QTL mapping for flowering time in a maize-teosinte population under well-watered and water-stressed conditions.

Maize grain yield can be greatly reduced when flowering time coincides with drought conditions, which delays silking and consequently increases the anthesis-silking interval. Although the genetic basis of delayed flowering time under water-stressed conditions has been elucidated in maize-maize populations, little is known in this regard about maize-teosinte populations. Here, 16 quantitative trait loci (QTL) for three flowering-time traits, namely days to anthesis, days to silk, and the anthesis-silking interval, were identified in a maize-teosinte introgression population under well-watered and water-stressed conditions; these QTL explained 3.98-32.61% of phenotypic variations. Six of these QTL were considered to be sensitive to drought stress, and the effect of any individual QTL was small, indicating the complex genetic nature of drought resistance in maize. To resolve which genes underlie the six QTL, 11 candidate genes were identified via colocalization analysis of known associations with flowering-time-related drought traits. Among the 11 candidate genes, five were found to be differentially expressed in response to drought stress or under selection during maize domestication, and thus represented the most likely candidates underlying the drought-sensitive QTL. The results lay a foundation for further studies of the genetic mechanisms of drought resistance and provide valuable information for improving drought resistance during maize breeding. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01413-0.

A high-resolution transcriptomic atlas depicting nitrogen fixation and nodule development in soybean.

Although root nodules are essential for biological nitrogen fixation in legumes, the cell types and molecular regulatory mechanisms contributing to nodule development and nitrogen fixation in determinate nodule legumes, such as soybean (Glycine max), remain incompletely understood. Here, we generated a single-nucleus resolution transcriptomic atlas of soybean roots and nodules at 14 days post inoculation (dpi) and annotated 17 major cell types, including six that are specific to nodules. We identified the specific cell types responsible for each step in the ureides synthesis pathway, which enables spatial compartmentalization of biochemical reactions during soybean nitrogen fixation. By utilizing RNA velocity analysis, we reconstructed the differentiation dynamics of soybean nodules, which differs from those of indeterminate nodules in Medicago truncatula. Moreover, we identified several putative regulators of soybean nodulation and two of these genes, GmbHLH93 and GmSCL1, were as-yet uncharacterized in soybean. Overexpression of each gene in soybean hairy root systems validated their respective roles in nodulation. Notably, enrichment for cytokinin-related genes in soybean nodules led to identification of the cytokinin receptor, GmCRE1, as a prominent component of the nodulation pathway. GmCRE1 knockout in soybean resulted in a striking nodule phenotype with decreased nitrogen fixation zone and depletion of leghemoglobins, accompanied by downregulation of nodule-specific gene expression, as well as almost complete abrogation of biological nitrogen fixation. In summary, this study provides a comprehensive perspective of the cellular landscape during soybean nodulation, shedding light on the underlying metabolic and developmental mechanisms of soybean nodule formation.

Genome-wide identification and comparative analysis of drought-related microRNAs in two maize inbred lines with contrasting drought tolerance by deep sequencing.

Drought has become one of the most serious abiotic stresses influencing crop production worldwide. Understanding the molecular regulatory networks underlying drought adaption and tolerance in crops is of great importance for future breeding. microRNAs (miRNAs), as important components of post-transcriptional regulation, play crucial roles in drought response and adaptation in plants. Here, we report a miRNome analysis of two maize inbred lines with contrasting levels of drought tolerance under soil drought in the field. Differential expression analysis showed 11 and 34 miRNAs were uniquely responded to drought in H082183 (drought tolerant) and Lv28 (drought sensitive), respectively, in leaves. In roots, 19 and 23 miRNAs uniquely responded to drought in H082183 and Lv28, respectively. Expression analysis of these drought-responsive miRNA-mRNA modules revealed miR164-MYB, miR164-NAC, miR159-MYB, miR156-SPL and miR160-ARF showed a negative regulatory relationship. Further analysis showed that the miR164-MYB and miR164-NAC modules in the tolerant line modulated the stress response in an ABA (abscisic acid)-dependent manner, while the miR156-SPL and miR160-ARF modules in the sensitive line participated in the inhibition of metabolism in drought-exposed leaves. Together, our results provide new insight into not only drought-tolerance-related miRNA regulation networks in maize but also key miRNAs for further characterization and improvement of maize drought tolerance.

