Integrating GWAS and Gene Expression Analysis Identifies Candidate Genes for Root Morphology Traits in Maize at the Seedling Stage

Genome-wide association analysis reveal candidate genes and haplotypes related to root weight in cucumber (Cucumis sativus L.)

Background

The plant root system is critical for the absorption of water and nutrients, and have a direct influence on growth and yield. In cucumber, a globally consumed crop, the molecular mechanism of root development remains unclear, and this has implications for developing stress tolerant varieties. This study sought to determine the genetic patterns and related genes of cucumber root weight. A core cucumber germplasms population was used to do the GWAS analysis in three environments.

Results

Here, we investigated four root-weight related traits including root fresh weight (RFW), root dry weight (RDW), ratio of root dry weight to root fresh weight (RDFW) and the comprehensive evaluation index, D-value of root weight (DRW) deduced based on the above three traits for the core germplasm of the cucumber global repository. According to the D-value, we identified 21 and 16 accessions with light and heavy-root, respectively. We also found that the East Asian ecotype accessions had significantly heavier root than other three ecotypes. The genome-wide association study (GWAS) for these four traits reveals that 4 of 10 significant loci (gDRW3.1, gDRW3.2, gDRW4.1 and gDRW5.1) were repeatedly detected for at least two traits. Further haplotype and expression analysis for protein-coding genes positioned within these 4 loci between light and heavy-root accessions predicted five candidate genes (i.e., Csa3G132020 and Csa3G132520 both encoding F-box protein PP2-B1 for gDRW3.1, Csa3G629240 encoding a B-cell receptor-associated protein for gDRW3.2, Csa4G499330 encodes a GTP binding protein for gDRW4.1, and Csa5G286040 encodes a proteinase inhibitor for gDRW5.1).

Conclusions

We conducted a systematic analysis of the root genetic basis and characteristics of cucumber core germplasms population. We detected four novel loci, which regulate the root weight in cucumber. Our study provides valuable candidate genes and haplotypes for the improvement of root system in cucumber breeding.

Residual networks without pooling layers improve the accuracy of genomic predictions

KEY MESSAGE

Residual neural network genomic selection is the first GS algorithm to reach 35 layers, and its prediction accuracy surpasses previous algorithms. With the decrease in DNA sequencing costs and the development of deep learning, phenotype prediction accuracy by genomic selection (GS) continues to improve. Residual networks, a widely validated deep learning technique, are introduced to deep learning for GS. Since each locus has a different weighted impact on the phenotype, strided convolutions are more suitable for GS problems than pooling layers. Through the above technological innovations, we propose a GS deep learning algorithm, residual neural network for genomic selection (ResGS). ResGS is the first neural network to reach 35 layers in GS. In 15 cases from four public data, the prediction accuracy of ResGS is higher than that of ridge-regression best linear unbiased prediction, support vector regression, random forest, gradient boosting regressor, and deep neural network genomic prediction in most cases. ResGS performs well in dealing with gene-environment interaction. Phenotypes from other environments are imported into ResGS along with genetic data. The prediction results are much better than just providing genetic data as input, which demonstrates the effectiveness of GS multi-modal learning. Standard deviation is recommended as an auxiliary GS evaluation metric, which could improve the distribution of predicted results. Deep learning for GS, such as ResGS, is becoming more accurate in phenotype prediction.

Ameliorating the effects of multiple stresses on agronomic traits in crops: modern biotechnological and omics approaches

While global climate change poses a significant environmental threat to agriculture, the increasing population is another big challenge to food security. To address this, developing crop varieties with increased productivity and tolerance to biotic and abiotic stresses is crucial. Breeders must identify traits to ensure higher and consistent yields under inconsistent environmental challenges, possess resilience against emerging biotic and abiotic stresses and satisfy customer demands for safer and more nutritious meals. With the advent of omics-based technologies, molecular tools are now integrated with breeding to understand the molecular genetics of genotype-based traits and develop better climate-smart crops. The rapid development of omics technologies offers an opportunity to generate novel datasets for crop species. Identifying genes and pathways responsible for significant agronomic traits has been made possible by integrating omics data with genetic and phenotypic information. This paper discusses the importance and use of omics-based strategies, including genomics, transcriptomics, proteomics and phenomics, for agricultural and horticultural crop improvement, which aligns with developing better adaptability in these crop species to the changing climate conditions.

