Despite intense investigation for over 25 years, the in vivo structure of plant mitochondrial genomes remains uncertain. Mapping studies and genome sequencing generally produce large circular chromosomes, whereas electrophoretic and microscopic studies typically reveal linear and multibranched molecules. To more fully assess the structure of plant mitochondrial genomes, the complete sequence of the monkeyflower (Mimulus guttatus DC. line IM62) mitochondrial DNA was constructed from a large (35 kb) paired-end shotgun sequencing library to a high depth of coverage (∼30×). The complete genome maps as a 525,671 bp circular molecule and exhibits a fairly conventional set of features including 62 genes (encoding 35 proteins, 24 transfer RNAs, and 3 ribosomal RNAs), 22 introns, 3 large repeats (2.7, 9.6, and 29 kb), and 96 small repeats (40–293 bp). Most paired-end reads (71%) mapped to the consensus sequence at the expected distance and orientation across the entire genome, validating the accuracy of assembly. Another 10% of reads provided clear evidence of alternative genomic conformations due to apparent rearrangements across large repeats. Quantitative assessment of these repeat-spanning read pairs revealed that all large repeat arrangements are present at appreciable frequencies in vivo, although not always in equimolar amounts. The observed stoichiometric differences for some arrangements are inconsistent with a predominant master circular structure for the mitochondrial genome of M. guttatus IM62. Finally, because IM62 contains a cryptic cytoplasmic male sterility (CMS) system, an in silico search for potential CMS genes was undertaken. The three chimeric open reading frames (ORFs) identified in this study, in addition to the previously identified ORFs upstream of the nad6 gene, are the most likely CMS candidate genes in this line.

Highlights d TRANSPORTER OF IBA1 (TOB1) identified as transporter of the auxin precursor IBA d TOB1 localizes to the vacuolar membrane d TOB1 regulates root system architecture (RSA) d TOB1 integrates cytokinin response and auxin homeostasis to regulate RSA

Understanding how an organism's phenotypic traits are conditioned by genetic and environmental variation is a central goal of biology. Root systems are one of the most important but poorly understood aspects of plants, largely due to the threedimensional (3D), dynamic, and multiscale phenotyping challenge they pose. A critical gap in our knowledge is how root systems build in complexity from a single primary root to a network of thousands of roots that collectively compete for ephemeral, heterogeneous soil resources. We used time-lapse 3D imaging and mathematical modeling to assess root system architectures (RSAs) of two maize (Zea mays) inbred genotypes and their hybrid as they grew in complexity from a few to many roots. Genetically driven differences in root branching zone size and lateral branching densities along a single root, combined with differences in peak growth rate and the relative allocation of carbon resources to new versus existing roots, manifest as sharply distinct global RSAs over time. The 3D imaging of mature field-grown root crowns showed that several genetic differences in seedling architectures could persist throughout development and across environments. This approach connects individual and system-wide scales of root growth dynamics, which could eventually be used to predict genetic variation for complex RSAs and their functions.

Phenotypic measurements and images of crops grown under controlled‐environment conditions can be analyzed to compare plant growth and other phenotypes from diverse varieties. Those demonstrating the most favorable phenotypic traits can then be used for crop improvement strategies. This article details a protocol for image‐based root and shoot phenotyping of plants grown in the greenhouse to compare traits among different varieties. Diverse maize lines were grown in the greenhouse in large 8‐gallon treepots in a clay granule substrate. Replicates of each line were harvested at 4 weeks, 6 weeks, and 8 weeks after planting to capture developmental information. Whole‐plant phenotypes include biomass accumulation, ontogeny, architecture, and photosynthetic efficiency of leaves. Image analysis was used to measure leaf surface area and tassel size and to extract shape variance information from complex 3D root architectures. Notably, this framework is extensible to any number of above‐ or below‐ground phenotypes, both morphological and physiological. © 2017 by John Wiley & Sons, Inc.

Root systems are branched networks that develop from simple growth properties of their individual roots. Yet a mature maize root system has many thousands of roots that each interact with soil structures, water and nutrient patches, and microbial ecologies in the microenvironments surrounding each root tip. Although the plasticity of root growth to these and other environmental factors is well known, how the many local processes contribute over time to global features of root system architecture is hardly understood. We employ an automated 3D root imaging pipeline to capture the growth of maize roots every four hours throughout seven days of seedling development. We model the contrasting architectures of two maize inbred genotypes and their hybrid to derive key parameters that distinguish complex growth patterns as a function of time. The statistical characteristics of local root growth defined the global system properties despite a large range of trait values. "Computational dissection" of a single root from each root system identified differences in the size of the root branching zone and lateral branching densities, but not radial patterns, that drove the contrasting root architectures from seedling to maturity. X-ray imaging of mature field-grown root crowns showed that seedling growth trajectories persisted throughout development and could predict eventual architectures, suggesting a strong genetic basis. The work connects individual and systemwide scales of root growth dynamics, providing the means for a function-valued approach to understanding the genetic and genetic x environment conditioning of root growth that will enable breeding for enhanced root traits. KEYWORDSroot architecture, growth modelling, multiscale, maize, genetics SIGNIFICANCE STATEMENTWhen and where roots grow determines their ability to capture short-lived and patchy water and nutrient resources to support the aboveground organs of the plant. Roots have no known longdistance external sensing mechanisms, but form branched networks that blindly explore the soil and respond to encountered local stimuli. How global architectures form from the many thousands of these local responses, and how they are controlled genetically are major open questions. Here we quantify differences in local root growth patterns of two inbred genotypes of maize that control contrasting systemwide properties. Measurements at the seedling stage were highly correlated with the complex architectures of mature root systems, paving the way for the development of crops with greater resource uptake capacity.