Palmer amaranth (Amaranthus palmeri) is a summer annual native to parts of the Southwestern United States and northern Mexico. Yet, over the past two decades, it has become one of the most extensive agricultural threats in the Southeast, parts of the Midwest, and more recently in Central California. Adaptive traits, such as herbicide resistance, have aided it in becoming an extremely opportunistic plant in various agronomic settings. Despite its recent emergence in Central California, no genome-wide evaluations have been done on its northern range expansion into agricultural areas in California's Central Valley. As part of a larger population genetic investigation, we are using genotyping-by-sequencing to elucidate the origin of A. palmeri populations found in the Central Valley and attempting to identify any genes linked to adaptation in recent emerging California populations. Neutral markers and adaptive herbicide resistance genes are being used to explore genetic clustering of Central California populations relative to native and nonnative populations in other parts of the U.S. Results from raw sequenced data from sequencing carried out at the DNA Technologies and Expression Analysis Core at the UC Davis Genome Center revealed roughly 840,983,496 total sequences and good quality scores for a total of 167 samples in 17 populations from Central California, Southeastern and Midwestern U.S. introduced ranges. Data were mapped to a draft genome with the Burrows-Wheeler Aligner (BWA). Ongoing genetic analysis of this data and previously collected data from the Southwestern native range, using clustering algorithms (ADMIXTURE, STRUCTURE, and adegenet’s implementation of discriminant analysis of principal components, DAPC), may suggest possible invasion scenarios of California populations. Support for different invasion scenarios will be further evaluated via analysis of single nucleotide polymorphisms (SNPs) using approximate Bayesian computation (ABC). In addition, selection analysis of SNP data from California populations will be used to screen for overlap in outliers possibly linked to adaptation to the climatic conditions in the Central Valley. This study has the potential to facilitate future research into how weeds spread, suggest alternative strategies for more sustainable weed management practices, and help create models for evolutionary adaptation applicable to invasions and other agronomic weedy plants.