Newly Identified Essential Amino Acids Affecting Chlorella ellipsoidea DGAT1 Function Revealed by Site-Directed Mutagenesis.

Diacylglycerol acyltransferase (DGAT) is a rate-limiting enzyme in the synthesis of triacylglycerol (TAG), the most important form of energy storage in plants. Some residues have previously been proven to be crucial for DGAT1 activity. In this study, we used site-directed mutagenesis of the CeDGAT1 gene from Chlorella ellipsoidea to alter 16 amino acids to investigate effects on DGAT1 function. Of the 16 residues (L482R, E542R, Y553A, G577R, R579D, Y582R, R596D, H603D, H609D, A624R, F629R, S632A, W650R, A651R, Q658H, and P660R), we newly identified 5 (L482, R579, H603, A651, and P660) as being essential for DGAT1 function and 7 (E542, G577, R596, H609, A624, S632, and Q658) that significantly affect DGAT1 function to different degrees, as revealed by heterologous expression of the mutants in yeast strain INVSc1. Importantly, compared with CeDGAT1, expression of the mutant CeDGAT1Y553A significantly increased the total fatty acid and TAG contents of INVSc1. Comparison among CeDGAT1Y553A, GmDGAT1Y341A, AtDGAT1Y364A, BnDGAT1Y347A, and BoDGAT1Y352A, in which tyrosine at the position corresponding to the 553rd residue in CeDGAT1 is changed into alanine, indicated that the impact of changing Y to A at position 553 is specific for CeDGAT1. Overall, the results provide novel insight into the structure and function of DGAT1, as well as a mutant gene with high potential for lipid improvement in microalgae and plants.

Genome-wide identification of gene expression in contrasting maize inbred lines under field drought conditions reveals the significance of transcription factors in drought tolerance.

Drought is a major threat to maize growth and production. Understanding the molecular regulation network of drought tolerance in maize is of great importance. In this study, two maize inbred lines with contrasting drought tolerance were tested in the field under natural soil drought and well-watered conditions. In addition, the transcriptomes of their leaves was analyzed by RNA-Seq. In total, 555 and 2,558 genes were detected to specifically respond to drought in the tolerant and the sensitive line, respectively, with a more positive regulation tendency in the tolerant genotype. Furthermore, 4,700, 4,748, 4,403 and 4,288 genes showed differential expression between the two lines under moderate drought, severe drought and their well-watered controls, respectively. Transcription factors were enriched in both genotypic differentially expressed genes and specifically responsive genes of the tolerant line. It was speculated that the genotype-specific response of 20 transcription factors in the tolerance line and the sustained genotypically differential expression of 22 transcription factors might enhance tolerance to drought in maize. Our results provide new insight into maize drought tolerance-related regulation systems and provide gene resources for subsequent studies and drought tolerance improvement.

Numerous genetic loci identified for drought tolerance in the maize nested association mapping populations.

BACKGROUND: Maize requires more water than most other crops; therefore, the water use efficiency of this crop must be improved for maize production under undesirable land and changing environmental conditions. RESULTS: To elucidate the genetic control of drought in maize, we evaluated approximately 5000 inbred lines from 30 linkage-association joint mapping populations under two contrasting water regimes for seven drought-related traits, including yield and anthesis-silking interval (ASI). The joint linkage analysis was conducted to identify 220 quantitative trait loci (QTLs) under well-watered conditions and 169 QTLs under water-stressed conditions. The genome-wide association analysis identified 365 single nucleotide polymorphisms (SNPs) associated with drought-related traits, and these SNPs were located in 354 candidate genes. Fifty-two of these genes showed significant differential expression in the inbred line B73 under the well-watered and water-stressed conditions. In addition, genomic predictions suggested that the moderate-density SNPs obtained through genotyping-by-sequencing were able to make accurate predictions in the nested association mapping population for drought-related traits with moderate-to-high heritability under the water-stressed conditions. CONCLUSIONS: The results of the present study provide important information that can be used to understand the genetic basis of drought stress responses and facilitate the use of beneficial alleles for the improvement of drought tolerance in maize.

Overexpression of the phosphatidylinositol synthase gene (ZmPIS) conferring drought stress tolerance by altering membrane lipid composition and increasing ABA synthesis in maize.

