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Breeding annual crops for enhanced root depth and biomass is considered a promising intervention to accrue soil organic carbon (SOC) in croplands, with benefits for climate change mitigation and soil health. In annual crops, genetic technology (seed) is replaced every year as part of a farmer's fixed costs, making breeding solutions to climate change more scalable and affordable than management approaches. However, mechanistic understanding and quantitative estimates of SOC accrual potentials from crops with enhanced root phenotypes are lacking. Maize is the highest acreage and yielding crop in the US, characterized by relatively low root biomass confined to the topsoil, making it a suitable candidate for improvement that could be rapidly scaled. We ran a 2‐year field experiment to quantify the formation and composition (i.e., particulate (POM), coarse and fine mineral–associated organic matter (chaOM and MAOM, respectively) of new SOC to a depth of 90 cm from the decomposition of isotopically labeled maize roots and exudates. Additionally, we used the process‐based MEMS 2 model to simulate the SOC accrual potential of maize root ideotypes enhanced to either shift root production to deeper depths or increase root biomass allocation, assuming no change in overall productivity. In our field experiment, maize root decomposition preferentially formed POM, with doubled efficiency below 50 cm, while root exudates preferentially formed MAOM. Modeling showed that shifting root inputs to deeper layer or increasing allocation to roots resulted in a deterministic increase in SOC, ranging from 0.05 to 0.15 Mg C ha−1 per year, which are at the low end of the range of published SOC per hectare annual accrual estimates from adoption of a variety of crop management practices. Our analysis indicates that for maize, breeding for increasing root inputs as a strategy for SOC accrual has limited impact on a per‐hectare basis, although given that globally maize is produced on hundreds of millions of hectares each year, there is potential for this technology and its effect to scale. For maize–soy system that dominates US acres, changes in the overall cropping system are needed for sizable greenhouse gas reductions and SOC accrual. This study demonstrated a modeling and experimental framework to quantify and forecast SOC changes created by changing crop root inputs. [ABSTRACT FROM AUTHOR]

Byline: Chris Wolverton (1), Jack L Mullen (1), Sachiko Aizawa (2), Izumi Yoshizaki (2), Shigeki Kamigaichi (2), Chiaki Mukai (2), Toru Shimazu (3), Keiji Fukui (3), Michael L Evans (1), Hideo Ishikawa (1) Keywords: Keywords: Electric field, Growth, Microgravity, Root, Vigna Abstract: Author Affiliation: (1) Department of Plant Biology, The Ohio State University, 1735 Neil Ave, Columbus, OH 43210, U.S.A., US (2) National Space Development Agency of Japan, 2--1--1 Sengen, Tsukuba-city, Ibaraki, 305--8505 Japan, JP (3) Japan Space Forum, 1--29--6 Hamamatsu-cho, Minato, Tokyo, 105--0013 Japan, JP Article note: Received 13 September 1999/ Accepted in revised form 12 October 1999

High-throughput, field-based characterization of root systems for hundreds of genotypes in thousands of plots is necessary for breeding and identifying loci underlying variation in root traits and their plasticity. We designed a large-scale sampling of root pulling force, the vertical force required to extract the root system from the soil, in a maize diversity panel under differing irrigation levels for two growing seasons. We then characterized the root system architecture of the extracted root crowns. We found consistent patterns of phenotypic plasticity for root pulling force for a subset of genotypes under differential irrigation, suggesting that root plasticity is predictable. Using genome-wide association analysis, we identified 54 SNPs as statistically significant for six independent root pulling force measurements across two irrigation levels and four developmental timepoints. For every significant GWAS SNP for any trait in any treatment and timepoint we conducted post hoc tests for genotype-by-environment interaction, using a mixed model ANOVA. We found that 8 of the 54 SNPs showed significant GxE. Candidate genes underlying variation in root pulling force included those involved in nutrient transport. Although they are often treated separately, variation in the ability of plant roots to sense and respond to variation in environmental resources including water and nutrients may be linked by the genes and pathways underlying this variation. While functional validation of the identified genes is needed, our results expand the current knowledge of root phenotypic plasticity at the whole plant and gene levels, and further elucidate the complex genetic architecture of maize root systems. [ABSTRACT FROM AUTHOR]