Transcriptome analysis reveals key regulatory genes for root growth related to potassium utilization efficiency in rapeseed (Brassica napus L.)

Root system architecture (RSA) is the primary predictor of nutrient intake and significantly influences potassium utilization efficiency (KUE). Uncertainty persists regarding the genetic factors governing root growth in rapeseed. The root transcriptome analysis reveals the genetic basis driving crop root growth. In this study, RNA-seq was used to profile the overall transcriptome in the root tissue of 20 Brassica napus accessions with high and low KUE. 71,437 genes in the roots displayed variable expression profiles between the two contrasting genotype groups. The 212 genes that had varied expression levels between the high and low KUE lines were found using a pairwise comparison approach. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional classification analysis revealed that the DEGs implicated in hormone and signaling pathways, as well as glucose, lipid, and amino acid metabolism, were all differently regulated in the rapeseed root system. Additionally, we discovered 33 transcription factors (TFs) that control root development were differentially expressed. By combining differential expression analysis, weighted gene co-expression network analysis (WGCNA), and recent genome-wide association study (GWAS) results, four candidate genes were identified as essential hub genes. These potential genes were located fewer than 100 kb from the peak SNPs of QTL clusters, and it was hypothesized that they regulated the formation of the root system. Three of the four hub genes' homologs-BnaC04G0560400ZS, BnaC04G0560400ZS, and BnaA03G0073500ZS-have been shown to control root development in earlier research. The information produced by our transcriptome profiling could be useful in revealing the molecular processes involved in the growth of rapeseed roots in response to KUE.

Identification of a new QTL underlying seminal root number in a maize-teosinte population

Seminal roots play an important role in acquisition of water and nutrients by maize seedlings. Compared with its teosinte ancestor, maize underwent a change in seminal root number (SRN). Although several key genes controlling SRN have been cloned, identification and utilization of new genes from teosinte would be useful for improving maize root architecture. In this study, a maize-teosinte BC₂F₆ population containing 206 individuals genotyped by resequencing was used to conduct high-resolution quantitative trait locus (QTL) mapping of SRN. A new major QTL on chromosome 7 (qSRN7) was identified. Differentially expressed genes (DEGs) based on RNA-Seq were identified between two inbred lines with no SRN and multiple SRN at two periods of seminal roots primordia formation. A total of 116 DEGs detected in at least one period were identified within the qSRN7 interval. Three DEGs (Zm00001d021572, Zm00001d021579 and Zm00001d021861) associated with SRN were identified through regional association mapping. When compared with reported domestication-related selective sweeps, Zm00001d021572 was selected during maize domestication. Our findings provide important insights into the genetic basis of SRN and identify a promising candidate gene for further studies on SRN.

Prospects of genetics and breeding for low-phosphate tolerance: an integrated approach from soil to cell

Improving phosphorus (P) crop nutrition has emerged as a key factor toward achieving a more resilient and sustainable agriculture. P is an essential nutrient for plant development and reproduction, and phosphate (Pi)-based fertilizers represent one of the pillars that sustain food production systems. To meet the global food demand, the challenge for modern agriculture is to increase food production and improve food quality in a sustainable way by significantly optimizing Pi fertilizer use efficiency. The development of genetically improved crops with higher Pi uptake and Pi-use efficiency and higher adaptability to environments with low-Pi availability will play a crucial role toward this end. In this review, we summarize the current understanding of Pi nutrition and the regulation of Pi-starvation responses in plants, and provide new perspectives on how to harness the ample repertoire of genetic mechanisms behind these adaptive responses for crop improvement. We discuss on the potential of implementing more integrative, versatile, and effective strategies by incorporating systems biology approaches and tools such as genome editing and synthetic biology. These strategies will be invaluable for producing high-yielding crops that require reduced Pi fertilizer inputs and to develop a more sustainable global agriculture.

