Natalia de Leon

Maize HapMap2 identifies extant variation from a genome in flux

Whereas breeders have exploited diversity in maize for yield improvements, there has been limited progress in using beneficial alleles in undomesticated varieties. Characterizing standing variation in this complex genome has been challenging, with only a small fraction of it described to date. Using a population genetics scoring model, we identified 55 million SNPs in 103 lines across pre-domestication and domesticated Zea mays varieties, including a representative from the sister genus Tripsacum. We find that structural variations are pervasive in the Z. mays genome and are enriched at loci associated with important traits. By investigating the drivers of genome size variation, we find that the larger Tripsacum genome can be explained by transposable element abundance rather than an allopolyploid origin. In contrast, intraspecies genome size variation seems to be controlled by chromosomal knob content. There is tremendous overlap in key gene content in maize and Tripsacum, suggesting that adaptations from Tripsacum (for example, perennialism and frost and drought tolerance) can likely be integrated into maize.

Genome-wide atlas of transcription during maize development

Maize is an important model species and a major constituent of human and animal diets. It has also emerged as a potential feedstock and model system for bioenergy research due to recent worldwide interest in developing plant biomass-based, carbon-neutral liquid fuels. To understand how the underlying genome sequence results in specific plant phenotypes, information on the temporal and spatial transcription patterns of genes is crucial. Here we present a comprehensive atlas of global transcription profiles across developmental stages and plant organs. We used a NimbleGen microarray containing 80,301 probe sets to profile transcription patterns in 60 distinct tissues representing 11 major organ systems of inbred line B73. Of the 30,892 probe sets representing the filtered B73 gene models, 91.4% were expressed in at least one tissue. Interestingly, 44.5% of the probe sets were expressed in all tissues, indicating a substantial overlap of gene expression among plant organs. Clustering of maize tissues based on global gene expression profiles resulted in formation of groups of biologically related tissues. We utilized this dataset to examine the expression of genes that encode enzymes in the lignin biosynthetic pathway, and found that expansion of distinct gene families was accompanied by divergent, tissue-specific transcription patterns of the paralogs. This comprehensive expression atlas represents a valuable resource for gene discovery and functional characterization in maize.

Insights into the Maize Pan-Genome and Pan-Transcriptome

Transcriptome sequencing of diverse maize inbreds provided insights into the nature of the maize pan-genome, including identification of 8681 loci absent in the B73 reference sequence. Genome-wide association studies using single nucleotide polymorphisms and transcript abundance variants in the maize pan-genome identified loci associated with traits important for fitness and adaptation. Genomes at the species level are dynamic, with genes present in every individual (core) and genes in a subset of individuals (dispensable) that collectively constitute the pan-genome. Using transcriptome sequencing of seedling RNA from 503 maize (Zea mays) inbred lines to characterize the maize pan-genome, we identified 8681 representative transcript assemblies (RTAs) with 16.4% expressed in all lines and 82.7% expressed in subsets of the lines. Interestingly, with linkage disequilibrium mapping, 76.7% of the RTAs with at least one single nucleotide polymorphism (SNP) could be mapped to a single genetic position, distributed primarily throughout the nonpericentromeric portion of the genome. Stepwise iterative clustering of RTAs suggests, within the context of the genotypes used in this study, that the maize genome is restricted and further sampling of seedling RNA within this germplasm base will result in minimal discovery. Genome-wide association studies based on SNPs and transcript abundance in the pan-genome revealed loci associated with the timing of the juvenile-to-adult vegetative and vegetative-to-reproductive developmental transitions, two traits important for fitness and adaptation. This study revealed the dynamic nature of the maize pan-genome and demonstrated that a substantial portion of variation may lie outside the single reference genome for a species.