Carbon isotope ratio (δ13C) and root pulling force (RPF) are associated with dehydration avoidance in plants. The δ13C measures the efficiency of C gain relative to water loss, whereas RPF, the vertical force required to pull plants from the ground, indirectly estimates root‐related dehydration avoidance capacity. To determine quantitative trait loci (QTL) controlling these traits in canola (Brassica napus L.), a mapping population was evaluated in 2011 and 2012 in Fort Collins, CO. The split‐plot experiment had two moisture regimes (main plot) and 148 doubled haploid lines (subplot), replicated three times. Analysis of variance indicated highly significant (P < .01) variation among genotypes for δ13C, RPF, days to flowering, and several other agronomic traits. In 2011, δ13C was correlated (P < .01) with days to flowering in both moisture treatments (r = .41 dry, 0.31 wet) and with fresh biomass in the dry treatment (r = .64). The RPF was consistently correlated with plant height (r = .32–.54, P < .01) and fresh biomass (r = .17–.58, P < .05) in all environments. In 2011, QTL were detected on chromosomes A09 and C08 for δ13C and on chromosomes A05, C01, C04, and C08 for RPF. The QTL for δ13C, RPF, and plant height co‐localized on C08. In 2012, QTL were detected on A02 for δ13C and on C01 and C08 for RPF. Moderate heritability and low QTL × environment interaction for δ13C and RPF suggest that if validated, markers for these traits could be used in marker‐assisted selection. [ABSTRACT FROM AUTHOR]

Background: Recent advances in nucleic acid sequencing technologies have led to a dramatic increase in the number of markers available to generate genetic linkage maps. This increased marker density can be used to improve genome assemblies as well as add much needed resolution for loci controlling variation in ecologically and agriculturally important traits. However, traditional genetic map construction methods from these large marker datasets can be computationally prohibitive and highly error prone. Results: We present TSPmap, a method which implements both approximate and exact Traveling Salesperson Problem solvers to generate linkage maps. We demonstrate that for datasets with large numbers of genomic markers (e.g. 10,000) and in multiple population types generated from inbred parents, TSPmap can rapidly produce high quality linkage maps with low sensitivity to missing and erroneous genotyping data compared to two other benchmark methods, JoinMap and MSTmap. TSPmap is open source and freely available as an R package. Conclusions: With the advancement of low cost sequencing technologies, the number of markers used in the generation of genetic maps is expected to continue to rise. TSPmap will be a useful tool to handle such large datasets into the future, quickly producing high quality maps using a large number of genomic markers. [ABSTRACT FROM AUTHOR]

Transpiration is controlled by evaporative demand and stomatal conductance ( gs), and there can be substantial genetic variation in gs. A key parameter in empirical models of transpiration is minimum stomatal conductance ( g0), a trait that can be measured and has a large effect on gs and transpiration. In A rabidopsis thaliana, g0 exhibits both environmental and genetic variation, and quantitative trait loci ( QTL) have been mapped. We used this information to create a genetically parameterized empirical model to predict transpiration of genotypes. For the parental lines, this worked well. However, in a recombinant inbred population, the predictions proved less accurate. When based only upon their genotype at a single g0 QTL, genotypes were less distinct than our model predicted. Follow-up experiments indicated that both genotype by environment interaction and a polygenic inheritance complicate the application of genetic effects into physiological models. The use of ecophysiological or 'crop' models for predicting transpiration of novel genetic lines will benefit from incorporating further knowledge of the genetic control and degree of independence of core traits/parameters underlying gs variation. [ABSTRACT FROM AUTHOR]

