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Pearl millet plays a major role in food security in arid and semi-arid areas of Africa and India. However, it lags behind the other cereal crops in terms of genetic improvement. The recent sequencing of its genome opens the way to the use of modern genomic tools for breeding. Our study aimed at identifying genetic components involved in early drought stress tolerance as a first step toward the development of improved pearl millet varieties or hybrids. A panel of 188 inbred lines from West Africa was phenotyped under early drought stress and well-irrigated conditions. We found a strong impact of drought stress on yield components. This impact was variable between inbred lines. We then performed an association analysis with a total of 392,493 SNPs identified using Genotyping-by-Sequencing (GBS). Correcting for genetic relatedness, genome wide association study identified QTLs for biomass production in early drought stress conditions and for stay-green trait. In particular, genes involved in the sirohaem and wax biosynthesis pathways were found to co-locate with two of these QTLs. Our results might contribute to breed pearl millet lines with improved yield under drought stress.

Pearl millet plays an important role for food security in arid regions of Africa and India. Nevertheless, it is considered an orphan crop as it lags far behind other cereals in terms of genetic improvement efforts. Breeding pearl millet varieties with improved root traits promises to deliver benefits in water and nutrient acquisition. Here, we characterize early pearl millet root system development using several different root phenotyping approaches that include rhizotrons and microCT. We report that early stage pearl millet root system development is characterized by a fast growing primary root that quickly colonizes deeper soil horizons. We also describe root anatomical studies that revealed three distinct types of lateral roots that form on both primary roots and crown roots. Finally, we detected significant variation for two root architectural traits, primary root lenght and lateral root density, in pearl millet inbred lines. This study provides the basis for subsequent genetic experiments to identify loci associated with interesting early root development traits in this important cereal.

Seedling root traits impact plant establishment under challenging environments. Pearl millet is one of the most heat and drought tolerant cereal crops that provides a vital food source across the sub-Saharan Sahel region. Pearl millet’s early root system features a single fast-growing primary root which we hypothesize is an adaptation to the Sahelian climate. Using crop modeling, we demonstrate that early drought stress is an important constraint in agrosystems in the Sahel where pearl millet was domesticated. Furthermore, we show that increased pearl millet primary root growth is correlated with increased early water stress tolerance in field conditions. Genetics including genome-wide association study and quantitative trait loci (QTL) approaches identify genomic regions controlling this key root trait. Combining gene expression data, re-sequencing and re-annotation of one of these genomic regions identified a glutaredoxin-encoding gene PgGRXC9 as the candidate stress resilience root growth regulator. Functional characterization of its closest Arabidopsis homolog AtROXY19 revealed a novel role for this glutaredoxin (GRX) gene clade in regulating cell elongation. In summary, our study suggests a conserved function for GRX genes in conferring root cell elongation and enhancing resilience of pearl millet to its Sahelian environment. Pearl millet is a staple food for over 90 million people living in regions of Africa and India that typically experience high temperatures and little rainfall. It was domesticated about 4,500 years ago in the Sahel region of West Africa and is one of the most heat and drought tolerant cereal crops worldwide. In most plants, organs known as roots absorb water and essential nutrients from the soil. Young pearl millet plants develop a fast-growing primary root, but it is unclear how this unique feature helps the crop to grow in hot and dry conditions. Using weather data collected from the Sahel over a 20-year period, Fuente, Grondin et al. predicted by modelling that early drought stress is the major factor limiting pearl millet growth and yield in this region. Field experiments found that plants with primary roots that grow faster within soil were better at tolerating early drought than those with slower growing roots. Further work using genetic approaches revealed that a gene known as PgGRXC9 promotes the growth of the primary root. To better understand how this gene works, the team examined a very similar gene in a well-studied model plant known as Arabidopsis. This suggested that PgGRXC9 helps the primary root to grow by stimulating cell elongation within the root. Since it is well adapted to dry conditions, pearl millet is expected to play an important role in helping agriculture adjust to climate change. The findings of Fuente, Grondin et al. may be used by plant breeders to create more resilient and productive varieties of pearl millet.

