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

Integrating QTL mapping with transcriptome analysis mined candidate genes of growth stages in castor (Ricinus communis L.)

BACKGROUND

The growth stages largely determine the crop yield, while little is known about their genetic mechanisms in castor. In this study, the QTL mapping and candidate gene mining of growth stages were conducted using populations F2 and BC1, combining with differential expression analysis and weighted gene co-expression network analysis (WGCNA). The traits studied included the emergence date (ED), the budding date of primary spike (PSBD), the flowering date of primary spike (PSFD), the maturation date of primary spike (PSMD), and the maturation date of primary branch spike (PBSMD).

RESULTS

A total of 20 QTLs conferring four traits (ED, PSBD, PSFD and PBSMD) were identified in the F2 population, with a phenotypic variation explained (PVE) of single QTL ranged from 0.24 to 25.46%. Five QTLs underlying PSMD and PBSMD were identified in the BC1 population, with a PVE of single QTL ranged from 4.74 to 10.82%. To our surprise, almost all the identified QTLs were clustered within two marker intervals, the RCM1769-RCM1838 on linkage group 6 and RCM950-RCM917 on linkage group 3. Subsequently, 473 open reading frames (ORFs) were searched out within these two clusters and 110 differentially expressed genes (DEGs) were screened out from these ORFs by the comparative transcriptome clean data (a total of 140.86 G) at the budding date, the initial flowering date and the full flowering date between parental racemes. With these DEGs, five distinct gene co-expression modules were generated using WGCNA. Showing significant differential expression between parents, four candidate genes (LOC8261128, LOC8278994, LOC8281165 and LOC8259049) in module MEturquoise, were recognized and were annotated as RcSYN3, RcNTT, RcGG3 and RcSAUR76 respectively. This finding implies their potential role in regulating the growth stages of castor.

CONCLUSION

In this study, numerous QTLs conferring growth stages were detected and four candidate genes were mined, which need to be functionally validated. The results provided a new insight into the genetic structure of ED, PSBD, PSFD, PSMD and PBSMD, offered the candidate genes and molecular markers for their improvement as well in castor.

Genetic Variation Analysis and Development of KASP Marker for Leaf Area and Hight in Southern-Type Populus deltoides

Populus deltoides holds significant ecological and economic importance and is a crucial gene donor for the world's staple poplar varieties. To select and breed P. deltoides with improved agronomic traits, nine growth and leaf traits were examined in 375 different genotypes, assessing their genetic diversity and performing correlation and comprehensive ranking analyses. Phenotyping results were then utilized to screen a total of 2,009,263 SNP (single nucleotide polymorphism) loci significantly associated with the nine phenotypic traits. A total of 45 SNP loci exhibited significant associations with growth traits based on a general linear model (GLM) analysis. By analyzing the Linkage disequilibrium (LD) block of five SNP loci with significant leaf area and height, we identified five candidate genes related to leaf area and height. Three of the five SNP loci were successfully validated using KASP (kompetitive allele-specific PCR) assays. One loci Chr08_16007979 was closely linked with leaf area, and two loci Chr05_12148738, and Chr05_17106547 were closely linked with height. The developed functional KASP markers offer valuable insights for subsequent further marker-assisted breeding and genetic improvement studies in southern-type poplars.

Identification of genetic loci and candidate genes regulating photosynthesis and leaf morphology through genome-wide association study in Brassica napus L

Rapeseed (Brassica napus L.) is a major agricultural crop with diverse applications, particularly in the production of seed oil for both culinary use and biodiesel. However, its photosynthetic efficiency, a pivotal determinant of yield, remains relatively low compared with other C3 plants such as rice and soybean, highlighting the necessity of identifying the genetic loci and genes regulating photosynthesis in rapeseed. In this study, we investigated 5 photosynthesis traits and 5 leaf morphology traits in a natural population of rapeseed, and conducted a genome-wide association study (GWAS) to identify significantly associated loci and genes. The results showed that the gas-exchange parameters of the dark reactions in photosynthesis exhibited a significant positive correlation with the chlorophyll content, whereas they showed a weaker negative correlation with the leaf area. By GWAS, a total of 538 quantitative trait nucleotides (QTNs) were identified as significantly associated with traits related to both leaf morphology and photosynthesis. These QTNs were classified into 84 QTL clusters, of which, 21 clusters exhibited remarkable stability across different traits and environmental conditions. In addition, a total of 3,129 potential candidate genes were identified to be significantly associated with the above-mentioned 10 traits, most of which were shared by certain traits, further indicating the reliability of the findings. By integrating GWAS data with GO enrichment analysis and gene expression analysis, we further identified 8 key candidate genes that are associated with the regulation of photosynthesis, chlorophyll content, leaf area, and leaf petiole angle. Taken together, this study identified key genetic loci and candidate genes with the potential to improve photosynthetic efficiency in rapeseed. These findings provide a theoretical framework for breeding new rapeseed varieties with enhanced photosynthetic capabilities.

