Genome-Wide Association Study of 13 Traits in Maize Seedlings under Low Phosphorus Stress

Characterization and functional analysis of conserved non-coding sequences among poaceae: insights into gene regulation and phenotypic variation in maize

BACKGROUND

Conserved non-coding sequences (CNS) are islands of non-coding sequences conserved across species and play an important role in regulating the spatiotemporal expression of genes. Identification of CNS provides valuable information about potentially functional genomic elements, regulatory regions, and helps to gain insights into the genetic basis of crop agronomic traits.

RESULTS

Here, we comprehensively analyze CNS in maize, by comparing the genomes of maize inbred line B73 (Zea mays ssp. mays), its close wild relative Zea mays spp. mexicana, and other grasses in Poaceae, including sorghum (Sorghum bicolor), foxtail millet (Setaria italica) and two adlay (Coix lacryma) cultivars. There were 289,931 CNS found in two syntenic gene pairs, while 51,701 CNS were conserved within at least three species. To explore the regulatory characteristics of the CNS identified, the flanking regions of CNS were compared with the peaks called using both transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) and chromatin immunoprecipitation with high-throughput sequencing (ChIP-Seq) data of histone modifications. It was found that CNS in maize were enriched in open chromatin regions compared with randomly selected non-coding regions of similar length. A significant enrichment of transcription factor binding sites was found within CNS sequences, including different transcription factors involved in abiotic stress response, such as OBP (OBF-BINDING PROTEIN) family and Adof1 (Encodes dof zinc finger protein). To investigate the epigenetic modification patterns in CNS, ChIP-Seq data for histone modifications H3K9ac, H3K4me3, H3K36me3, H3K9me3, and H3K27ac were further analyzed to depict the changes along CNS. Our findings revealed significantly elevated levels of transcription-promoting histone modifications in the CNS regions compared to randomly selected non-coding sequences with an equal number and similar length. Notably, CNS were also identified on both Vgt1 (Vegetative to generative transition 1) and ZmCCT10. In addition, CNS with potential functions were identified based on SNPs within CNS significantly associated with various agronomic traits in maize, which holds potential utility in molecular breeding for maize.

CONCLUSIONS

In summary, we identified and characterized CNS in maize through genomic comparative analysis, which provides valuable insights into their potential regulatory effects on gene expression and phenotypic variation.

Genetic diversity, relationships among traits and selection of tropical maize inbred lines for low-P tolerance based on root and shoot traits at seedling stage

The tropical maize breeding for low-P tolerance and good performance under low-P stress environments can be achieved through selection based on root morphology traits at seedling stage. Here, we assessed the genotypic variation and genetic diversity of a panel of 151 tropical maize inbred lines for root and shoot seedling traits, investigated the relationship among traits and selected a set of promising inbred lines for low-P tolerance and performance. We evaluated the inbred lines at seedling stage in a greenhouse experiment under two conditions: applied P (AP) and non-applied P (NAP). A mixed model approach was used to estimate variance components and predict the genotypic values of each inbred line. The genetic diversity among inbred lines based on root and shoot traits was assessed, and correlations were estimated between tested traits under AP and NAP. Our panel of inbred lines showed huge genetic variability for all traits and presented large genetic diversity under both P conditions. Variance components due to the inbred line × P condition interaction were also highly significant (P < 0.01) for all traits. Root dry weight (RDW) was positively associated with stalk dimeter (SD), shoot dry weight (SDW) and root length, volume, and area under both P conditions. Also, the SD and SDW were associated with most root traits under AP. Based on low-P tolerance and performance indices, we selected a set of top 20 inbred lines to be used in our maize breeding program. We therefore concluded that there is a significant genetic diversity in the tropical maize inbred lines which have the genetic potential to be use in association mapping studies and also to develop improved low-P tolerant and P-efficient hybrids and maize breeding populations for low-P stress environments.

