Current challenges and future of agricultural genomes to phenomes in the USA.

Dramatic improvements in measuring genetic variation across agriculturally relevant populations (genomics) must be matched by improvements in identifying and measuring relevant trait variation in such populations across many environments (phenomics). Identifying the most critical opportunities and challenges in genome to phenome (G2P) research is the focus of this paper. Previously (Genome Biol, 23(1):1-11, 2022), we laid out how Agricultural Genome to Phenome Initiative (AG2PI) will coordinate activities with USA federal government agencies expand public-private partnerships, and engage with external stakeholders to achieve a shared vision of future the AG2PI. Acting on this latter step, AG2PI organized the "Thinking Big: Visualizing the Future of AG2PI" two-day workshop held September 9-10, 2022, in Ames, Iowa, co-hosted with the United State Department of Agriculture's National Institute of Food and Agriculture (USDA NIFA). During the meeting, attendees were asked to use their experience and curiosity to review the current status of agricultural genome to phenome (AG2P) work and envision the future of the AG2P field. The topic summaries composing this paper are distilled from two 1.5-h small group discussions. Challenges and solutions identified across multiple topics at the workshop were explored. We end our discussion with a vision for the future of agricultural progress, identifying two areas of innovation needed: (1) innovate in genetic improvement methods development and evaluation and (2) innovate in agricultural research processes to solve societal problems. To address these needs, we then provide six specific goals that we recommend be implemented immediately in support of advancing AG2P research.

Topological data analysis reveals a core gene expression backbone that defines form and function across flowering plants.

Since they emerged approximately 125 million years ago, flowering plants have evolved to dominate the terrestrial landscape and survive in the most inhospitable environments on earth. At their core, these adaptations have been shaped by changes in numerous, interconnected pathways and genes that collectively give rise to emergent biological phenomena. Linking gene expression to morphological outcomes remains a grand challenge in biology, and new approaches are needed to begin to address this gap. Here, we implemented topological data analysis (TDA) to summarize the high dimensionality and noisiness of gene expression data using lens functions that delineate plant tissue and stress responses. Using this framework, we created a topological representation of the shape of gene expression across plant evolution, development, and environment for the phylogenetically diverse flowering plants. The TDA-based Mapper graphs form a well-defined gradient of tissues from leaves to seeds, or from healthy to stressed samples, depending on the lens function. This suggests that there are distinct and conserved expression patterns across angiosperms that delineate different tissue types or responses to biotic and abiotic stresses. Genes that correlate with the tissue lens function are enriched in central processes such as photosynthetic, growth and development, housekeeping, or stress responses. Together, our results highlight the power of TDA for analyzing complex biological data and reveal a core expression backbone that defines plant form and function.

Cross-species predictive modeling reveals conserved drought responses between maize and sorghum.

Drought tolerance is a highly complex trait controlled by numerous interconnected pathways with substantial variation within and across plant species. This complexity makes it difficult to distill individual genetic loci underlying tolerance, and to identify core or conserved drought-responsive pathways. Here, we collected drought physiology and gene expression datasets across diverse genotypes of the C4 cereals sorghum and maize and searched for signatures defining water-deficit responses. Differential gene expression identified few overlapping drought-associated genes across sorghum genotypes, but using a predictive modeling approach, we found a shared core drought response across development, genotype, and stress severity. Our model had similar robustness when applied to datasets in maize, reflecting a conserved drought response between sorghum and maize. The top predictors are enriched in functions associated with various abiotic stress-responsive pathways as well as core cellular functions. These conserved drought response genes were less likely to contain deleterious mutations than other gene sets, suggesting that core drought-responsive genes are under evolutionary and functional constraints. Our findings support a broad evolutionary conservation of drought responses in C4 grasses regardless of innate stress tolerance, which could have important implications for developing climate resilient cereals.

Association mapping across a multitude of traits collected in diverse environments in maize.

Classical genetic studies have identified many cases of pleiotropy where mutations in individual genes alter many different phenotypes. Quantitative genetic studies of natural genetic variants frequently examine one or a few traits, limiting their potential to identify pleiotropic effects of natural genetic variants. Widely adopted community association panels have been employed by plant genetics communities to study the genetic basis of naturally occurring phenotypic variation in a wide range of traits. High-density genetic marker data-18M markers-from 2 partially overlapping maize association panels comprising 1,014 unique genotypes grown in field trials across at least 7 US states and scored for 162 distinct trait data sets enabled the identification of of 2,154 suggestive marker-trait associations and 697 confident associations in the maize genome using a resampling-based genome-wide association strategy. The precision of individual marker-trait associations was estimated to be 3 genes based on a reference set of genes with known phenotypes. Examples were observed of both genetic loci associated with variation in diverse traits (e.g., above-ground and below-ground traits), as well as individual loci associated with the same or similar traits across diverse environments. Many significant signals are located near genes whose functions were previously entirely unknown or estimated purely via functional data on homologs. This study demonstrates the potential of mining community association panel data using new higher-density genetic marker sets combined with resampling-based genome-wide association tests to develop testable hypotheses about gene functions, identify potential pleiotropic effects of natural genetic variants, and study genotype-by-environment interaction.

SNP-Based Genome-Wide Association Mapping of Pollen Viability Under Heat Stress in Tropical Zea mays L. Inbred Lines.

