Genome-wide association analysis of seedling root development in maize (Zea mays L.)

Leveraging Multiomics Insights and Exploiting Wild Relatives' Potential for Drought and Heat Tolerance in Maize

Climate change, particularly drought and heat stress, may slash agricultural productivity by 25.7% by 2080, with maize being the hardest hit. Therefore, unraveling the molecular nature of plant responses to these stressors is vital for the development of climate-smart maize. This manuscript's primary objective was to examine how maize plants respond to these stresses, both individually and in combination. Additionally, the paper delved into harnessing the potential of maize wild relatives as a valuable genetic resource and leveraging AI-based technologies to boost maize resilience. The role of multiomics approaches particularly genomics and transcriptomics in dissecting the genetic basis of stress tolerance was also highlighted. The way forward was proposed to utilize a bunch of information obtained through omics technologies by an interdisciplinary state-of-the-art forward-looking big-data, cyberagriculture system, and AI-based approach to orchestrate the development of climate resilient maize genotypes.

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.

Genomic basis determining root system architecture in maize

KEY MESSAGE

A total of 389 and 344 QTLs were identified by GWAS and QTL mapping explaining accumulatively 32.2-65.0% and 23.7-63.4% of phenotypic variation for 14 shoot-borne root traits using more than 1300 individuals across multiple field trails. Efficient nutrient and water acquisition from soils depends on the root system architecture (RSA). However, the genetic determinants underlying RSA in maize remain largely unexplored. In this study, we conducted a comprehensive genetic analysis for 14 shoot-borne root traits using 513 inbred lines and 800 individuals from four recombinant inbred line (RIL) populations at the mature stage across multiple field trails. Our analysis revealed substantial phenotypic variation for these 14 root traits, with a total of 389 and 344 QTLs identified through genome-wide association analysis (GWAS) and linkage analysis, respectively. These QTLs collectively explained 32.2-65.0% and 23.7-63.4% of the trait variation within each population. Several a priori candidate genes involved in auxin and cytokinin signaling pathways, such as IAA26, ARF2, LBD37 and CKX3, were found to co-localize with these loci. In addition, a total of 69 transcription factors (TFs) from 27 TF families (MYB, NAC, bZIP, bHLH and WRKY) were found for shoot-borne root traits. A total of 19 genes including PIN3, LBD15, IAA32, IAA38 and ARR12 and 19 GWAS signals were overlapped with selective sweeps. Further, significant additive effects were found for root traits, and pyramiding the favorable alleles could enhance maize root development. These findings could contribute to understand the genetic basis of root development and evolution, and provided an important genetic resource for the genetic improvement of root traits in maize.

Evidence that variation in root anatomy contributes to local adaptation in Mexican native maize

Mexican native maize (Zea mays ssp. mays) is adapted to a wide range of climatic and edaphic conditions. Here, we focus specifically on the potential role of root anatomical variation in this adaptation. Given the investment required to characterize root anatomy, we present a machine-learning approach using environmental descriptors to project trait variation from a relatively small training panel onto a larger panel of genotyped and georeferenced Mexican maize accessions. The resulting models defined potential biologically relevant clines across a complex environment that we used subsequently for genotype-environment association. We found evidence of systematic variation in maize root anatomy across Mexico, notably a prevalence of trait combinations favoring a reduction in axial hydraulic conductance in varieties sourced from cooler, drier highland areas. We discuss our results in the context of previously described water-banking strategies and present candidate genes that are associated with both root anatomical and environmental variation. Our strategy is a refinement of standard environmental genome-wide association analysis that is applicable whenever a training set of georeferenced phenotypic data is available.

Root responses to abiotic stress: a comparative look at root system architecture in maize and sorghum

Under all environments, roots are important for plant anchorage and acquiring water and nutrients. However, there is a knowledge gap regarding how root architecture contributes to stress tolerance in a changing climate. Two closely related plant species, maize and sorghum, have distinct root system architectures and different levels of stress tolerance, making comparative analysis between these two species an ideal approach to resolve this knowledge gap. However, current research has focused on shared aspects of the root system that are advantageous under abiotic stress conditions rather than on differences. Here we summarize the current state of knowledge comparing the root system architecture relative to plant performance under water deficit, salt stress, and low phosphorus in maize and sorghum. Under water deficit, steeper root angles and deeper root systems are proposed to be advantageous for both species. In saline soils, a reduction in root length and root number has been described as advantageous, but this work is limited. Under low phosphorus, root systems that are shallow and wider are beneficial for topsoil foraging. Future work investigating the differences between these species will be critical for understanding the role of root system architecture in optimizing plant production for a changing global climate.

Genome-wide association study of agronomic traits related to nitrogen use efficiency in Henan wheat

BACKGROUND

Nitrogen use efficiency (NUE) is closely related to crop yield and nitrogen fertilizer application rate. Although NUE is susceptible to environments, quantitative trait nucleotides (QTNs) for NUE in wheat germplasm populations have been rarely reported in genome-wide associated study.

RESULTS

In this study, 244 wheat accessions were phenotyped by three NUE-related traits in three environments and genotyped by 203,224 SNPs. All the phenotypes for each trait were used to associate with all the genotypes of these SNP markers for identifying QTNs and QTN-by-environment interactions via 3VmrMLM. Among 279 QTNs and one QTN-by-environment interaction for low nitrogen tolerance, 33 were stably identified, especially, one large QTN (r2 > 10%), qPHR3A.2, was newly identified for plant height ratio in one environment and multi-environment joint analysis. Among 52 genes around qPHR3A.2, four genes (TraesCS3A01G101900, TraesCS3A01G102200, TraesCS3A01G104100, and TraesCS3A01G105400) were found to be differentially expressed in low-nitrogen-tolerant wheat genotypes, while TaCLH2 (TraesCS3A01G101900) was putatively involved in porphyrin metabolism in KEGG enrichment analyses.

CONCLUSIONS

This study identified valuable candidate gene for low-N-tolerant wheat breeding and provides new insights into the genetic basis of low N tolerance in wheat.

Genome-wide association study and pathway analysis to decipher loci associated with Fusarium ear rot resistance in tropical maize germplasm

Breeding for host resistance is the most efficient and environmentally safe method to curb the spread of fusarium ear rot (FER). However, conventional breeding for resistance to FER is hampered by the complex polygenic nature of this trait, which is highly influenced by environmental conditions. This study aimed to identify genomic regions, single nucleotide polymorphisms (SNPs), and putative candidate genes associated with FER resistance as well as candidate metabolic pathways and pathway genes involved in it. A panel of 151 tropical inbred maize lines were used to assess the genetic architecture of FER resistance over two seasons. During the study period, seven SNPs associated with FER resistance were identified on chromosomes 1, 2, 4, 5, and 9, accounting for 4-11% of the phenotypic variance. These significant markers were annotated into four genes. Seven significant metabolic pathways involved in FER resistance were identified using the Pathway Association Study Tool, the most significant being the superpathway of the glyoxylate cycle. Overall, this study confirmed that resistance to FER is indeed a complex mechanism controlled by several small to medium-effect loci. Our findings may contribute to fast-tracking the efforts to develop disease-resistant maize lines through marker-assisted selection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10722-023-01793-4.

Dissecting the genetic architecture of root-related traits in a grafted wild Vitis berlandieri population for grapevine rootstock breeding

In woody perennial plants, quantitative genetics and association studies remain scarce for root-related traits, due to the time required to obtain mature plants and the complexity of phenotyping. In grapevine, a grafted cultivated plant, most of the rootstocks used are hybrids between American Vitis species (V. rupestris, V. riparia, and V. berlandieri). In this study, we used a wild population of an American Vitis species (V. berlandieri) to analyze the genetic architecture of the root-related traits of rootstocks in a grafted context. We studied a population consisting of 211 genotypes, with one to five replicates each (n = 846 individuals), plus four commercial rootstocks as control genotypes (110R, 5BB, Börner, and SO4). After two independent years of experimentation, the best linear unbiased estimates method revealed root-related traits with a moderate-to-high heritability (0.36-0.82) and coefficient of genetic variation (0.15-0.45). A genome-wide association study was performed with the BLINK model, leading to the detection of 11 QTL associated with four root-related traits (one QTL was associated with the total number of roots, four were associated with the number of small roots (< 1 mm in diameter), two were associated with the number of medium-sized roots (1 mm < diameter < 2 mm), and four were associated with mean diameter) accounting for up to 25.1% of the variance. Three genotypes were found to have better root-related trait performances than the commercial rootstocks and therefore constitute possible new candidates for use in grapevine rootstock breeding programs.

