Coregulation of ribosomal RNA with hundreds of genes contributes to phenotypic variation.

Ribosomal repeats occupy 5% of a plant genome, yet there has been little study of their diversity in the modern age of genomics. Ribosomal copy number and expression variation present an opportunity to tap a novel source of diversity. In the present study, we estimated the ribosomal DNA (rDNA) copy number and ribosomal RNA (rRNA) expression for a population of maize inbred lines and investigated the potential role of rDNA and rRNA dosage in regulating global gene expression. Extensive variation was found in both ribosomal DNA copy number and ribosomal RNA expression among maize inbred lines. However, rRNA abundance was not consistent with the copy number of the rDNA. We have not found that the rDNA gene dosage has a regulatory role in gene expression; however, thousands of genes are identified to be coregulated with rRNA expression, including genes participating in ribosome biogenesis and other functionally relevant pathways. We further investigated the potential roles of copy number and the expression level of rDNA on agronomic traits and found that both correlated with flowering time but through different regulatory mechanisms. This comprehensive analysis suggested that rRNA expression variation is a valuable source of functional diversity that affects gene expression variation and field-based phenotypic changes.

Genome-wide association study of Fusarium ear rot disease in the U.S.A. maize inbred line collection.

BACKGROUND: Resistance to Fusarium ear rot of maize is a quantitative and complex trait. Marker-trait associations to date have had small additive effects and were inconsistent between previous studies, likely due to the combined effects of genetic heterogeneity and low power of detection of many small effect variants. The complexity of inheritance of resistance hinders the use marker-assisted selection for ear rot resistance. RESULTS: We conducted a genome-wide association study (GWAS) for Fusarium ear rot resistance in a panel of 1687 diverse inbred lines from the USDA maize gene bank with 200,978 SNPs while controlling for background genetic relationships with a mixed model and identified seven single nucleotide polymorphisms (SNPs) in six genes associated with disease resistance in either the complete inbred panel (1687 lines with highly unbalanced phenotype data) or in a filtered inbred panel (734 lines with balanced phenotype data). Different sets of SNPs were detected as associated in the two different data sets. The alleles conferring greater disease resistance at all seven SNPs were rare overall (below 16%) and always higher in allele frequency in tropical maize than in temperate dent maize. Resampling analysis of the complete data set identified one robust SNP association detected as significant at a stringent p-value in 94% of data sets, each representing a random sample of 80% of the lines. All associated SNPs were in exons, but none of the genes had predicted functions with an obvious relationship to resistance to fungal infection. CONCLUSIONS: GWAS in a very diverse maize collection identified seven SNP variants each associated with between 1% and 3% of trait variation. Because of their small effects, the value of selection on these SNPs for improving resistance to Fusarium ear rot is limited. Selection to combine these resistance alleles combined with genomic selection to improve the polygenic background resistance might be fruitful. The genes associated with resistance provide candidate gene targets for further study of the biological pathways involved in this complex disease resistance.

Mapping of QTL for resistance to the Mediterranean corn borer attack using the intermated B73 x Mo17 (IBM) population of maize.

The Mediterranean corn borer or pink stem borer (MCB, Sesamia nonagrioides Lefebvre) causes important yield losses as a consequence of stalk tunneling and direct kernel damage. B73 and Mo17 are the source of the most commercial valuable maize inbred lines in temperate zones, while the intermated B73 x Mo17 (IBM) population is an invaluable source for QTL identification. However, no or few experiments have been carried out to detect QTL for corn borer resistance in the B73 x Mo17 population. The objective of this work was to locate QTL for resistance to stem tunneling and kernel damage by MCB in the IBM population. We detected a QTL for kernel damage at bin 8.05, although the effect was small and two QTL for stalk tunneling at bins 1.06 and 9.04 in which the additive effects were 4 cm, approximately. The two QTL detected for MCB resistance were close to other QTL consistently found for European corn borer (ECB, Ostrinia nubilalis Hübner) resistance, indicating mechanisms of resistance common to both pests or gene clusters controlling resistance to different plagues. The precise mapping achieved with the IBM population will facilitate the QTL pyramiding and the positional cloning of the detected QTL.