Phosphatidylinositol (PtdIns) synthase is a key enzyme in the phospholipid pathway and catalyses the formation of PtdIns. PtdIns is not only a structural component of cell membranes, but also the precursor of the phospholipid signal molecules that regulate plant response to environment stresses. Here, we obtained transgenic maize constitutively overexpressing or underexpressing PIS from maize (ZmPIS) under the control of a maize ubiquitin promoter. Transgenic plants were confirmed by PCR, Southern blotting analysis and real-time RT-PCR assay. The electrospray ionization tandem mass spectrometry (ESI-MS/MS)-based lipid profiling analysis showed that, under drought stress conditions, the overexpression of ZmPIS in maize resulted in significantly elevated levels of most phospholipids and galactolipids in leaves compared with those in wild type (WT). At the same time, the expression of some genes involved in the phospholipid metabolism pathway and the abscisic acid (ABA) biosynthesis pathway including ZmPLC, ZmPLD, ZmDGK1, ZmDGK3, ZmPIP5K9, ZmABA1, ZmNCED, ZmAAO1, ZmAAO2 and ZmSCA1 was markedly up-regulated in the overexpression lines after drought stress. Consistent with these results, the drought stress tolerance of the ZmPIS sense transgenic plants was enhanced significantly at the pre-flowering stages compared with WT maize plants. These results imply that ZmPIS regulates the plant response to drought stress through altering membrane lipid composition and increasing ABA synthesis in maize.

Correlations and comparisons of quantitative trait loci with family per se and testcross performance for grain yield and related traits in maize.

Simultaneous improvement in grain yield and related traits in maize hybrids and their parents (inbred lines) requires a better knowledge of genotypic correlations between family per se performance (FP) and testcross performance (TP). Thus, to understand the genetic basis of yield-related traits in both inbred lines and their testcrosses, two F (2:3) populations (including 230 and 235 families, respectively) were evaluated for both FP and TP of eight yield-related traits in three diverse environments. Genotypic correlations between FP and TP, [Formula: see text] (FP, TP), were low (0-0.16) for grain yield per plant (GYPP) and kernel number per plant (KNPP) in the two populations, but relatively higher (0.32-0.69) for the other six traits with additive effects as the primary gene action. Similar results were demonstrated by the genotypic correlations between observed and predicted TP values based on quantitative trait loci positions and effects for FP, [Formula: see text] (M (FP), Y (TP)). A total of 88 and 35 QTL were detected with FP and TP, respectively, across all eight traits in the two populations. However, the genotypic variances explained by the QTL detected in the cross-validation analysis were much lower than those in the whole data set for all traits. Several common QTL between FP and TP that accounted for large phenotypic variances were clustered in four genomic regions (bin 1.10, 4.05-4.06, 9.02, and 10.04), which are promising candidate loci for further map-based cloning and improvement in grain yield in maize. Compared with publicly available QTL data, these QTL were also detected in a wide range of genetic backgrounds and environments in maize. These results imply that effective selection based on FP to improve TP could be achieved for traits with prevailing additive effects.

QTL analysis for yield components and kernel-related traits in maize across multi-environments.

Huangzaosi, Qi319, and Ye478 are foundation inbred lines widely used in maize breeding in China. To elucidate genetic base of yield components and kernel-related traits in these elite lines, two F(2:3) populations derived from crosses Qi319 × Huangzaosi (Q/H, 230 families) and Ye478 × Huangzaosi (Y/H, 235 families), as well as their parents were evaluated in six environments including Henan, Beijing, and Xinjiang in 2007 and 2008. Correlation and hypergeometric probability function analyses showed the dependence of yield components on kernel-related traits. Three mapping procedures were used to identify quantitative trait loci (QTL) for each population: (1) analysis for each of the six environments, (2) joint analysis for each of the three locations across 2 years, and (3) joint analysis across all environments. For the eight traits measured, 90, 89, and 58 QTL for Q/H, and 72, 76, and 51 QTL for Y/H were detected by the three QTL mapping procedures, respectively. About 70% of the QTL from Q/H and 90% of the QTL from Y/H did not show significant QTL × environment interactions in the joint analysis across all environments. Most of the QTL for kernel traits exhibited high stability across 2 years at the same location, even across different locations. Seven major QTL detected under at least four environments were identified on chromosomes 1, 4, 6, 7, 9, and 10 in the populations. Moreover, QTL on chr. 1, chr. 4, and chr. 9 were detected in both populations. These chromosomal regions could be targets for marker-assisted selection, fine mapping, and map-based cloning in maize.