Multi-locus genome-wide association study for phosphorus use efficiency in a tropical maize germplasm

Phosphorus (P) is an essential macronutrient for maize (Zea mays L.) growth and development. Therefore, generating cultivars with upgraded P use efficiency (PUE) represents one of the main strategies to reduce the global agriculture dependence on phosphate fertilizers. In this work, genome-wide association studies (GWAS) were performed to detect quantitative trait nucleotide (QTN) and potential PUE-related candidate genes and associated traits in greenhouse and field trials under contrasting P conditions. The PUE and other agronomy traits of 132 maize inbred lines were assessed in low and normal P supply through the greenhouse and field experiments and Multi-locus GWAS was used to map the associated QTNs. Wide genetic variability was observed among the maize inbred lines under low and normal P supply. In addition, we confirm the complex and quantitative nature of PUE. A total of 306 QTNs were associated with the 24 traits evaluated using different multi-locus GWAS methods. A total of 186 potential candidate genes were identified, mainly involved with transcription regulator, transporter, and transference activity. Further studies are still needed to elucidate the functions and relevance of these genes regarding PUE. Nevertheless, pyramiding the favorable alleles pinpointed in the present study can be considered an efficient strategy for molecular improvement to increase maize PUE.

Genome-wide association studies dissect low-phosphorus stress response genes underling field and seedling traits in maize

Phosphorus (P) is an essential element for plant growth, and its deficiency can cause decreased crop yield. This study systematically evaluated the low-phosphate (Pi) response traits in a large population at maturity and seedling stages, and explored candidate genes and their interrelationships with specific traits. The results revealed a greater sensitivity of seedling maize to low-Pi stress compared to that at maturity stage. The phenotypic response patterns to low-Pi stress at different stages were independent. Chlorophyll content was found to be a potential indicator for screening low-Pi-tolerant materials in the field. A total of 2900 and 1446 significantly associated genes at the maturity and seedling stages were identified, respectively. Among these genes, 972 were uniquely associated with maturity traits, while 330 were specifically detected at the seedling stage under low-Pi stress. Moreover, 768 and 733 genes were specifically associated with index values (low-Pi trait/normal-Pi trait) at maturity and seedling stage, respectively. Genetic network diagrams showed that the low-Pi response gene Zm00001d022226 was specifically associated with multiple primary P-related traits under low-Pi conditions. A total of 963 out of 2966 genes specifically associated with traits under low-Pi conditions or index values were found to be induced by low-Pi stress. Notably, ZmSPX4.1 and ZmSPX2 were sharply up-regulated in response to low-Pi stress across different lines or tissues. These findings advance our understanding of maize's response to low-Pi stress at different developmental stages, shedding light on the genes and pathways implicated in this response.

The Myb73-GDPD2-GA2ox1 transcriptional regulatory module confers phosphate deficiency tolerance in soybean

Phosphorus is indispensable in agricultural production. An increasing food supply requires more efficient use of phosphate due to limited phosphate resources. However, how crops regulate phosphate efficiency remains largely unknown. Here, we identified a major quantitative trait locus, qPE19, that controls 7 low-phosphate (LP)-related traits in soybean (Glycine max) through linkage mapping and genome-wide association studies. We identified the gene responsible for qPE19 as GLYCEROPHOSPHORYL DIESTER PHOSPHODIESTERASE2 (GmGDPD2), and haplotype 5 represents the optimal allele favoring LP tolerance. Overexpression of GmGDPD2 significantly affects hormone signaling and improves root architecture, phosphate efficiency and yield-related traits; conversely, CRISPR/Cas9-edited plants show decreases in these traits. GmMyb73 negatively regulates GmGDPD2 by directly binding to its promoter; thus, GmMyb73 negatively regulates LP tolerance. GmGDPD2 physically interacts with GA 2-oxidase 1 (GmGA2ox1) in the plasma membrane, and overexpressing GmGA2ox1 enhances LP-associated traits, similar to GmGDPD2 overexpression. Analysis of double mutants for GmGDPD2 and GmGA2ox1 demonstrated that GmGDPD2 regulates LP tolerance likely by influencing auxin and gibberellin dose-associated cell division in the root. These results reveal a regulatory module that plays a major role in regulating LP tolerance in soybeans and is expected to be utilized to develop phosphate-efficient varieties to enhance soybean production, particularly in phosphate-deficient soils.

