A dynamic regulome of shoot-apical-meristem-related homeobox transcription factors modulates plant architecture in maize.

BACKGROUND: The shoot apical meristem (SAM), from which all above-ground tissues of plants are derived, is critical to plant morphology and development. In maize (Zea mays), loss-of-function mutant studies have identified several SAM-related genes, most encoding homeobox transcription factors (TFs), located upstream of hierarchical networks of hundreds of genes. RESULTS: Here, we collect 46 transcriptome and 16 translatome datasets across 62 different tissues or stages from the maize inbred line B73. We construct a dynamic regulome for 27 members of three SAM-related homeobox subfamilies (KNOX, WOX, and ZF-HD) through machine-learning models for the detection of TF targets across different tissues and stages by combining tsCUT&Tag, ATAC-seq, and expression profiling. This dynamic regulome demonstrates the distinct binding specificity and co-factors for these homeobox subfamilies, indicative of functional divergence between and within them. Furthermore, we assemble a SAM dynamic regulome, illustrating potential functional mechanisms associated with plant architecture. Lastly, we generate a wox13a mutant that provides evidence that WOX13A directly regulates Gn1 expression to modulate plant height, validating the regulome of SAM-related homeobox genes. CONCLUSIONS: The SAM-related homeobox transcription-factor regulome presents an unprecedented opportunity to dissect the molecular mechanisms governing SAM maintenance and development, thereby advancing our understanding of maize growth and shoot architecture.

Next-generation bulked segregant analysis for Breeding 4.0.

Functional cloning and manipulation of genes controlling various agronomic traits are important for boosting crop production. Although bulked segregant analysis (BSA) is an efficient method for functional cloning, its low throughput cannot satisfy the current need for crop breeding and food security. Here, we review the rationale and development of conventional BSA and discuss its strengths and drawbacks. We then propose next-generation BSA (NG-BSA) integrating multiple cutting-edge technologies, including high-throughput phenotyping, biological big data, and the use of machine learning. NG-BSA increases the resolution of genetic mapping and throughput for cloning quantitative trait genes (QTGs) and optimizes candidate gene selection while providing a means to elucidate the interaction network of QTGs. The ability of NG-BSA to efficiently batch-clone QTGs makes it an important tool for dissecting molecular mechanisms underlying various traits, as well as for the improvement of Breeding 4.0 strategy, especially in targeted improvement and population improvement of crops.

QTG-Miner aids rapid dissection of the genetic base of tassel branch number in maize.

Genetic dissection of agronomic traits is important for crop improvement and global food security. Phenotypic variation of tassel branch number (TBN), a major breeding target, is controlled by many quantitative trait loci (QTLs). The lack of large-scale QTL cloning methodology constrains the systematic dissection of TBN, which hinders modern maize breeding. Here, we devise QTG-Miner, a multi-omics data-based technique for large-scale and rapid cloning of quantitative trait genes (QTGs) in maize. Using QTG-Miner, we clone and verify seven genes underlying seven TBN QTLs. Compared to conventional methods, QTG-Miner performs well for both major- and minor-effect TBN QTLs. Selection analysis indicates that a substantial number of genes and network modules have been subjected to selection during maize improvement. Selection signatures are significantly enriched in multiple biological pathways between female heterotic groups and male heterotic groups. In summary, QTG-Miner provides a large-scale approach for rapid cloning of QTGs in crops and dissects the genetic base of TBN for further maize breeding.

Genetic mapping and functional analysis of a classical tassel branch number mutant Tp2 in maize.

