Junming Sun

Junming Sun

Head of Soybean Genetics and Breeding

Deputy Director, Center for Crop Genetics and Breeding

Institute of Crop Sciences

No.12 Zhongguancun South Street

Beijing, 100081, China

Tel:86-10-82105805

Fax:86-10-821082105805

Email:sunjunming@caas.cn

Educations

l  2005, PhD., Biochemistry and Molecular Biology, College of Biology, China Agricultural University, Beijing, China

l  1997, M.S., Crop Genetics and Breeding, Graduate School of Chinese Academy of Agricultural Sciences, Beijing, China

l  1994, B.S., Fruit Tree, Department of Horticulture, Qing Dao Agricultural University, Shandong, China

Working Experience

l  2011-now, Professor, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences

l  2002-2010, Associate Professor, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences

l  1999-2001, Assistant Professor, Institute of Crop Breeding and Cultivation, Chinese Academy of Agricultural Sciences

l  1997-1998, Research Assistant, Institute of Crop Breeding and Cultivation, Chinese Academy of Agricultural Sciences

Research Interests

l  Soybean Molecular Breeding for High-Yield and High-Quality Traits

Academic Qualifications

l  2022, Selected for the National High-Level Talent Program

l  2018, Member of the Council of China Rural Technical Association and Chairman of the Soybean Professional Committee

l  2012, Won the first prize of National Science and Technology Progress

l  2007, Selected as a Class A talent in Beijing's New Star Program

Selected Publications (*corresponding authors)

1.       Liu Y, Zhang S, Li J, Muhammad A, Feng Y, Qi J, Sha D, Hao Y, Li B^*, Sun J^*. An R2R3-type MYB transcription factor, GmMYB77, negatively regulates isoflavone accumulation in soybean [Glycine max (L.) Merr.]. Plant Biotechnology Journal, 2025, 23:824-838. https://doi.org/10.1111/pbi.14541.

2.       Iqbal A, Zhang S, Khattak A N, Tazeb A, Hou Y, Ahsan M, Sie E K, Li J, Li B^*, Sun J*. Insights into non-isoflavone flavonoid distribution and variation across soybean germplasm using HPLC-MS/MS. LWT, 2025, 231:118317. https://doi.org/10.1016/j.lwt.2025.118317.

3.       Khattak A N, Zhang S, Agyenim-Boateng KG , Qi J, Ahsan M, Iqbal A, Sie E K, Tazeb A, Li B, Li J, Sun J^*. Geographical and genetic insights into riboflavin and its derivatives compositions in 1186 soybean accessions. Journal of Composition and Analysis, 2025, 148:108278. https://doi.org/10.1016/j.jfca.2025.108278.

4.       Gebregziabher B S, Zhang S, Li J, Li B^*, Sun J^*. Identification of genomic region and candidate genes underlying carotenoid accumulation in soybeans using next generation sequencing based bulk segregant analysis. Journal of Integrative Agriculture, 2025, 24(6): 2063-2079. https://doi.org/10.1016/j.jia.2024.02.005.

5.       Abdelghany A M, Zhang S, Li J, Li B, Sun J^*. Seed phenotype and maturity groups as determinants of protein, oil, and fatty acid composition patterns in diverse soybean germplasm. BMC Plant Biology, 2025, 25:1189. https://doi.org/10.1186/s12870-025-07182-6.

6.       Zhang S, Feng H, Agyenim-Boateng KG, Zhang S, Gu Y, Qi J, Feng Y, Li Y, Ma C, Liu Y, Azam M, Li J, Sun J^*, Qiu L^*, Li B*. High resolution QTL mapping and candidate gene mining for seed oil content and fatty acid composition in soybean. BMC Plant Biology, 2025, 25:867. https://doi.org/10.1186/s12870-025-06911-1.

