Xuelei Lin, Yongxin Xu, Dongzhi Wang, Yiman Yang, Xiaoyu Zhang, Xiaomin Bie, Lixuan Gui, Zhongxu Chen, Yiliang Ding, Long Mao, Xueyong Zhang, Fei Lu, Xiansheng Zhang, Cristobal Uauy, Xiangdong Fu, Jun Xiao <<<

The spike architecture of wheat plays a crucial role in determining grain number, making it a key trait for optimization in wheat breeding programs. In this study, we used a multi-omic approach to analyze the transcriptome and epigenome profiles of the young spike at eight developmental stages, revealing coordinated changes in chromatin accessibility and H3K27me3 abundance during the flowering transition. We constructed a core transcriptional regulatory network (TRN) that drives wheat spike formation and experimentally validated a multi-layer regulatory module involving TaSPL15, TaAGLG1, and TaFUL2. By integrating the TRN with genome-wide association studies, we identified 227 transcription factors, including 42 with known functions and 185 with unknown functions. Further investigation of 61 novel transcription factors using multiple homozygous mutant lines revealed 36 transcription factors that regulate spike architecture or flowering time, such as TaMYC2-A1, TaMYB30-A1, and TaWRKY37-A1. Of particular interest, TaMYB30-A1, downstream of and repressed by WFZP, was found to regulate fertile spikelet number. Notably, the excellent haplotype of TaMYB30-A1, which contains a C allele at the WFZP binding site, was enriched during wheat breeding improvement in China, leading to improved agronomic traits. Finally, we constructed a free and open access Wheat Spike Multi-Omic Database (http://39.98.48.156:8800/#/). Our study identifies novel and high-confidence regulators and offers an effective strategy for dissecting the genetic basis of wheat spike development, with practical value for wheat breeding. <<<

Jizeng Jia, Guangyao Zhao, Danping Li, Kai Wang, Chuizheng Kong, Pingchuan Deng, Xueqing Yan, Xueyong Zhang, Zefu Lu, Shujuan Xu, Yuannian Jiao, Kang Chong, Xu Liu, Dangqun Cui, Guangwei Li, Yijing Zhang, Chunguang Du, Liang Wu, Tianbao Li, Dong Yan, Kehui Zhan, Feng Chen, Zhiyong Wang, Lichao Zhang, Xiuying Kong, Zhengang Ru, Daowen Wang, Lifeng Gao <<<

Despite recent progress in crop genomics studies, the genomic changes brought about by modern breeding selection are still poorly understood, thus hampering genomics-assisted breeding, especially in polyploid crops with compound genomes such as common wheat (Triticum aestivum). In this work, we constructed genome resources for the modern elite common wheat variety Aikang 58 (AK58). Comparative genomics between AK58 and the landrace cultivar Chinese Spring (CS) shed light on genomic changes that occurred through recent varietal improvement. We also explored subgenome diploidization and divergence in common wheat and developed a homoeologous locus-based genome-wide association study (HGWAS) approach, which was more effective than single homoeolog-based GWAS in unraveling agronomic trait-associated loci. A total of 123 major HGWAS loci were detected using a genetic population derived from AK58 and CS. Elite homoeologous haplotypes (HHs), formed by combinations of subgenomic homoeologs of the associated loci, were found in both parents and progeny, and many could substantially improve wheat yield and related traits. We built a website where users can download genome assembly sequence and annotation data for AK58, perform blast analysis, and run JBrowse. Our work enriches genome resources for wheat, provides new insights into genomic changes during modern wheat improvement, and suggests that efficient mining of elite HHs can make a substantial contribution to genomics-assisted breeding in common wheat and other polyploid crops. <<<

Yan Li, Yang Chen, Lu Zhou, Shengjie You, Heng Deng, Ya Chen, Saleh Alseekh, Yong Yuan, Rao Fu, Zixin Zhang, Dan Su, Alisdair R Fernie, Mondher Bouzayen, Tao Ma, Mingchun Liu, Yang Zhang <<<

Tomato (Solanum lycopersicum) is a major horticultural crop worldwide and has emerged as a preeminent model for metabolic research. Although many research efforts have focused on the analysis of metabolite differences between varieties and species, the dynamics of metabolic changes during the tomato growth cycle and the regulatory networks that underlie these changes are poorly understood. In this study, we integrated high-resolution spatio-temporal metabolome and transcriptome data to systematically explore the metabolic landscape across 20 major tomato tissues and growth stages. In the resulting MicroTom Metabolic Network, the 540 detected metabolites and their co-expressed genes could be divided into 10 distinct clusters based on their biological functions. Using this dataset, we constructed a global map of the major metabolic changes that occur throughout the tomato growth cycle and dissected the underlying regulatory network. In addition to verifying previously well-established regulatory networks for important metabolites, we identified novel transcription factors that regulate the biosynthesis of important secondary metabolites such as steroidal glycoalkaloids and flavonoids. Our findings provide insights into spatio-temporal changes in tomato metabolism and generate a valuable resource for the study of metabolic regulatory processes in model plants. <<<