Drought stress in maize: stress perception to molecular response and strategies for its improvement

Given the future demand for food crops, increasing crop productivity in drought-prone rainfed areas has become essential. Drought-tolerant varieties are warranted to solve this problem in major crops, with drought tolerance as a high-priority trait for future research. Maize is one such crop affected by drought stress, which limits production, resulting in substantial economic losses. It became a more serious issue due to global climate change. The most drought sensitive among all stages of maize is the reproductive stages and the most important for overall maize production. The exact molecular basis of reproductive drought sensitivity remains unclear due to genes' complex regulation of drought stress. Understanding the molecular biology and signaling of the unexplored area of reproductive drought tolerance will provide an opportunity to develop climate-smart drought-tolerant next-generation maize cultivars. In recent decades, significant progress has been made in maize to understand the drought tolerance mechanism. However, improving maize drought tolerance through breeding is ineffective due to the complex nature and multigenic control of drought traits. With the help of advanced breeding techniques, molecular genetics, and a precision genome editing approach like CRISPR-Cas, candidate genes for drought-tolerant maize can be identified and targeted. This review summarizes the effects of drought stress on each growth stage of maize, potential genes, and transcription factors that determine drought tolerance. In addition, we discussed drought stress sensing, its molecular mechanisms, different approaches to developing drought-resistant maize varieties, and how molecular breeding and genome editing will help with the current unpredictable climate change.

Hybrid performance evaluation and genome-wide association analysis of root system architecture in a maize association population

KEY MESSAGE

The genetic architecture of RSA traits was dissected by GWAS and coexpression networks analysis in a maize association population. Root system architecture (RSA) is a crucial determinant of water and nutrient uptake efficiency in crops. However, the maize genetic architecture of RSA is still poorly understood due to the challenges in quantifying root traits and the lack of dense molecular markers. Here, an association mapping panel including 356 inbred lines were crossed with a common tester, Zheng58, and the test crosses were phenotyped for 12 RSA traits in three locations. We observed a 1.3 ~ sixfold phenotypic variation for measured RSA in the association panel. The association panel consisted of four subpopulations, non-stiff stalk (NSS) lines, stiff stalk (SS), tropical/subtropical (TST), and mixed. Zheng58 × TST has a 2.1% higher crown root number (CRN) and 8.6% less brace root number (BRN) than Zheng58 × NSS and Zheng58 × SS, respectively. Using a genome-wide association study (GWAS) with 1.25 million SNPs and correction for population structure, 191 significant SNPs were identified for root traits. Ninety (47%) of the significant SNPs showed positive allelic effects, and 101 (53%) showed negative effects. Each locus could explain 0.39% to 11.8% of phenotypic variation. By integrating GWAS results and comparing coexpression networks, 26 high-priority candidate genes were identified. Gene GRMZM2G377215, which belongs to the COBRA-like gene family, affected root growth and development. Gene GRMZM2G468657 encodes the aspartic proteinase nepenthesin-1, related to root development and N-deficient response. Collectively, our research provides progress in the genetic dissection of root system architecture. These findings present the further possibility for the genetic improvement of root traits in maize.

Genetic variation among elite inbred lines suggests potential to breed for BNI-capacity in maize

Biological nitrification inhibition (BNI) is a plant function where root systems release antibiotic compounds (BNIs) specifically aimed at suppressing nitrifiers to limit soil-nitrate formation in the root zone. Little is known about BNI-activity in maize (Zea mays L.), the most important food, feed, and energy crop. Two categories of BNIs are released from maize roots; hydrophobic and hydrophilic BNIs, that determine BNI-capacity in root systems. Zeanone is a recently discovered hydrophobic compound with BNI-activity, released from maize roots. The objectives of this study were to understand/quantify the relationship between zeanone activity and hydrophobic BNI-capacity. We assessed genetic variability among 250 CIMMYT maize lines (CMLs) characterized for hydrophobic BNI-capacity and zeanone activity, towards developing genetic markers linked to this trait in maize. CMLs with high BNI-capacity and ability to release zeanone from roots were identified. GWAS was performed using 27,085 SNPs (with unique positions on the B73v.4 reference genome, and false discovery rate = 10), and phenotypic information for BNI-capacity and zeanone production from root systems. Eighteen significant markers were identified; three associated with specific BNI-activity (SBNI), four with BNI-activity per plant (BNIPP), another ten were common between SBNI and BNIPP, and one with zeanone release. Further, 30 annotated genes were associated with the significant SNPs; most of these genes are involved in pathways of "biological process", and one (AMT5) in ammonium regulation in maize roots. Although the inbred lines in this study were not developed for BNI-traits, the identification of markers associated with BNI-capacity suggests the possibility of using these genomic tools in marker-assisted selection to improve hydrophobic BNI-capacity in maize.

Molecular characterization of doubled haploid lines derived from different cycles of the Iowa Stiff Stalk Synthetic (BSSS) maize population

Molecular characterization of a given set of maize germplasm could be useful for understanding the use of the assembled germplasm for further improvement in a breeding program, such as analyzing genetic diversity, selecting a parental line, assigning heterotic groups, creating a core set of germplasm and/or performing association analysis for traits of interest. In this study, we used single nucleotide polymorphism (SNP) markers to assess the genetic variability in a set of doubled haploid (DH) lines derived from the unselected Iowa Stiff Stalk Synthetic (BSSS) maize population, denoted as C0 (BSSS(R)C0), the seventeenth cycle of reciprocal recurrent selection in BSSS (BSSS(R)C17), denoted as C17 and the cross between BSSS(R)C0 and BSSS(R)C17 denoted as C0/C17. With the aim to explore if we have potentially lost diversity from C0 to C17 derived DH lines and observe whether useful genetic variation in C0 was left behind during the selection process since C0 could be a reservoir of genetic diversity that could be untapped using DH technology. Additionally, we quantify the contribution of the BSSS progenitors in each set of DH lines. The molecular characterization analysis confirmed the apparent separation and the loss of genetic variability from C0 to C17 through the recurrent selection process. Which was observed by the degree of differentiation between the C0_DHL versus C17_DHL groups by Wright's F-statistics (FST). Similarly for the population structure based on principal component analysis (PCA) revealed a clear separation among groups of DH lines. Some of the progenitors had a higher genetic contribution in C0 compared with C0/C17 and C17 derived DH lines. Although genetic drift can explain most of the genetic structure genome-wide, phenotypic data provide evidence that selection has altered favorable allele frequencies in the BSSS maize population through the reciprocal recurrent selection program.

Genomic insight into changes of root architecture under drought stress in maize

Drought stress is a central environmental factor that severely limits maize production worldwide. Root architecture plays an important role in drought tolerance and can be targeted in breeding programmes. Here, we conducted phenotyping of root architecture under different water treatments for 373 maize inbred lines, representative germplasm from both China and the United States in different breeding eras. We found that seminal root length in response to drought stress experienced convergent increase during breeding in both countries. Using a genome-wide association study, we identified a total of 221 associated loci underlying 13 root traits under well-watered and water-stressed conditions. These loci harboured many reported root- and abiotic stress-related genes. Furthermore, a total of 75 strong candidate genes were prioritised by integrating candidate genes associated with seminal root length and differentially expressed genes in seminal root. One of high-confidence candidate genes, ZmCIPK3 was functionally characterised and probably plays a role in enhancing drought tolerance through regulating seminal root growth. This study provides valuable information for genetic improvement of root architecture and drought tolerance in maize.