7.       Azam M, Usman M, Manzoor MA, Yao L, Ma X, Zhang Y, Shah IH, Rehman A, Malik MS, Sun J^*, Wang B^*. Comprehensive characterization and expression profiling of BBX gene family in soybean in response to UV-B stress. Plant Stress, 2024, 100560, https://doi.org/10.1016/j.stress.2024.100560.

8.       Li J, Li Y, Agyenim-Boateng K,Shaibu A S, Liu Y, Feng Y, Qi J, Li B, Zhang S, Sun J^*. Natural variation of domestication-related genes contributed to latitudinal expansion and adaptation in soybean. BMC Plant Biology, 2024, 24, 651. https://doi.org/10.1186/s12870-024-05382-0.

9.       Feng Y, Zhang S, Li J, Pei R, Tian L, Qi J, Azam M, Agyenim-Boateng K G, Abdulwahab S S, Liu Y, Zhu Z, Li B^*, Sun J^*. Dual-function C2H2-type Zinc-finger transcription factor GmZFP7 contributes to isoflavone accumulation in soybean. New Phytologist, 2023, 237(5):1794-1809. doi: 10.1111/nph.18610.

10.    Agyenim-Boateng G K, Zhang S, Gu R, Zhang SB, Qi J, Azam M, Ma C, Li Y, Feng Y, Liu Y, Li J, Li B^*, Qiu L^*, Sun J^*. Identification of quatitative trait loci and candidate genes for seed folate content in soybean. Theoretical and Applied Genetics, 2023, 136:149. https://doi.org/10.1007/s00122-023-04396-w.

11.    Zhang S, Abdelghany A M, Azam M, Qi J, Li J, Feng Y, Liu Y, Feng H, Ma C, Gebregziabher BS, Ghosh S, Agyenim-Boateng KG, Shaibu A S, Htway T P H, Wu, T, Li B^*, Qiu L^*, Sun J^*. Mining candidate genes underlying seed oil content using BSA-seq in soybean. Industrial Crops and Products, 2023, 194: 116308. https://doi.org/10.1016/j.indcrop.2023.116308.

12.    Azam M, Zhang S, Huai Y, Abdelghany A, Shaibu A, Qi J, Feng Y, Liu Y, Li J, Qiu L, Li B^*, Sun J^*. Identification of genes for seed isoflavones based on bulk segregant analysis sequencing in soybean natural population. Theoretical and Applied Genetics, 2023, 136(1):1-12. https://doi.org/10.1007/s00122-023-04258-5.

13.    Gebregziabher B S, Zhang S, Azam M, Qi J, Agyenim-Boateng K G, Feng Y, Liu Y, Li J, Li B^*, Sun J^*. Natural variations and geographical distribution of seed carotenoids and chlorophylls in 1167 Chinese soybean accessions. Journal of Integrative Agriculture, 2023, 22(9):2632-2647. https://doi.org/10.1016/j.jia.2022.10.011.

14.    Agyenim-Boateng G K, Zhang S, Zhang SB, Khattak A N, Shaibu A S, Abdelghany AM, Qi J, Azam M, Ma C, Feng Y, Liu Y, Li J, Li B^*, Sun J^*. The nutritional composition of the vegetable soybean (Maodou) and its potential in combating malnutrition. Frontiers in Nutrition, 2023, 9: 1034115. doi: 10.3389/fnut.2022.1034115.

15.    Qi J, Zhang S, Azam M, Shaibu A S, Abdelghany A M, Feng Y, Huai Y, Feng H, Liu Y, Ma C, Gebregziabher B S, Ghosh S, Li J, Li B^*, Sun J^*. Profiling seed soluble sugar compositions in 1164 Chinese soybean accessions from major growing ecoregions. The Crop Journal, 2022, 2022, 10: 1825-1831. https://doi.org/10.1016/j.cj.2022.04.015.