Mapping of Candidate Genes in Response to Low Nitrogen in Rice Seedlings

Nitrogen is not only a macronutrient essential for crop growth and development, but also one of the most critical nutrients in farmland ecosystem. Insufficient nitrogen supply will lead to crop yield reduction, while excessive application of nitrogen fertilizer will cause agricultural and eco-environment damage. Therefore, mining low-nitrogen tolerant rice genes and improving nitrogen use efficiency are of great significance to the sustainable development of agriculture. This study was conducted by Genome-wide association study on a basis of two root morphological traits (root length and root diameter) and 788,396 SNPs of a natural population of 295 rice varieties. The transcriptome of low-nitrogen tolerant variety (Longjing 31) and low-nitrogen sensitive variety (Songjing 10) were sequenced between low and high nitrogen treatments. A total of 35 QTLs containing 493 genes were mapped. 3085 differential expressed genes were identified. Among these 493 genes, 174 genes showed different haplotype patterns. There were significant phenotype differences among different haplotypes of 58 genes with haplotype differences. These 58 genes were hypothesized as candidate genes for low nitrogen tolerance related to root morphology. Finally, six genes (Os07g0471300, Os11g0230400, Os11g0229300, Os11g0229400, Os11g0618300 and Os11g0229333) which expressed differentially in Longjing 31 were defined as more valuable candidate genes for low-nitrogen tolerance. The results revealed the response characteristics of rice to low-nitrogen, and provided insights into regulatory mechanisms of rice to nitrogen deficiency.

Genome-wide association study reveals the genetic basis of brace root angle and diameter in maize

Brace roots are the main organ to support the above-ground part of maize plant. It involves in plant growth and development by water absorption and lodging resistance. The bracing root angle (BRA) and diameter (BRD) are important components of brace root traits. Illuminating the genetic basis of BRA and BRD will contribute the improvement for mechanized harvest and increasing production. A GWAS of BRA and BRD was conducted using an associated panel composed of 508 inbred lines of maize. The broad-sense heritability of BRA and BRD was estimated to be respectively 71% ± 0.19 and 52% ± 0.14. The phenotypic variation of BRA and BRD in the non-stiff stalk subgroup (NSS) and the stiff stalk subgroup (SS) subgroups are significantly higher than that in the tropical/subtropical subgroup (TST) subgroups. In addition, BRA and BRD are significantly positive with plant height (PH), ear length (EL), and kernel number per row (KNPR). GWAS revealed 27 candidate genes within the threshold of p < 1.84 × 10⁻⁶ by both MLM and BLINK models. Among them, three genes, GRMZM2G174736, GRMZM2G445169 and GRMZM2G479243 were involved in cell wall function, and GRMZM2G038073 encoded the NAC transcription factor family proteins. These results provide theoretical support for clarifying the genetic basis of brace roots traits.

GWAS and Transcriptome Analysis Reveal Key Genes Affecting Root Growth under Low Nitrogen Supply in Maize

