Correction: Incomplete dominance of deleterious alleles contributes substantially to trait variation and heterosis in maize.

[This corrects the article DOI: 10.1371/journal.pgen.1007019.].

Repetitive DNA content in the maize genome is uncoupled from population stratification at SNP loci.

BACKGROUND: Repetitive DNA is a major component of plant genomes and is thought to be a driver of evolutionary novelty. Describing variation in repeat content among individuals and between populations is key to elucidating the evolutionary significance of repetitive DNA. However, the cost of producing references genomes has limited large-scale intraspecific comparisons to a handful of model organisms where multiple reference genomes are available. RESULTS: We examine repeat content variation in the genomes of 94 elite inbred maize lines using graph-based repeat clustering, a reference-free and rapid assay of repeat content. We examine population structure using genome-wide repeat profiles, and demonstrate the stiff-stalk and non-stiff-stalk heterotic populations are homogenous with regard to global repeat content. In contrast, and similar to previously reported results, the same individuals show clear differentiation, and aggregate into two populations when examining population structure using genome-wide SNPs. Additionally, we develop a novel kmer based technique to examine the chromosomal distribution of repeat clusters in silico and show a cluster dependent association with gene density. CONCLUSION: Our results indicate global repeat content variation in the heterotic populations of maize has not diverged, and is uncoupled from population stratification at SNP loci. We show that repeat families exhibit divergent patterns with regard to chromosomal distribution, some repeat clusters accumulate in regions of high gene density, whereas others aggregate in regions of low gene density.

Incomplete dominance of deleterious alleles contributes substantially to trait variation and heterosis in maize.

Deleterious alleles have long been proposed to play an important role in patterning phenotypic variation and are central to commonly held ideas explaining the hybrid vigor observed in the offspring of a cross between two inbred parents. We test these ideas using evolutionary measures of sequence conservation to ask whether incorporating information about putatively deleterious alleles can inform genomic selection (GS) models and improve phenotypic prediction. We measured a number of agronomic traits in both the inbred parents and hybrids of an elite maize partial diallel population and re-sequenced the parents of the population. Inbred elite maize lines vary for more than 350,000 putatively deleterious sites, but show a lower burden of such sites than a comparable set of traditional landraces. Our modeling reveals widespread evidence for incomplete dominance at these loci, and supports theoretical models that more damaging variants are usually more recessive. We identify haplotype blocks using an identity-by-decent (IBD) analysis and perform genomic prediction analyses in which we weigh blocks on the basis of complementation for segregating putatively deleterious variants. Cross-validation results show that incorporating sequence conservation in genomic selection improves prediction accuracy for grain yield and other fitness-related traits as well as heterosis for those traits. Our results provide empirical support for an important role for incomplete dominance of deleterious alleles in explaining heterosis and demonstrate the utility of incorporating functional annotation in phenotypic prediction and plant breeding.

Genome-wide analysis of alternative splicing in Zea mays: landscape and genetic regulation.

Alternative splicing enhances transcriptome diversity in all eukaryotes and plays a role in plant tissue identity and stress adaptation. To catalog new maize (Zea mays) transcripts and identify genomic loci that regulate alternative splicing, we analyzed over 90 RNA-seq libraries from maize inbred lines B73 and Mo17, as well as Syn10 doubled haploid lines (progenies from B73 × Mo17). Transcript discovery was augmented with publicly available data from 14 maize tissues, expanding the maize transcriptome by more than 30,000 and increasing the percentage of intron-containing genes that undergo alternative splicing to 40%. These newly identified transcripts greatly increase the diversity of the maize proteome, sometimes coding for entirely different proteins compared with their most similar annotated isoform. In addition to increasing proteome diversity, many genes encoding novel transcripts gained an additional layer of regulation by microRNAs, often in a tissue-specific manner. We also demonstrate that the majority of genotype-specific alternative splicing can be genetically mapped, with cis-acting quantitative trait loci (QTLs) predominating. A large number of trans-acting QTLs were also apparent, with nearly half located in regions not shown to contain genes associated with splicing. Taken together, these results highlight the currently underappreciated role that alternative splicing plays in tissue identity and genotypic variation in maize.

A giant NLR gene confers broad-spectrum resistance to Phytophthora sojae in soybean.

Phytophthora root and stem rot caused by P. sojae is a destructive soybean soil-borne disease found worldwide. Discovery of genes conferring broad-spectrum resistance to the pathogen is a need to prevent the outbreak of the disease. Here, we show that soybean Rps11 is a 27.7-kb nucleotide-binding site-leucine-rich repeat (NBS-LRR or NLR) gene conferring broad-spectrum resistance to the pathogen. Rps11 is located in a genomic region harboring a cluster of large NLR genes of a single origin in soybean, and is derived from rounds of unequal recombination. Such events result in promoter fusion and LRR expansion that may contribute to the broad resistance spectrum. The NLR gene cluster exhibits drastic structural diversification among phylogenetically representative varieties, including gene copy number variation ranging from five to 23 copies, and absence of allelic copies of Rps11 in any of the non-Rps11-donor varieties examined, exemplifying innovative evolution of NLR genes and NLR gene clusters.

Mixed model approaches for the identification of QTLs within a maize hybrid breeding program.

Two outlines for mixed model based approaches to quantitative trait locus (QTL) mapping in existing maize hybrid selection programs are presented: a restricted maximum likelihood (REML) and a Bayesian Markov Chain Monte Carlo (MCMC) approach. The methods use the in-silico-mapping procedure developed by Parisseaux and Bernardo (2004) as a starting point. The original single-point approach is extended to a multi-point approach that facilitates interval mapping procedures. For computational and conceptual reasons, we partition the full set of relationships from founders to parents of hybrids into two types of relations by defining so-called intermediate founders. QTL effects are defined in terms of those intermediate founders. Marker based identity by descent relationships between intermediate founders define structuring matrices for the QTL effects that change along the genome. The dimension of the vector of QTL effects is reduced by the fact that there are fewer intermediate founders than parents. Furthermore, additional reduction in the number of QTL effects follows from the identification of founder groups by various algorithms. As a result, we obtain a powerful mixed model based statistical framework to identify QTLs in genetic backgrounds relevant to the elite germplasm of a commercial breeding program. The identification of such QTLs will provide the foundation for effective marker assisted and genome wide selection strategies. Analyses of an example data set show that QTLs are primarily identified in different heterotic groups and point to complementation of additive QTL effects as an important factor in hybrid performance.