Genomic variation within the maize stiff-stalk heterotic germplasm pool

Integration of ATAC-Seq and RNA-Seq Reveals the Role of FaTIP1 in Red Light-Induced Fruit Ripening in Strawberry

Light is an important environmental factor affecting the ripening and quality of strawberry fruit. Previous studies have shown that red light treatment can promote strawberry ripening. Gene expression is closely associated with chromatin openness, and changes in chromatin accessibility are crucial for the binding of transcription factors to downstream regulatory sequences. However, the changes in chromatin accessibility in response to different light treatments in octoploid strawberry plants are still unclear. In this study, the landscape of chromatin accessibility of octoploid strawberry under red (R) and yellow-green (YG) light conditions was analyzed by the assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq). Through bioinformatics and Venn diagram analyses, a total of 1456 and 1854 group-specific genes (GSGs) were screened in the R and YG groups, respectively. By using RNA sequencing (RNA-seq), 440 differentially expressed genes (DEGs) were identified. Among these genes, 194 were upregulated under red light treatment. Through joint analysis of ATAC-seq and RNA-seq data, three red group-specific genes with increased expression were identified, namely, FaTIP1, FaQKY and FaLBD1. Through gene expression and transient transformation analyses of strawberry fruit, we further demonstrated that FaTIP1 can respond to red light induction and promote the ripening process of strawberry fruit. Our results provide a reference for the study of chromatin accessibility in octoploid strawberry and reveal new factors involved in the fruit's response to red light and the regulation of the ripening process of strawberry fruit.

Global Genotype by Environment Prediction Competition Reveals That Diverse Modeling Strategies Can Deliver Satisfactory Maize Yield Estimates

Predicting phenotypes from a combination of genetic and environmental factors is a grand challenge of modern biology. Slight improvements in this area have the potential to save lives, improve food and fuel security, permit better care of the planet, and create other positive outcomes. In 2022 and 2023 the first open-to-the-public Genomes to Fields (G2F) initiative Genotype by Environment (GxE) prediction competition was held using a large dataset including genomic variation, phenotype and weather measurements and field management notes, gathered by the project over nine years. The competition attracted registrants from around the world with representation from academic, government, industry, and non-profit institutions as well as unaffiliated. These participants came from diverse disciplines include plant science, animal science, breeding, statistics, computational biology and others. Some participants had no formal genetics or plant-related training, and some were just beginning their graduate education. The teams applied varied methods and strategies, providing a wealth of modeling knowledge based on a common dataset. The winner's strategy involved two models combining machine learning and traditional breeding tools: one model emphasized environment using features extracted by Random Forest, Ridge Regression and Least-squares, and one focused on genetics. Other high-performing teams' methods included quantitative genetics, classical machine learning/deep learning, mechanistic models, and model ensembles. The dataset factors used, such as genetics; weather; and management data, were also diverse, demonstrating that no single model or strategy is far superior to all others within the context of this competition.

Multiscale physiological responses to nitrogen supplementation of maize hybrids

Maize (Zea mays) production systems are heavily reliant on the provision of managed inputs such as fertilizers to maximize growth and yield. Hence, the effective use of nitrogen (N) fertilizer is crucial to minimize the associated financial and environmental costs, as well as maximize yield. However, how to effectively utilize N inputs for increased grain yields remains a substantial challenge for maize growers that requires a deeper understanding of the underlying physiological responses to N fertilizer application. We report a multiscale investigation of five field-grown maize hybrids under low or high N supplementation regimes that includes the quantification of phenolic and prenyl-lipid compounds, cellular ultrastructural features, and gene expression traits at three developmental stages of growth. Our results reveal that maize perceives the lack of supplemented N as a stress and, when provided with additional N, will prolong vegetative growth. However, the manifestation of the stress and responses to N supplementation are highly hybrid-specific. Eight genes were differentially expressed in leaves in response to N supplementation in all tested hybrids and at all developmental stages. These genes represent potential biomarkers of N status and include two isoforms of Thiamine Thiazole Synthase involved in vitamin B1 biosynthesis. Our results uncover a detailed view of the physiological responses of maize hybrids to N supplementation in field conditions that provides insight into the interactions between management practices and the genetic diversity within maize.

