We generated a high-quality reference genome sequence for foxtail millet (Setaria italica). The ∼ 400-Mb assembly covers ∼ 80% of the genome and >95% of the gene space. The assembly was anchored to a 992-locus genetic map and was annotated by comparison with >1.3 million expressed sequence tag reads. We produced more than 580 million RNA-Seq reads to facilitate expression analyses. We also sequenced Setaria viridis, the ancestral wild relative of S. italica, and identified regions of differential single-nucleotide polymorphism density, distribution of transposable elements, small RNA content, chromosomal rearrangement and segregation distortion. The genus Setaria includes natural and cultivated species that demonstrate a wide capacity for adaptation. The genetic basis of this adaptation was investigated by comparing five sequenced grass genomes. We also used the diploid Setaria genome to evaluate the ongoing genome assembly of a related polyploid, switchgrass (Panicum virgatum).

Peanut (Arachis hypogaea; 2n = 4x = 40) is a nutritious food and a good source of vitamins, minerals, and healthy fats. Expansion of genetic and genomic resources for genetic enhancement of cultivated peanut has gained momentum from the sequenced genomes of the diploid ancestors of cultivated peanut. To facilitate high-throughput genotyping of Arachis species, 20 genotypes were re-sequenced and genome-wide single nucleotide polymorphisms (SNPs) were selected to develop a large-scale SNP genotyping array. For flexibility in genotyping applications, SNPs polymorphic between tetraploid and diploid species were included for use in cultivated and interspecific populations. A set of 384 accessions was used to test the array resulting in 54 564 markers that produced high-quality polymorphic clusters between diploid species, 47 116 polymorphic markers between cultivated and interspecific hybrids, and 15 897 polymorphic markers within A. hypogaea germplasm. An additional 1193 markers were identified that illuminated genomic regions exhibiting tetrasomic recombination. Furthermore, a set of elite cultivars that make up the pedigree of US runner germplasm were genotyped and used to identify genomic regions that have undergone positive selection. These observations provide key insights on the inclusion of new genetic diversity in cultivated peanut and will inform the development of high-resolution mapping populations. Due to its efficiency, scope, and flexibility, the newly developed SNP array will be very useful for further genetic and breeding applications in Arachis.

In January 2014, an international meeting sponsored by the International Life Sciences Institute/Health and Environmental Sciences Institute and the Canadian Food Inspection Agency titled “Genetic Basis of Unintended Effects in Modified Plants” was held in Ottawa, Canada, bringing together over 75 scientists from academia, government, and the agro-biotech industry. The objectives of the meeting were to explore current knowledge and identify areas requiring further study on unintended effects in plants and to discuss how this information can inform and improve genetically modified (GM) crop risk assessments. The meeting featured presentations on the molecular basis of plant genome variability in general, unintended changes at the molecular and phenotypic levels, and the development and use of hypothesis-driven evaluations of unintended effects in assessing conventional and GM crops. The development and role of emerging “omics” technologies in the assessment of unintended effects was also discussed. Several themes recurred in a number of talks; for example, a common observation was that no system for genetic modification, including conventional methods of plant breeding, is without unintended effects. Another common observation was that “unintended” does not necessarily mean “harmful”. This paper summarizes key points from the information presented at the meeting to provide readers with current viewpoints on these topics.

Genomic selection (GS) has become viable for selection of quantitative traits for which marker-assisted selection has often proven less effective. The potential of GS for soybean was characterized using 483 elite breeding lines, genotyped with BARCSoySNP6K iSelect BeadChips. Cross validation was performed using RR-BLUP and predictive abilities (r_MP) of 0.81, 0.71, and 0.26 for protein, oil, and yield, were achieved at the largest tested training set size. Minimal differences were observed when comparing different marker densities and there appeared to be inflation in r_MP due to population structure. For comparison purposes, two additional methods to predict breeding values for lines of four bi-parental populations within the GS dataset were tested. The first method predicted within each bi-parental population (WP method) and utilized a training set of full-sibs of the validation set. The second method utilized a training set of all remaining breeding lines except for full-sibs of the validation set to predict across populations (AP method). The AP method is more practical as the WP method would likely delay the breeding cycle and leverage smaller training sets. Averaging across populations for protein and oil content, r_MP for the AP method (0.55, 0.30) approached r_MP for the WP method (0.60, 0.52). Though comparable, r_MP for yield was low for both AP and WP methods (0.12, 0.13). Based on increases in r_MP as training sets increased and the effectiveness of WP versus AP method, the AP method could potentially improve with larger training sets and increased relatedness between training and validation sets.

Upstream open reading frames (uORFs) are protein coding elements in the 5′ leader of messenger RNAs. uORFs generally inhibit translation of the main ORF because ribosomes that perform translation elongation suffer either permanent or conditional loss of reinitiation competence. After conditional loss, reinitiation competence may be regained by, at the minimum, reacquisition of a fresh methionyl-tRNA. The conserved h subunit of Arabidopsis eukaryotic initiation factor 3 (eIF3) mitigates the inhibitory effects of certain uORFs. Here, we define more precisely how this occurs, by combining gene expression data from mutated 5′ leaders of Arabidopsis AtbZip11 (At4g34590) and yeast GCN4 with a computational model of translation initiation in wild-type and eif3h mutant plants. Of the four phylogenetically conserved uORFs in AtbZip11, three are inhibitory to translation, while one is anti-inhibitory. The mutation in eIF3h has no major effect on uORF start codon recognition. Instead, eIF3h supports efficient reinitiation after uORF translation. Modeling suggested that the permanent loss of reinitiation competence during uORF translation occurs at a faster rate in the mutant than in the wild type. Thus, eIF3h ensures that a fraction of uORF-translating ribosomes retain their competence to resume scanning. Experiments using the yeast GCN4 leader provided no evidence that eIF3h fosters tRNA reaquisition. Together, these results attribute a specific molecular function in translation initiation to an individual eIF3 subunit in a multicellular eukaryote.