Drought escape and dehydration avoidance represent alternative strategies for drought adaptation in annual crops. The mechanisms underlying these two strategies are reported to have a negative correlation, suggesting a trade-off. We conducted a quantitative trait locus (QTL) analysis of flowering time and root mass, traits representing each strategy, in Brassica napus to understand if a trade-off exists and what the genetic basis might be. Our field experiment used a genotyped population of doubled haploid lines and included both irrigated and rainfed treatments, allowing analysis of plasticity in each trait. We found strong genetic correlations among all traits, suggesting a trade-off among traits may exist. Summing across traits and treatments we found 20 QTLs, but many of these co-localized to two major QTLs, providing evidence that the trade-off is genetically constrained. To understand the mechanistic relationship between root mass, flowering time, and QTLs, we analysed the data by conditioning upon correlated traits. Our results suggest a causal model where such QTLs affect root mass directly as well as through their impacts on flowering time. Additionally, we used draft Brassica genomes to identify orthologues of well characterized Arabidopsis thaliana flowering time genes as candidate genes. This research provides valuable clues to breeding for drought adaptation as it is the first to analyse the inheritance of the root system in B. napus in relation to drought. [ABSTRACT FROM AUTHOR]

Background: The identification of the loci and specific alleles underlying variation in quantitative traits is an important goal for evolutionary biologists and breeders. Despite major advancements in genomics technology, moving from QTL to causal alleles remains a major challenge in genetics research. Near-isogenic lines are the ideal raw material for QTL validation, refinement of QTL location and, ultimately, gene discovery. Results: In this study, a population of 75 Arabidopsis thaliana near-isogenic lines was developed from an existing recombinant inbred line (RIL) population derived from a cross between physiologically divergent accessions Kas-1 and Tsu-1. First, a novel algorithm was developed to utilize genome-wide marker data in selecting RILs fully isogenic to Kas-1 for a single chromosome. Seven such RILs were used in 2 generations of crossing to Tsu-1 to create BC1 seed. BC1 plants were genotyped with SSR markers so that lines could be selected that carried Kas-1 introgressions, resulting in a population carrying chromosomal introgressions spanning the genome. BC1 lines were genotyped with 48 genome-wide SSRs to identify lines with a targeted Kas-1 introgression and the fewest genomic introgressions elsewhere. 75 such lines were selected and genotyped at an additional 41 SNP loci and another 930 tags using 2b-RAD genotyping by sequencing. The final population carried an average of 1.35 homozygous and 2.49 heterozygous introgressions per line with average introgression sizes of 5.32 and 5.16 Mb, respectively. In a simple case study, we demonstrate the advantage of maintaining heterozygotes in our library whereby fine-mapping efforts are conducted simply by self-pollination. Crossovers in the heterozygous interval during this single selfing generation break the introgression into smaller, homozygous fragments (sub-NILs). Additionally, we utilize a homozygous NIL for validation of a QTL underlying stomatal conductance, a low heritability trait. Conclusions: The present results introduce a new and valuable resource to the Brassicaceae research community that enables rapid fine-mapping of candidate loci in parallel with QTL validation. These attributes along with dense marker coverage and genome-wide chromosomal introgressions make this population an ideal starting point for discovery of genes underlying important complex traits of agricultural and ecological significance. [ABSTRACT FROM AUTHOR]

As a rosette plant, Arabidopsis thaliana forms leaves near to the ground, which causes the plant to be vulnerable to shading by neighbours. One mechanism to avoid such shading is the regulation of leaf inclination, such that leaves can be raised to more vertical orientations to prevent neighbouring leaves from overtopping them. Throughout Arabidopsis rosette development, rosette leaves move to more vertical orientations when shaded by neighbouring leaves, exposed to low light levels or placed in the dark. After dark-induced reorientation of leaves, returning them to white light causes the leaves to reorient to more horizontal inclinations. These light-dependent leaf movements are more robust than, and distinct from, the diurnal movements of rosette leaves. However, the movements are gated by the circadian clock. The light-dependent leaf orientation response is mediated primarily through phytochromes A, B and E, with the orientation varying with the ratio of red light to far-red light, consistent with other shade-avoidance responses. However, even plants lacking these phytochromes were able to alter leaf inclination in response to white light, suggesting a role for other photoreceptors. In particular, we found significant changes in leaf inclination for plants exposed to green light. This green light response may be caused, in part, by light-dependent regulation of abscisic acid (ABA) biosynthesis. [ABSTRACT FROM AUTHOR]

