RootBot: High-throughput root stress phenotyping robot.

Premise: Higher temperatures across the globe are causing an increase in the frequency and severity of droughts. In agricultural crops, this results in reduced yields, financial losses, and increased food costs at the supermarket. Root growth maintenance in drying soils plays a major role in a plant's ability to survive and perform under drought, but phenotyping root growth is extremely difficult due to roots being under the soil.

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

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

Single-plant GWAS coupled with bulk segregant analysis allows rapid identification and corroboration of plant-height candidate SNPs.

Background: Genome wide association studies (GWAS) are a powerful tool for identifying quantitative trait loci (QTL) and causal single nucleotide polymorphisms (SNPs)/genes associated with various important traits in crop species. Typically, GWAS in crops are performed using a panel of inbred lines, where multiple replicates of the same inbred are measured and the average phenotype is taken as the response variable. Here we describe and evaluate single plant GWAS (sp-GWAS) for performing a GWAS on individual plants, which does not require an association panel of inbreds.

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.

Improved maize reference genome with single-molecule technologies.

Complete and accurate reference genomes and annotations provide fundamental tools for characterization of genetic and functional variation. These resources facilitate the determination of biological processes and support translation of research findings into improved and sustainable agricultural technologies. Many reference genomes for crop plants have been generated over the past decade, but these genomes are often fragmented and missing complex repeat regions.

Expanding Maize Genetic Resources with Predomestication Alleles: Maize-Teosinte Introgression Populations.

Teosinte ( subsp. H. H.

The Genomic Impacts of Drift and Selection for Hybrid Performance in Maize.

Although maize is naturally an outcrossing organism, modern breeding utilizes highly inbred lines in controlled crosses to produce hybrids. The U.S.

MADS-box genes of maize: frequent targets of selection during domestication.

MADS-box genes encode transcription factors that are key regulators of plant inflorescence and flower development. We examined DNA sequence variation in 32 maize MADS-box genes and 32 randomly chosen maize loci and investigated their involvement in maize domestication and improvement. Using neutrality tests and a test based on coalescent simulation of a bottleneck model, we identified eight MADS-box genes as putative targets of the artificial selection associated with domestication.

A genome-wide characterization of microRNA genes in maize.

MicroRNAs (miRNAs) are small, non-coding RNAs that play essential roles in plant growth, development, and stress response. We conducted a genome-wide survey of maize miRNA genes, characterizing their structure, expression, and evolution. Computational approaches based on homology and secondary structure modeling identified 150 high-confidence genes within 26 miRNA families.

DNAAlignEditor: DNA alignment editor tool.

Background: With advances in DNA re-sequencing methods and Next-Generation parallel sequencing approaches, there has been a large increase in genomic efforts to define and analyze the sequence variability present among individuals within a species. For very polymorphic species such as maize, this has lead to a need for intuitive, user-friendly software that aids the biologist, often with naïve programming capability, in tracking, editing, displaying, and exporting multiple individual sequence alignments. To fill this need we have developed a novel DNA alignment editor.