High-resolution genetic mapping of maize pan-genome sequence anchors.

In addition to single-nucleotide polymorphisms, structural variation is abundant in many plant genomes. The structural variation across a species can be represented by a 'pan-genome', which is essential to fully understand the genetic control of phenotypes. However, the pan-genome's complexity hinders its accurate assembly via sequence alignment. Here we demonstrate an approach to facilitate pan-genome construction in maize. By performing 18 trillion association tests we map 26 million tags generated by reduced representation sequencing of 14,129 maize inbred lines. Using machine-learning models we select 4.4 million accurately mapped tags as sequence anchors, 1.1 million of which are presence/absence variations. Structural variations exhibit enriched association with phenotypic traits, indicating that it is a significant source of adaptive variation in maize. The ability to efficiently map ultrahigh-density pan-genome sequence anchors enables fine characterization of structural variation and will advance both genetic research and breeding in many crops.

The genetic architecture of maize height.

Height is one of the most heritable and easily measured traits in maize (Zea mays L.). Given a pedigree or estimates of the genomic identity-by-state among related plants, height is also accurately predictable. But, mapping alleles explaining natural variation in maize height remains a formidable challenge. To address this challenge, we measured the plant height, ear height, flowering time, and node counts of plants grown in >64,500 plots across 13 environments. These plots contained >7300 inbreds representing most publically available maize inbreds in the United States and families of the maize Nested Association Mapping (NAM) panel. Joint-linkage mapping of quantitative trait loci (QTL), fine mapping in near isogenic lines (NILs), genome-wide association studies (GWAS), and genomic best linear unbiased prediction (GBLUP) were performed. The heritability of maize height was estimated to be >90%. Mapping NAM family-nested QTL revealed the largest explained 2.1 ± 0.9% of height variation. The effects of two tropical alleles at this QTL were independently validated by fine mapping in NIL families. Several significant associations found by GWAS colocalized with established height loci, including brassinosteroid-deficient dwarf1, dwarf plant1, and semi-dwarf2. GBLUP explained >80% of height variation in the panels and outperformed bootstrap aggregation of family-nested QTL models in evaluations of prediction accuracy. These results revealed maize height was under strong genetic control and had a highly polygenic genetic architecture. They also showed that multiple models of genetic architecture differing in polygenicity and effect sizes can plausibly explain a population's variation in maize height, but they may vary in predictive efficacy.

Comprehensive genotyping of the USA national maize inbred seed bank.

BACKGROUND: Genotyping by sequencing, a new low-cost, high-throughput sequencing technology was used to genotype 2,815 maize inbred accessions, preserved mostly at the National Plant Germplasm System in the USA. The collection includes inbred lines from breeding programs all over the world. RESULTS: The method produced 681,257 single-nucleotide polymorphism (SNP) markers distributed across the entire genome, with the ability to detect rare alleles at high confidence levels. More than half of the SNPs in the collection are rare. Although most rare alleles have been incorporated into public temperate breeding programs, only a modest amount of the available diversity is present in the commercial germplasm. Analysis of genetic distances shows population stratification, including a small number of large clusters centered on key lines. Nevertheless, an average fixation index of 0.06 indicates moderate differentiation between the three major maize subpopulations. Linkage disequilibrium (LD) decays very rapidly, but the extent of LD is highly dependent on the particular group of germplasm and region of the genome. The utility of these data for performing genome-wide association studies was tested with two simply inherited traits and one complex trait. We identified trait associations at SNPs very close to known candidate genes for kernel color, sweet corn, and flowering time; however, results suggest that more SNPs are needed to better explore the genetic architecture of complex traits. CONCLUSIONS: The genotypic information described here allows this publicly available panel to be exploited by researchers facing the challenges of sustainable agriculture through better knowledge of the nature of genetic diversity.