Drought stress is seriously affecting the growth and production of crops, especially when agricultural irrigation still remains quantitatively restricted in some arid and semi-arid areas. The identification of drought-tolerant genes is important for improving the adaptability of maize under stress. Here, we found that a new member of the actin-depolymerizing factor (ADF) family; the ZmADF5 gene was tightly linked with a consensus drought-tolerant quantitative trait locus, and the significantly associated signals were detected through genome wide association analysis. ZmADF5 expression could be induced by osmotic stress and the application of exogenous abscisic acid. Its overexpression in Arabidopsis and maize helped plants to keep a higher survival rate after water-deficit stress, which reduced the stomatal aperture and the water-loss rate, as well as improved clearance of reactive oxygen species. Moreover, seventeen differentially expressed genes were identified as regulated by both drought stress and ZmADF5, four of which were involved in the ABA-dependent drought stress response. ZmADF5-overexpressing plants were also identified as sensitive to ABA during the seed germination and seedling stages. These results suggested that ZmADF5 played an important role in the response to drought stress.

Genomic prediction enables rapid selection of maize varieties with low kernel water content (KWC), facilitating the development of mechanized maize harvesting and reducing costs. This study evaluated and characterized the KWC and grain yield (GY) of hybrid maize in northern China and used genomic prediction to identify superior hybrid combinations with low kernel water content at maturity (MKWC) and high GY adapted to northern China. A total of 285 hybrids obtained from single crosses of 34 inbred lines from Stiff Stalk and Non-Stiff Stalk heterotic groups were used for genomic prediction of KWC and GY. We tested 20 different statistical prediction models considering additive effects and evaluating the impact of dominance and epistasis on prediction accuracy. Employing 10-fold cross-validation, it showed that the average prediction accuracy ranged drastically from 0.386 to 0.874 across traits and models. Eight linear statistical methods displayed a very similar prediction accuracy for each trait. The average prediction accuracy of machine learning methods was lower than that of linear statistical methods for KWC-related traits, but the random forest model had a high prediction accuracy of 0.510 for GY. When genetic effects were incorporated into the prediction model, the prediction accuracy for each trait was improved. Overall, the model with dominant and epistatic effects (G:AD(AA)) performed best. For the same number of markers, predictions using trait-specific markers resulted in higher prediction accuracy than randomly selected markers. When the number of trait-specific SNPs was set to 100, the prediction accuracy of GY increased by 33.27%, from 0.406 to 0.541. Out of all the 561 potential hybrids, the TOP 30 hybrids selected by genomic prediction would lead to a 1.44% decrease in MKWC compared with Xianyu335, a hybrid with a fast kernel water dry-down, and these hybrids also had higher GY simultaneously. Our results confirm the value of genomic prediction for hybrid breeding low MKWC suitable for maize mechanized harvesting in northern China. In conclusion, this study highlights the potential of genomic prediction to optimize maize hybrid breeding, enhancing efficiency and providing insights into genotype-accuracy relationships. The findings offer new strategies for hybrid design and advancing mechanized harvesting in northern China.

Rice black-streaked dwarf virus is transmitted by small brown planthoppers, which causes maize rough dwarf disease and rice black-streaked dwarf disease. This virus leads to slow growth or death of the host plants. During the coevolutionary arms race between viruses and plants, virus-derived small interfering RNAs (vsiRNAs) challenge the plant’s defense response and inhibit host immunity through the RNA silencing system. However, it is currently unknown if rice black-streaked dwarf virus can produce the same siRNAs to mediate the RNA silencing in different infected species. In this study, four small RNA libraries and four degradome libraries were constructed by extracting total RNAs from the leaves of the maize (Zea mays) inbred line B73 and japonica rice (Oryza sativa) variety Nipponbare exposed to feeding by viruliferous and nonviruliferous small brown planthoppers. We analyzed the characteristics of small RNAs and explored virus-derived siRNAs in small RNA libraries through high-throughput sequencing. On analyzing the characteristics of small RNA, we noted that the size distributions of small RNAs were mainly 24 nt (19.74 to 62.00%), whereas those of vsiRNAs were mostly 21 nt (41.06 to 41.87%) and 22 nt (39.72 to 42.26%). The 5′-terminal nucleotides of vsiRNAs tended to be adenine or uracil. Exploring the distribution of vsiRNA hot spots on the viral genome segments revealed that the frequency of hotspots in B73 was higher than those in Nipponbare. Meanwhile, hotspots in the S9 and S10 virus genome segments were distributed similarly in both hosts. In addition, the target genes of small RNA were explored by degradome sequencing. Analyses of the regulatory pathway of these target genes unveiled that viral infection affected the ribosome-related target genes in maize and the target genes in the metabolism and biosynthesis pathways in rice. Here, 562 and 703 vsiRNAs were separately obtained in maize and rice and 73 vsiRNAs named as coexisting vsiRNAs (co-vsiRNAs) were detected in both hosts. Stem-loop PCR and real-time quantitative PCR confirmed that co-vsiRNA 3.1 and co-vsiRNA 3.5, derived from genome segment S3, simultaneously play a role in maize and rice and inhibited host gene expression. The study revealed that rice black-streaked dwarf virus can produce the same siRNAs in different species and provides a new direction for developing new antiviral strategies.

Maize (Zea mays L.) is the most extensively cultivated food crop in China, and current studies on maize general combining ability (GCA) focus primarily on the genetic basis of traits. However, the dynamic trends and underlying genetic loci associated with GCA for yield-related traits during breeding remain underexplored. This study was designed to investigate the changing trends of the general combining ability (GCA) and the frequency of elite alleles among 218 major maize inbred lines from Northeast China, spanning the 1970s to the 2010s. PH6WC and PH4CV were used as testers to develop 436 hybrid combinations via the North Carolina design II (NCII) method, and these combinations were evaluated across three environments. We further analyzed the combining ability (particularly the GCA) of 16 yield-related traits and their dynamic trends during breeding, grouped into three age periods (AGE1: 1960s–1970s; AGE2: 1980s–1990s; AGE3: 2000s–2010s). We also screened for genetic loci associated with the GCA effects of these traits. Results show that breeding selection significantly affected the GCA of six yield-related traits (ear length (EL), tassel branch number (TBN), tassel main axis length (TL), kernel length (KL), stem diameter (SDR), and hundred kernel weight (HKW)). Specifically, the mean TBN_GCA value decreased from 2.51 in AGE1 to −1.28 in AGE3, and the mean HKW_GCA increased from −1.58 in AGE1 to 0.36 in AGE3. Yield per plant GCA (YPP_GCA) was positively correlated with the GCA values of EL, ear diameter (ED), kernel row number (KRN), kernel number per row (KNPR), and HKW. Association analysis identified 38 single nucleotide polymorphisms (SNP_S) related to GCA. The T/T alleles for TBN were absent in AGE1, emerged in AGE2 (1980s–1990s), and persisted in AGE3—consistent with the decreasing trend of TBN_GCA from AGE1 to AGE3. For HKW, the A/A alleles not only exhibited higher GCA (effectively improving the HKW_GCA of inbred lines) but also showed an 11% increase in allelic frequency from AGE1 to AGE3. Taken together, these results suggest that the accumulation of elite alleles is the primary factor driving the GCA improvement during maize breeding in Northeast China.

Globulin in maize kernels is a high-quality protein, which is mainly enriched in the embryo. However, academic research focusing on the molecular mechanism