Nitrogen (N) is one of the most important factors affecting crop production. Root morphology exhibits a high degree of plasticity to nitrogen deficiency. However, the mechanisms underlying the root foraging response under low-N conditions remain poorly understood. In this study, we analyzed 213 maize inbred lines using hydroponic systems and regarding their natural variations in 22 root traits and 6 shoot traits under normal (2 mM nitrate) and low-N (0 mM nitrate) conditions. Substantial phenotypic variations were detected for all traits. N deficiency increased the root length and decreased the root diameter and shoot related traits. A total of 297 significant marker-trait associations were identified by a genome-wide association study involving different N levels and the N response value. A total of 51 candidate genes with amino acid variations in coding regions or differentially expressed under low nitrogen conditions were identified. Furthermore, a candidate gene ZmNAC36 was resequenced in all tested lines. A total of 38 single nucleotide polymorphisms and 12 insertions and deletions were significantly associated with lateral root length of primary root, primary root length between 0 and 0.5 mm in diameter, primary root surface area, and total length of primary root under a low-N condition. These findings help us to improve our understanding of the genetic mechanism of root plasticity to N deficiency, and the identified loci and candidate genes will be useful for the genetic improvement of maize tolerance cultivars to N deficiency.

Genome-wide association study reveals that GhTRL1 and GhPIN8 affect cotton root development

Two regions located at chromosome A05 and D04 were found to be significantly associated with 0-0.5 mm and 0.5-2 mm diameter roots, respectively, and two candidate genes related to root development were identified. Roots absorb water and nutrients, and play an important role in plant growth. However, there are few genetic developmental studies on cotton root structural traits. In this study, we used 200 upland cotton (Gossypium hirsutum L.) varieties to analyze the phenotypic variation of 43 traits. A total of 2001 related single-nucleotide polymorphism (SNP) sites located within or near 1046 genes were detected through a genome-wide association study (GWAS). The 32 root traits were linked to SNPs that corresponded to 317 nonrepetitive genes. For SNPs associated with root length and 0-0.5 mm diameter root traits, a significant peak appeared on chromosome A05 (between 21.91 and 22.24 Mb). For SNPs associated with root surface area, root volume and 0.5-2 mm diameter root traits, a significant peak appeared on chromosome D04 (between 7.35 and 7.70 Mb). Within these two key regions, SNPs were detected in the promoter and coding regions of two candidate genes, GhTRL1-A05 and GhPIN8-D04. The expression levels of these two genes also changed significantly according to transcriptome sequencing and quantitative real-time PCR (qRT-PCR). After silencing the GhTRL1 and GhPIN8 genes via virus-induced gene silencing (VIGS), we found that the plants expressing TRV2::GhTRL1 and TRV2::GhPIN8 had a reduced root length, surface area. Moreover, the contents of cis-12-oxo-phytodienoic acid (cis-OPDA), isopentenyl adenosine (iPR) and cis-zeatin (cZ) in the roots of the plants expressing TRV2::GhTRL1 decreased. This study contributes to the cultivation and improvement of cotton varieties.

GWAS and RNA-seq analysis uncover candidate genes associated with alkaline stress tolerance in maize (Zea mays L.) seedlings

Soil salt-alkalization is a common yet critical environmental stress factor for plant growth and development. Discovering and exploiting genes associated with alkaline tolerance in maize (Zea mays L.) is helpful for improving alkaline resistance. Here, an association panel consisting of 200 maize lines was used to identify the genetic loci responsible for alkaline tolerance-related traits in maize seedlings. A total of nine single-nucleotide polymorphisms (SNPs) and their associated candidate genes were found to be significantly associated with alkaline tolerance using a genome-wide association study (GWAS). An additional 200 genes were identified when the screen was extended to include a linkage disequilibrium (LD) decay distance of r2 ≥ 0.2 from the SNPs. RNA-sequencing (RNA-seq) analysis was then conducted to confirm the linkage between the candidate genes and alkali tolerance. From these data, a total of five differentially expressed genes (DEGs; |log2FC| ≥ 0.585, p < 0.05) were verified as the hub genes involved in alkaline tolerance. Subsequently, two candidate genes, Zm00001d038250 and Zm00001d001960, were verified to affect the alkaline tolerance of maize seedlings by qRT-PCR analysis. These genes were putatively involved protein binding and "flavonoid biosynthesis process," respectively, based on Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses. Gene promoter region contains elements related to stress and metabolism. The results of this study will help further elucidate the mechanisms of alkaline tolerance in maize, which will provide the groundwork for future breeding projects.