Natural variation in root traits identifies significant SNPs and candidate genes for phosphate deficiency tolerance in Zea mays L

Phosphorus (P) is a crucial macronutrient required for normal plant growth. Its effective uptake from the soil is a trait of agronomic importance. Natural variation in maize (339 accessions) root traits, namely root length and number of primary, seminal, and crown roots, root and shoot phosphate (Pi) contents, and root-to-shoot Pi translocation (root: shoot Pi) under normal (control, 40 ppm) and low phosphate (LP, 1 ppm) conditions, were used for genome-wide association studies (GWAS). The Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) model of GWAS provided 23 single nucleotide polymorphisms (SNPs) and 12 relevant candidate genes putatively linked with root Pi, root: shoot Pi, and crown root number (CRN) under LP. The DNA-protein interaction analysis of Zm00001d002842, Zm00001d002837, Zm00001d002843 for root Pi, and Zm00001d044312, Zm00001d045550, Zm00001d025915, Zm00001d044313, Zm00001d051842 for root: shoot Pi, and Zm00001d031561, Zm00001d001803, and Zm00001d001804 for CRN showed the presence of potential binding sites of key transcription factors like MYB62, bZIP11, ARF4, ARF7, ARF10 and ARF16 known for induction/suppression of phosphate starvation response (PHR). The in-silico RNA-seq analysis revealed up or down-regulation of candidate genes along with key transcription factors of PHR, while Uniprot analysis provided genetic relatedness. Candidate genes that may play a role in P uptake and root-to-shoot Pi translocation under LP are proposed using common PHR signaling components like MYB62, ARF4, ARF7, ARF10, ARF16, and bZIP11 to induce changes in root growth in maize. Candidate genes may be used to improve low P tolerance in maize using the CRISPR strategy.

Advancements and Prospects of Genome-Wide Association Studies (GWAS) in Maize

Genome-wide association studies (GWAS) have emerged as a powerful tool for unraveling intricate genotype-phenotype association across various species. Maize (Zea mays L.), renowned for its extensive genetic diversity and rapid linkage disequilibrium (LD), stands as an exemplary candidate for GWAS. In maize, GWAS has made significant advancements by pinpointing numerous genetic loci and potential genes associated with complex traits, including responses to both abiotic and biotic stress. These discoveries hold the promise of enhancing adaptability and yield through effective breeding strategies. Nevertheless, the impact of environmental stress on crop growth and yield is evident in various agronomic traits. Therefore, understanding the complex genetic basis of these traits becomes paramount. This review delves into current and future prospectives aimed at yield, quality, and environmental stress resilience in maize and also addresses the challenges encountered during genomic selection and molecular breeding, all facilitated by the utilization of GWAS. Furthermore, the integration of omics, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics has enriched our understanding of intricate traits in maize, thereby enhancing environmental stress tolerance and boosting maize production. Collectively, these insights not only advance our understanding of the genetic mechanism regulating complex traits but also propel the utilization of marker-assisted selection in maize molecular breeding programs, where GWAS plays a pivotal role. Therefore, GWAS provides robust support for delving into the genetic mechanism underlying complex traits in maize and enhancing breeding strategies.

Integrating genome-wide association study with transcriptomic data to predict candidate genes influencing Brassica napus root and biomass-related traits under low phosphorus conditions

BACKGROUND

Rapeseed (Brassica napus L.) is an essential source of edible oil and livestock feed, as well as a promising source of biofuel. Breeding crops with an ideal root system architecture (RSA) for high phosphorus use efficiency (PUE) is an effective way to reduce the use of phosphate fertilizers. However, the genetic mechanisms that underpin PUE in rapeseed remain elusive. To address this, we conducted a genome-wide association study (GWAS) in 327 rapeseed accessions to elucidate the genetic variability of 13 root and biomass traits under low phosphorus (LP; 0.01 mM P +). Furthermore, RNA-sequencing was performed in root among high/low phosphorus efficient groups (HP1/LP1) and high/low phosphorus stress tolerance groups (HP2/LP2) at two-time points under control and P-stress conditions.