Conservation and diversity of the pollen microbiome of Pan-American maize using PacBio and MiSeq

Pollen is a vector for diversification, fitness-selection, and transmission of plant genetic material. The extent to which the pollen microbiome may contribute to host diversification is largely unknown, because pollen microbiome diversity within a plant species has not been reported, and studies have been limited to conventional short-read 16S rRNA gene sequencing (e.g., V4-MiSeq) which suffers from poor taxonomic resolution. Here we report the pollen microbiomes of 16 primitive and traditional accessions of maize (corn) selected by indigenous peoples across the Americas, along with the modern U.S. inbred B73. The maize pollen microbiome has not previously been reported. The pollen microbiomes were identified using full-length (FL) 16S rRNA gene PacBio SMRT sequencing compared to V4-MiSeq. The Pan-American maize pollen microbiome encompasses 765 taxa spanning 39 genera and 46 species, including known plant growth promoters, insect-obligates, plant pathogens, nitrogen-fixers and biocontrol agents. Eleven genera and 13 species composed the core microbiome. Of 765 taxa, 63% belonged to only four genera: 28% were Pantoea, 15% were Lactococcus, 11% were Pseudomonas, and 10% were Erwinia. Interestingly, of the 215 Pantoea taxa, 180 belonged to a single species, P. ananatis. Surprisingly, the diversity within P. ananatis ranged nearly 10-fold amongst the maize accessions analyzed (those with ≥3 replicates), despite being grown in a common field. The highest diversity within P. ananatis occurred in accessions that originated near the center of diversity of domesticated maize, with reduced diversity associated with the north-south migration of maize. This sub-species diversity was revealed by FL-PacBio but missed by V4-MiSeq. V4-MiSeq also mis-identified some dominant genera captured by FL-PacBio. The study, though limited to a single season and common field, provides initial evidence that pollen microbiomes reflect evolutionary and migratory relationships of their host plants.

Benchmarking Oxford Nanopore read alignment-based insertion and deletion detection in crop plant genomes

Structural variations (SVs) are larger polymorphisms (> 50 bp in length), which consist of insertions, deletions, inversions, duplications, and translocations. They can have a strong impact on agronomical traits and play an important role in environmental adaptation. The development of long-read sequencing technologies, including Oxford Nanopore, allows for comprehensive SV discovery and characterization even in complex polyploid crop genomes. However, many of the SV discovery pipeline benchmarks do not include complex plant genome datasets. In this study, we benchmarked insertion and deletion detection by popular long-read alignment-based SV detection tools for crop plant genomes. We used real and simulated Oxford Nanopore reads for two crops, allotetraploid Brassica napus (oilseed rape) and diploid Solanum lycopersicum (tomato), and evaluated several read aligners and SV callers across 5×, 10×, and 20× coverages typically used in re-sequencing studies. We further validated our findings using maize and soybean datasets. Our benchmarks provide a useful guide for designing Oxford Nanopore re-sequencing projects and SV discovery pipelines for crop plants.

A DEK domain-containing protein GhDEK2D mediated Gossypium hirsutum enhanced resistance to Verticillium dahliae

DEK is associated with DNA replication and break repair, mRNA splicing, and transcriptional regulation, which had been studied in humans and mammals. The function of DEK in plants was poorly understood. In this study, GhDEK2D was identified in Gossypium hirsutum by genome-wide and post-translational modifications. GhDEK2D had been phosphorylated, acetylated and ubiquitylated under Verticillium dahliae (Vd) challenge. The GhDEK2D-silenced cotton decreased resistance against Vd. In GhDEK2D-silenced cotton plants, the reactive oxygen species was activated, the callose, xylogen, hypersensitive reaction (HR) and expression levels of defense-related genes were reduced. Homozygous overexpressing-GhDEK2D transgenic Arabidopsis lines were more resistant to Verticillium wilt (Vw). We propose that GhDEK2D was a potential molecular target for improving resistance to Vw in cotton.

Core circadian clock and light signaling genes brought into genetic linkage across the green lineage