16.    Agyenim-Boateng G K, Zhang S, Islam S, Gu Y, Li B, Azam M, Abdelghany AM, Qi J, Ghosh S, Shaibu AS, Gebregziabher B, Feng Y, Li J, Li Y, Zhang C, Qiu L, Liu Z^*, Liang Q^*, Sun J^*. Profiling of naturally occurring folates in a diverse soybean germplasm by HPLC-MS/MS. Food Chemistry, 2022, 384: 132520. https://doi.org/10.1016/j.foodchem.2022.132520.

17.    Ghosh S, Zhang S, Azam M, Qi J, Abdelghany A M, Shaibu A S, Gebregziabher B S, Feng Y, Huai Y, Htway H, Agyenim-Boateng K, Liu Y, Feng H, Li J, Li B^*, Sun J^* Seed tocopherol assessment and geographical distribution of 1151 Chinese soybean accessions from diverse ecoregions. Journal of Food Composition and Analysis, 2021, 100:103932. https://doi.org/10.1016/j.jfca.2021.103932.

18.    Azam M, Zhang S, Qi J, Abdelghany A M, Shaibu A S, Ghosh S, Feng Y, Huai Y, Gebregziabher B S, Li J, Li B^*, Sun J^* Profiling and associations of seed nutritional characteristics in Chinese and USA soybean cultivars. Journal of Food Composition and Analysis, 2021, 98:103803. https://doi.org/10.1016/j.jfca.2021.103803.

19.    Shaibu A S, Li B^*, Zhang S, Sun J^*. Soybean cyst nematode resistance: Gene identification and breeding strategies. The Crop Journal, 2020, 8(6):892-904. https://doi.org/10.1016/ j.cj.2020.03.001.

20.    Azam M, Zhang S, Abdelghany M A, Shaibu S A, Feng, Y, Li Y, Tian Y, Hong H, Li B^*, Sun J^*. Seed isoflavone profiling of 1168 soybean accessions from major growing ecoregions in China. Food Research International, 2020, 2020, 130, 108957. doi:10.1016/j.foodres.2019. 108957.

21.    Abdelghany M A, Zhang S, Azam M, Shaibu S A, Feng, Y, Li Y, Tian Y, Hong H, Li B^*, Sun J^*. Profiling of seed fatty acid composition in 1,025 Chinese soybean accessions from different ecoregions. The Crop Journal, 2020, 8(4): 635-644. doi:10.1016/j.cj.2019.11.002.

22.    Pei R, Zhang J, Tian L, Zhang S, Han F, Yan S, Wang L, Li B^*, Sun J^*. Identification of novel QTL associated with soybean isoflavone content. The Crop Journal, 2018, 6: 244-252. doi:10.1016/j.cj.2017.10.004

23.    Li, B., Fan, S., Yu, F, Chen Y, Zhang S, Han F, Yan S, Wang L, Sun J^*. High-resolution mapping of QTL for fatty acid composition in soybean using specific-locus amplified fragment sequencing. Theoretical and Applied Genetics, 2017, 130(7), 1467-1479. doi:10.1007/s00122-017-2902-8.

24.    Ma L, Li B, Han F, Yan S, Wang L, Sun J^*. Evaluation of the chemical quality traits of soybean seeds, as related to sensory attributes of soymilk. Food Chemistry, 2015, 73: 694-701. https://doi.org/10.1016/j.foodchem.2014.10.096.

25.    Li B, Tian L, Zhang J, Huang L, Han F, Yan S, Wang L, Zheng H, Sun J^*. Construction of a high-density genetic map based on large-scale markers developed by specific length amplified fragment sequencing (SLAF-seq) and its application to QTL analysis for isoflavone content in Glycine max. BMC Genomics, 2014, 15:1086. doi:10.1186/1471-2164-15-1086.

26.    Sun J*, Irzykowski W, Jedryczka M and Han F. Analysis of the genetic structure of Sclerotinia sclerotiorum populations from different regions and host plants by random amplified polymorphic DNA markers, Journal of Integrative Plant Biology, 2005, 47: 385-395. doi:10.1111/j.1744-7909.2005.00077.x