Genome-Wide Association Study for Root Morphology and Phosphorus Acquisition Efficiency in Diverse Maize Panels

Maximizing soil exploration through modifications of the root system is a strategy for plants to overcome phosphorus (P) deficiency. Genome-wide association with 561 tropical maize inbred lines from Embrapa and DTMA panels was undertaken for root morphology and P acquisition traits under low- and high-P concentrations, with 353,540 SNPs. P supply modified root morphology traits, biomass and P content in the global maize panel, but root length and root surface area changed differentially in Embrapa and DTMA panels. This suggests that different root plasticity mechanisms exist for maize adaptation to low-P conditions. A total of 87 SNPs were associated to phenotypic traits in both P conditions at −log10(p-value) ≥ 5, whereas only seven SNPs reached the Bonferroni significance. Among these SNPs, S9_137746077, which is located upstream of the gene GRMZM2G378852 that encodes a MAPKKK protein kinase, was significantly associated with total seedling dry weight, with the same allele increasing root length and root surface area under P deficiency. The C allele of S8_88600375, mapped within GRMZM2G044531 that encodes an AGC kinase, significantly enhanced root length under low P, positively affecting root surface area and seedling weight. The broad genetic diversity evaluated in this panel suggests that candidate genes and favorable alleles could be exploited to improve P efficiency in maize breeding programs of Africa and Latin America.

Genome-Wide Meta-Analysis of QTLs Associated with Root Traits and Implications for Maize Breeding

Root system architecture (RSA), also known as root morphology, is critical in plant acquisition of soil resources, plant growth, and yield formation. Many QTLs associated with RSA or root traits in maize have been identified using several bi-parental populations, particularly in response to various environmental factors. In the present study, a meta-analysis of QTLs associated with root traits was performed in maize using 917 QTLs retrieved from 43 mapping studies published from 1998 to 2020. A total of 631 QTLs were projected onto a consensus map involving 19,714 markers, which led to the prediction of 68 meta-QTLs (MQTLs). Among these 68 MQTLs, 36 MQTLs were validated with the marker-trait associations available from previous genome-wide association studies for root traits. The use of comparative genomics approaches revealed several gene models conserved among the maize, sorghum, and rice genomes. Among the conserved genomic regions, the ortho-MQTL analysis uncovered 20 maize MQTLs syntenic to 27 rice MQTLs for root traits. Functional analysis of some high-confidence MQTL regions revealed 442 gene models, which were then subjected to in silico expression analysis, yielding 235 gene models with significant expression in various tissues. Furthermore, 16 known genes viz., DXS2, PHT, RTP1, TUA4, YUC3, YUC6, RTCS1, NSA1, EIN2, NHX1, CPPS4, BIGE1, RCP1, SKUS13, YUC5, and AW330564 associated with various root traits were present within or near the MQTL regions. These results could aid in QTL cloning and pyramiding in developing new maize varieties with specific root architecture for proper plant growth and development under optimum and abiotic stress conditions.

Combined genome-wide association study and gene co-expression network analysis identified ZmAKINβγ1 involved in lead tolerance and accumulation in maize seedlings

Lead (Pb) contamination has become an important abiotic stress that negatively influences crop biomass and yield, threatening human health via food chains. The excavation of causal genes for Pb tolerance in maize will contribute to the breeding of Pb-tolerant maize germplasms. This study aimed to demonstrate the effects of AKINbetagamma-1 protein kinase (ZmAKINβγ1) on maize tolerance to Pb and reveal its molecular mechanisms underlying Pb tolerance. ZmAKINβγ1 was identified using genome-wide association study and weighted gene co-expression network analysis for shoot dry weight (SDW) and root dry weight (RDW) under Pb treatment. The OE and RNAi experiments showed that ZmAKINβγ1 negatively regulated maize tolerance to Pb by reducing SDW and RDW and increasing Pb accumulation in maize. Comparative transcriptome analysis between the OE/RNAi and wild-type lines revealed that ZmAKINβγ1 participated in the pectin metabolism process and nitrogen compound response. Gene-based association analyses revealed that three variants located in ZmAKINβγ1 promoter induced changes in its expression and Pb tolerance among maize lines. The dual-luciferase reporter system verified that the two genotypes (AAT and CGG) of ZmAKINβγ1 promoter had contrasting transcriptional activities. Collectively, ZmAKINβγ1-mediated Pb tolerance provided new insights into the cultivation of Pb-tolerant maize varieties and phytoremediation of Pb-polluted soils.

Identification of quantitative trait loci for related traits of stalk lodging resistance using genome-wide association studies in maize (Zea mays L.)

BACKGROUND

Stalk lodging is one of the main factors affecting maize (Zea mays L.) yield and limiting mechanized harvesting. Developing maize varieties with high stalk lodging resistance requires exploring the genetic basis of lodging resistance-associated agronomic traits. Stalk strength is an important indicator to evaluate maize lodging and can be evaluated by measuring stalk rind penetrometer resistance (RPR) and stalk buckling strength (SBS). Along with morphological traits of the stalk for the third internodes length (TIL), fourth internode length (FIL), third internode diameter (TID), and the fourth internode diameter (FID) traits are associated with stalk lodging resistance.

RESULTS

In this study, a natural population containing 248 diverse maize inbred lines genotyped with 83,057 single nucleotide polymorphism (SNP) markers was used for genome-wide association study (GWAS) for six stalk lodging resistance-related traits. The heritability of all traits ranged from 0.59 to 0.72 in the association mapping panel. A total of 85 significant SNPs were identified for the association mapping panel using best linear unbiased prediction (BLUP) values of all traits. Additionally, five candidate genes were associated with stalk strength traits, which were either directly or indirectly associated with cell wall components.

CONCLUSIONS

These findings contribute to our understanding of the genetic basis of maize stalk lodging and provide valuable theoretical guidance for lodging resistance in maize breeding in the future.

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.

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.

Genome-Wide Association Study Reveals the Genetic Basis of Kernel and Cob Moisture Changes in Maize at Physiological Maturity Stage

Low moisture content (MC) and high dehydration rate (DR) at physiological maturity affect grain mechanical harvest, transport, and storage. In this study, we used an association panel composed of 241 maize inbred lines to analyze ear moisture changes at physiological maturity stage. A genome-wide association study revealed nine significant SNPs and 91 candidate genes. One SNP (SYN38588) was repeatedly detected for two traits, and 15 candidate genes were scanned in the linkage disequilibrium regions of this SNP. Of these, genes Zm00001d020615 and Zm00001d020623 were individually annotated as a polygalacturonase (PG) and a copper transporter 5.1 (COPT5.1), respectively. Candidate gene association analysis showed that three SNPs located in the exons of Zm00001d020615 were significantly associated with the dehydration rate, and AATTAA was determined as the superior haplotype. All these findings suggested that Zm00001d020615 was a key gene affecting moisture changes of maize at the physiological maturity stage. These results have demonstrated the genetic basis of ear moisture changes in maize and indicated a superior haplotype for cultivating maize varieties with low moisture content and high dehydration rates.

Genome-Wide Association Studies of Root-Related Traits in Brassica napus L. under Low-Potassium Conditions

Roots are essential organs for a plant’s ability to absorb water and obtain mineral nutrients, hence they are critical to its development. Plants use root architectural alterations to improve their chances of absorbing nutrients when their supply is low. Nine root traits of a Brassica napus association panel were explored in hydroponic-system studies under low potassium (K) stress to unravel the genetic basis of root growth in rapeseed. The quantitative trait loci (QTL) and candidate genes for root development were discovered using a multilocus genome-wide association study (ML-GWAS). For the nine traits, a total of 453 significant associated single-nucleotide polymorphism (SNP) loci were discovered, which were then integrated into 206 QTL clusters. There were 45 pleiotropic clusters, and qRTA04-4 and qRTC04-7 were linked to TRL, TSA, and TRV at the same time, contributing 5.25–11.48% of the phenotypic variance explained (PVE) to the root traits. Additionally, 1360 annotated genes were discovered by examining genomic regions within 100 kb upstream and downstream of lead SNPs within the 45 loci. Thirty-five genes were identified as possibly regulating root-system development. As per protein–protein interaction analyses, homologs of three genes (BnaC08g29120D, BnaA07g10150D, and BnaC04g45700D) have been shown to influence root growth in earlier investigations. The QTL clusters and candidate genes identified in this work will help us better understand the genetics of root growth traits and could be employed in marker-assisted breeding for rapeseed adaptable to various conditions with low K levels.