Comparative transcriptomic and hormonal analyses reveal potential regulation networks of adventitious root formation in Metasequoia glyptostroboides Hu et Cheng

BACKGROUND

The extract from Metasequoia glyptostroboides Hu et Cheng, a rare and endangered species native to China, exhibits numerous biological and pharmacological activities. The species is recalcitrant to rooting during micropropagation, a challenge that has yet to be resolved. In this study, transcriptomic and hormonal analyses were conducted to appreciate the molecular mechanism of adventitious root (AR) formation in optimized rooting conditions.

RESULTS

The use of 2/5-strength Woody Plant Medium (WPM) significantly promoted AR formation of M. glyptostroboides shoots while the content of endogenous auxin, cytokinins and gibberellins (GAs) varied at different stages of AR formation. Transcriptomic analysis showed the significant up- or down-regulation of differentially expressed genes (DEGs) associated with plant hormone signal transduction and the phenylpropanoid biosynthesis pathway in response to 2/5-strength WPM. DEGs related to the biosynthesis of indole-3-acetic acid, cytokinins and GAs were identified. Transcript factors involved in 13 families were also revealed. A weighted gene co-expression network analysis indicated a strong correlation between hormones and genes involved in plant hormone signal transduction and the phenylpropanoid biosynthetic pathway.

CONCLUSIONS

These results indicate that the AR-promoting potential of 2/5-strength WPM in M. glyptostroboides was due to complex interactions between hormones and the expression of genes related to plant hormone signal transduction and the phenylpropanoid biosynthetic pathway.

Genome-wide association study and selective sweep analysis uncover candidate genes controlling curd branch length in cauliflower

Cauliflower is a distinct subspecies of the Brassica oleracea plants due to its specialized and edible floral organ. Cauliflower curd is composed of enlarged inflorescence meristems that developed by a series of precise molecular regulations. Based solely on the curd solidity, cauliflower is generally classified into two groups (compact-curd and loose-curd), where curd branch length acts as a crucial parameter to determine the curd morphological difference. Herein, to understand the genetic basis of curd branch development, we utilized a total of 298 inbred lines representing two groups of cauliflower to comprehensively investigate the causal genes and regulatory mechanisms. Phylogenetic and population structure analyses revealed that two subgroups could be further categorized into the compact-curd and the loose-curd groups, respectively. Integrating the genotype and phenotype data, we conducted a genome-wide association study for the length of the outermost branch (LOB) and secondary branch (LSB) of the curd. Sixty-four significant loci were identified that are highly associated with curd branch development. Evidence from genome-wide selective sweep analysis (FST and XP-EHH) narrowed down the major signal on chromosome 8 into an approximately 79 kb region which encodes eleven protein-coding genes. After further analysis of haplotypes, transcriptome profiling, and gene expression validation, we finally inferred that BOB08G028680, as a homologous counterpart of AtARR9, might be the causal gene for simultaneously regulating LOB and LSB traits in cauliflower. This result provides valuable information for improving curd solidity in future cauliflower breeding.

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.

Unraveling the genetic and molecular basis of heat stress in cotton

Human activities and climate change have resulted in frequent and intense weather fluctuations, leading to diverse abiotic stresses on crops which hampers greatly their metabolic activities. Heat stress, a prevalent abiotic factor, significantly influences cotton plant biological activities resulting in reducing yield and production. We must deepen our understanding of how plants respond to heat stress across various dimensions, encompassing genes, RNAs, proteins, metabolites for effective cotton breeding. Multi-omics methods, primarily genomics, transcriptomics, proteomics, metabolomics, and phenomics, proves instrumental in studying cotton's responses to abiotic stresses. Integrating genomics, transcriptomics, proteomics, and metabolomic is imperative for our better understanding regarding genetics and molecular basis of heat tolerance in cotton. The current review explores fundamental omics techniques, covering genomics, transcriptomics, proteomics, and metabolomics, to highlight the progress made in cotton omics research.

