-15
49. He G, Zhu X, Elling AA, Chen L, Wang X, Guo L, Liang M, He H, Zhang H, Chen F, Qi Y, Chen R and Deng XW. Global Epigenetic and Transcriptional Trends among Two Rice Subspecies and Their Reciprocal Hybrids. 2010. The Plant Cell; 22:17-33.
50. Zhou J, Wang X, He K, Stocl V, Tongprasit W, Elling A, Charron J, Deng XW. Genome-wide profiling of histone H3 lysine 9 acetylation and dimethylation in Arabidopsis reveals correlation between multiple histone marks and gene expression. 2010. Plant Molecular Biology; 72:6, 585-595
51. Wang X*, Elling A*, Li X*, Li L*, Charron J, Martinessen R, Wang J, Peng Z, Qi Y, Liu XS and Deng X. Genome-wide and organ-specific landscapes of epigenetic modifications and their relationships to mRNA and smRNA transcriptomes in maize. 2009. The Plant Cell; 21(4): 1053–1069
52. Wang X*, Yu Z*, Deng XW, Li L. Transcriptionally active gene fragments derived from potentially fast-evolving donor genes in the rice genome. (2009). Bioinformatics; 15;25(10): 1215-1218.
53. Li X*, Wang X*, He K, Ma Y, Su N, He H, Stolc V, Tongprasit W, Jin W, Jiang J, Terzaghi W, Li S & Deng XW. High-resolution mapping of epigenetic modifications of the rice genome uncovers interplay between DNA methylation, histone methylation, and gene expression. (2008). The Plant Cell; 20: 259-276
54. Wang X. Statistical Analysis of Tiling-path microarrays. (2008) A Chapter for the book: Oligonucleotide Array Sequence Analysis; NOVA Science Publisher, New York, USA ISBN: 978-1-60456-542-3
55. Peng Z, Zhang H, Liu T, Dzikiewicz K, Li S, Wang X, Hu G, Zhu Z, Wei X, Zhu Q, Sun Z,Ge S, Ma L, Li L and Deng XW. Characterization of the genome expression trends in the heading-stage panicle of six rice lineages. (2008). Genomics; 93: 169-178;
56. Yin BL, Guo L, Zhang DF, Terzaghi W, Wang X, Liu TT, He H, Cheng ZK and Deng XW. Integration of Cytological Features with Molecular and Epigenetic Properties of Rice Chromosome 4. (2008). Molecular Plant; 1: 816-829;