Global environmental changes with more extreme episodes of heat waves are major threats to agricultural productivity. Heat stress in spring affects the reproductive stage of maize, resulting in tassel blast, pollen abortion, poor pollination, reduced seed set, barren ears and ultimately yield loss. As an aneamophelous crop, maize has a propensity for pollen abortion under heat stress conditions. To overcome the existing challenges of heat stress and pollen abortion, this study utilized a broad genetic base of maize germplasm to identify superior alleles to be utilized in breeding programs. A panel of 375 inbred lines was morpho-physiologically screened under normal and heat stress conditions in two locations across two consecutive planting seasons, 2017 and 2018. The exposure of pollen to high temperature showed drastic decline in pollen germination percentage. The average pollen germination percentage (PGP) at 35 and 45°C was 40.3% and 9.7%, respectively, an average decline of 30.6%. A subset of 275 inbred lines were sequenced using tunable genotyping by sequencing, resulting in 170,098 single nucleotide polymorphisms (SNPs) after filtration. Genome wide association of PGP in a subset of 122 inbred lines resulted in ten SNPs associated with PGP35°C (p ≤ 10-5), nine with PGP45°C (p ≤ 10-6-10-8) and ten SNPs associated with PGP ratio (p ≤ 10-5). No SNPs were found to be in common across PGP traits. The number of favorable alleles possessed by each inbred line for PGP35°C, PGP45°C, and the PGP ratio ranged between 4 and 10, 3-13 and 5-13, respectively. In contrast, the number of negative alleles for these traits ranged between 2 and 8, 3-13 and 3-13, respectively. Genetic mapping of yield (adjusted weight per plant, AWP-1) and flowering time (anthesis-silking interval, ASI) in 275 lines revealed five common SNPs: three shared for AWP-1 between normal and heat stress conditions, one for ASI between conditions, and one SNP, CM007648.1-86615409, was associated with both ASI and AWP-1. Variety selection can be performed based on these favorable alleles for various traits. These marker trait associations identified in the diversity panel can be utilized in breeding programs to improve heat stress tolerance in maize.

Germplasm Architecture Revealed through Chromosomal Effects for Quantitative Traits in Maize.

Germplasm architecture refers to how favorable alleles for a given trait are distributed across the genome in a germplasm collection. Our objective was to assess germplasm architecture for quantitative traits among US maize ( L.) inbreds. A total of 271 inbreds were genotyped at 28,626 single nucleotide polymorphism (SNP) loci and phenotyped for anthesis date, plant height, starch and protein concentration, and resistance to northern corn leaf blight (NCLB, caused by ). Chromosomal effects were calculated as the sum of the trait effects of SNP alleles carried on a specific chromosome by an inbred. The chromosomal effects were further decomposed into the mean effects of chromosomes, mean effects of inbreds, and chromosome × inbred effects. On average, none of the 10 maize chromosomes was particularly rich or poor in favorable quantitative trait locus (QTL) alleles. However, extreme values of chromosome × inbred effects often involved chromosomes 5 and 8 for anthesis date, chromosomes 1 and 5 for plant height, and chromosome 9 for protein concentration. Inbreds with one or two chromosomes deficient in favorable alleles were candidates for improvement via chromosome-substitution lines. Specific chromosomes for which each of five genetic backgrounds (B73, Mo17, Oh43, A321, and PH207) were rich or poor for unknown favorable alleles were also identified. Chromosomal effects varied widely even when prior association mapping in the same germplasm collection had failed to identify any QTL. Genomewide marker effects, particularly when partitioned into chromosomal effects, provide a simple way to dissect germplasm architecture for quantitative traits.

Diversity of maize shoot apical meristem architecture and its relationship to plant morphology.

The shoot apical meristem contains a pool of undifferentiated stem cells and controls initiation of all aerial plant organs. In maize (Zea mays), leaves are formed throughout vegetative development; on transition to floral development, the shoot meristem forms the tassel. Due to the regulated balance between stem cell maintenance and organogenesis, the structure and morphology of the shoot meristem are constrained during vegetative development. Previous work identified loci controlling meristem architecture in a recombinant inbred line population. The study presented here expanded on this by investigating shoot apical meristem morphology across a diverse set of maize inbred lines. Crosses of these lines to common parents showed varying phenotypic expression in the F1, with some form of heterosis occasionally observed. An investigation of meristematic growth throughout vegetative development in diverse lines linked the timing of reproductive transition to flowering time. Phenotypic correlations of meristem morphology with adult plant traits showed an association between the meristem and flowering time, leaf shape, and yield traits, revealing links between the control and architecture of undifferentiated and differentiated plant organs. Finally, quantitative trait loci mapping was utilized to map the genetic architecture of these meristem traits in two divergent populations. Control of meristem architecture was mainly population-specific, with 15 total unique loci mapped across the two populations with only one locus identified in both populations.

Genetic control of maize shoot apical meristem architecture.

The shoot apical meristem contains a pool of undifferentiated stem cells and generates all above-ground organs of the plant. During vegetative growth, cells differentiate from the meristem to initiate leaves while the pool of meristematic cells is preserved; this balance is determined in part by genetic regulatory mechanisms. To assess vegetative meristem growth and genetic control in Zea mays, we investigated its morphology at multiple time points and identified three stages of growth. We measured meristem height, width, plastochron internode length, and associated traits from 86 individuals of the intermated B73 × Mo17 recombinant inbred line population. For meristem height-related traits, the parents exhibited markedly different phenotypes, with B73 being very tall, Mo17 short, and the population distributed between. In the outer cell layer, differences appeared to be related to number of cells rather than cell size. In contrast, B73 and Mo17 were similar in meristem width traits and plastochron internode length, with transgressive segregation in the population. Multiple loci (6-9 for each trait) were mapped, indicating meristem architecture is controlled by many regions; none of these coincided with previously described mutants impacting meristem development. Major loci for height and width explaining 16% and 19% of the variation were identified on chromosomes 5 and 8, respectively. Significant loci for related traits frequently coincided, whereas those for unrelated traits did not overlap. With the use of three near-isogenic lines, a locus explaining 16% of the parental variation in meristem height was validated. Published expression data were leveraged to identify candidate genes in significant regions.