RESULTS

Significant variations were observed in all measured traits, with heritabilities ranging from 0.47 to 0.72, and significant correlations were found between most of the traits. There were 39 significant trait-SNP associations and 31 suggestive associations, which integrated into 11 valid quantitative trait loci (QTL) clusters, explaining 4.24-24.43% of the phenotypic variance observed. In total, RNA-seq identified 692, 1076, 648, and 934 differentially expressed genes (DEGs) specific to HP1/LP1 and HP2/LP2 under P-stress and control conditions, respectively, while 761 and 860 DEGs common for HP1/LP1 and HP2/LP2 under both conditions. An integrated approach of GWAS, weighted co-expression network, and differential expression analysis identified 12 genes associated with root growth and development under LP stress. In this study, six genes (BnaA04g23490D, BnaA09g08440D, BnaA09g04320D, BnaA09g04350D, BnaA09g04930D, BnaA09g09290D) that showed differential expression were identified as promising candidate genes for the target traits.

CONCLUSION

11 QTL clusters and 12 candidate genes associated with root and development under LP stress were identified in this study. Our study's phenotypic and genetic information may be exploited for genetic improvement of root traits to increase PUE in rapeseed.

Weighted kernels improve multi-environment genomic prediction

Crucial to variety improvement programs is the reliable and accurate prediction of genotype's performance across environments. However, due to the impactful presence of genotype by environment (G×E) interaction that dictates how changes in expression and function of genes influence target traits in different environments, prediction performance of genomic selection (GS) using single-environment models often falls short. Furthermore, despite the successes of genome-wide association studies (GWAS), the genetic insights derived from genome-to-phenome mapping have not yet been incorporated in predictive analytics, making GS models that use Gaussian kernel primarily an estimator of genomic similarity, instead of the underlying genetics characteristics of the populations. Here, we developed a GS framework that, in addition to capturing the overall genomic relationship, can capitalize on the signal of genetic associations of the phenotypic variation as well as the genetic characteristics of the populations. The capacity of predicting the performance of populations across environments was demonstrated by an overall gain in predictability up to 31% for the winter wheat DH population. Compared to Gaussian kernels, we showed that our multi-environment weighted kernels could better leverage the significance of genetic associations and yielded a marked improvement of 4-33% in prediction accuracy for half-sib families. Furthermore, the flexibility incorporated in our Bayesian implementation provides the generalizable capacity required for predicting multiple highly genetic heterogeneous populations across environments, allowing reliable GS for genetic improvement programs that have no access to genetically uniform material.

Genetic Dissection of Phosphorus Use Efficiency and Genotype-by-Environment Interaction in Maize

Genotype-by-environment interaction (G-by-E) is a common but potentially problematic phenomenon in plant breeding. In this study, we investigated the genotypic performance and two measures of plasticity on a phenotypic and genetic level by assessing 234 maize doubled haploid lines from six populations for 15 traits in seven macro-environments with a focus on varying soil phosphorus levels. It was found intergenic regions contributed the most to the variation of phenotypic linear plasticity. For 15 traits, 124 and 31 quantitative trait loci (QTL) were identified for genotypic performance and phenotypic plasticity, respectively. Further, some genes associated with phosphorus use efficiency, such as Zm00001eb117170, Zm00001eb258520, and Zm00001eb265410, encode small ubiquitin-like modifier E3 ligase were identified. By significantly testing the main effect and G-by-E effect, 38 main QTL and 17 interaction QTL were identified, respectively, in which MQTL38 contained the gene Zm00001eb374120, and its effect was related to phosphorus concentration in the soil, the lower the concentration, the greater the effect. Differences in the size and sign of the QTL effect in multiple environments could account for G-by-E. At last, the superiority of G-by-E in genomic selection was observed. In summary, our findings will provide theoretical guidance for breeding P-efficient and broadly adaptable varieties.

Combining datasets for maize root seedling traits increases the power of GWAS and genomic prediction accuracies

The identification of genomic regions associated with root traits and the genomic prediction of untested genotypes can increase the rate of genetic gain in maize breeding programs targeting roots traits. Here, we combined two maize association panels with different genetic backgrounds to identify single nucleotide polymorphisms (SNPs) associated with root traits, and used a genome-wide association study (GWAS) and to assess the potential of genomic prediction for these traits in maize. For this, we evaluated 377 lines from the Ames panel and 302 from the Backcrossed Germplasm Enhancement of Maize (BGEM) panel in a combined panel of 679 lines. The lines were genotyped with 232 460 SNPs, and four root traits were collected from 14-day-old seedlings. We identified 30 SNPs significantly associated with root traits in the combined panel, whereas only two and six SNPs were detected in the Ames and BGEM panels, respectively. Those 38 SNPs were in linkage disequilibrium with 35 candidate genes. In addition, we found higher prediction accuracy in the combined panel than in the Ames or BGEM panel. We conclude that combining association panels appears to be a useful strategy to identify candidate genes associated with root traits in maize and improve the efficiency of genomic prediction.