The circadian clock is conserved at both the level of transcriptional networks as well as core genes in plants, ensuring that biological processes are phased to the correct time of day. In the model plant Arabidopsis (Arabidopsis thaliana), the core circadian SHAQKYF-type-MYB (sMYB) genes CIRCADIAN CLOCK ASSOCIATED 1 (CCA1) and REVEILLE (RVE4) show genetic linkage with PSEUDO-RESPONSE REGULATOR 9 (PRR9) and PRR7, respectively. Leveraging chromosome-resolved plant genomes and syntenic ortholog analysis enabled tracing this genetic linkage back to Amborella trichopoda, a sister lineage to the angiosperm, and identifying an additional evolutionarily conserved genetic linkage in light signaling genes. The LHY/CCA1-PRR5/9, RVE4/8-PRR3/7, and PIF3-PHYA genetic linkages emerged in the bryophyte lineage and progressively moved within several genes of each other across an array of angiosperm families representing distinct whole-genome duplication and fractionation events. Soybean (Glycine max) maintained all but two genetic linkages, and expression analysis revealed the PIF3-PHYA linkage overlapping with the E4 maturity group locus was the only pair to robustly cycle with an evening phase, in contrast to the sMYB-PRR morning and midday phase. While most monocots maintain the genetic linkages, they have been lost in the economically important grasses (Poaceae), such as maize (Zea mays), where the genes have been fractionated to separate chromosomes and presence/absence variation results in the segregation of PRR7 paralogs across heterotic groups. The environmental robustness model is put forward, suggesting that evolutionarily conserved genetic linkages ensure superior microhabitat pollinator synchrony, while wide-hybrids or unlinking the genes, as seen in the grasses, result in heterosis, adaptation, and colonization of new ecological niches.

Genome-Wide Characterization of DGATs and Their Expression Diversity Analysis in Response to Abiotic Stresses in Brassica napus

Triacylglycerol (TAG) is the most important storage lipid for oil plant seeds. Diacylglycerol acyltransferases (DGATs) are a key group of rate-limiting enzymes in the pathway of TAG biosynthesis. In plants, there are three types of DGATs, namely, DGAT1, DGAT2 and DGAT3. Brassica napus, an allotetraploid plant, is one of the most important oil plants in the world. Previous studies of Brassica napus DGATs (BnaDGATs) have mainly focused on BnaDGAT1s. In this study, four DGAT1s, four DGAT2s and two DGAT3s were identified and cloned from B. napus ZS11. The analyses of sequence identity, chromosomal location and collinearity, phylogenetic tree, exon/intron gene structures, conserved domains and motifs, and transmembrane domain (TMD) revealed that BnaDGAT1, BnaDGAT2 and BnaDGAT3 were derived from three different ancestors and shared little similarity in gene and protein structures. Overexpressing BnaDGATs showed that only four BnaDGAT1s can restore TAG synthesis in yeast H1246 and promote the accumulation of fatty acids in yeast H1246 and INVSc1, suggesting that the three BnaDGAT subfamilies had greater differentiation in function. Transcriptional analysis showed that the expression levels of BnaDGAT1s, BnaDGAT2s and BnaDGAT3s were different during plant development and under different stresses. In addition, analysis of fatty acid contents in roots, stems and leaves under abiotic stresses revealed that P starvation can promote the accumulation of fatty acids, but no obvious relationship was shown between the accumulation of fatty acids with the expression of BnaDGATs under P starvation. This study provides an extensive evaluation of BnaDGATs and a useful foundation for dissecting the functions of BnaDGATs in biochemical and physiological processes.

Genetic mapping and prediction of flowering time and plant height in a maize Stiff Stalk MAGIC population

The Stiff Stalk heterotic pool is a foundation of US maize seed parent germplasm and has been heavily utilized by both public and private maize breeders since its inception in the 1930's. Flowering time and plant height are critical characteristics for both inbred parents and their test crossed hybrid progeny. To study these traits, a six parent multiparent advanced generation intercross (MAGIC) population was developed including maize inbred lines B73, B84, PHB47 (B37 type), LH145 (B14 type), PHJ40 (novel early Stiff Stalk), and NKH8431 (B73/B14 type). A set of 779 doubled haploid lines were evaluated for flowering time and plant height in two field replicates in 2016 and 2017, and a subset of 689 and 561 doubled haploid lines were crossed to two testers, respectively, and evaluated as hybrids in two locations in 2018 and 2019 using an incomplete block design. Markers were derived from a Practical Haplotype Graph built from the founder whole genome assemblies and genotype-by-sequencing and exome capture-based sequencing of the population. Genetic mapping utilizing an update to R/qtl2 revealed differing profiles of significant loci for both traits between 635 of the DH lines and two sets of 570 and 471 derived hybrids. Genomic prediction was used to test the feasibility of predicting hybrid phenotypes based on the per se data. Predictive abilities were highest on direct models trained using the data they would predict (0.55 to 0.63), and indirect models trained using per se data to predict hybrid traits had slightly lower predictive abilities (0.49 to 0.55). Overall, this finding is consistent with the overlapping and non-overlapping significant QTL found within the per se and hybrid populations and suggests that selections for phenology traits can be made effectively on doubled haploid lines before hybrid data is available.