A xylan glucuronosyltransferase gene exhibits pleiotropic effects on cellular composition and leaf development in rice

Determination of leaf nitrogen content in apple and jujube by near-infrared spectroscopy

The nitrogen content of apple leaves and jujube leaves is an important index to judge the growth and development of apple trees and jujube trees to a certain extent. The prediction performance of the two samples was compared between different models for leaf nitrogen content, respectively. The near-infrared absorption spectra of 287 apple leaf samples and 192 jujube leaf samples were collected. After eliminating the outliers by Mahalanobis distance method, the remaining spectral data were processed by six different preprocessing methods. BP neural network (BP), random forest regression (RF), least partial squares (PLS), K-Nearest Neighbor (KNN), and support vector regression (SVR) were compared to establish prediction models of nitrogen content in apple leaves and jujube leaves. The results showed that the determination coefficient (R2), root mean square error (RMSE) and residual prediction deviation (RPD) of the models established by different combined pretreatment methods were compared among the five methods. Compared with the performance of the other four models, the modeling method of SG + SD + CARS + RF was suitable for the prediction of nitrogen content in apple leaves, and its modeling set R2 was 0.85408, RMSE was 0.082188, and RPD was 2.5864. The validation set R2 is 0.75527, RMSE is 0.099028, RPD is 2.1956. The modeling method of FD + CARS + PLS was suitable for the prediction of nitrogen content in jujube leaves. The modeling set R2 was 0.7954, RMSE was 0.14558, and RPD was 2.4264; the validation set R2 is 0.81348, RMSE is 0.089217, and RPD is 2.4552.In the prediction modeling of apple leaf nitrogen content in the characteristic band, the model quality of RF was better than the other four prediction models. The model quality of PLS in predictive modeling of nitrogen content of jujube leaves in characteristic bands is superior to the other four predictive models, These results provide a reference for the use of near-infrared spectroscopy to determine whether apple trees and jujube trees are deficient in nutrients.

Xylan-directed cell wall assembly in grasses

Xylan is the most abundant hemicellulosic polysaccharide in the cell walls of grasses and is pivotal for the assembly of distinct cell wall structures that govern various cellular functions. Xylan also plays a crucial role in regulating biomass recalcitrance, ultimately affecting the utilization potential of lignocellulosic materials. Over the past decades, our understanding of the xylan biosynthetic machinery and cell wall organization has substantially improved due to the innovative application of multiple state-of-the-art techniques. Notably, novel xylan-based nanostructures have been revealed in the cell walls of xylem vessels, promoting a more extensive exploration of the role of xylan in the formation of cell wall structures. This Update summarizes recent achievements in understanding xylan biosynthesis, modification, modeling, and compartmentalization in grasses, providing a brief overview of cell wall assembly regarding xylan. We also discuss the potential for tailoring xylan to facilitate the breeding of elite energy and feed crops.

Characteristics and candidate genes associated with excellent stalk strength in maize (Zea mays L.)

Lodging is a major problem in maize production, which seriously affects yield and hinders mechanized harvesting. Improving stalk strength is an effective way to improve lodging. The maize inbred line Jing2416 (J2416) was an elite germplasm in maize breeding which had strong stalk mechanical strength. To explore the characteristics its stalk strength, we conducted physiological, metabolic and transcriptomic analyses of J2416 and its parents Jing24 (J24) and 5237. At the kernel dent stage, the stalk rind penetrometer strength of J2416 was significantly higher than those of its two parents in multiple environments. The rind thickness, sclerenchyma tissue thickness, and cellulose, hemicellulose, and lignin contents of J2416 were significantly higher than those of its parents. Based on the significant differences between J2416 and 5237, we detected metabolites and gene transcripts showing differences in abundance between these two materials. A total of 212 (68.60%) metabolites and 2287 (43.34%) genes were up-regulated in J2416 compared with 5237. The phenylpropanoid and glycan synthesis/metabolism pathways were enriched in metabolites and genes that were up-regulated in J2416. Twenty-eight of the up-regulated genes in J2416 were involved in lignin, cellulose, and hemicellulose synthesis pathways. These analyses have revealed important physiological characteristics and candidate genes that will be useful for research and breeding of inbred lines with excellent stalk strength.

Introgression Lines: Valuable Resources for Functional Genomics Research and Breeding in Rice (Oryza sativa L.)

