Eleven biosynthetic genes explain the majority of natural variation in carotenoid levels in maize grain.

Vitamin A deficiency remains prevalent in parts of Asia, Latin America, and sub-Saharan Africa where maize (Zea mays) is a food staple. Extensive natural variation exists for carotenoids in maize grain. Here, to understand its genetic basis, we conducted a joint linkage and genome-wide association study of the US maize nested association mapping panel. Eleven of the 44 detected quantitative trait loci (QTL) were resolved to individual genes. Six of these were correlated expression and effect QTL (ceeQTL), showing strong correlations between RNA-seq expression abundances and QTL allelic effect estimates across six stages of grain development. These six ceeQTL also had the largest percentage of phenotypic variance explained, and in major part comprised the three to five loci capturing the bulk of genetic variation for each trait. Most of these ceeQTL had strongly correlated QTL allelic effect estimates across multiple traits. These findings provide an in-depth genome-level understanding of the genetic and molecular control of carotenoids in plants. In addition, these findings provide a roadmap to accelerate breeding for provitamin A and other priority carotenoid traits in maize grain that should be readily extendable to other cereals.

A sorghum practical haplotype graph facilitates genome-wide imputation and cost-effective genomic prediction.

Successful management and utilization of increasingly large genomic datasets is essential for breeding programs to accelerate cultivar development. To help with this, we developed a Sorghum bicolor Practical Haplotype Graph (PHG) pangenome database that stores haplotypes and variant information. We developed two PHGs in sorghum that were used to identify genome-wide variants for 24 founders of the Chibas sorghum breeding program from 0.01x sequence coverage. The PHG called single nucleotide polymorphisms (SNPs) with 5.9% error at 0.01x coverage-only 3% higher than PHG error when calling SNPs from 8x coverage sequence. Additionally, 207 progenies from the Chibas genomic selection (GS) training population were sequenced and processed through the PHG. Missing genotypes were imputed from PHG parental haplotypes and used for genomic prediction. Mean prediction accuracies with PHG SNP calls range from .57-.73 and are similar to prediction accuracies obtained with genotyping-by-sequencing or targeted amplicon sequencing (rhAmpSeq) markers. This study demonstrates the use of a sorghum PHG to impute SNPs from low-coverage sequence data and shows that the PHG can unify genotype calls across multiple sequencing platforms. By reducing input sequence requirements, the PHG can decrease the cost of genotyping, make GS more feasible, and facilitate larger breeding populations. Our results demonstrate that the PHG is a useful research and breeding tool that maintains variant information from a diverse group of taxa, stores sequence data in a condensed but readily accessible format, unifies genotypes across genotyping platforms, and provides a cost-effective option for genomic selection.

Temporal covariance structure of multi-spectral phenotypes and their predictive ability for end-of-season traits in maize.

KEY MESSAGE: Heritable variation in phenotypes extracted from multi-spectral images (MSIs) and strong genetic correlations with end-of-season traits indicates the value of MSIs for crop improvement and modeling of plant growth curve. Vegetation indices (VIs) derived from multi-spectral imaging (MSI) platforms can be used to study properties of crop canopy, providing non-destructive phenotypes that could be used to better understand growth curves throughout the growing season. To investigate the amount of variation present in several VIs and their relationship with important end-of-season traits, genetic and residual (co)variances for VIs, grain yield and moisture were estimated using data collected from maize hybrid trials. The VIs considered were Normalized Difference Vegetation Index (NDVI), Green NDVI, Red Edge NDVI, Soil-Adjusted Vegetation Index, Enhanced Vegetation Index and simple Ratio of Near Infrared to Red (Red) reflectance. Genetic correlations of VIs with grain yield and moisture were used to fit multi-trait models for prediction of end-of-season traits and evaluated using within site/year cross-validation. To explore alternatives to fitting multiple phenotypes from MSI, random regression models with linear splines were fit using data collected in 2016 and 2017. Heritability estimates ranging from (0.10 to 0.82) were observed, indicating that there exists considerable amount of genetic variation in these VIs. Furthermore, strong genetic and residual correlations of the VIs, NDVI and NDRE, with grain yield and moisture were found. Considerable increases in prediction accuracy were observed from the multi-trait model when using NDVI and NDRE as a secondary trait. Finally, random regression with a linear spline function shows potential to be used as an alternative to mixed models to fit VIs from multiple time points.

Transcriptomic and evolutionary analysis of the mechanisms by which P. argentatum, a rubber producing perennial, responds to drought.

