Common bean (Phaseolus vulgaris L.) is the most important grain legume for human consumption and has a role in sustainable agriculture owing to its ability to fix atmospheric nitrogen. We assembled 473 Mb of the 587-Mb genome and genetically anchored 98% of this sequence in 11 chromosome-scale pseudomolecules. We compared the genome for the common bean against the soybean genome to find changes in soybean resulting from polyploidy. Using resequencing of 60 wild individuals and 100 landraces from the genetically differentiated Mesoamerican and Andean gene pools, we confirmed 2 independent domestications from genetic pools that diverged before human colonization. Less than 10% of the 74 Mb of sequence putatively involved in domestication was shared by the two domestication events. We identified a set of genes linked with increased leaf and seed size and combined these results with quantitative trait locus data from Mesoamerican cultivars. Genes affected by domestication may be useful for genomics-enabled crop improvement.

Long-term climate change and periodic environmental extremes threaten food and fuel security1 and global crop productivity2–4. Although molecular and adaptive breeding strategies can buffer the effects of climatic stress and improve crop resilience5, these approaches require sufficient knowledge of the genes that underlie productivity and adaptation6—knowledge that has been limited to a small number of well-studied model systems. Here we present the assembly and annotation of the large and complex genome of the polyploid bioenergy crop switchgrass (Panicum virgatum). Analysis of biomass and survival among 732 resequenced genotypes, which were grown across 10 common gardens that span 1,800 km of latitude, jointly revealed extensive genomic evidence of climate adaptation. Climate–gene–biomass associations were abundant but varied considerably among deeply diverged gene pools. Furthermore, we found that gene flow accelerated climate adaptation during the postglacial colonization of northern habitats through introgression of alleles from a pre-adapted northern gene pool. The polyploid nature of switchgrass also enhanced adaptive potential through the fractionation of gene function, as there was an increased level of heritable genetic diversity on the nondominant subgenome. In addition to investigating patterns of climate adaptation, the genome resources and gene–trait associations developed here provide breeders with the necessary tools to increase switchgrass yield for the sustainable production of bioenergy.

Common bean (Phaseolus vulgaris L.) breeding programs aim to improve both agronomic and seed characteristics traits. However, the genetic architecture of the many traits that affect common bean production are not completely understood. Genome-wide association studies (GWAS) provide an experimental approach to identify genomic regions where important candidate genes are located. A panel of 280 modern bean genotypes from race Mesoamerica, referred to as the Middle American Diversity Panel (MDP), were grown in four US locations, and a GWAS using >150,000 single-nucleotide polymorphisms (SNPs) (minor allele frequency [MAF] ³ 5%) was conducted for six agronomic traits. The degree of inter-and intrachromosomal linkage disequilibrium (LD) was estimated after accounting for population structure and relatedness. The LD varied between chromosomes for the entire MDP and among race Mesoamerica and DurangoJalisco genotypes within the panel. The LD patterns reflected the breeding history of common bean. Genome-wide association studies led to the discovery of new and known genomic regions affecting the agronomic traits at the entire population, race, and location levels. We observed strong colocalized signals in a narrow genomic interval for three interrelated traits: growth habit, lodging, and canopy height. Overall, this study detected ~30 candidate genes based on a priori and candidate gene search strategies centered on the 100-kb region surrounding a significant SNP. These results provide a framework from which further research can begin to understand the actual genes controlling important agronomic production traits in common bean.

Environmental stress is a major driver of ecological community dynamics and agricultural productivity. This is especially true for soil water availability, because drought is the greatest abiotic inhibitor of worldwide crop yields. Here, we test the genetic basis of drought responses in the genetic model for C4 perennial grasses, Panicum hallii, through population genomics, field-scale gene-expression (eQTL) analysis, and comparison of two complete genomes. While gene expression networks are dominated by local cis-regulatory elements, we observe three genomic hotspots of unlinked trans-regulatory loci. These regulatory hubs are four times more drought responsive than the genome-wide average. Additionally, cis- and trans-regulatory networks are more likely to have opposing effects than expected under neutral evolution, supporting a strong influence of compensatory evolution and stabilizing selection. These results implicate trans-regulatory evolution as a driver of drought responses and demonstrate the potential for crop improvement in drought-prone regions through modification of gene regulatory networks.

Accelerated wheat development and deployment of high-yielding, climate resilient, and disease resistant cultivars can contribute to enhanced food security and sustainable intensification. To facilitate gene discovery, we assembled an association mapping panel of 528 spring wheat landraces of diverse geographic origin for a genome-wide association study (GWAS). All accessions were genotyped using an Illumina Infinium 9K wheat single nucleotide polymorphism (SNP) chip and 4781 polymorphic SNPs were used for analysis. To identify loci underlying resistance to the major leaf spot diseases and to better understand the genomic patterns, we quantified population structure, allelic diversity, and linkage disequilibrium. Our results showed 32 loci were significantly associated with resistance to the major leaf spot diseases. Further analysis identified QTL effective against major leaf spot diseases of wheat which appeared to be novel and others that were previously identified by association analysis using Diversity Arrays Technology (DArT) and bi-parental mapping. In addition, several identified SNPs co-localized with genes that have been implicated in plant disease resistance. Future work could aim to select the putative novel loci and pyramid them in locally adapted wheat cultivars to develop broad-spectrum resistance to multiple leaf spot diseases of wheat via marker-assisted selection (MAS).