Effects of ZmHIPP on lead tolerance in maize seedlings: Novel ideas for soil bioremediation

Extensive lead (Pb) absorption by plants affects their growth and development and causes damage to the human body by entering the food chain. In this study, we cloned ZmHIPP, a gene associated with Pb tolerance and accumulation in maize, using combined linkage mapping and weighted gene co-expression network analysis. We show that ZmHIPP, which encodes a heavy metal-associated isoprenylated plant protein, positively modulated Pb tolerance and accumulation in maize seedlings, Arabidopsis, and yeast. The genetic variation locus (A/G) in the promoter of ZmHIPP contributed to the phenotypic disparity in Pb tolerance among different maize inbred lines by altering the expression abundance of ZmHIPP. Knockdown of ZmHIPP significantly inhibited growth and decreased Pb accumulation in maize seedlings under Pb stress. ZmHIPP facilitated Pb deposition in the cell wall and prevented it from entering the intracellular organelles, thereby alleviating Pb toxicity in maize seedlings. Compared to that in the mutant zmhipp, the accumulated Pb in the wild-type line mainly consisted of the low-toxicity forms of Pb. Our study increases the understanding of the mechanism underlying Pb tolerance in maize and provides new insights into the bioremediation of Pb-polluted soil.

Dissection of the Genetic Basis of Yield Traits in Line per se and Testcross Populations and Identification of Candidate Genes for Hybrid Performance in Maize

Dissecting the genetic basis of yield traits in hybrid populations and identifying the candidate genes are important for molecular crop breeding. In this study, a BC1F3:4 population, the line per se (LPS) population, was constructed by using elite inbred lines Zheng58 and PH4CV as the parental lines. The population was genotyped with 55,000 SNPs and testcrossed to Chang7-2 and PH6WC (two testers) to construct two testcross (TC) populations. The three populations were evaluated for hundred kernel weight (HKW) and yield per plant (YPP) in multiple environments. Marker-trait association analysis (MTA) identified 24 to 151 significant SNPs in the three populations. Comparison of the significant SNPs identified common and specific quantitative trait locus/loci (QTL) in the LPS and TC populations. Genetic feature analysis of these significant SNPs proved that these SNPs were associated with the tested traits and could be used to predict trait performance of both LPS and TC populations. RNA-seq analysis was performed using maize hybrid varieties and their parental lines, and differentially expressed genes (DEGs) between hybrid varieties and parental lines were identified. Comparison of the chromosome positions of DEGs with those of significant SNPs detected in the TC population identified potential candidate genes that might be related to hybrid performance. Combining RNA-seq analysis and MTA results identified candidate genes for hybrid performance, providing information that could be useful for maize hybrid breeding.

GWAS and transcriptome analysis reveal MADS26 involved in seed germination ability in maize

MADS26 affecting maize seed germination was identified by GWAS and transcriptomics. Gene-based association analyses revealed three variations within MADS26 regulating seed germination traits. Overexpressed MADS26 in Arabidopsis improved seed germination. Seed germination ability is extremely important for maize production. Exploring the genetic control of seed germination ability is useful for improving maize yield. In this study, a genome-wide association study (GWAS) was conducted to excavate the significant SNPs involved in seed germination ability based on an association panel consisting of 300 lines. A total of 11 SNPs and 75 candidate genes were significantly associated with the seed germination traits. In addition, we constructed 24 transcriptome libraries from maize seeds at four germination stages using two inbred lines with contrasting germination rates. In total, 15,865 differentially expressed genes were induced during seed germination. Integrating the results of GWAS and transcriptome analysis uncovered four prioritized genes underlying maize seed germination. The variations located in the promoter of Zm00001d017932, a MADS-transcription factor 26 (MADS26), were verified to affect the seed germination, and the haplotype TAT was determined as a favorable haplotype for high-germination capability. MADS26 was induced to express by ethylene during seed germination in maize and overexpressing MADS26 increased the seed germination ability in Arabidopsis. These findings will contribute to understanding of the genetic and molecular mechanisms on seed germination and the genetic modification of seed germination ability in maize.

Discovery of Genomic Regions and Candidate Genes Controlling Root Development Using a Recombinant Inbred Line Population in Rapeseed (Brassica napus L.)

Marker-assisted selection enables breeders to quickly select excellent root architectural variations, which play an essential role in plant productivity. Here, ten root-related and shoot biomass traits of a new F₆ recombinant inbred line (RIL) population were investigated under hydroponics and resulted in high heritabilities from 0.61 to 0.83. A high-density linkage map of the RIL population was constructed using a Brassica napus 50k Illumina single nucleotide polymorphism (SNP) array. A total of 86 quantitative trait loci (QTLs) explaining 4.16–14.1% of the phenotypic variances were detected and integrated into eight stable QTL clusters, which were repeatedly detected in different experiments. The codominant markers were developed to be tightly linked with three major QTL clusters, qcA09-2, qcC08-2, and qcC08-3, which controlled both root-related and shoot biomass traits and had phenotypic contributions greater than 10%. Among these, qcA09-2, renamed RT.A09, was further fine-mapped to a 129-kb interval with 19 annotated genes in the B. napus reference genome. By integrating the results of real-time PCR and comparative sequencing, five genes with expression differences and/or amino acid differences were identified as important candidate genes for RT.A09. Our findings laid the foundation for revealing the molecular mechanism of root development and developed valuable markers for root genetic improvement in rapeseed.

Genome-Wide Association Study of Root System Architecture in Maize

Roots are important plant organs for the absorption of water and nutrients. To date, there have been few genome-wide association studies of maize root system architecture (RSA) in the field. The genetic basis of maize RSA is poorly understood, and the maize RSA-related genes that have been cloned are very limited. Here, 421 maize inbred lines of an association panel were planted to measure the root systems at the maturity stage, and a genome-wide association study was performed. There was a strong correlation among eight RSA traits, and the RSA traits were highly correlated with the aboveground plant architecture traits (e.g., plant height and ear leaf length, r = 0.13–0.25, p < 0.05). The RSA traits of the stiff stalk subgroup (SS) showed lower values than those of the non-stiff stalk subgroup (NSS) and tropical/subtropical subgroup (TST). Using the RSA traits, the genome-wide association study identified 63 SNPs and 189 candidate genes. Among them, nine candidate genes co-localized between RSA and aboveground architecture traits. A further co-expression analysis identified 88 candidate genes having high confidence levels. Furthermore, we identified four highly reliable RSA candidate genes, GRMZM2G099797, GRMZM2G354338, GRMZM2G085042, and GRMZM5G812926. This research provides theoretical support for the genetic improvement of maize root systems, and it identified candidate genes that may act as genetic resources for breeding.

Genome-Wide Association Analyses to Identify SNPs Related to Drought Tolerance

Drought stress is a serious agronomic problem resulting in significant yield losses globally. Breeding cultivars with drought tolerance is an important strategy that can be used to address this problem. Drought tolerance, however, is a complex multigenic trait, making advancements with conventional breeding approaches very challenging. This emphasizes the importance of dissecting the genetics of this trait and the identification and cloning of genes responsible for drought tolerance. With the rapid development of sequencing technologies and analytic methodologies, genome-wide association study (GWAS) has become an important tool for detecting natural variations underlying complex traits in crops. Identified loci can serve as targets for genomic selection or precise editing that enables the molecular design of new cultivars. This chapter describes the pipeline of statistical methods used in GWAS analysis, and covers field design, quality control, population structure control, association tests, and visualization of data. GWAS methodology used to dissect the genetic basis of drought tolerance is presented, and perspectives for optimizing the design and analysis of GWAS are discussed. The provided information serves as a valuable resource for researchers interested in GWAS technology.

