Biology subjects

Rangarajan, H.

Publications and source records attributed to Rangarajan, H..

4 recordsLinked to original sources

bioRxiv2025

Ploidy alters root anatomy and shapes the evolution of wheat polyploids

Polyploidization played a crucial role in crop domestication and modern agriculture. While increased cell size in polyploids is known to enhance plant biomass and vigor, its impact on soil exploration remains poorly understood. Using wheat as a model, we identify a ploidy-induced belowground domestication syndrome, characterized by (a) increased root cortical cell size reducing root respiration, nitrogen content, and phosphorus content; (b) enlarged metaxylem vessels, increasing axial hydraulic conductance; and (c) blunter root tips, limiting penetration ability in compacted soils. Our empirical and in silico experiments show that reduced root respiration and reduced cellular nutrient content in wheat polyploids improved nutrient use and acquisition efficiency under suboptimal nitrogen and phosphorus availability. These adaptations would have been advantageous in nutrient-depleted agroecosystems of the Pre-Pottery Neolithic B (PPNB) Fertile Crescent, where continuous cultivation depleted soil fertility over time. Functional-structural modeling indicates that larger cortical cells in wheat polyploids increase vacuolar occupancy, reducing root metabolic costs. Enhanced axial hydraulic conducta nce may have improved water transport, an advantage in irrigated PPNB agroecosystems. However, polyploids have blunter root tips, which reduces their penetration ability in compacted soils, making them less suited for native soils with greater mechanical impedance. We propose that root anatomical changes driven by ploidy played an important role in adaptations of wheat domesticates to PPNB agriculture. One-Sentence SummaryPolyploidy induced changes in root anatomy may have improved adaptation of wheat to Neolithic agroecosystems.

plant biology↗

bioRxiv2024

In silico analysis of the evolution of root phenotypes during maize domestication in Neolithic soils of Tehuacan

Roots are essential for plant adaptation to changing environments, yet the role of roots in crop domestication remains unclear. This study examines the evolution of root phenotypes from teosinte to maize, a transition resulting in reduced nodal root number (NRN), multiseriate cortical sclerenchyma (MCS), and increased seminal root number (SRN). We reconstructed the root phenotypes of maize and teosinte, as well as the environments of the Tehuacan Valley over the last 18,000 years using a combination of ancient DNA, paleobotany, and functional-structural modeling. Our models reveal that increasing Holocene atmospheric CO2 concentrations favored the appearance of reduced NRN and MCS between 12000 to 8000 years before present (yBP), promoting deeper root systems. The advent of irrigation by 6000 yBP switched nitrogen distribution from topsoil to subsoil domains, a change which increased the utility of reduced NRN and MCS. Comparison of allelic frequencies among ancient samples ranging from 5500 to 500 yBP suggest that increased SRN may have appeared around 3500 yBP, coinciding with a period of increased human population, agricultural intensification, and soil degradation. Our results suggest that root phenotypes that enhance plant performance under nitrogen stress were important for maize adaptation to changing agricultural practices in the Tehuacan Valley. ClassificationPhysiology & Development

plant biology↗

bioRxiv2024

Exploring yield stability and the fitness landscape of maize landrace root phenotypes in silico

Integrated root phenotypes contribute to environmental adaptation and yield stability. We used the functional-structural plant/soil model OpenSimRoot_v2 to reconstruct the root phenotypes and environments of eight maize landraces to understand the phenotypic and environmental factors associated with broad adaptation. We found that accessions from low phosphorus regions have root phenotypes with shallow growth angles and greater nodal root numbers, allowing them to adapt to their native environments by improved topsoil foraging. We used machine learning algorithms to detect the most important phenotypes responsible for adaptation to multiple environments. The most important phene states responsible for stability across environments are large cortical cell size and reduced diameter of roots in nodes 5 and 6. When we dissected the components of root diameter, we observed that large cortical cell size improved growth by 28%, 23 % and 114%, while reduced cortical cell file number alone improved shoot growth by 137%, 66% and 216%, under drought, nitrogen and phosphorus stress, respectively. Functional-structural analysis of 96 maize landraces from the Americas, previously phenotyped in mesocosms in the greenhouse, suggested that parsimonious anatomical phenotypes, which reduce the metabolic cost of soil exploration, are the main phenotypes associated with adaptation to multiple environments, while root architectural traits were related to adaptation to specific environments. Our results indicate that integrated phenotypes with root anatomical phenes that reduce the metabolic cost of soil exploration will increase tolerance to stress across multiple environments and therefore improve yield stability, regardless of their root architecture.

plant biology↗

bioRxiv2020

A comparative analysis of quantitative metrics of root architectural phenotypes

High throughput phenotyping is important to bridge the gap between genotype and phenotype. The methods used to describe the phenotype therefore should be robust to measurement errors, relatively stable over time, and most importantly, provide a reliable estimate of elementary phenotypic components. In this study, we use functional-structural modeling to evaluate quantitative phenotypic metrics used to describe root architecture to determine how they fit these criteria. Our results show that phenes such as root number, root diameter, lateral root branching density are stable, reliable measures and are not affected by imaging method or plane. Metrics aggregating multiple phenes such as total length, total volume, convexhull volume, bushiness index etc. estimate different subsets of the constituent phenes, they however do not provide any information regarding the underlying phene states. Estimates of phene aggregates are not unique representations of underlying constituent phenes: multiple phenotypes having phenes in different states could have similar aggregate metrics. Root growth angle is an important phene which is susceptible to measurement errors when 2D projection methods are used. Metrics that aggregate phenes which are complex functions of root growth angle and other phenes are also subject to measurement errors when 2D projection methods are used. These results support the hypothesis that estimates of phenes are more useful than metrics aggregating multiple phenes for phenotyping root architecture. We propose that these concepts are broadly applicable in phenotyping and phenomics.

plant biology↗