Recent progress in root phenotyping has focused mainly on increasing throughput for genetic studies, while identifying root developmental patterns has been comparatively underexplored. We introduce a new phenotyping pipeline for producing high-quality spatiotemporal root system development data and identifying developmental patterns within these data. The SmartRoot image-analysis system and temporal and spatial statistical models were applied to two cereals, pearl millet (Pennisetum glaucum) and maize (Zea mays). Semi-Markov switching linear models were used to cluster lateral roots based on their growth rate profiles. These models revealed three types of lateral roots with similar characteristics in both species. The first type corresponds to fast and accelerating roots, the second to rapidly arrested roots, and the third to an intermediate type where roots cease elongation after a few days. These types of lateral roots were retrieved in different proportions in a maize mutant affected in auxin signaling, while the first most vigorous type was absent in maize plants exposed to severe shading. Moreover, the classification of growth rate profiles was mirrored by a ranking of anatomical traits in pearl millet. Potential dependencies in the succession of lateral root types along the primary root were then analyzed using variable-order Markov chains. The lateral root type was not influenced by the shootward neighbor root type or by the distance from this root. This random branching pattern of primary roots was remarkably conserved, despite the high variability of root systems in both species. Our phenotyping pipeline opens the door to exploring the genetic variability of lateral root developmental patterns.

In the recent years, many computational tools, such as image analysis, data management, process-based simulation and upscaling tools, were developed to help quantify and understand water flow in the soil-root system, at multiple scales (tissue, organ, plant and population). Several of these tools work together or, at least, are compatible. However, for the un-informed researcher, they might seem disconnected, forming a unclear and disorganised succession of tools.In this article, we present how different pieces of work can be further developed by connecting them to analyse soil-root-water relations in a comprehensive and structured network. This \"explicit network of soil-root computational tools\" informs the reader about existing tools and help them understand how their data (past and future) might fit within the network. We also demonstrate the novel possibilities of scale-consistent parameterizations made possible by the network with a set of case studies from the literature. Finally, we discuss existing gaps in the network and how we can move forward to fill them.

Seedling root traits impact plant establishment under challenging environments. Pearl millet is one of the most heat and drought tolerant cereal crops that provides a vital food source across the sub-Saharan Sahel region. Pearl millet’s early root system features a single fast-growing primary root which we hypothesize is an adaptation to the Sahelian climate. Using crop modeling, we demonstrate that early drought stress is an important constraint in agrosystems in the Sahel where pearl millet was domesticated. Furthermore, we show that increased pearl millet primary root growth is correlated with increased early water stress tolerance in field conditions. Genetics including genome-wide association study and quantitative trait loci (QTL) approaches identify genomic regions controlling this key root trait. Combining gene expression data, re-sequencing and re-annotation of one of these genomic regions identified a glutaredoxin-encoding gene PgGRXC9 as the candidate stress resilience root growth regulator. Functional characterization of its closest Arabidopsis homolog AtROXY19 revealed a novel role for this glutaredoxin (GRX) gene clade in regulating cell elongation. In summary, our study suggests a conserved function for GRX genes in conferring root cell elongation and enhancing resilience of pearl millet to its Sahelian environment. Pearl millet is a staple food for over 90 million people living in regions of Africa and India that typically experience high temperatures and little rainfall. It was domesticated about 4,500 years ago in the Sahel region of West Africa and is one of the most heat and drought tolerant cereal crops worldwide. In most plants, organs known as roots absorb water and essential nutrients from the soil. Young pearl millet plants develop a fast-growing primary root, but it is unclear how this unique feature helps the crop to grow in hot and dry conditions. Using weather data collected from the Sahel over a 20-year period, Fuente, Grondin et al. predicted by modelling that early drought stress is the major factor limiting pearl millet growth and yield in this region. Field experiments found that plants with primary roots that grow faster within soil were better at tolerating early drought than those with slower growing roots. Further work using genetic approaches revealed that a gene known as PgGRXC9 promotes the growth of the primary root. To better understand how this gene works, the team examined a very similar gene in a well-studied model plant known as Arabidopsis. This suggested that PgGRXC9 helps the primary root to grow by stimulating cell elongation within the root. Since it is well adapted to dry conditions, pearl millet is expected to play an important role in helping agriculture adjust to climate change. The findings of Fuente, Grondin et al. may be used by plant breeders to create more resilient and productive varieties of pearl millet.