Maize (Zea mays L.) Genome Diversity as Revealed by RNA-Sequencing

Maize is rich in genetic and phenotypic diversity. Understanding the sequence, structural, and expression variation that contributes to phenotypic diversity would facilitate more efficient varietal improvement. RNA based sequencing (RNA-seq) is a powerful approach for transcriptional analysis, assessing sequence variation, and identifying novel transcript sequences, particularly in large, complex, repetitive genomes such as maize. In this study, we sequenced RNA from whole seedlings of 21 maize inbred lines representing diverse North American and exotic germplasm. Single nucleotide polymorphism (SNP) detection identified 351,710 polymorphic loci distributed throughout the genome covering 22,830 annotated genes. Tight clustering of two distinct heterotic groups and exotic lines was evident using these SNPs as genetic markers. Transcript abundance analysis revealed minimal variation in the total number of genes expressed across these 21 lines (57.1% to 66.0%). However, the transcribed gene set among the 21 lines varied, with 48.7% expressed in all of the lines, 27.9% expressed in one to 20 lines, and 23.4% expressed in none of the lines. De novo assembly of RNA-seq reads that did not map to the reference B73 genome sequence revealed 1,321 high confidence novel transcripts, of which, 564 loci were present in all 21 lines, including B73, and 757 loci were restricted to a subset of the lines. RT-PCR validation demonstrated 87.5% concordance with the computational prediction of these expressed novel transcripts. Intriguingly, 145 of the novel de novo assembled loci were present in lines from only one of the two heterotic groups consistent with the hypothesis that, in addition to sequence polymorphisms and transcript abundance, transcript presence/absence variation is present and, thereby, may be a mechanism contributing to the genetic basis of heterosis.

Maize Gene Atlas Developed by RNA Sequencing and Comparative Evaluation of Transcriptomes Based on RNA Sequencing and Microarrays

Transcriptome analysis is a valuable tool for identification and characterization of genes and pathways underlying plant growth and development. We previously published a microarray-based maize gene atlas from the analysis of 60 unique spatially and temporally separated tissues from 11 maize organs [1]. To enhance the coverage and resolution of the maize gene atlas, we have analyzed 18 selected tissues representing five organs using RNA sequencing (RNA-Seq). For a direct comparison of the two methodologies, the same RNA samples originally used for our microarray-based atlas were evaluated using RNA-Seq. Both technologies produced similar transcriptome profiles as evident from high Pearsons correlation statistics ranging from 0.70 to 0.83, and from nearly identical clustering of the tissues. RNA-Seq provided enhanced coverage of the transcriptome, with 82.1% of the filtered maize genes detected as expressed in at least one tissue by RNA-Seq compared to only 56.5% detected by microarrays. Further, from the set of 465 maize genes that have been historically well characterized by mutant analysis, 427 show significant expression in at least one tissue by RNA-Seq compared to 390 by microarray analysis. RNA-Seq provided higher resolution for identifying tissue-specific expression as well as for distinguishing the expression profiles of closely related paralogs as compared to microarray-derived profiles. Co-expression analysis derived from the microarray and RNA-Seq data revealed that broadly similar networks result from both platforms, and that co-expression estimates are stable even when constructed from mixed data including both RNA-Seq and microarray expression data. The RNA-Seq information provides a useful complement to the microarray-based maize gene atlas and helps to further understand the dynamics of transcription during maize development.

Marker Density and Read Depth for Genotyping Populations Using Genotyping-by-Sequencing

Genotyping-by-sequencing (GBS) approaches provide low-cost, high-density genotype information. However, GBS has unique technical considerations, including a substantial amount of missing data and a nonuniform distribution of sequence reads. The goal of this study was to characterize technical variation using this method and to develop methods to optimize read depth to obtain desired marker coverage. To empirically assess the distribution of fragments produced using GBS, ∼8.69 Gb of GBS data were generated on the Zea mays reference inbred B73, utilizing ApeKI for genome reduction and single-end reads between 75 and 81 bp in length. We observed wide variation in sequence coverage across sites. Approximately 76% of potentially observable cut site-adjacent sequence fragments had no sequencing reads whereas a portion had substantially greater read depth than expected, up to 2369 times the expected mean. The methods described in this article facilitate determination of sequencing depth in the context of empirically defined read depth to achieve desired marker density for genetic mapping studies.

Utility of RNA Sequencing for Analysis of Maize Reproductive Transcriptomes

Transcriptome sequencing is a powerful method for studying global expression patterns in large, complex genomes. Evaluation of sequence‐based expression profiles during reproductive development would provide functional annotation to genes underlying agronomic traits. We generated transcriptome profiles for 12 diverse maize (Zea mays L.) reproductive tissues representing male, female, developing seed, and leaf tissues using high throughput transcriptome sequencing. Overall, ∼80% of annotated genes were expressed. Comparative analysis between sequence and hybridization‐based methods demonstrated the utility of ribonucleic acid sequencing (RNA‐seq) for expression determination and differentiation of paralagous genes (∼85% of maize genes). Analysis of 4975 gene families across reproductive tissues revealed expression divergence is proportional to family size. In all pairwise comparisons between tissues, 7 (pre‐ vs. postemergence cobs) to 48% (pollen vs. ovule) of genes were differentially expressed. Genes with expression restricted to a single tissue within this study were identified with the highest numbers observed in leaves, endosperm, and pollen. Coexpression network analysis identified 17 gene modules with complex and shared expression patterns containing many previously described maize genes. The data and analyses in this study provide valuable tools through improved gene annotation, gene family characterization, and a core set of candidate genes to further characterize maize reproductive development and improve grain yield potential.