BACKGROUND: Guayule (Parthenium argentatum Gray) is a drought tolerant, rubber producing perennial shrub native to northern Mexico and the US Southwest. Hevea brasiliensis, currently the world's only source of natural rubber, is grown as a monoculture, leaving it vulnerable to both biotic and abiotic stressors. Isolation of rubber from guayule occurs by mechanical harvesting of the entire plant. It has been reported that environmental conditions leading up to harvest have a profound impact on rubber yield. The link between rubber biosynthesis and drought, a common environmental condition in guayule's native habitat, is currently unclear. RESULTS: We took a transcriptomic and comparative genomic approach to determine how drought impacts rubber biosynthesis in guayule. We compared transcriptional profiles of stem tissue, the location of guayule rubber biosynthesis, collected from field-grown plants subjected to water-deficit (drought) and well-watered (control) conditions. Plants subjected to the imposed drought conditions displayed an increase in production of transcripts associated with defense responses and water homeostasis, and a decrease in transcripts associated with rubber biosynthesis. An evolutionary and comparative analysis of stress-response transcripts suggests that more anciently duplicated transcripts shared among the Asteraceae, rather than recently derived duplicates, are contributing to the drought response observed in guayule. In addition, we identified several deeply conserved long non-coding RNAs (lncRNAs) containing microRNA binding motifs. One lncRNA in particular, with origins at the base of Asteraceae, may be regulating the vegetative to reproductive transition observed in water-stressed guayule by acting as a miRNA sponge for miR166. CONCLUSIONS: These data represent the first genomic analyses of how guayule responds to drought like conditions in agricultural production settings. We identified an inverse relationship between stress-responsive transcripts and those associated with precursor pathways to rubber biosynthesis suggesting a physiological trade-off between maintaining homeostasis and plant productivity. We also identify a number of regulators of abiotic responses, including transcription factors and lncRNAs, that are strong candidates for future projects aimed at modulating rubber biosynthesis under water-limiting conditions common to guayules' native production environment.

Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain.

Tocopherols, tocotrienols, and plastochromanols (collectively termed tocochromanols) are lipid-soluble antioxidants synthesized by all plants. Their dietary intake, primarily from seed oils, provides vitamin E and other health benefits. Tocochromanol biosynthesis has been dissected in the dicot Arabidopsis thaliana, which has green, photosynthetic seeds, but our understanding of tocochromanol accumulation in major crops, whose seeds are nonphotosynthetic, remains limited. To understand the genetic control of tocochromanols in grain, we conducted a joint linkage and genome-wide association study in the 5000-line U.S. maize (Zea mays) nested association mapping panel. Fifty-two quantitative trait loci for individual and total tocochromanols were identified, and of the 14 resolved to individual genes, six encode novel activities affecting tocochromanols in plants. These include two chlorophyll biosynthetic enzymes that explain the majority of tocopherol variation, which was not predicted given that, like most major cereal crops, maize grain is nonphotosynthetic. This comprehensive assessment of natural variation in vitamin E levels in maize establishes the foundation for improving tocochromanol and vitamin E content in seeds of maize and other major cereal crops.

Population Genomic Analysis Reveals Differential Evolutionary Histories and Patterns of Diversity across Subgenomes and Subpopulations of Brassica napus L.

The allotetraploid species Brassica napus L. is a global crop of major economic importance, providing canola oil (seed) and vegetables for human consumption and fodder and meal for livestock feed. Characterizing the genetic diversity present in the extant germplasm pool of B. napus is fundamental to better conserve, manage and utilize the genetic resources of this species. We used sequence-based genotyping to identify and genotype 30,881 SNPs in a diversity panel of 782 B. napus accessions, representing samples of winter and spring growth habits originating from 33 countries across Europe, Asia, and America. We detected strong population structure broadly concordant with growth habit and geography, and identified three major genetic groups: spring (SP), winter Europe (WE), and winter Asia (WA). Subpopulation-specific polymorphism patterns suggest enriched genetic diversity within the WA group and a smaller effective breeding population for the SP group compared to WE. Interestingly, the two subgenomes of B. napus appear to have different geographic origins, with phylogenetic analysis placing WE and WA as basal clades for the other subpopulations in the C and A subgenomes, respectively. Finally, we identified 16 genomic regions where the patterns of diversity differed markedly from the genome-wide average, several of which are suggestive of genomic inversions. The results obtained in this study constitute a valuable resource for worldwide breeding efforts and the genetic dissection and prediction of complex B. napus traits.

Identification of haplotypes at the Rsv4 genomic region in soybean associated with durable resistance to soybean mosaic virus.