Identification of a unique allele in the quantitative trait locus for crown root number in japonica rice from Japan using genome-wide association studies

To explore the genetic resources that could be utilized to help improve root system architecture phenotypes in rice (Oryza sativa), we have conducted genome-wide association studies to investigate maximum root length and crown root number in 135 10-day-old Japanese rice accessions grown hydroponically. We identified a quantitative trait locus for crown root number at approximately 32.7 Mbp on chromosome 4 and designated it qNCR1 (quantitative trait locus for Number of Crown Root 1). A linkage disequilibrium map around qNCR1 suggested that three candidate genes are involved in crown root number: a cullin (LOC_Os04g55030), a gibberellin 20 oxidase 8 (LOC_Os04g55070), and a cyclic nucleotide-gated ion channel (LOC_Os04g55080). The combination of haplotypes for each gene was designated as a haploblock, and haploblocks 1, 2, and 3 were defined. Compared to haploblock 1, the accessions with haploblocks 2 and 3 had fewer crown roots; approximately 5% and 10% reductions in 10-day-old plants and 15% and 25% reductions in 42-day-old plants, respectively. A Japanese leading variety Koshihikari and its progenies harbored haploblock 3. Their crown root number could potentially be improved using haploblocks 1 and 2.

Genome-Wide Association Studies of Maize Seedling Root Traits under Different Nitrogen Levels

Nitrogen (N) is one of the important factors affecting maize root morphological construction and growth development. An association panel of 124 maize inbred lines was evaluated for root and shoot growth at seedling stage under normal N (CK) and low N (LN) treatments, using the paper culture method. Twenty traits were measured, including three shoot traits and seventeen root traits, a genome-wide association study (GWAS) was performed using the Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) methods. The results showed that LN condition promoted the growth of the maize roots, and normal N promoted the growth of the shoots. A total of 185 significant SNPs were identified, including 27 SNPs for shoot traits and 158 SNPs for root traits. Four important candidate genes were identified. Under LN conditions, the candidate gene Zm00001d004123 was significantly correlated with the number of crown roots, Zm00001d025554 was correlated with plant height. Under CK conditions, the candidate gene Zm00001d051083 was correlated with the length and area of seminal roots, Zm00001d050798 was correlated with the total root length. The four candidate genes all responded to the LN treatment. The research results provide genetic resources for the genetic improvement of maize root traits.

Phenotypic Diversity and Association Mapping of Ascorbic Acid Content in Spinach

Ascorbic acid (AsA), or vitamin C, is an essential nutrient for humans. In plants, AsA functions as an antioxidant during normal metabolism or in response to stress. Spinach is a highly nutritious green leafy vegetable that is consumed fresh, cooked or as a part of other dishes. One current goal in spinach breeding programs is to enhance quality and nutritional content. However, little is known about the diversity of nutritional content present in spinach germplasm, especially for AsA content. In this study, a worldwide panel of 352 accessions was screened for AsA content showing that variability in spinach germplasm is high and could be utilized for cultivar improvement. In addition, a genome-wide association study for marker-trait association was performed using three models, and associated markers were searched in the genome for functional annotation analysis. The generalized linear model (GLM), the compressed mixed linear model (CMLM) based on population parameters previously determined (P3D) and the perMarker model together identified a total of 490 significant markers distributed across all six spinach chromosomes indicating the complex inheritance of the trait. The different association models identified unique and overlapping marker sets, where 27 markers were identified by all three models. Identified high AsA content accessions can be used as parental lines for trait introgression and to create segregating populations for further genetic analysis. Bioinformatic analysis indicated that identified markers can differentiate between high and low AsA content accessions and that, upon validation, these markers should be useful for breeding programs.