Forage quality and composition measurements as predictors of ethanol yield from maize (Zea mays L.) stover.

BackgroundImprovement of biofeedstock quality for cellulosic ethanol production will be facilitated by inexpensive and rapid methods of evaluation, such as those already employed in the field of ruminant nutrition. Our objective was to evaluate whether forage quality and compositional measurements could be used to estimate ethanol yield of maize stover as measured by a simplified pretreatment and simultaneous saccharification and fermentation assay. Twelve maize varieties selected to be diverse for stover digestibility and composition were evaluated.ResultsVariation in ethanol yield was driven by glucan convertibility rather than by glucan content. Convertibility was highly correlated with ruminal digestibility and lignin content. There was no relationship between structural carbohydrate content (glucan and neutral detergent fiber) and ethanol yield. However, when these variables were included in multiple regression equations including convertibility or neutral detergent fiber digestibility, their partial regression coefficients were significant and positive. A regression model including both neutral detergent fiber and its ruminal digestibility explained 95% of the variation in ethanol yield.ConclusionForage quality and composition measurements may be used to predict cellulosic ethanol yield to guide biofeedstock improvement through agronomic research and plant breeding.

The Genetic Architecture of Maize Stalk Strength

Stalk strength is an important trait in maize (Zea mays L.). Strong stalks reduce lodging and maximize harvestable yield. Studies show rind penetrometer resistance (RPR), or the force required to pierce a stalk rind with a spike, is a valid approximation of strength. We measured RPR across 4,692 recombinant inbreds (RILs) comprising the maize nested association mapping (NAM) panel derived from crosses of diverse inbreds to the inbred, B73. An intermated B73×Mo17 family (IBM) of 196 RILs and a panel of 2,453 diverse inbreds from the North Central Regional Plant Introduction Station (NCRPIS) were also evaluated. We measured RPR in three environments. Family-nested QTL were identified by joint-linkage mapping in the NAM panel. We also performed a genome-wide association study (GWAS) and genomic best linear unbiased prediction (GBLUP) in each panel. Broad sense heritability computed on a line means basis was low for RPR. Only 8 of 26 families had a heritability above 0.20. The NCRPIS diversity panel had a heritability of 0.54. Across NAM and IBM families, 18 family-nested QTL and 141 significant GWAS associations were identified for RPR. Numerous weak associations were also found in the NCRPIS diversity panel. However, few were linked to loci involved in phenylpropanoid and cellulose synthesis or vegetative phase transition. Using an identity-by-state (IBS) relationship matrix estimated from 1.6 million single nucleotide polymorphisms (SNPs) and RPR measures from 20% of the NAM panel, genomic prediction by GBLUP explained 64±2% of variation in the remaining RILs. In the NCRPIS diversity panel, an IBS matrix estimated from 681,257 SNPs and RPR measures from 20% of the panel explained 33±3% of variation in the remaining inbreds. These results indicate the high genetic complexity of stalk strength and the potential for genomic prediction to hasten its improvement.

B73-Mo17 Near-Isogenic Lines Demonstrate Dispersed Structural Variation in Maize

Recombinant inbred lines developed from the maize (Zea mays ssp. mays) inbreds B73 and Mo17 have been widely used to discover quantitative trait loci controlling a wide variety of phenotypic traits and as a resource to produce high-resolution genetic maps. These two parents were used to produce a set of near-isogenic lines (NILs) with small regions of introgression into both backgrounds. A novel array-based genotyping platform was used to score genotypes of over 7,000 loci in 100 NILs with B73 as the recurrent parent and 50 NILs with Mo17 as the recurrent parent. This population contains introgressions that cover the majority of the maize genome. The set of NILs displayed an excess of residual heterozygosity relative to the amount expected based on their pedigrees, and this excess residual heterozygosity is enriched in the low-recombination regions near the centromeres. The genotyping platform provided the ability to survey copy number variants that exist in more copies in Mo17 than in B73. The majority of these Mo17-specific duplications are located in unlinked positions throughout the genome. The utility of this population for the discovery and validation of quantitative trait loci was assessed through analysis of plant height variation.