The pho1;2a'-m1.1 allele of Phosphate1 conditions misregulation of the phosphorus starvation response in maize (Zea mays ssp. mays L.)

Plant PHO1 proteins play a central role in the translocation and sensing of inorganic phosphate. The maize (Zea mays ssp. mays) genome encodes two co-orthologs of the Arabidopsis PHO1 gene, designated ZmPho1;2a and ZmPho1;2b. Here, we report the characterization of the transposon footprint allele Zmpho1;2a'-m1.1, which we refer to hereafter as pho1;2a. The pho1;2a allele is a stable derivative formed by excision of an Activator transposable element from the ZmPho1;2a gene. The pho1;2a allele contains an 8-bp insertion at the point of transposon excision that disrupts the reading frame and is predicted to generate a premature translational stop. We show that the pho1;2a allele is linked to a dosage-dependent reduction in Pho1;2a transcript accumulation and a mild reduction in seedling growth. Characterization of shoot and root transcriptomes under full nutrient, low nitrogen, low phosphorus, and combined low nitrogen and low phosphorus conditions identified 1100 differentially expressed genes between wild-type plants and plants carrying the pho1;2a mutation. Of these 1100 genes, 966 were upregulated in plants carrying pho1;2a, indicating the wild-type PHO1;2a to predominantly impact negative gene regulation. Gene set enrichment analysis of the pho1;2a-misregulated genes revealed associations with phytohormone signaling and the phosphate starvation response. In roots, differential expression was broadly consistent across all nutrient conditions. In leaves, differential expression was largely specific to low phosphorus and combined low nitrogen and low phosphorus conditions. Of 276 genes upregulated in the leaves of pho1;2a mutants in the low phosphorus condition, 153 were themselves induced in wild-type plants with respect to the full nutrient condition. Our observations suggest that Pho1;2a functions in the fine-tuning of the transcriptional response to phosphate starvation through maintenance and/or sensing of plant phosphate status.

Genotypic variation in root architectural traits under contrasting phosphorus levels in Mediterranean and Indian origin lentil genotypes

The development of phosphorus-efficient crop cultivars boosts productivity while lowering eutrophication in the environment. It is feasible to improve the efficiency of phosphorus (P) absorption in lentils by enhancing phosphorus absorption through root architectural traits. The root architectural traits of 110 diverse lentil genotypes of Indian and Mediterranean origin were assessed, and the relationships between traits were investigated. In a hydroponics experiment, the lentil lines were examined at the seedling stage under two conditions: adequate P supply and deficient P supply. The Pearson correlation coefficients between root architectural traits and genetic diversity among lentil lines were assessed. To estimate variance components, a model (fixed factor) was used. In this experiment, both phosphorus (P) and genotype were fixed variables. Our lentil lines showed significant genetic variability and considerable genetic diversity for all traits under both treatments. The TRL (total root length) and PRL (primary root length) showed strong positive associations with all other characteristics excluding root average diameter (RAD) in both P treatments. In both P treatments, the RAD revealed a negative significant association with Total Root Tips (TRT), as well as total root volume (TRV) and total root forks (TRF) in the deficit conditions of P. Total root volume (TRV), total surface area (TSA), and total root tips had higher coefficient variance values. The first two principal components represented 67.88% and 66.19% of the overall variance in the adequate and deficit P treatments respectively. The Shannon-Weaver diversity index (H') revealed that RAD, PRL, and TSA had more variability than TRT and TRF under both treatments. According to the Comprehensive Phosphorus Efficiency Measure (CPEM), the best five highly efficient genotypes are PLL 18-09, PLS 18-01, PLL 18-25, PLS 18-23, and PLL 18-07, while IG112131, P560206, IG334, L11-231, and PLS18-67 are highly inefficient genotypes. The above contrasting diverse lentil genotypes can be utilized to produce P-efficient lentil cultivars. The lentil germplasm with potentially favorable root traits can be suggested to evaluated for other abiotic stress to use them in crop improvement programme. The scientific breakthroughs in root trait phenotyping have improved the chances of establishing trait-allele relationships. As a result, genotype-to-phenotype connections can be predicted and verified with exceptional accuracy, making it easier to find and incorporate favourable nutrition-related genes/QTLs in to breeding programme.

