Combined physiological, transcriptome, and genetic analysis reveals a molecular network of nitrogen remobilization in maize

Mining genic resources regulating nitrogen-use efficiency based on integrative biological analyses and their breeding applications in maize and other crops

Nitrogen (N) is an essential factor for limiting crop yields, and cultivation of crops with low nitrogen-use efficiency (NUE) exhibits increasing environmental and ecological risks. Hence, it is crucial to mine valuable NUE improvement genes, which is very important to develop and breed new crop varieties with high NUE in sustainable agriculture system. Quantitative trait locus (QTL) and genome-wide association study (GWAS) analysis are the most common methods for dissecting genetic variations underlying complex traits. In addition, with the advancement of biotechnology, multi-omics technologies can be used to accelerate the process of exploring genetic variations. In this study, we integrate the substantial data of QTLs, quantitative trait nucleotides (QTNs) from GWAS, and multi-omics data including transcriptome, proteome, and metabolome and further analyze their interactions to predict some NUE-related candidate genes. We also provide the genic resources for NUE improvement among maize, rice, wheat, and sorghum by homologous alignment and collinearity analysis. Furthermore, we propose to utilize the knowledge gained from classical cases to provide the frameworks for improving NUE and breeding N-efficient varieties through integrated genomics, systems biology, and modern breeding technologies.

Comparative physiological and transcriptome analysis of leaf nitrogen fluxes in stay-green maize during the vegetative stage

In maize, nitrogen (N) stored in leaves is an important internal source for supporting subsequent growth and development. However, the regulation of N fluxes and photosynthesis and the molecular and genotypic regulations that modify them are less clear in source leaves during the vegetative stage. This knowledge is crucial for improving N use efficiency (NUE). By using 15N labeling and transcriptome methods, an analysis of the physiological and molecular basis of leaf N import and export processes and photosynthetic N use efficiency (PNUE) was conducted in two maize hybrids (XY335 and XY696) with different stay-green characteristics during the vegetative stage. Leaf N import and export in XY696 were 45% and 33% greater than those in XY335. However, the PNUE in XY335 was 17% greater than that in XY696 due to the higher net photosynthetic rate (A) and lower SLN. Correspondingly, the chlorophyll content and photosynthesis-related enzyme (PEPc, PEPck, PPDK) activities increased by 18∼30% in XY335. Transcriptome analysis indicated that the expression levels of several N and carbon metabolism-related genes encoding Rubisco, PEPc, Nir, GS and AS were significantly increased or decreased in XY696 in parallel with enzyme activities. Moreover, there was a large difference in the expression abundance of genes encoding nitrate/nitrite transporters and transmembrane proteins. Our results suggest that two hybrids modulate leaf N fluxes and photosynthesis differently by altering gene expression and enzyme activities. Our study contributes to understanding leaf N fluxes and PNUE regulation and serves as a crucial reference for NUE improvement in maize breeding research.

Comparative transcriptome profiling of near isogenic lines PBW343 and FLW29 to unravel defense related genes and pathways contributing to stripe rust resistance in wheat

Stripe rust (Sr), caused by Puccinia striiformis f. sp. tritici (Pst), is the most devastating disease that poses serious threat to the wheat-growing nations across the globe. Developing resistant cultivars is the most challenging aspect in wheat breeding. The function of resistance genes (R genes) and the mechanisms by which they influence plant-host interactions are poorly understood. In the present investigation, comparative transcriptome analysis was carried out by involving two near-isogenic lines (NILs) PBW343 and FLW29. The seedlings of both the genotypes were inoculated with Pst pathotype 46S119. In total, 1106 differentially expressed genes (DEGs) were identified at early stage of infection (12 hpi), whereas expressions of 877 and 1737 DEGs were observed at later stages (48 and 72 hpi) in FLW29. The identified DEGs were comprised of defense-related genes including putative R genes, 7 WRKY transcriptional factors, calcium, and hormonal signaling associated genes. Moreover, pathways involved in signaling of receptor kinases, G protein, and light showed higher expression in resistant cultivar and were common across different time points. Quantitative real-time PCR was used to further confirm the transcriptional expression of eight critical genes involved in plant defense mechanism against stripe rust. The information about genes are likely to improve our knowledge of the genetic mechanism that controls the stripe rust resistance in wheat, and data on resistance response-linked genes and pathways will be a significant resource for future research.

