Jie Wang

Dr. Jie Wang

orcid

Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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9 May 2024 in Nature Plants
Verified
Journal Article
Closed access
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XZXiangbin Zhong
Xiangbin Zhong
JWJie Wang
Jie Wang
XSXiaolei Shi
Xiaolei Shi
MBMengyan Bai
Mengyan Bai
CYCuicui Yuan
Cuicui Yuan
YGYuefeng Guan
Yuefeng Guan

10 September 2021 in Biotechnology for Biofuels
Verified
Journal Article
Open access
PDF file
KLKeqi Li
Keqi Li
JWJie Wang
Jie Wang
LKLieqiong Kuang
Lieqiong Kuang
ZTZe Tian
Ze Tian
XWXinfa Wang
Xinfa Wang
Hanzhong WangHanzhong Wang
Hanzhong Wang
Background: In terms of global demand, rapeseed is the third-largest oilseed crop after soybeans and palm, which produces vegetable oil for human consumption and biofuel for industrial production. Roots are vital organs for plant to absorb water and attain mineral nutrients, thus they are of great importance to plant productivity. However, the genetic mechanisms regulating root development in rapeseed remain unclear. In the present study, seven root-related traits and shoot biomass traits in 280 Brassica napus accessions at five continuous vegetative stages were measured to establish the genetic basis of root growth in rapeseed. Results: The persistent and stage-specific genetic mechanisms were revealed by root dynamic analysis. Sixteen persistent and 32 stage-specific quantitative trait loci (QTL) clusters were identified through genome-wide association study (GWAS). Root samples with contrasting (slow and fast) growth rates throughout the investigated stages and those with obvious stage-specific changes in growth rates were subjected to transcriptome analysis. A total of 367 differentially expressed genes (DEGs) with persistent differential expressions throughout root development were identified, and these DEGs were significantly enriched in GO terms, such as energy metabolism and response to biotic or abiotic stress. Totally, 485 stage-specific DEGs with different expressions at specific stage were identified, and these DEGs were enriched in GO terms, such as nitrogen metabolism. Four candidate genes were identified as key persistent genetic factors and eight as stage-specific ones by integrating GWAS, weighted gene co-expression network analysis (WGCNA), and differential expression analysis. These candidate genes were speculated to regulate root system development, and they were less than 100 kb away from peak SNPs of QTL clusters. The homologs of three genes (BnaA03g52990D, BnaA06g37280D, and BnaA09g07580D) out of 12 candidate genes have been reported to regulate root development in previous studies. Conclusions: Sixteen QTL clusters and four candidate genes controlling persistently root development, and 32 QTL clusters and eight candidate genes stage-specifically regulating root growth in rapeseed were detected in this study. Our results provide new insights into the temporal genetic mechanisms of root growth by identifying key candidate QTL/genes in rapeseed.

25 May 2026 in Agronomy
Verified
Journal Article
Open access
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田T田莉 Tu
田莉 Tu
JCJinyu Chen
Jinyu Chen
TXTao Xu
Tao Xu
LHLaimei Huang
Laimei Huang
JCJiaomei Chen
Jiaomei Chen
ZHEN GAOZHEN GAO
ZHEN GAO
Soybean is the dominant source of plant-derived protein, yet improving seed protein content without reducing yield remains a breeding challenge. While the phytohormone auxin is well-established as a crucial regulator of seed development, its precise role in metabolic homeostasis governing protein accumulation remains largely unexplored. Here, we show that disrupting auxin conjugation via CRISPR-Cas9-generated gh3Q (GH3 quadruple) mutants elevates free auxin levels and is associated with increased seed size, hundred-seed weight, and protein content. Time-course transcriptome profiling of seed coats and embryos identified the R6-stage seed coat as a pivotal tissue for protein accumulation, where seven key seed storage protein genes (2S albumin and 11S glycinin family members) were significantly up-regulated. Weighted gene co-expression network analysis (WGCNA) further uncovered auxin polar transport modules and novel hub genes that are co-expressed with potentially link auxin signaling to protein storage pathways. These findings suggest that auxin homeostasis may link phytohormone signaling and metabolism allocation in soybean seed development. Our study provides genetic targets and a regulatory network for developing high-protein soybean varieties.