Recent progress in root phenotyping has focused mainly on increasing throughput for genetic studies while identifying root developmental patterns has been comparatively underexplored. We introduce a new phenotyping pipeline for producing high-quality spatio-temporal root system development data and identifying developmental patterns within these data. The SmartRoot image analysis system and temporal and spatial statistical models were applied to two cereals, pearl millet (Pennisetum glaucum) and maize (Zea mays). Semi-Markov switching linear models were used to cluster lateral roots based on their growth rate profiles. These models revealed three types of lateral roots with similar characteristics in both species. The first type corresponds to fast and accelerating roots, the second to rapidly arrested roots, and the third to an intermediate type where roots cease elongation after a few days. These types of lateral roots were retrieved in different proportions in a maize mutant affected in auxin signaling, while the first most vigorous type was absent in maize plants exposed to severe shading. Moreover, the classification of growth rate profiles was mirrored by a ranking of anatomical traits in pearl millet. Potential dependencies in the succession of lateral root types along the primary root were then analyzed using variable-order Markov chains. The lateral root type was not influenced by the shootward neighbor root type or by the distance from this root. This random branching pattern of primary roots was remarkably conserved, despite the high variability of root systems in both species. Our phenotyping pipeline opens the door to exploring the genetic variability of lateral root developmental patterns.

Seedling root traits impact plant establishment under challenging environments. Pearl millet is one of the most heat and drought tolerant cereal crops that provides a vital food source across the sub-Saharan Sahel region. Pearl millet early root system features a single fast-growing primary root which we hypothesize is an adaptation to the Sahelian climate. Using crop modelling, we demonstrate that early drought stress is an important constraint in agrosystems in the Sahel where pearl millet was domesticated. Furthermore, we show that increased pearl millet primary root growth is correlated with increased early water stress tolerance in field conditions. Genetics including GWAS and QTL approaches identify genomic regions controlling this key root trait. Combining gene expression data, re-sequencing and re-annotation of one of these genomic regions identified a glutaredoxin-encoding gene PgGRXC9 as the candidate stress resilience root growth regulator. Functional characterization of its closest Arabidopsis homolog AtROXY19 revealed a novel role for this glutaredoxin (GRX) gene clade in regulating cell elongation. In summary, our study suggests a conserved function for GRX genes in conferring root cell elongation and enhancing resilience of pearl millet to its Sahelian environment.Competing Interest StatementThe authors have declared no competing interest.Footnotes* Added explanation on the population genetics and transcriptomics. Revised figure 4 to include a scalebar. Changed the conclusion to tone down some sentences.

Pearl millet plays a major role in food security in arid and semi-arid areas of Africa and India. However, it lags behind the other cereal crops in terms of genetic improvement. The recent sequencing of its genome opens the way to the use of modern genomic tools for breeding. Our study aimed at identifying genetic components involved in early drought stress tolerance as a first step toward the development of improved pearl millet varieties or hybrids. A panel of 188 inbred lines from West Africa was phenotyped under early drought stress and well-irrigated conditions. We found a strong impact of drought stress on yield components. This impact was variable between inbred lines. We then performed an association analysis with a total of 392,493 SNPs identified using Genotyping-by-Sequencing (GBS). Correcting for genetic relatedness, genome wide association study identified QTLs for biomass production in early drought stress conditions and for stay-green trait. In particular, genes involved in the sirohaem and wax biosynthesis pathways were found to co-locate with association loci. Our results open the way to use genomic selection to breed pearl millet lines with improved yield under drought stress.

In the recent years, many computational tools, such as image analysis, data management, process-based simulation and upscaling tools, were developed to help quantify and understand water flow in the soil-root system, at multiple scales (tissue, organ, plant and population). Several of these tools work together or, at least, are compatible. However, for the un-informed researcher, they might seem disconnected, forming a unclear and disorganised succession of tools. In this article, we present how different pieces of work can be further developed by connecting them to analyse soil-root-water relations in a comprehensive and structured network. This explicit network of soil-root computational tools informs the reader about existing tools and help them understand how their data (past and future) might fit within the network. We also demonstrate the novel possibilities of scale-consistent parameterizations made possible by the network with a set of case studies from the literature. Finally, we discuss existing gaps in the network and how we can move forward to fill them.