Mining genes regulating root system architecture in maize based on data integration analysis

KEY MESSAGE

A new strategy that integrated multiple public data resources was established to construct root gene co-expression network and mine genes regulating root system architecture in maize. A root gene co-expression network, containing 13,874 genes, was constructed. A total of 53 root hub genes and 16 priority root candidate genes were identified. One priority root candidate was further functionally verified using overexpression transgenic maize lines. Root system architecture (RSA) is crucial for crops productivity and stress tolerance. In maize, few RSA genes are functionally cloned, and effective discovery of RSA genes remains a great of challenge. In this work, we established a strategy to mine maize RSA genes by integrating functionally characterized root genes, root transcriptome, weighted gene co-expression network analysis (WGCNA) and genome-wide association analysis (GWAS) of RSA traits based on public data resources. A total of 589 maize root genes were collected by searching well-characterized root genes in maize or homologous genes of other species. We performed WGCNA to construct a maize root gene co-expression network containing 13874 genes based on public available root transcriptome data, and further discovered the 53 hub genes related to root traits. In addition, by the prediction function of obtained root gene co-expression network, a total of 1082 new root candidate genes were explored. By further overlapping the obtained new root candidate gene with the root-related GWAS of RSA candidate genes, 16 priority root candidate genes were identified. Finally, a priority root candidate gene, Zm00001d023379 (encodes pyruvate kinase 2), was validated to modulate root open angle and shoot-borne roots number using its overexpression transgenic lines. Our results develop an integration analysis method for effectively exploring regulatory genes of RSA in maize and open a new avenue to mine the candidate genes underlying complex traits.

Integrated physiological, proteome and gene expression analyses provide new insights into nitrogen remobilization in citrus trees

Nitrogen (N) remobilization is an important physiological process that supports the growth and development of trees. However, in evergreen broad-leaved tree species, such as citrus, the mechanisms of N remobilization are not completely understood. Therefore, we quantified the potential of N remobilization from senescing leaves of spring shoots to mature leaves of autumn shoots of citrus trees under different soil N availabilities and further explored the underlying N metabolism characteristics by physiological, proteome and gene expression analyses. Citrus exposed to low N had an approximately 38% N remobilization efficiency (NRE), whereas citrus exposed to high N had an NRE efficiency of only 4.8%. Integrated physiological, proteomic and gene expression analyses showed that photosynthesis, N and carbohydrate metabolism interact with N remobilization. The improvement of N metabolism and photosynthesis, the accumulation of proline and arginine, and delayed degradation of storage protein in senescing leaves are the result of sufficient N supply and low N remobilization. Proteome further showed that energy generation proteins and glutamate synthase were hub proteins affecting N remobilization. In addition, N requirement of mature leaves is likely met by soil supply at high N nutrition, thereby resulting in low N remobilization. These results provide insight into N remobilization mechanisms of citrus that are of significance for N fertilizer management in orchards.

Nitrogen use efficiency (NUE): elucidated mechanisms, mapped genes and gene networks in maize (Zea mays L.)

Nitrogen, the vital primary plant growth nutrient at deficit soil conditions, drastically affects the growth and yield of a crop. Over the years, excess use of inorganic nitrogenous fertilizers resulted in pollution, eutrophication and thereby demanding the reduction in the use of chemical fertilizers. Being a C₄ plant with fibrous root system and high NUE, maize can be deployed to be the best candidate for better N uptake and utilization in nitrogen deficient soils. The maize germplasm sources has enormous genetic variation for better nitrogen uptake contributing traits. Adoption of single cross maize hybrids as well as inherent property of high NUE has helped maize cultivars to achieve the highest growth rate among the cereals during last decade. Further, considering the high cost of nitrogenous fertilizers, adverse effects on soil health and environmental impact, maize improvement demands better utilization of existing genetic variation for NUE via introgression of novel allelic combinations in existing cultivars. Marker assisted breeding efforts need to be supplemented with introgression of genes/QTLs related to NUE in ruling varieties and thereby enhancing the overall productivity of maize in a sustainable manner. To achieve this, we need mapped genes and network of interacting genes and proteins to be elucidated. Identified genes may be used in screening ideal maize genotypes in terms of better physiological functionality exhibiting high NUE. Future genome editing may help in developing lines with increased productivity under low N conditions in an environment of optimum agronomic practices.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-021-01113-z.