KEY MESSAGE: Discovery of new germplasm sources and identification of haplotypes for the durable Soybean mosaic virus resistance gene, Rsv 4, provide novel resources for map-based cloning and genetic improvement efforts in soybean. The Soybean mosaic virus (SMV) resistance locus Rsv4 is of interest because it provides a durable type of resistance in soybean [Glycine max (L.) Merr.]. To better understand its molecular basis, we used a population of 309 BC3F2 individuals to fine-map Rsv4 to a ~120 kb interval and leveraged this genetic information in a second study to identify accessions 'Haman' and 'Ilpumgeomjeong' as new sources of Rsv4. These two accessions along with three other Rsv4 and 14 rsv4 accessions were used to examine the patterns of nucleotide diversity at the Rsv4 region based on high-depth resequencing data. Through a targeted association analysis of these 19 accessions within the ~120 kb interval, a cluster of four intergenic single-nucleotide polymorphisms (SNPs) was found to perfectly associate with SMV resistance. Interestingly, this ~120 kb interval did not contain any genes similar to previously characterized dominant disease resistance genes. Therefore, a haplotype analysis was used to further resolve the association signal to a ~94 kb region, which also resulted in the identification of at least two Rsv4 haplotypes. A haplotype phylogenetic analysis of this region suggests that the Rsv4 locus in G. max is recently introgressed from G. soja. This integrated study provides a strong foundation for efforts focused on the cloning of this durable virus resistance gene and marker-assisted selection of Rsv4-mediated SMV resistance in soybean breeding programs.

Genome-wide analysis of the omega-3 fatty acid desaturase gene family in Gossypium.

BACKGROUND: The majority of commercial cotton varieties planted worldwide are derived from Gossypium hirsutum, which is a naturally occurring allotetraploid produced by interspecific hybridization of A- and D-genome diploid progenitor species. While most cotton species are adapted to warm, semi-arid tropical and subtropical regions, and thus perform well in these geographical areas, cotton seedlings are sensitive to cold temperature, which can significantly reduce crop yields. One of the common biochemical responses of plants to cold temperatures is an increase in omega-3 fatty acids, which protects cellular function by maintaining membrane integrity. The purpose of our study was to identify and characterize the omega-3 fatty acid desaturase (FAD) gene family in G. hirsutum, with an emphasis on identifying omega-3 FADs involved in cold temperature adaptation. RESULTS: Eleven omega-3 FAD genes were identified in G. hirsutum, and characterization of the gene family in extant A and D diploid species (G. herbaceum and G. raimondii, respectively) allowed for unambiguous genome assignment of all homoeologs in tetraploid G. hirsutum. The omega-3 FAD family of cotton includes five distinct genes, two of which encode endoplasmic reticulum-type enzymes (FAD3-1 and FAD3-2) and three that encode chloroplast-type enzymes (FAD7/8-1, FAD7/8-2, and FAD7/8-3). The FAD3-2 gene was duplicated in the A genome progenitor species after the evolutionary split from the D progenitor, but before the interspecific hybridization event that gave rise to modern tetraploid cotton. RNA-seq analysis revealed conserved, gene-specific expression patterns in various organs and cell types and semi-quantitative RT-PCR further revealed that FAD7/8-1 was specifically induced during cold temperature treatment of G. hirsutum seedlings. CONCLUSIONS: The omega-3 FAD gene family in cotton was characterized at the genome-wide level in three species, showing relatively ancient establishment of the gene family prior to the split of A and D diploid progenitor species. The FAD genes are differentially expressed in various organs and cell types, including fiber, and expression of the FAD7/8-1 gene was induced by cold temperature. Collectively, these data define the genetic and functional genomic properties of this important gene family in cotton and provide a foundation for future efforts to improve cotton abiotic stress tolerance through molecular breeding approaches.

Defining loci in restriction-based reduced representation genomic data from nonmodel species: sources of bias and diagnostics for optimal clustering.

Next generation sequencing holds great promise for applications of phylogeography, landscape genetics, and population genomics in wild populations of nonmodel species, but the robustness of inferences hinges on careful experimental design and effective bioinformatic removal of predictable artifacts. Addressing this issue, we use published genomes from a tunicate, stickleback, and soybean to illustrate the potential for bioinformatic artifacts and introduce a protocol to minimize two sources of error expected from similarity-based de-novo clustering of stacked reads: the splitting of alleles into different clusters, which creates false homozygosity, and the grouping of paralogs into the same cluster, which creates false heterozygosity. We present an empirical application focused on Ciona savignyi, a tunicate with very high SNP heterozygosity (~0.05), because high diversity challenges the computational efficiency of most existing nonmodel pipelines while also potentially exacerbating paralog artifacts. The simulated and empirical data illustrate the advantages of using higher sequence difference clustering thresholds than is typical and demonstrate the utility of our protocol for efficiently identifying an optimum threshold from data without prior knowledge of heterozygosity. The empirical Ciona savignyi data also highlight null alleles as a potentially large source of false homozygosity in restriction-based reduced representation genomic data.

A comparative transcriptomic study of an allotetraploid and its diploid progenitors illustrates the unique advantages and challenges of RNA-seq in plant species.