Joint GWAS and WGCNA uncover the genetic control of calcium accumulation under salt treatment in maize seedlings

Soil salinization is an important factor threatening the yield and quality of maize. Ca²⁺ plays a considerable role in regulating plant growth under salt stress. Herein, we examined the shoot Ca²⁺ concentrations, root Ca²⁺ concentrations, and transport coefficients of seedlings in an association panel composed of 305 maize inbred lines under normal and salt conditions. A genome-wide association study was conducted by using the investigated phenotypes and 46,408 single-nucleotide polymorphisms of the panel. As a result, 53 significant SNPs were specifically detected under salt treatment, and 544 genes were identified in the linkage disequilibrium regions of these SNPs. According to the expression data of the 544 genes, we carried out a weighted coexpression network analysis. Combining the enrichment analyses and functional annotations, four hub genes (GRMZM2G051032, GRMZM2G004314, GRMZM2G421669, and GRMZM2G123314) were finally determined, which were then used to evaluate the genetic variation effects by gene-based association analysis. Only GRMZM2G123314, which encodes a pentatricopeptide repeat protein, was significantly associated with Ca²⁺ transport and the haplotype G-CT was identified as the superior haplotype. Our study brings novel insights into the genetic and molecular mechanisms of salt stress response and contributes to the development of salt-tolerant varieties in maize.

Genetic Dissection of Mature Root Characteristics by Genome-Wide Association Studies in Rapeseed (Brassica napus L.)

Roots are complicated quantitative characteristics that play an essential role in absorbing water and nutrients. To uncover the genetic variations for root-related traits in rapeseed, twelve mature root traits of a Brassica napus association panel were investigated in the field within three environments. All traits showed significant phenotypic variation among genotypes, with heritabilities ranging from 55.18% to 79.68%. Genome-wide association studies (GWAS) using 20,131 SNPs discovered 172 marker-trait associations, including 103 significant SNPs (-log10 (p) > 4.30) that explained 5.24-20.31% of the phenotypic variance. With the linkage disequilibrium r² > 0.2, these significant associations were binned into 40 quantitative trait loci (QTL) clusters. Among them, 14 important QTL clusters were discovered in two environments and/or with phenotypic contributions greater than 10%. By analyzing the genomic regions within 100 kb upstream and downstream of the peak SNPs within the 14 loci, 334 annotated genes were found. Among these, 32 genes were potentially associated with root development according to their expression analysis. Furthermore, the protein interaction network using the 334 annotated genes gave nine genes involved in a substantial number of interactions, including a key gene associated with root development, BnaC09g36350D. This research provides the groundwork for deciphering B. napus' genetic variations and improving its root system architecture.

Advances and Challenges for QTL Analysis and GWAS in the Plant-Breeding of High-Yielding: A Focus on Rapeseed

Yield is one of the most important agronomic traits for the breeding of rapeseed (Brassica napus L), but its genetic dissection for the formation of high yield remains enigmatic, given the rapid population growth. In the present review, we review the discovery of major loci underlying important agronomic traits and the recent advancement in the selection of complex traits. Further, we discuss the benchmark summary of high-throughput techniques for the high-resolution genetic breeding of rapeseed. Biparental linkage analysis and association mapping have become powerful strategies to comprehend the genetic architecture of complex agronomic traits in crops. The generation of improved crop varieties, especially rapeseed, is greatly urged to enhance yield productivity. In this sense, the whole-genome sequencing of rapeseed has become achievable to clone and identify quantitative trait loci (QTLs). Moreover, the generation of high-throughput sequencing and genotyping techniques has significantly enhanced the precision of QTL mapping and genome-wide association study (GWAS) methodologies. Furthermore, this study demonstrates the first attempt to identify novel QTLs of yield-related traits, specifically focusing on ovule number per pod (ON). We also highlight the recent breakthrough concerning single-locus-GWAS (SL-GWAS) and multi-locus GWAS (ML-GWAS), which aim to enhance the potential and robust control of GWAS for improved complex traits.

GWAS and WGCNA uncover hub genes controlling salt tolerance in maize (Zea mays L.) seedlings

KEYMESSAGE

Two hub genes GRMZM2G075104 and GRMZM2G333183 involved in salt tolerance were identified by GWAS and WGCNA. Furthermore, they were verified to affect salt tolerance by candidate gene association analysis. Salt stress influences maize growth and development. To decode the genetic basis and hub genes controlling salt tolerance is a meaningful exploration for cultivating salt-tolerant maize varieties. Herein, we used an association panel consisting of 305 lines to identify the genetic loci responsible for Na+- and K+-related traits in maize seedlings. Under the salt stress, seven significant single nucleotide polymorphisms were identified using a genome-wide association study, and 120 genes were obtained by scanning the linkage disequilibrium regions of these loci. According to the transcriptome data of the above 120 genes under salinity treatment, we conducted a weighted gene co-expression network analysis. Combined the gene annotations, two SNaC/SKC (shoot Na+ content/shoot K+ content)-associated genes GRMZM2G075104 and GRMZM2G333183 were finally identified as the hub genes involved in salt tolerance. Subsequently, these two genes were verified to affect salt tolerance of maize seedlings by candidate gene association analysis. Haplotypes TTGTCCG-CT and CTT were determined as favorable/salt-tolerance haplotypes for GRMZM2G075104 and GRMZM2G333183, respectively. These findings provide novel insights into genetic architectures underlying maize salt tolerance and contribute to the cultivation of salt-tolerant varieties in maize.

Identification and characterization of circRNAs in maize seedlings under deficient nitrogen

Here, deep sequencing results of the maize transcriptome in leaves and roots were compared under high-nitrogen (HN) and low-nitrogen (LN) conditions to identify differentially expressed circRNAs (DECs). Circular RNAs (circRNAs) are covalently closed non-coding RNA with widely regulatory potency that has been identified in animals and plants. However, the understanding of circRNAs involved in responsive nitrogen deficiency remains to be elucidated. A total of 24 and 22 DECs were obtained from the leaves and roots, respectively. Ten circRNAs were validated by divergent and convergent primers, and 6 DECs showed the same expression tendency validated by reverse transcriptase-quantitative PCR. Integrating the identified differentially expressed miRNAs, 34 circRNAs could act as miRNA decoys, which might play important roles in multiple biological processes, including organonitrogen compound biosynthesis and regulation of the metabolic process. A total of 51 circRNA-parent genes located in the genome-wide association study identified loci were assessed between HN and LN conditions and were associated with root growth and development. In summary, our results provide valuable information regarding further study of maize circRNAs under nitrogen deficiency and provide new insights into screening of candidate genes as well as the improvement of maize regarding nitrogen deficiency resistance. CircRNA-miRNA-mRNA co-expression networks were constructed to explore the circRNAs that participated in biological development and nitrogen metabolism.

GWAS with a PCA uncovers candidate genes for accumulations of microelements in maize seedlings

Microelements are necessary for plant growth and development, they control key processes of physiological metabolism. Herein, we evaluated three accumulation-related performances for each of the four microelements (Fe, Zn, Cu, and Mn) among 305 inbred maize lines. Quantification of these microelements in maize roots and shoots revealed abundant phenotypic variations in the association panel, with the variation coefficients ranging from 0.31 to 0.76. Principal component analysis (PCA) of the three related traits (concentration in root, concentration in shoot, and transport coefficient) showed that PC1 and PC2 explained >95% of phenotypic variations for each element. The scores of PC1 and PC2 were thereby used for a genome-wide association study by combining 44,134 SNPs of this panel. A total of 27, 1, 5, and 3 SNPs were significantly (P < .05) associated with Zn-PC1, Zn-PC2, Cu-PC1, and Mn-PC2, respectively, with 11 genes closely linked (r²  > 0.8) to these SNPs. Of them, GRMZM2G142870, GRMZM2G045531, and GRMZM2G143512 were individually annotated as ABC transporter C family member 14, zinc transporter 3, and heavy metal ATPase10. A candidate gene association analysis further verified that GRMZM2G142870 and GRMZM2G045531 affect Zn and Mn accumulations, respectively. Evaluation of contrasting allele ratios in elite lines indicated that the majority of the alleles correlating with higher Zn or Cu had not been utilized in maize breeding. Integration of more "higher-accumulation" alleles in the elite lines will be practical for improving Zn and Cu accumulations in maize. Our findings contribute to genetic revelation and molecular marker-assisted selection of microelement accumulations in maize.