Association mapping uncovers maize ZmbZIP107 regulating root system architecture and lead absorption under lead stress

Lead (Pb) is a highly toxic contaminant to living organisms and the environment. Excessive Pb in soils affects crop yield and quality, thus threatening human health via the food chain. Herein, we investigated Pb tolerance among a maize association panel using root bushiness (BSH) under Pb treatment as an indicator. Through a genome-wide association study of relative BSH, we identified four single nucleotide polymorphisms (SNPs) and 30 candidate genes associated with Pb tolerance in maize seedlings. Transcriptome analysis showed that four of the 30 genes were differentially responsive to Pb treatment between two maize lines with contrasting Pb tolerance. Among these, the ZmbZIP107 transcription factor was confirmed as the key gene controlling maize tolerance to Pb by using gene-based association studies. Two 5' UTR_variants in ZmbZIP107 affected its expression level and Pb tolerance among different maize lines. ZmbZIP107 protein was specifically targeted to the nucleus and ZmbZIP107 mRNA showed the highest expression in maize seedling roots among different tissues. Heterologous expression of ZmbZIP107 enhanced rice tolerance to Pb stress and decreased Pb absorption in the roots. Our study provided the basis for revelation of the molecular mechanism underlying Pb tolerance and contributed to cultivation of Pb-tolerant varieties in maize.

Omics for the Improvement of Abiotic, Biotic, and Agronomic Traits in Major Cereal Crops: Applications, Challenges, and Prospects

Omics technologies, namely genomics, transcriptomics, proteomics, metabolomics, and phenomics, are becoming an integral part of virtually every commercial cereal crop breeding program, as they provide substantial dividends per unit time in both pre-breeding and breeding phases. Continuous advances in omics assure time efficiency and cost benefits to improve cereal crops. This review provides a comprehensive overview of the established omics methods in five major cereals, namely rice, sorghum, maize, barley, and bread wheat. We cover the evolution of technologies in each omics section independently and concentrate on their use to improve economically important agronomic as well as biotic and abiotic stress-related traits. Advancements in the (1) identification, mapping, and sequencing of molecular/structural variants; (2) high-density transcriptomics data to study gene expression patterns; (3) global and targeted proteome profiling to study protein structure and interaction; (4) metabolomic profiling to quantify organ-level, small-density metabolites, and their composition; and (5) high-resolution, high-throughput, image-based phenomics approaches are surveyed in this review.

Genome-wide association study and transcriptome analysis reveal key genes affecting root growth dynamics in rapeseed

BACKGROUND

In terms of global demand, rapeseed is the third-largest oilseed crop after soybeans and palm, which produces vegetable oil for human consumption and biofuel for industrial production. Roots are vital organs for plant to absorb water and attain mineral nutrients, thus they are of great importance to plant productivity. However, the genetic mechanisms regulating root development in rapeseed remain unclear. In the present study, seven root-related traits and shoot biomass traits in 280 Brassica napus accessions at five continuous vegetative stages were measured to establish the genetic basis of root growth in rapeseed.

RESULTS

The persistent and stage-specific genetic mechanisms were revealed by root dynamic analysis. Sixteen persistent and 32 stage-specific quantitative trait loci (QTL) clusters were identified through genome-wide association study (GWAS). Root samples with contrasting (slow and fast) growth rates throughout the investigated stages and those with obvious stage-specific changes in growth rates were subjected to transcriptome analysis. A total of 367 differentially expressed genes (DEGs) with persistent differential expressions throughout root development were identified, and these DEGs were significantly enriched in GO terms, such as energy metabolism and response to biotic or abiotic stress. Totally, 485 stage-specific DEGs with different expressions at specific stage were identified, and these DEGs were enriched in GO terms, such as nitrogen metabolism. Four candidate genes were identified as key persistent genetic factors and eight as stage-specific ones by integrating GWAS, weighted gene co-expression network analysis (WGCNA), and differential expression analysis. These candidate genes were speculated to regulate root system development, and they were less than 100 kb away from peak SNPs of QTL clusters. The homologs of three genes (BnaA03g52990D, BnaA06g37280D, and BnaA09g07580D) out of 12 candidate genes have been reported to regulate root development in previous studies.