Using sensors and electronic systems for characterization of plant traits provides valuable digital inputs to support complex analytical modeling in genetics research. In field applications, frequent sensor deployment enables the study of the dynamics of these traits and their interaction with the environment. This study focused on implementing lidar (light detection and ranging) technology to generate 2D displacement data at high spatial resolution and extract plant architectural parameters, namely canopy height and cover, in a diverse population of 252 maize (Zea mays L.) genotypes. A prime objective was to develop the mechanical and electrical subcomponents for field deployment from a ground vehicle. Data reduction approaches were implemented for efficient same-day post-processing to generate by-plot statistics. The lidar system was successfully deployed six times in a span of 42 days. Lidar data accuracy was validated through independent measurements in a subset of 75 experimental units. Manual and lidar-derived canopy height measurements were compared resulting in root mean square error (RMSE) = 0.068 m and r2 = 0.81. Subsequent genome-wide association study (GWAS) analyses for quantitative trait locus (QTL) identification and comparisons of genetic correlations and heritabilities for manual and lidar-based traits showed statistically significant associations. Low-cost, field-ready lidar of computational simplicity make possible timely phenotyping of diverse populations in multiple environments. [ABSTRACT FROM AUTHOR]

Brassica napus is a globally important oilseed for which little is known about the genetics of drought adaptation. We previously mapped twelve quantitative trait loci (QTL) underlying drought-related traits in a biparental mapping population created from a cross between winter and spring B. napus cultivars. Here we resequence the genomes of the mapping population parents to identify genetic diversity across the genome and within QTL regions. We sequenced each parental cultivar on the Illumina HiSeq platform to a minimum depth of 23 and performed a reference based assembly in order to describe the molecular variation differentiating them at the scale of the genome, QTL and gene. Genome-wide patterns of variation were characterized by an overall higher single nucleotide polymorphism (SNP) density in the A genome and a higher ratio of nonsynonymous to synonymous substitutions in the C genome. Nonsynonymous substitutions were used to categorize gene ontology terms differentiating the parent genomes along with a list of putative functional variants contained within each QTL. Marker assays were developed for several of the discovered polymorphisms within a pleiotropic QTL on chromosome A10. QTL analysis with the new, denser map showed the most associated marker to be that developed from an insertion/deletion polymorphism located in the candidate gene Bna.FLC.A10, and it was the only candidate within the QTL interval with observed polymorphism. Together, these results provide a glimpse of genome-wide variation differentiating annual and biennial B. napus ecotypes as well as a better understanding of the genetic basis of root and drought phenotypes. [ABSTRACT FROM AUTHOR]

Understanding the genetic basis of complex traits is a fundamental goal of evolutionary genetics. Yet, the genetics controlling complex traits in many important species such as hemp (Cannabis sativa) remain poorly investigated. Because hemp's change in legal status with the 2014 and 2018 U.S. Federal Farm Bills, interest in the genetics controlling its numerous agriculturally important traits has steadily increased. To better understand the genetics of agriculturally important traits in hemp, we developed an F2 population by crossing two phenotypically distinct hemp cultivars (Carmagnola and USO31). Using whole-genome sequencing, we mapped quantitative trait loci (QTL) associated with variation in numerous agronomic and biochemical traits. A total of 69 loci associated with agronomic (34) and biochemical (35) trait variation were identified. We found that most QTL co-localized, suggesting that the phenotypic distinctions between Carmagnola and USO31 are largely controlled by a small number of loci. We identified TINY and olivetol synthase as candidate genes underlying colocalized QTL clusters for agronomic and biochemical traits, respectively. We functionally validated the olivetol synthase candidate by expressing the alleles in yeast. Gas chromatography-mass spectrometry assays of extracts from these yeast colonies suggest that the USO31 olivetol synthase is functionally less active and potentially explains why USO31 produces lower cannabinoids compared to Carmagnola. Overall, our results help modernize the genomic understanding of complex traits in hemp. [ABSTRACT FROM AUTHOR]