Genome-wide association screening and verification of potential genes associated with root architectural traits in maize (Zea mays L.) at multiple seedling stages

Background

Breeding for new maize varieties with propitious root systems has tremendous potential in improving water and nutrients use efficiency and plant adaptation under suboptimal conditions. To date, most of the previously detected root-related trait genes in maize were new without functional verification. In this study, seven seedling root architectural traits were examined at three developmental stages in a recombinant inbred line population (RIL) of 179 RILs and a genome-wide association study (GWAS) panel of 80 elite inbred maize lines through quantitative trait loci (QTL) mapping and genome-wide association study.

Results

Using inclusive composite interval mapping, 8 QTLs accounting for 6.44–8.83 % of the phenotypic variation in root traits, were detected on chromosomes 1 (qRDW_v3-1-1 and qRDW/SDW_v3-1-1), 2 (qRBN_v1-2-1), 4 (qSUA_v1-4-1, qSUA_v2-4-1, and qROV_v2-4-1), and 10 (qTRL_v1-10-1, qRBN_v1-10-1). GWAS analysis involved three models (EMMAX, FarmCPU, and MLM) for a set of 1,490,007 high-quality single nucleotide polymorphisms (SNPs) obtained via whole genome next-generation sequencing (NGS). Overall, 53 significant SNPs with a phenotypic contribution rate ranging from 5.10 to 30.2 % and spread all over the ten maize chromosomes exhibited associations with the seven root traits. 17 SNPs were repeatedly detected from at least two growth stages, with several SNPs associated with multiple traits stably identified at all evaluated stages. Within the average linkage disequilibrium (LD) distance of 5.2 kb for the significant SNPs, 46 candidate genes harboring substantial SNPs were identified. Five potential genes viz. Zm00001d038676, Zm00001d015379, Zm00001d018496, Zm00001d050783, and Zm00001d017751 were verified for expression levels using maize accessions with extreme root branching differences from the GWAS panel and the RIL population. The results showed significantly (P < 0.001) different expression levels between the outer materials in both panels and at all considered growth stages.

Conclusions

This study provides a key reference for uncovering the complex genetic mechanism of root development and genetic enhancement of maize root system architecture, thus supporting the breeding of high-yielding maize varieties with propitious root systems.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07874-x.

Genome-wide association study uncovers new genetic loci and candidate genes underlying seed chilling-germination in maize

As one of the major crops, maize (Zea mays L.) is mainly distributed in tropical and temperate regions. However, with the changes of the environments, chilling stress has become a significantly abiotic stress affecting seed germination and thus the reproductive and biomass accumulation of maize. Herein, we investigated five seed germination-related phenotypes among 300 inbred lines under low-temperature condition (10 °C). By combining 43,943 single nucleotide polymorphisms (SNPs), a total of 15 significant (P < 2.03 ×  10^-6) SNPs were identified to correlate with seed germination under cold stress based on the FarmCPU model in GWAS, among which three loci were repeatedly associated with multiple traits. Ten gene models were closely linked to these three variations, among which Zm00001d010454, Zm00001d010458, Zm00001d010459, and Zm00001d050021 were further verified by candidate gene association study and expression pattern analysis. Importantly, these candidate genes were previously reported to involve plant tolerance to chilling stress and other abiotic stress. Our findings contribute to the understanding of the genetic and molecular mechanisms underlying chilling germination in maize.

Genetic dissection of maize seedling traits in an IBM Syn10 DH population under the combined stress of lead and cadmium

The heavy metals lead and cadmium have become important pollutants in the environment, which exert negative effects on plant morphology, growth and photosynthesis. It is particularly significant to uncover the genetic loci and the causal genes for lead and cadmium tolerance in plants. This study used an IBM Syn10 DH population to identify the quantitative trait loci (QTL) controlling maize seedling tolerance to lead and cadmium by linkage mapping. The broad-sense heritability of these seedling traits ranged from 65.8-97.3% and 32.0-98.8% under control (CK) and treatment (T) conditions, respectively. A total of 53 and 64 QTL were detected under CK and T conditions, respectively. Moreover, 42 QTL were identified using lead and cadmium tolerance coefficient (LCTC). Among these QTL, five and two major QTL that explained > 10% of phenotypic variation were identified under T condition and using LCTC, respectively. Furthermore, eight QTL were simultaneously identified by T and LCTC, explaining 5.23% to 9.21% of the phenotypic variations. Within these major and common QTL responsible for the combined heavy metal tolerance, four candidate genes (Zm00001d048759, Zm00001d004689, Zm00001d004843, Zm00001d033527) were previously reported to correlate with heavy metal transport and tolerance. These findings will contribute to functional gene identification and molecular marker-assisted breeding for improving heavy metal tolerance 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 worldwide maize panel revealed new genetic variation for cold tolerance

A large association panel of 836 maize inbreds revealed a broader genetic diversity of cold tolerance, as predominantly favorable QTL with small effects were identified, indicating that genomic selection is the most promising option for breeding maize for cold tolerance. Maize (Zea mays L.) has limited cold tolerance, and breeding for cold tolerance is a noteworthy bottleneck for reaching the high potential of maize production in temperate areas. In this study, we evaluate a large panel of 836 maize inbred lines to detect genetic loci and candidate genes for cold tolerance at the germination and seedling stages. Genetic variation for cold tolerance was larger than in previous reports with moderately high heritability for most traits. We identified 187 significant single-nucleotide polymorphisms (SNPs) that were integrated into 159 quantitative trait loci (QTL) for emergence and traits related to early growth. Most of the QTL have small effects and are specific for each environment, with the majority found under control conditions. Favorable alleles are more frequent in 120 inbreds including all germplasm groups, but mainly from Minnesota and Spain. Therefore, there is a large, potentially novel, genetic variability in the germplasm groups represented by these inbred lines. Most of the candidate genes are involved in metabolic processes and intracellular membrane-bounded organelles. We expect that further evaluations of germplasm with broader genetic diversity could identify additional favorable alleles for cold tolerance. However, it is not likely that further studies will find favorable alleles with large effects for improving cold tolerance in maize.

Transcriptomic and genome-wide association study reveal long noncoding RNAs responding to nitrogen deficiency in maize

BACKGROUND

Long noncoding RNAs (lncRNAs) play important roles in essential biological processes. However, our understanding of lncRNAs as competing endogenous RNAs (ceRNAs) and their responses to nitrogen stress is still limited.

RESULTS

Here, we surveyed the lncRNAs and miRNAs in maize inbred line P178 leaves and roots at the seedling stage under high-nitrogen (HN) and low-nitrogen (LN) conditions using lncRNA-Seq and small RNA-Seq. A total of 894 differentially expressed lncRNAs and 38 different miRNAs were identified. Co-expression analysis found that two lncRNAs and four lncRNA-targets could competitively combine with ZmmiR159 and ZmmiR164, respectively. To dissect the genetic regulatory by which lncRNAs might enable adaptation to limited nitrogen availability, an association mapping panel containing a high-density single-nucleotide polymorphism (SNP) array (56,110 SNPs) combined with variable LN tolerant-related phenotypes obtained from hydroponics was used for a genome-wide association study (GWAS). By combining GWAS and RNA-Seq, 170 differently expressed lncRNAs within the range of significant markers were screened. Moreover, 40 consistently LN-responsive genes including those involved in glutamine biosynthesis and nitrogen acquisition in root were identified. Transient expression assays in Nicotiana benthamiana demonstrated that LNC_002923 could inhabit ZmmiR159-guided cleavage of Zm00001d015521.

CONCLUSIONS

These lncRNAs containing trait-associated significant SNPs could consider to be related to root development and nutrient utilization. Taken together, the results of our study can provide new insights into the potential regulatory roles of lncRNAs in response to LN stress, and give valuable information for further screening of candidates as well as the improvement of maize resistance to LN stress.

