Carrot is a globally important crop, yet efficient and accurate methods for quantifying its most important agronomic traits are lacking. To address this problem, we developed an automated image analysis platform that extracts components of size and shape for carrot shoots and roots, which are necessary to advance carrot breeding and genetics. This method reliably measured variation in shoot size and shape, petiole number, petiole length, and petiole width as evidenced by high correlations with hundreds of manual measurements. Similarly, root length and biomass were accurately measured from the images. This platform also quantified shoot and root shapes in terms of principal components, which do not have traditional, manually measurable equivalents. We applied the pipeline in a study of a six-parent diallel population and an F2 mapping population consisting of 316 individuals. We found high levels of repeatability within a growing environment, with low to moderate repeatability across environments. We also observed co-localization of quantitative trait loci for shoot and root characteristics on chromosomes 1, 2, and 7, suggesting these traits are controlled by genetic linkage and/or pleiotropy. By increasing the number of individuals and phenotypes that can be reliably quantified, the development of a rapid, automated image analysis pipeline to measure carrot shoot and root morphology will expand the scope and scale of breeding and genetic studies.

Understanding the evolutionary history of crops, including identifying wild relatives, helps to provide insight for conservation and crop breeding efforts. Cultivated Brassica oleracea has intrigued researchers for centuries due to its wide diversity in forms, which include cabbage, broccoli, cauliflower, kale, kohlrabi, and Brussels sprouts. Yet, the evolutionary history of this species remains understudied. With such different vegetables produced from a single species, B. oleracea is a model organism for understanding the power of artificial selection. Persistent challenges in the study of B. oleracea include conflicting hypotheses regarding domestication and the identity of the closest living wild relative. Using newly generated RNA-seq data for a diversity panel of 224 accessions, which represents 14 different B. oleracea crop types and nine potential wild progenitor species, we integrate phylogenetic and population genetic techniques with ecological niche modeling, archaeological, and literary evidence to examine relationships among cultivars and wild relatives to clarify the origin of this horticulturally important species. Our analyses point to the Aegean endemic B. cretica as the closest living relative of cultivated B. oleracea, supporting an origin of cultivation in the Eastern Mediterranean region. Additionally, we identify several feral lineages, suggesting that cultivated plants of this species can revert to a wild-like state with relative ease. By expanding our understanding of the evolutionary history in B. oleracea, these results contribute to a growing body of knowledge on crop domestication that will facilitate continued breeding efforts including adaptation to changing environmental conditions.

Crop establishment in carrot (Daucus carota L.) is limited by slow seedling growth and delayed canopy closure, resulting in high management costs for weed control. Varieties with improved growth habit (i.e., larger canopy and increased shoot biomass) may help mitigate weed control, but the underlying genetics of these traits in carrot is unknown. This project used a diallel mating design coupled with recent Bayesian analytical methods to determine the genetic basis of carrot shoot growth. Six diverse carrot inbred lines with variable shoot size were crossed in WI in 2014. F1 hybrids, reciprocal crosses, and parental selfs were grown in a randomized complete block design with two blocks in WI (2015) and CA (2015, 2016). Measurements included canopy height, canopy width, shoot biomass, and root biomass. General and specific combining abilities were estimated using Griffing’s Model I, which is a common analysis for plant breeding experiments. In parallel, additive, inbred, cross-specific, and maternal effects were estimated from a Bayesian mixed model, which is robust to dealing with data imbalance and outliers. Both additive and nonadditive effects significantly influenced shoot traits, with nonadditive effects playing a larger role early in the growing season, when weed control is most critical. Results suggest the presence of heritable variation and thus potential for improvement of these phenotypes in carrot. In addition, results present evidence of heterosis for root biomass, which is a major component of carrot yield.

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Ph: (608) 262-1248 25 philipp.simon@ars.usda.gov 26 27 Article Summary 28Breeding for improved competitive ability is a priority in carrot, which suffers yield losses under 29 weed pressure. However, improvement and in-depth genetic studies for these traits relies on 30 knowledge of the underlying genetic architecture. This study estimated heritable and non-31 heritable components of carrot shoot growth from a diallel mating design using a Bayesian 32 mixed model. Results directly contribute to improvement efforts by providing estimates of 33 combining ability, identifying a useful tester line, and characterizing the genetic and non-genetic 34 influences on traits for improved competitive ability in carrot. 35peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission.The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/115519 doi: bioRxiv preprint first posted online Mar. 9, 2017; 3 ABSTRACT 36Crop establishment in carrot (Daucus carota L.) is limited by slow seedling growth and 37 delayed canopy closure, resulting in high management costs for weed control. Varieties with 38 improved growth habit (i.e. larger canopy and increased shoot biomass) may help mitigate weed 39 control, but the underlying genetics of these traits in carrot is unknown. This project used a 40 diallel mating design coupled with recent Bayesian analytical methods to determine the genetic 41 basis of carrot shoot growth. Six diverse carrot inbred lines with variable shoot size were crossed 42 in WI in 2014. F1 hybrids, reciprocal crosses, and parental selfs were grown in a randomized 43 complete block design (RCBD) with two blocks in CA (2015, 2016) and in WI (2015). 44Measurements included canopy height, canopy width, shoot biomass, and root biomass. General 45 and specific combining abilities were estimated using Griffing's Model I. In parallel, additive, 46 inbreeding, epistatic, and maternal effects were estimated from a Bayesian linear mixed model, 47 which is more robust to dealing with missing data, outliers, and theoretical constraints than 48 traditional biometric methods. Both additive and non-additive effects significantly influenced 49 shoot traits, with non-additive effects playing a larger role early in the growing season, when 50 weed control is most critical. Results suggest that early season canopy growth and root size 51 express hybrid vigor and can be improved through reciprocal recurrent selection. 52peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission.The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/115519 doi: bioRxiv preprint first posted online Mar. 9, 2017; 4 Author Contribution Statement 53 SDT and PWS conceived and designed this study. SDT performed the crosses, collected 54 phenotypic data, ran analyses, and wrote the manuscript. PLM and WV contributed to 55 descriptions of BayesDiallel and assisted with corresponding analyses and interpretations. BSY 56 helped perform i...