Threats to crop production due to climate change are one of the greatest challenges facing plant breeders today. While considerable adaptive variation exists in traditional landraces, natural populations of crop wild relatives, and ex situ germplasm collections, separating adaptive alleles from linked deleterious variants that impact agronomic traits is challenging and has limited the utility of these diverse germplasm resources. Modern genome editing techniques such as CRISPR offer a potential solution by targeting specific alleles for transfer to new backgrounds, but such methods require a higher degree of precision than traditional mapping approaches can achieve. Here we present a high-resolution genome-wide association analysis to identify loci exhibiting adaptive patterns in a large panel of more than 4500 traditional maize landraces representing the breadth of genetic diversity of maize in Mexico. We evaluate associations between genotype and plant performance in 13 common gardens across a range of environments, identifying hundreds of candidate genes underlying genotype by environment interaction. We further identify genetic associations with environment across Mexico and show that such loci are associated with variation in yield and flowering time in our field trials and predict performance in independent drought trials. Our results indicate that the variation necessary to adapt crops to changing climate exists in traditional landraces that have been subject to ongoing environmental adaptation and can be identified by both phenotypic and environmental association.

Background: Cassava, an allotetraploid known for its remarkable tolerance to abiotic stresses is an important source of energy for humans and animals and a raw material for many industrial processes. A full-length cDNA library of cassava plants under normal, heat, drought, aluminum and post harvest physiological deterioration conditions was built; 19968 clones were sequencecharacterized using expressed sequence tags (ESTs).

The study of microRNAs (miRNAs) in plants has gained significant attention in recent years due to their regulatory role during development and in response to biotic and abiotic stresses. Although cassava (Manihot esculenta Crantz) is tolerant to drought and other adverse conditions, most cassava miRNAs have been predicted using bioinformatics alone or through sequencing of plants challenged by biotic stress. Here, we use high-throughput sequencing and different bioinformatics methods to identify potential cassava miRNAs expressed in different tissues subject to heat and drought conditions. We identified 60 miRNAs conserved in other plant species and 821 potential cassava-specific miRNAs. We also predicted 134 and 1002 potential target genes for these two sets of sequences. Using real time PCR, we verified the condition-specific expression of 5 cassava small RNAs relative to a non-stress control. We also found, using publicly available expression data, a significantly lower expression of the predicted target genes of conserved and nonconserved miRNAs under drought stress compared to other cassava genes. Gene Ontology enrichment analysis along with condition specific expression of predicted miRNA targets, allowed us to identify several interesting miRNAs which may play a role in stress-induced posttranscriptional regulation in cassava and other plants.

After domestication from lowland teosinte parviglumis (Zea mays ssp. parviglumis) in the warm Mexican southwest, maize (Zea mays ssp. mays) colonized the highlands of Mexico and South America. In the highlands, maize was exposed to lower temperatures that imposed strong selection on flowering time. Phospholipids are important metabolites in plant responses to low-temperature, low phosphorus availability and have also been suggested to influence flowering time. Here, we combined linkage mapping analysis with genome scans to identify High PhosphatidylCholine 1 (HPC1), a gene which encodes a phospholipase A1 enzyme, as a major driver of phospholipid variation in highland maize. Common garden experiments demonstrated strong genotype-by-environment interactions associated with variation at HPC1, with the highland HPC1 allele leading to higher fitness in highlands, possibly by hastening flowering. The HPC1 variant we identified in highland maize results in impaired function of the encoded protein due to a polymorphism in a highly conserved sequence. A meta-analysis indicated a strong association between the identity of the amino acid at this position and optimal growth in prokaryotes. Mutagenesis of HPC1 via genome editing validated its role in regulating phospholipid metabolism. Finally, we show that the highland HPC1 allele entered cultivated maize by introgression from the wild highland teosinte Zea mays ssp. mexicana and has been maintained in maize breeding lines from Northern US, Canada and Europe. Thus, HPC1 introgressed from teosinte mexicana underlies a large metabolic QTL that modulates phosphatidylcholine levels and has an adaptive effect at least in part via induction of early flowering time.