The narrow base of genetic diversity of modern rice varieties is mainly attributed to the overuse of the common backbone parents that leads to the lack of varied favorable alleles in the process of breeding new varieties. Introgression lines (ILs) developed by a backcross strategy combined with marker-assisted selection (MAS) are powerful prebreeding tools for broadening the genetic base of existing cultivars. They have high power for mapping quantitative trait loci (QTLs) either with major or minor effects, and are used for precisely evaluating the genetic effects of QTLs and detecting the gene-by-gene or gene-by-environment interactions due to their low genetic background noise. ILs developed from multiple donors in a fixed background can be used as an IL platform to identify the best alleles or allele combinations for breeding by design. In the present paper, we reviewed the recent achievements from ILs in rice functional genomics research and breeding, including the genetic dissection of complex traits, identification of elite alleles and background-independent and epistatic QTLs, analysis of genetic interaction, and genetic improvement of single and multiple target traits. We also discussed how to develop ILs for further identification of new elite alleles, and how to utilize IL platforms for rice genetic improvement.

Candidate Genes and Pathways in Rice Co-Responding to Drought and Salt Identified by gcHap Network

Drought and salinity stresses are significant abiotic factors that limit rice yield. Exploring the co-response mechanism to drought and salt stress will be conducive to future rice breeding. A total of 1748 drought and salt co-responsive genes were screened, most of which are enriched in plant hormone signal transduction, protein processing in the endoplasmic reticulum, and the MAPK signaling pathways. We performed gene-coding sequence haplotype (gcHap) network analysis on nine important genes out of the total amount, which showed significant differences between the Xian/indica and Geng/japonica population. These genes were combined with related pathways, resulting in an interesting mechanistic draft called the ‘gcHap-network pathway’. Meanwhile, we collected a lot of drought and salt breeding varieties, especially the introgression lines (ILs) with HHZ as the parent, which contained the above-mentioned nine genes. This might imply that these ILs have the potential to improve the tolerance to drought and salt. In this paper, we focus on the relationship of drought and salt co-response gene gcHaps and their related pathways using a novel angle. The haplotype network will be helpful to explore the desired haplotypes that can be implemented in haplotype-based breeding programs.

Genetic regulation of the traits contributing to wheat nitrogen use efficiency

High nitrogen application aimed at increasing crop yield is offset by higher production costs and negative environmental consequences. For wheat, only one third of the applied nitrogen is utilized, which indicates there is scope for increasing Nitrogen Use Efficiency (NUE). However, achieving greater NUE is challenged by the complexity of the trait, which comprises processes associated with nitrogen uptake, transport, reduction, assimilation, translocation and remobilization. Thus, knowledge of the genetic regulation of these processes is critical in increasing NUE. Although primary nitrogen uptake and metabolism-related genes have been well studied, the relative influence of each towards NUE is not fully understood. Recent attention has focused on engineering transcription factors and identification of miRNAs acting on expression of specific genes related to NUE. Knowledge obtained from model species needs to be translated into wheat using recently-released whole genome sequences, and by exploring genetic variations of NUE-related traits in wild relatives and ancient germplasm. Recent findings indicate the genetic basis of NUE is complex. Pyramiding various genes will be the most effective approach to achieve a satisfactory level of NUE in the field.

Deciphering the Genetic Basis of Lodging Resistance in Wild Rice Oryza longistaminata

The abuse of fertilizer results in tall rice plants that are susceptible to lodging and reduced plant yield. Hence, it is important to identify and utilize the quantitative trait loci (QTLs)/genes for lodging resistance breeding. Oryza longistaminata exhibits a strong stem and high biomass productivity, which could be a candidate gene pool for cultivars lodging resistance improvement. Here, a set of 152 BC2F20 lines derived from a cross between a cultivated line 93-11 and O. longistaminata was evaluated for lodging resistance. QTL mapping analysis combined with single-nucleotide polymorphism (SNP) marker derived from high-throughput sequencing identified 12 QTLs for stem diameter (SD), 11 QTLs for stem length (SL), and 3 QTLs for breaking strength (BS). Of which, 14 QTLs were first identified from O. longistaminata. A major QTL, qLR1, which was delimited to a region ∼80 kb on chromosome 1, increased stem diameter, stem length, and breaking strength. Another major QTL, qLR8, that was delimited in an interval ∼120 kb on chromosome 8, significantly enhanced the breaking strength. These results provide evidence that O. longistaminata can be exploited to develop lodging-resistant rice lines.