Tassel branch number is a key trait that contributes greatly to grain yield in maize (Zea mays). We obtained a classical mutant from maize genetics cooperation stock center, Teopod2 (Tp2), which exhibits severely decreased tassel branch. We conducted a comprehensive study, including phenotypic investigation, genetic mapping, transcriptome analysis, overexpression and CRISPR knock-out, and tsCUT&Tag of Tp2 gene for the molecular dissection of Tp2 mutant. Phenotypic investigation showed that it is a pleiotropic dominant mutant, which is mapped to an interval of approximately 139-kb on Chromosome 10 harboring two genes Zm00001d025786 and zma-miR156h. Transcriptome analysis showed that the relative expression level of zma-miR156h was significantly increased in mutants. Meanwhile, overexpression of zma-miR156h and knockout materials of ZmSBP13 exhibited significantly decreased tassel branch number, a similar phenotype with Tp2 mutant, suggesting that zma-miR156h is the causal gene of Tp2 and targets ZmSBP13 gene. Besides, the potential downstream genes of ZmSBP13 were uncovered and showed that it may target multiple proteins to regulate inflorescence structure. Overall, we characterized and cloned Tp2 mutant, and proposed a zma-miR156h-ZmSBP13 model functioning in regulating tassel branch development in maize, which is an essential measure to satisfy the increasing demands of cereals.

A translatome-transcriptome multi-omics gene regulatory network reveals the complicated functional landscape of maize.

BACKGROUND: Maize (Zea mays L.) is one of the most important crops worldwide. Although sophisticated maize gene regulatory networks (GRNs) have been constructed for functional genomics and phenotypic dissection, a multi-omics GRN connecting the translatome and transcriptome is lacking, hampering our understanding and exploration of the maize regulatome. RESULTS: We collect spatio-temporal translatome and transcriptome data and systematically explore the landscape of gene transcription and translation across 33 tissues or developmental stages of maize. Using this comprehensive transcriptome and translatome atlas, we construct a multi-omics GRN integrating mRNAs and translated mRNAs, demonstrating that translatome-related GRNs outperform GRNs solely using transcriptomic data and inter-omics GRNs outperform intra-omics GRNs in most cases. With the aid of the multi-omics GRN, we reconcile some known regulatory networks. We identify a novel transcription factor, ZmGRF6, which is associated with growth. Furthermore, we characterize a function related to drought response for the classic transcription factor ZmMYB31. CONCLUSIONS: Our findings provide insights into spatio-temporal changes across maize development at both the transcriptome and translatome levels. Multi-omics GRNs represent a useful resource for dissection of the regulatory mechanisms underlying phenotypic variation.

The Impact of Atorvastatin on Cardiac Performance for Dilated Cardiomyopathy: A Meta-analysis of Randomized Controlled Studies.

INTRODUCTION: The efficacy of atorvastatin for dilated cardiomyopathy remains controversial. We conducted a systematic review and meta-analysis to explore the influence of atorvastatin on cardiac performance for dilated cardiomyopathy. METHODS: We searched PubMed, Embase, Web of Science, EBSCO, and Cochrane library databases through February 2019 for randomized controlled trials (RCTs) assessing the effect of atorvastatin on cardiac performance for dilated cardiomyopathy. This meta-analysis was performed using the random-effects model. RESULTS: Five RCTs involving 401 patients were included in the meta-analysis. Overall, compared with control groups for dilated cardiomyopathy, atorvastatin treatment resulted in a significantly positive impact on left ventricular ejection fraction (standard mean difference [SMD] = 0.58; 95% confidence interval [CI] = 0.33 to 0.84; P < .00001), 6-minute walk test (SMD = 0.79; 95% CI = 0.27 to 1.31; P = .003), N-terminal pro-brain natriuretic peptide (SMD = -0.60; 95% CI = -1.18 to -0.01; P = .04), left ventricular systolic volume (SMD = 0.41; 95% CI = 0.03 to 0.79; P = .03), low-density lipoprotein (SMD = -1.37; 95% CI = -1.92 to -0.82; P = .00001), and C-reactive protein (SMD = -0.47; 95% CI = -0.72 to -0.22; P = .0002), but showed no obvious influence on left ventricular end-diastolic volume (SMD = 0.14; 95% CI = -0.37 to 0.64; P = .59). CONCLUSIONS: Atorvastatin treatment provides significant benefits for dilated cardiomyopathy.