Genetic Variation for Traits Related to Phosphorus Use Efficiency in Lens Species at the Seedling Stage

Phosphorus (P) is an essential, non-renewable resource critical for crop productivity across the world. P is immobile in nature and, therefore, the identification of novel genotypes with efficient P uptake and utilization under a low P environment is extremely important. This study was designed to characterize eighty genotypes of different Lens species for shoot and root traits at two contrasting levels of P. A significant reduction in primary root length (PRL), total surface area (TSA), total root tips (TRT), root forks (RF), total dry weight (TDW), root dry weight (RDW) and shoot dry weight (SDW) in response to P deficiency was recorded. A principal component analysis revealed that the TDW, SDW and RDW were significantly correlated to P uptake and utilization efficiency in lentils. Based on total dry weight (TDW) under low P, L4727, EC718309, EC714238, PL-97, EC718348, DPL15, PL06 and EC718332 were found promising. The characterization of different Lens species revealed species-specific variations for the studied traits. Cultivated lentils exhibited higher P uptake and utilization efficiency as compared to the wild forms. The study, based on four different techniques, identified EC714238 as the most P use-efficient genotype. The genotypes identified in this study can be utilized for developing mapping populations and deciphering the genetics for breeding lentil varieties suited for low P environments.

Deciphering the change in root system architectural traits under limiting and non-limiting phosphorus in Indian bread wheat germplasm

The root system architectures (RSAs) largely decide the phosphorus use efficiency (PUE) of plants by influencing the phosphorus uptake. Very limited information is available on wheat's RSAs and their deciding factors affecting phosphorus uptake efficiency (PupE) due to difficulties in adopting scoring values used for evaluating root traits. Based on our earlier research experience on nitrogen uptake efficiency screening under, hydroponics and soil-filled pot conditions, a comprehensive study on 182 Indian bread wheat genotypes was carried out under hydroponics with limited P (LP) and non-limiting P (NLP) conditions. The findings revealed a significant genetic variation, root traits correlation, and moderate to high heritability for RSAs traits namely primary root length (PRL), total root length (TRL), total root surface area (TSA), root average diameter (RAD), total root volume (TRV), total root tips (TRT) and total root forks (TRF). In LP, the expressions of TRL, TRV, TSA, TRT and TRF were enhanced while PRL and RAD were diminished. An almost similar pattern of correlations among the RSAs was also observed in both conditions except for RAD. RAD exhibited significant negative correlations with PRL, TRL, TSA, TRT and TRF under LP (r = -0.45, r = -0.35, r = -0.16, r = -0.30, and r = -0.28 respectively). The subclass of TRL, TSA, TRV and TRT representing the 0-0.5 mm diameter had a higher root distribution percentage in LP than NLP. Comparatively wide range of H' value i.e. 0.43 to 0.97 in LP than NLP indicates that expression pattern of these traits are highly influenced by the level of P. In which, RAD (0.43) expression was reduced in LP, and expressions of TRF (0.91) and TSA (0.97) were significantly enhanced. The principal component analysis for grouping of traits and genotypes over LP and NLP revealed a high PC1 score indicating the presence of non-crossover interactions. Based on the comprehensive P response index value (CPRI value), the top five highly P efficient wheat genotypes namely BW 181, BW 103, BW 104, BW 143 and BW 66, were identified. Considering the future need for developing resource-efficient wheat varieties, these genotypes would serve as valuable genetic sources for improving P efficiency in wheat cultivars. This set of genotypes would also help in understanding the genetic architecture of a complex trait like P use efficiency.