PREMISE OF THE STUDY: RNA-seq analysis of plant transcriptomes poses unique challenges due to the highly duplicated nature of plant genomes. We address these challenges in the context of recently formed polyploid species and detail an RNA-seq experiment comparing the leaf transcriptome profile of an allopolyploid relative of soybean with the diploid species that contributed its homoeologous genomes. METHODS: RNA-seq reads were obtained from the three species and were aligned against the genome sequence of Glycine max. Transcript levels were estimated for each gene, relative contributions of polyploidy-duplicated loci (homoeologues) in the tetraploid were identified, and comparisons of transcript profiles and individual genes were used to analyze the regulation of transcript levels. KEY RESULTS: We present a novel metric developed to address issues arising from high degrees of gene space duplication and a method for dissecting a gene's measured transcript level in a polyploid species into the relative contribution of its homoeologues. We identify the gene family likely contributing to differences in photosynthetic rate between the allotetraploid and its progenitors and show that the tetraploid appears to be using the "redundant" gene copies in novel ways. CONCLUSIONS: Given the prevalence of polyploidy events in plants, we believe many of the approaches developed here to be applicable, and often necessary, in most plant RNA-seq experiments. The deep sampling provided by RNA-seq allows us to dissect the genetic underpinnings of specific phenotypes as well as examine complex interactions within polyploid genomes.

EST database for early flower development in California poppy (Eschscholzia californica Cham., Papaveraceae) tags over 6,000 genes from a basal eudicot.

The Floral Genome Project (FGP) selected California poppy (Eschscholzia californica Cham. ssp. Californica) to help identify new florally-expressed genes related to floral diversity in basal eudicots. A large, non-normalized cDNA library was constructed from premeiotic and meiotic floral buds and sequenced to generate a database of 9,079 high quality Expressed Sequence Tags (ESTs). These sequences clustered into 5,713 unigenes, including 1,414 contigs and 4,299 singletons. Homologs of genes regulating many aspects of flower development were identified, including those for organ identity and development, cell and tissue differentiation, cell cycle control, and secondary metabolism. Over 5% of the transcriptome consisted of homologs to known floral gene families. Most are the first representatives of their respective gene families in basal eudicots and their conservation suggests they are important for floral development and/or function. App. 10% of the transcripts encoded transcription factors and other regulatory genes, including nine genes from the seven major lineages of the important MADS-box family of developmental regulators. Homologs of alkaloid pathway genes were also recovered, providing opportunities to explore adaptive evolution in secondary products. Furthermore, comparison of the poppy ESTs with the Arabidopsis genome provided support for putative Arabidopsis genes that previously lacked annotation. Finally, over 1,800 unique sequences had no observable homology in the public databases. The California poppy EST database and library will help bridge our understanding of flower initiation and development among higher eudicot and monocot model plants and provide new opportunities for comparative analysis of gene families across angiosperm species.

Floral gene resources from basal angiosperms for comparative genomics research.

BACKGROUND: The Floral Genome Project was initiated to bridge the genomic gap between the most broadly studied plant model systems. Arabidopsis and rice, although now completely sequenced and under intensive comparative genomic investigation, are separated by at least 125 million years of evolutionary time, and cannot in isolation provide a comprehensive perspective on structural and functional aspects of flowering plant genome dynamics. Here we discuss new genomic resources available to the scientific community, comprising cDNA libraries and Expressed Sequence Tag (EST) sequences for a suite of phylogenetically basal angiosperms specifically selected to bridge the evolutionary gaps between model plants and provide insights into gene content and genome structure in the earliest flowering plants. RESULTS: Random sequencing of cDNAs from representatives of phylogenetically important eudicot, non-grass monocot, and gymnosperm lineages has so far (as of 12/1/04) generated 70,514 ESTs and 48,170 assembled unigenes. Efficient sorting of EST sequences into putative gene families based on whole Arabidopsis/rice proteome comparison has permitted ready identification of cDNA clones for finished sequencing. Preliminarily, (i) proportions of functional categories among sequenced floral genes seem representative of the entire Arabidopsis transcriptome, (ii) many known floral gene homologues have been captured, and (iii) phylogenetic analyses of ESTs are providing new insights into the process of gene family evolution in relation to the origin and diversification of the angiosperms. CONCLUSION: Initial comparisons illustrate the utility of the EST data sets toward discovery of the basic floral transcriptome. These first findings also afford the opportunity to address a number of conspicuous evolutionary genomic questions, including reproductive organ transcriptome overlap between angiosperms and gymnosperms, genome-wide duplication history, lineage-specific gene duplication and functional divergence, and analyses of adaptive molecular evolution. Since not all genes in the floral transcriptome will be associated with flowering, these EST resources will also be of interest to plant scientists working on other functions, such as photosynthesis, signal transduction, and metabolic pathways.