Insights into the maize pan-genome and pan-transcriptome.

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.

Large effect QTL explain natural phenotypic variation for the developmental timing of vegetative phase change in maize (Zea mays L.).

KEY MESSAGE: Natural variation for the timing of vegetative phase change in maize is controlled by several large effect loci, one corresponding to Glossy15 , a gene known for regulating juvenile tissue traits. Vegetative phase change is an intrinsic component of developmental programs in plants. Juvenile and adult vegetative tissues in grasses differ dramatically in their anatomical and biochemical composition affecting the utility of specific genotypes as animal feed and biofuel feedstock. The molecular network controlling the process of developmental transition is incompletely characterized. In this study, we used scoring for juvenile and adult epicuticular wax as an entry point to discover quantitative trait loci (QTL) controlling phenotypic variation for the developmental timing of juvenile to adult transition in maize. We scored the last leaf with juvenile wax on 25 recombinant inbred line families of the B73 reference Nested Association Mapping (NAM) population and the intermated B73×Mo17 (IBM) population across multiple seasons. A total of 13 unique QTL were identified through genome-wide association analysis across the NAM populations, three of which have large effects. A QTL located on chromosome nine had the most significant SNPs within Glossy15, a gene controlling expression of juvenile leaf traits. The second large effect QTL is located on chromosome two. The most significant SNP in this QTL is located adjacent to a homolog of the Arabidopsis transcription factor, enhanced downy mildew-2, which has been shown to promote the transition from juvenile to adult vegetative phase. Overall, these results show that several major QTL and potential candidate genes underlie the extensive natural variation for this developmental trait.

QTL mapping and phenotypic variation of root anatomical traits in maize (Zea mays L.).

KEY MESSAGE: Root anatomical trait variation is described for three maize RIL populations. Six quantitative trait loci (QTL) are presented for anatomical traits: root cross-sectional area, % living cortical area, aerenchyma area, and stele area. Root anatomy is directly related to plant performance, influencing resource acquisition and transport, the metabolic cost of growth, and the mechanical strength of the root system. Ten root anatomical traits were measured in greenhouse-grown plants from three recombinant inbred populations of maize [intermated B73 × Mo17 (IBM), Oh43 × W64a (OhW), and Ny821 × H99 (NyH)]. Traits included areas of cross section, stele, cortex, aerenchyma, and cortical cells, percentages of the cortex occupied by aerenchyma, and cortical cell file number. Significant phenotypic variation was observed for each of the traits, with maximum values typically seven to ten times greater than minimum values. Means and ranges were similar for the OhW and NyH populations for all traits, while the IBM population had lower mean values for the majority of traits, but a 50% greater range of variation for aerenchyma area. A principal component analysis showed a similar trait structure for the three families, with clustering of area and count traits. Strong correlations were observed among area traits in the cortex, stele, and cross-section. The aerenchyma and percent living cortical area traits were independent of other traits. Six QTL were identified for four of the traits. The phenotypic variation explained by the QTL ranged from 4.7% (root cross-sectional area, OhW population) to 12.0% (percent living cortical area, IBM population). Genetic variation for root anatomical traits can be harnessed to increase abiotic stress tolerance and provide insights into mechanisms controlling phenotypic variation for root anatomy.

QTL mapping and phenotypic variation for root architectural traits in maize (Zea mays L.).

KEY MESSAGE: QTL were identified for root architectural traits in maize. Root architectural traits, including the number, length, orientation, and branching of the principal root classes, influence plant function by determining the spatial and temporal domains of soil exploration. To characterize phenotypic patterns and their genetic control, three recombinant inbred populations of maize were grown for 28 days in solid media in a greenhouse and evaluated for 21 root architectural traits, including length, number, diameter, and branching of seminal, primary and nodal roots, dry weight of embryonic and nodal systems, and diameter of the nodal root system. Significant phenotypic variation was observed for all traits. Strong correlations were observed among traits in the same root class, particularly for the length of the main root axis and the length of lateral roots. In a principal component analysis, relationships among traits differed slightly for the three families, though vectors grouped together for traits within a given root class, indicating opportunities for more efficient phenotyping. Allometric analysis showed that trajectories of growth for specific traits differ in the three populations. In total, 15 quantitative trait loci (QTL) were identified. QTL are reported for length in multiple root classes, diameter and number of seminal roots, and dry weight of the embryonic and nodal root systems. Phenotypic variation explained by individual QTL ranged from 0.44% (number of seminal roots, NyH population) to 13.5% (shoot dry weight, OhW population). Identification of QTL for root architectural traits may be useful for developing genotypes that are better suited to specific soil environments.

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.

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.