Genetic dissection of maize drought tolerance for trait improvement

Maize is one of the most important crops, but its production is threatened by drought stress worldwide. Thus, increased drought tolerance has been a major goal of maize breeding. Conventional breeding strategies have led to significantly increase of maize yields; however, these strategies often fail to meet the need for drought stress tolerance enhancement. Here, we focus on progress related to the genetic dissection of drought tolerance in maize at different developmental stages achieved through linkage mapping and association mapping. Moreover, recent molecular breeding systems, including transgenic, genome-wide marker-assisted selection, and genome editing technologies, have provided a more direct, efficient, and accurate approach for trait improvement. We also provide perspectives on future directions regarding multi-omics studies and maize improvement. Overall, the application of acquired knowledge will facilitate maize breeding to meet the challenges.

Genome-Wide Association Study of Root and Shoot Related Traits in Spring Soybean (Glycine max L.) at Seedling Stages Using SLAF-Seq

Root systems can display variable genetic architectures leading to nutrient foraging or improving abiotic stress tolerance. Breeding for new soybean varieties with efficient root systems has tremendous potential in enhancing resource use efficiency and plant adaptation for challenging climates. In this study, root related traits were analyzed in a panel of 260 spring soybean with genome-wide association study (GWAS). Genotyping was done with specific locus amplified fragment sequencing (SLAF-seq), and five GWAS models (GLM, MLM, CMLM, FaST-LMM, and EMMAX) were used for analysis. A total of 179,960 highly consistent SNP markers distributed over the entire genome with an inter-marker distance of 2.36 kb was used for GWAS analysis. Overall, 27 significant SNPs with a phenotypic contribution ranging from 20 to 72% and distributed on chromosomes 2, 6, 8, 9, 13, 16 and 18 were identified and two of them were found to be associated with multiple root-related traits. Based on the linkage disequilibrium (LD) distance of 9.5 kb for the different chromosomes, 11 root and shoot regulating genes were detected based on LD region of a maximum 55-bp and phenotypic contribution greater than 22%. Expression analysis revealed an association between expression levels of those genes and the degree of root branching number. The current study provides new insights into the genetic architecture of soybean roots, and the underlying SNPs/genes could be critical for future breeding of high-efficient root system in soybean.

Natural Variation and Domestication Selection of ZmCKX5 with Root Morphological Traits at the Seedling Stage in Maize

Root system architecture plays a crucial role in water and nutrient acquisition in maize. Cytokinins, which can be irreversibly degraded by the cytokinin oxidase/dehydrogenase (CKX), are important hormones that regulate root development in plants. In this study, ZmCKX5 was resequenced in 285 inbred lines, 68 landraces, and 32 teosintes to identify the significant variants associated with root traits in maize. Sequence polymorphisms and nucleotide diversity revealed that ZmCKX5 might be selected during domestication and improvement processes. Marker–trait association analysis in inbred lines identified 12 variants of ZmCKX5 that were significantly associated with six root traits, including seed root number (SRN), lateral root length (LRL), total root area (RA), root length in 0 to 0.5 mm diameter class (RL005), total root volume (RV), and total root length (TRL). SNP-1195 explained the most (6.01%) phenotypic variation of SRN, and the frequency of this allele G increased from 6.25% and 1.47% in teosintes and landraces, respectively, to 17.39% in inbred lines. Another significant variant, SNP-1406, with a pleiotropic effect, is strongly associated with five root traits, with the frequency of T allele increased from 25.00% and 23.73% in teosintes and landraces, respectively, to 35.00% in inbred lines. These results indicate that ZmCKX5 may be involved in the development of the maize root system and that the significant variants can be used to develop functional markers to accelerate the improvement in the maize root system.

Genome-wide association studies in tropical maize germplasm reveal novel and known genomic regions for resistance to Northern corn leaf blight

Northern Corn Leaf Blight (NCLB) caused by Setosphaeria turcica, is one of the most important diseases of maize world-wide, and one of the major reasons behind yield losses in maize crop in Asia. In the present investigation, a high-resolution genome wide association study (GWAS) was conducted for NCLB resistance in three association mapping panels, predominantly consisting of tropical lines adapted to different agro-ecologies. These panels were phenotyped for disease severity across three locations with high disease prevalence in India. High density SNPs from Genotyping-by-sequencing were used in GWAS, after controlling for population structure and kinship matrices, based on single locus mixed linear model (MLM). Twenty-two SNPs were identified, that revealed a significant association with NCLB in the three mapping panels. Haplotype regression analysis revealed association of 17 significant haplotypes at FDR ≤ 0.05, with two common haplotypes across three maize panels. Several of the significantly associated SNPs/haplotypes were found to be co-located in chromosomal bins previously reported for major genes like Ht2, Ht3 and Htn1 and QTL for NCLB resistance and multiple foliar disease resistance. Phenotypic variance explained by these significant SNPs/haplotypes ranged from low to moderate, suggesting a breeding strategy of combining multiple resistance alleles towards resistance for NCLB.

Genome-Wide Association Study Reveals the Genetic Architecture of Seed Vigor in Oats

Seed vigor is crucial for crop early establishment in the field and is particularly important for forage crop production. Oat (Avena sativa L.) is a nutritious food crop and also a valuable forage crop. However, little is known about the genetics of seed vigor in oats. To investigate seed vigor-related traits and their genetic architecture in oats, we developed an easy-to-implement image-based phenotyping pipeline and applied it to 650 elite oat lines from the Collaborative Oat Research Enterprise (CORE). Root number, root surface area, and shoot length were measured in two replicates. Variables such as growth rate were derived. Using a genome-wide association (GWA) approach, we identified 34 and 16 unique loci associated with root traits and shoot traits, respectively, which corresponded to 41 and 16 unique SNPs at a false discovery rate < 0.1. Nine root-associated loci were organized into four sets of homeologous regions, while nine shoot-associated loci were organized into three sets of homeologous regions. The context sequences of five trait-associated markers matched to the sequences of rice, Brachypodium and maize (E-value < 10-10), including three markers matched to known gene models with potential involvement in seed vigor. These were a glucuronosyltransferase, a mitochondrial carrier protein domain containing protein, and an iron-sulfur cluster protein. This study presents the first GWA study on oat seed vigor and data of this study can provide guidelines and foundation for further investigations.

Testing methods and statistical models of genomic prediction for quantitative disease resistance to Phytophthora sojae in soybean [Glycine max (L.) Merr] germplasm collections

KEY MESSAGE

Genomic prediction of quantitative resistance toward Phytophthora sojae indicated that genomic selection may increase breeding efficiency. Statistical model and marker set had minimal effect on genomic prediction with > 1000 markers. Quantitative disease resistance (QDR) toward Phytophthora sojae in soybean is a complex trait controlled by many small-effect loci throughout the genome. Along with the technical and rate-limiting challenges of phenotyping resistance to a root pathogen, the trait complexity can limit breeding efficiency. However, the application of genomic prediction to traits with complex genetic architecture, such as QDR toward P. sojae, is likely to improve breeding efficiency. We provide a novel example of genomic prediction by measuring QDR to P. sojae in two diverse panels of more than 450 plant introductions (PIs) that had previously been genotyped with the SoySNP50K chip. This research was completed in a collection of diverse germplasm and contributes to both an initial assessment of genomic prediction performance and characterization of the soybean germplasm collection. We tested six statistical models used for genomic prediction including Bayesian Ridge Regression; Bayesian LASSO; Bayes A, B, C; and reproducing kernel Hilbert spaces. We also tested how the number and distribution of SNPs included in genomic prediction altered predictive ability by varying the number of markers from less than 50 to more than 34,000 SNPs, including SNPs based on sequential sampling, random sampling, or selections from association analyses. Predictive ability was relatively independent of statistical model and marker distribution, with a diminishing return when more than 1000 SNPs were included in genomic prediction. This work estimated relative efficiency per breeding cycle between 0.57 and 0.83, which may improve the genetic gain for P. sojae QDR in soybean breeding programs.

Intricate genetic variation networks control the adventitious root growth angle in apple

Background

The root growth angle (RGA) typically determines plant rooting depth, which is significant for plant anchorage and abiotic stress tolerance. Several quantitative trait loci (QTLs) for RGA have been identified in crops. However, the underlying mechanisms of the RGA remain poorly understood, especially in apple rootstocks. The objective of this study was to identify QTLs, validate genetic variation networks, and develop molecular markers for the RGA in apple rootstock.