CONCLUSIONS

Sixteen QTL clusters and four candidate genes controlling persistently root development, and 32 QTL clusters and eight candidate genes stage-specifically regulating root growth in rapeseed were detected in this study. Our results provide new insights into the temporal genetic mechanisms of root growth by identifying key candidate QTL/genes in rapeseed.

Exploiting natural variation in crown root traits via genome-wide association studies in maize

BACKGROUND

Root system architecture (RSA), which is determined by the crown root angle (CRA), crown root diameter (CRD), and crown root number (CRN), is an important factor affecting the ability of plants to obtain nutrients and water from the soil. However, the genetic mechanisms regulating crown root traits in the field remain unclear.

METHODS

In this study, the CRA, CRD, and CRN of 316 diverse maize inbred lines were analysed in three field trials. Substantial phenotypic variations were observed for the three crown root traits in all environments. A genome-wide association study was conducted using two single-locus methods (GLM and MLM) and three multi-locus methods (FarmCPU, FASTmrMLM, and FASTmrEMMA) with 140,421 SNP.

RESULTS

A total of 38 QTL including 126 SNPs were detected for CRA, CRD, and CRN. Additionally, 113 candidate genes within 50 kb of the significant SNPs were identified. Combining the gene annotation information and the expression profiles, 3 genes including GRMZM2G141205 (IAA), GRMZM2G138511 (HSP) and GRMZM2G175910 (cytokinin-O-glucosyltransferase) were selected as potentially candidate genes related to crown root development. Moreover, GRMZM2G141205, encoding an AUX/IAA transcriptional regulator, was resequenced in all tested lines. Five variants were identified as significantly associated with CRN in different environments. Four haplotypes were detected based on these significant variants, and Hap1 has more CRN.

CONCLUSIONS

These findings may be useful for clarifying the genetic basis of maize root system architecture. Furthermore, the identified candidate genes and variants may be relevant for breeding new maize varieties with root traits suitable for diverse environmental conditions.

Primary Root and Mesocotyl Elongation in Maize Seedlings: Two Organs with Antagonistic Growth below the Soil Surface

Maize illustrates one of the most complex cases of embryogenesis in higher plants that results in the development of early embryo with distinctive organs such as the mesocotyl, seminal and primary roots, coleoptile, and plumule. After seed germination, the elongation of root and mesocotyl follows opposite directions in response to specific tropisms (positive and negative gravitropism and hydrotropism). Tropisms represent the differential growth of an organ directed toward several stimuli. Although the life cycle of roots and mesocotyl takes place in darkness, their growth and functions are controlled by different mechanisms. Roots ramify through the soil following the direction of the gravity vector, spreading their tips into new territories looking for water; when water availability is low, the root hydrotropic response is triggered toward the zone with higher moisture. Nonetheless, there is a high range of hydrotropic curvatures (angles) in maize. The processes that control root hydrotropism and mesocotyl elongation remain unclear; however, they are influenced by genetic and environmental cues to guide their growth for optimizing early seedling vigor. Roots and mesocotyls are crucial for the establishment, growth, and development of the plant since both help to forage water in the soil. Mesocotyl elongation is associated with an ancient agriculture practice known as deep planting. This tradition takes advantage of residual soil humidity and continues to be used in semiarid regions of Mexico and USA. Due to the genetic diversity of maize, some lines have developed long mesocotyls capable of deep planting while others are unable to do it. Hence, the genetic and phenetic interaction of maize lines with a robust hydrotropic response and higher mesocotyl elongation in response to water scarcity in time of global heating might be used for developing more resilient maize plants.