Genetic Dissection of Phosphorus Use Efficiency in a Maize Association Population under Two P Levels in the Field

Phosphorus (P) deficiency is an important challenge the world faces while having to increase crop yields. It is therefore necessary to select maize (Zea may L.) genotypes with high phosphorus use efficiency (PUE). Here, we extensively analyzed the biomass, grain yield, and PUE-related traits of 359 maize inbred lines grown under both low-P and normal-P conditions. A significant decrease in grain yield per plant and biomass, an increase in PUE under low-P condition, as well as significant correlations between the two treatments were observed. In a genome-wide association study, 49, 53, and 48 candidate genes were identified for eleven traits under low-P, normal-P conditions, and in low-P tolerance index (phenotype under low-P divided by phenotype under normal-P condition) datasets, respectively. Several gene ontology pathways were enriched for the genes identified under low-P condition. In addition, seven key genes related to phosphate transporter or stress response were molecularly characterized. Further analyses uncovered the favorable haplotype for several core genes, which is less prevalent in modern lines but often enriched in a specific subpopulation. Collectively, our research provides progress in the genetic dissection and molecular characterization of PUE in maize.

Population structure and genome-wide association studies in bread wheat for phosphorus efficiency traits using 35 K Wheat Breeder's Affymetrix array

Soil bioavailability of phosphorus (P) is a major concern for crop productivity worldwide. As phosphatic fertilizers are a non-renewable resource associated with economic and environmental issues so, the sustainable option is to develop P use efficient crop varieties. We phenotyped 82 diverse wheat (Triticum aestivum L.) accessions in soil and hydroponics at low and sufficient P. To identify the genic regions for P efficiency traits, the accessions were genotyped using the 35 K-SNP array and genome-wide association study (GWAS) was performed. The high-quality SNPs across the genomes were evenly distributed with polymorphic information content values varying between 0.090 and 0.375. Structure analysis revealed three subpopulations (C1, C2, C3) and the phenotypic responses of these subpopulations were assessed for P efficiency traits. The C2 subpopulation showed the highest genetic variance and heritability values for numerous agronomically important traits as well as strong correlation under both P levels in soil and hydroponics. GWAS revealed 78 marker-trait associations (MTAs) but only 35 MTAs passed Bonferroni Correction. A total of 297 candidate genes were identified for these MTAs and their annotation suggested their involvement in several biological process. Out of 35, nine (9) MTAs were controlling polygenic trait (two controlling four traits, one controlling three traits and six controlling two traits). These multi-trait MTAs (each controlling two or more than two correlated traits) could be utilized for improving bread wheat to tolerate low P stress through marker-assisted selection (MAS).

Genome-Wide Association Analysis for Phosphorus Use Efficiency Traits in Mungbean (Vigna radiata L. Wilczek) Using Genotyping by Sequencing Approach

Mungbean (Vigna radiata L. Wilczek) is an annual grain legume crop affected by low availability of phosphorus. Phosphorus deficiency mainly affects the growth and development of plants along with changes in root morphology and increase in root-to-shoot ratio. Deciphering the genetic basis of phosphorus use efficiency (PUE) traits can benefit our understanding of mungbean tolerance to low-phosphorus condition. To address this issue, 144 diverse mungbean genotypes were evaluated for 12 PUE traits under hydroponics with optimum- and low-phosphorus levels. The broad sense heritability of traits ranged from 0.63 to 0.92 and 0.58 to 0.92 under optimum- and low-phosphorus conditions, respectively. This study, reports for the first time such a large number of genome wide Single nucleotide polymorphisms (SNPs) (76,160) in mungbean. Further, genome wide association study was conducted using 55,634 SNPs obtained by genotyping-by-sequencing method. The results indicated that total 136 SNPs shared by both GLM and MLM models were associated with tested PUE traits under different phosphorus regimes. We have identified SNPs with highest p value (-log10(p)) for some traits like, TLA and RDW with p value (-log10(p)) of more than 6.0 at LP/OP and OP condition. We have identified nine SNPs (three for TLA and six for RDW trait) which was found to be present in chromosomes 8, 4, and 7. One SNP present in Vradi07g06230 gene contains zinc finger CCCH domain. In total, 71 protein coding genes were identified, of which 13 genes were found to be putative candidate genes controlling PUE by regulating nutrient uptake and root architectural development pathways in mungbean. Moreover, we identified three potential candidate genes VRADI11G08340, VRADI01G05520, and VRADI04G10750 with missense SNPs in coding sequence region, which results in significant variation in protein structure at tertiary level. The identified SNPs and candidate genes provide the essential information for genetic studies and marker-assisted breeding program for improving low-phosphorus tolerance in mungbean.