Results

Bulked segregant analysis by sequencing (BSA-seq) identified 25 QTLs for RGA using 1955 hybrids of the apple rootstock cultivars ‘Baleng Crab’ (Malus robusta Rehd., large RGA) and ‘M9’ (M. pumila Mill., small RGA). With RNA sequencing (RNA-seq) and parental resequencing, six major functional genes were identified and constituted two genetic variation networks for the RGA. Two single nucleotide polymorphisms (SNPs) of the MdLAZY1 promoter damaged the binding sites of MdDREB2A and MdHSFB3, while one SNP of MdDREB2A and MdIAA1 affected the interactions of MdDREB2A/MdHSFB3 and MdIAA1/MdLAZY1, respectively. A SNP within the MdNPR5 promoter damaged the interaction between MdNPR5 and MdLBD41, while one SNP of MdLBD41 interrupted the MdLBD41/MdbHLH48 interaction that affected the binding ability of MdLBD41 on the MdNPR5 promoter. Twenty six SNP markers were designed on candidate genes in each QTL interval, and the marker effects varied from 0.22°-26.11°.

Conclusions

Six diagnostic markers, SNP592, G122, b13, Z312, S1272, and S1288, were used to identify two intricate genetic variation networks that control the RGA and may provide new insights into the accuracy of the molecular markers. The QTLs and SNP markers can potentially be used to select deep-rooted apple rootstocks.

A combination of linkage mapping and GWAS brings new elements on the genetic basis of yield-related traits in maize across multiple environments

Using GWAS and QTL mapping identified 100 QTL and 138 SNPs, which control yield-related traits in maize. The candidate gene GRMZM2G098557 was further validated to regulate ear row number by using a segregation population. Understanding the genetic basis of yield-related traits contributes to the improvement of grain yield in maize. This study used an inter-mated B73 × Mo17 (IBM) Syn10 doubled-haploid (DH) population and an association panel to identify the genetic loci responsible for nine yield-related traits in maize. Using quantitative trait loci (QTL) mapping, 100 QTL influencing these traits were detected across different environments in the IBM Syn10 DH population, with 25 co-detected in multiple environments. Using a genome-wide association study (GWAS), 138 single-nucleotide polymorphisms (SNPs) were identified as correlated with these traits (P < 2.04E-06) in the association panel. Twenty-one pleiotropic QTL/SNPs were identified to control different traits in both populations. A combination of QTL mapping and GWAS uncovered eight significant SNPs (PZE-101097575, PZE-103169263, ZM011204-0763, PZE-104044017, PZE-104123110, SYN8062, PZE-108060911, and PZE-102043341) that were co-located within seven QTL confidence intervals. According to the eight co-localized SNPs by the two populations, 52 candidate genes were identified, among which the ear row number (ERN)-associated SNP SYN8062 was closely linked to SBP-transcription factor 7 (GRMZM2G098557). Several SBP-transcription factors were previously demonstrated to modulate maize ERN. We then validated the phenotypic effects of SYN8062 in the IBM Syn10 DH population, indicating that the ERN of the lines with the A-allele in SYN8062 was significantly (P < 0.05) larger than that of the lines with the G-allele in SYN8062 in each environment. These findings provide valuable information for understanding the genetic mechanisms of maize grain yield formation and for improving molecular marker-assisted selection for the high-yield breeding of maize.

Genome-wide association studies and QTL mapping uncover the genetic architecture of ear tip-barrenness in maize

Ear tip-barrenness (ETB) phenotype threatens crop yield, because it reduces the kernel number per ear. The genetic basis of ETB in maize remains largely unknown. Herein, a genome-wide association study (GWAS) and quantitative trait loci (QTL) mapping were jointly applied to identify the significant genetic loci interrelated with ETB. Six significant SNPs were detected at a stringent P-value threshold (1.95 × 10^-6 ). Additionally, four environment-stable SNPs were co-detected across a single environment and best linear unbiased prediction (BLUP) model at a less stringent P-value threshold (1 × 10^-4 ). The above 10 SNPs were closely linked to 6 candidate genes, which mainly involved seed development, photosynthesis and ethylene response. Moreover, the ratio of superior allele at each significant SNP ranged from 0 to 83.33% in 30 investigated maize elite lines. QTL mapping identified 14 QTL with phenotypic variation explained (PVE) ranging from 3.64 to 7.09%, of which one QTL (qETB2-1) was repeatedly identified in two environments. Combined analysis of GWAS and QTL mapping showed that one SNP (PZE-102175229, chromosome 2: 217 66 Mb) was located in the QTL (qETB2-2, chromosome 2: 215 90-217 82 Mb). Eighteen gene models situated in the linkage disequilibrium (LD) region of the co-localized SNP were further used to evaluate their correlation with ETB by candidate gene association analysis. Two superior haplotypes and two superior alleles were detected among 74 lines for Zm00001d007195, Zm00001d007197 and Zm00001d007201. These results provide more information for clarifying the molecular mechanism of ETB and for speeding up the genetic improvement of maize varieties.

Association mapping for yield traits in Paeonia rockii based on SSR markers within transcription factors of comparative transcriptome

BACKGROUND

Allelic variation underlying the quantitative traits in plants is caused by the extremely complex regulation process. Tree peony originated in China is a peculiar ornamental, medicinal and oil woody plant. Paeonia rockii, one of tree peony species, is a precious emerging woody oil crop. However, in this valuable plant, the study of functional loci associated with yield traits has rarely been identified. Therefore, to explore the genetic architecture of 24 yield quantitative traits, the association mapping was first reported in 420 unrelated cultivated P. rockii individuals based on the next-generation sequencing (NGS) and single-molecule long-read sequencing (SMLRS).

RESULTS

The developed 58 pairs of polymorphic expressed sequence tag-simple sequence repeat (EST-SSR) markers from 959 candidate transcription factors (TFs) associated with yield were used for genotyping the 420 P. rockii accessions. We observed a high level of genetic diversity (polymorphic information content, PIC = 0.514) and low linkage disequilibrium (LD) between EST-SSRs. Moreover, four subpopulations in the association population were revealed by STRUCTURE analyses. Further, single-marker association analysis identified 141 significant associations, involving 17 quantitative traits and 41 EST-SSRs. These loci were mainly from AP2, TCP, MYB, HSF, bHLH, GATA, and B3 gene families and showed a small proportion of the phenotypic variance (3.79 to 37.45%).

CONCLUSIONS

Our results summarize a valuable collection of functional loci associated with yield traits in P. rockii, and provide a precious resource that reveals allelic variation underlying quantitative traits in Paeonia and other woody oil crops.

Genome-wide association study of leaf chemistry traits in tobacco

Leaf chemistry traits are some of the key factors influencing tobacco quality, which can be significantly reduced by lower chemical components in cured leaf. To improve tobacco quality through breeding, genetic diversity analysis, population structure analysis, and genome-wide association studies were performed in a panel of 347 tobacco germplasms and the markers associated with five leaf chemistry traits, including total sugar (TS), reducing sugar (RS), total nitrogen (TN), nicotine (NIC), and total potassium (TP) contents were identified. Four groups were classified at a genetic distance of 0.316 by genetic diversity analysis based on coefficient parameter NEI72 using a program NTSYS-pc2.10e, whereas four well-differentiated subpopulations were postulated in the 347 tobacco accessions. A total of 47 target trait-associated SNPs was detected in at least three environments as well as the best linear unbiased predictions (BLUPs) across all environments, among which two, two, four, six, and one highly suggestive associated SNPs were repeatedly detected in all environments and BLUPs for TS, RS, TN, NIC, and TP, respectively. On the basis of the phenotypic effects of the alleles corresponding to suggestive associated SNPs, five tobacco accessions harboring favorable alleles with elite phenotypic performance in leaf chemistry traits were identified. The results could facilitate quality tobacco breeding for higher leaf chemistry trait contents through molecular marker-assisted approaches.