Integrating transcriptome, co-expression and QTL-seq analysis reveals that primary root growth in maize is regulated via flavonoid biosynthesis and auxin signal transduction

The primary root is critical for early seedling growth and survival. To understand the molecular mechanisms governing primary root development, we performed a dynamic transcriptome analysis of two maize (Zea mays) inbred lines with contrasting primary root length at nine time points over a 12-day period. A total of 18 702 genes were differentially expressed between two lines or different time points. Gene enrichment, phytohormone content determination, and metabolomics analysis showed that auxin biosynthesis and signal transduction, as well as the phenylpropanoid and flavonoid biosynthesis pathways, were associated with root development. Co-expression network analysis revealed that eight modules were associated with lines/stages, as well as primary or lateral root length. In root-related modules, flavonoid metabolism accompanied by auxin biosynthesis and signal transduction constituted a complex gene regulatory network during primary root development. Two candidate genes (rootless concerning crown and seminal roots, rtcs and Zm00001d012781) involved in auxin signaling and flavonoid biosynthesis were identified by co-expression network analysis, QTL-seq and functional annotation. These results increase our understanding of the regulatory network controlling the development of primary and lateral root length, and provide a valuable genetic resource for improvement of root performance in maize.

Genetic control of root plasticity in response to salt stress in maize

GWAS identified 559 significant SNPs associated with the remodelling of the root architecture in response to salt, and 168 candidate genes were prioritized by integrating RNA-seq, DEG and WGCNA data. Salinity is a major environmental factor limiting crop growth and productivity. The root is the first plant organ to encounter salt stress, yet the effects of salinity on maize root development remain unclear. In this study, the natural variations in 14 root and 4 shoot traits were evaluated in 319 maize inbred lines under control and saline conditions. Considerable phenotypic variations were observed for all traits, with high salt concentrations decreasing the root length, but increasing the root diameter. A genome-wide association study was conducted to analyse these traits and their plasticity (relative variation). We detected 559 significant single nucleotide polymorphisms, of which 125, 181 and 253 were associated with the control condition, stress condition and trait plasticity, respectively. A total of 168 of 587 candidate genes identified by genome-wide association study were supported by the differentially expressed genes or co-expression networks. Two candidate genes ZmIAA1 and ZmGRAS43 were validated by resequencing. Among these genes, 130 were detected under stress condition or trait plasticity that involved in diverse biological processes including plant hormone signal transduction, phenylpropanoid biosynthesis and fatty acid biosynthesis. Our findings clarify the root remodelling to salinity, and the identified loci and candidate genes may be important for the genetic improvement of root traits and salt tolerance in maize.

A novel motif in the 5'-UTR of an orphan gene 'Big Root Biomass' modulates root biomass in sesame

Developing crops with improved root system is crucial in current global warming scenario. Underexploited crops are valuable reservoirs of unique genes that can be harnessed for the improvement of major crops. In this study, we performed genome-wide association studies on seven root traits in sesame (Sesamum indicum L.) and uncovered 409 significant signals, 19 quantitative trait loci containing 32 candidate genes. A peak SNP significantly associated with root number and root dry weight traits was located in the promoter of the gene named 'Big Root Biomass' (BRB), which was subsequently validated in a bi-parental population. BRB has no functional annotation and is restricted to the Lamiales order. We detected the presence of a novel motif 'AACACACAC' located in the 5'-UTR of BRB in single and duplicated copy in accessions with high and small root biomass, respectively. A strong expression level of BRB was negatively correlated with high root biomass, and this was attributed to the gene SiMYB181 which represses the activity of BRB by binding specifically to the single motif but not to the duplicated one. Curiously, the allele that enhanced BRB expression has been intensively selected by modern breeding. Overexpression of BRB in Arabidopsis modulates auxin pathway leading to reduced root biomass, improved yield parameters under normal growth conditions and increased drought stress sensitivity. Overall, BRB represents a solid gene model for improving the performance of sesame and other crops.