GWAS and WGCNA Analysis Uncover Candidate Genes Associated with Oil Content in Soybean

Soybean vegetable oil is an important source of the human diet. However, the analysis of the genetic mechanism leading to changes in soybean oil content is still incomplete. In this study, a total of 227 soybean materials were applied and analyzed by a genome-wide association study (GWAS). There are 44 quantitative trait nucleotides (QTNs) that were identified as associated with oil content. A total of six, four, and 34 significant QTN loci were identified in Xiangyang, Hulan, and Acheng, respectively. Of those, 26 QTNs overlapped with or were near the known oil content quantitative trait locus (QTL), and 18 new QTNs related to oil content were identified. A total of 594 genes were located near the peak single nucleotide polymorphism (SNP) from three tested environments. These candidate genes exhibited significant enrichment in tropane, piperidine, and pyridine alkaloid biosynthesiss (ko00960), ABC transporters (ko02010), photosynthesis-antenna proteins (ko00196), and betalain biosynthesis (ko00965). Combined with the GWAS and weighted gene co-expression network analysis (WGCNA), four candidate genes (Glyma.18G300100, Glyma.11G221100, Glyma.13G343300, and Glyma.02G166100) that may regulate oil content were identified. In addition, Glyma.18G300100 was divided into two main haplotypes in the studied accessions. The oil content of haplotype 1 is significantly lower than that of haplotype 2. Our research findings provide a theoretical basis for improving the regulatory mechanism of soybean oil content.

Integrating Genome-Wide Association Study, Transcriptome and Metabolome Reveal Novel QTL and Candidate Genes That Control Protein Content in Soybean

Protein content (PC) is crucial to the nutritional quality of soybean [Glycine max (L.) Merrill]. In this study, a total of 266 accessions were used to perform a genome-wide association study (GWAS) in three tested environments. A total of 23,131 high-quality SNP markers (MAF ≥ 0.02, missing data ≤ 10%) were identified. A total of 40 association signals were significantly associated with PC. Among them, five novel quantitative trait nucleotides (QTNs) were discovered, and another 32 QTNs were found to be overlapping with the genomic regions of known quantitative trait loci (QTL) related to soybean PC. Combined with GWAS, metabolome and transcriptome sequencing, 59 differentially expressed genes (DEGs) that might control the change in protein content were identified. Meantime, four commonly upregulated differentially abundant metabolites (DAMs) and 29 commonly downregulated DAMs were found. Remarkably, the soybean gene Glyma.08G136900, which is homologous with Arabidopsis hydroxyproline-rich glycoproteins (HRGPs), may play an important role in improving the PC. Additionally, Glyma.08G136900 was divided into two main haplotype in the tested accessions. The PC of haplotype 1 was significantly lower than that of haplotype 2. The results of this study provided insights into the genetic mechanisms regulating protein content in soybean.

Analysis of Growth Trajectories and Verification of Related SNPs in Populus deltoides

As an important timber genus with high economic and ecological values, Populus is a model for dissecting the genetic architecture of growth traits in perennial forest trees. However, the genetic mechanisms of longitudinal growth traits in poplar remain incompletely understood. In this study, we conducted longitudinal genetic analysis of height and diameter at breast height (DBH) in eleven-year poplar clones using ultra-deep sequencing datasets. We compared four S-shaped growth models, including asymptotic, Gompertz, logistic, and Richard, on eleven-year height and DBH records in terms of five metrics. We constructed the best-fitting growth model (Richard) and determined poplar ontogenetic stages by virtue of growth curve fitting and likelihood ratio testing. This study provides some scientific clues for temporal variation of longitudinal growth traits in Populus species.

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.

Genome-wide association study of multiyear dynamic growth traits in hybrid Liriodendron identifies robust genetic loci associated with growth trajectories

The genetic factors underlying growth traits differ over time points or stages. However, most current studies of phenotypes at single time points do not capture all loci or explain the genetic differences underlying growth trajectories. Hybrid Liriodendron exhibits obvious heterosis and is widely cultivated, although its complex genetic mechanism underlying growth traits remains unknown. A genome-wide association study (GWAS) is an effective method for elucidating the genetic architecture by identifying genetic loci underlying complex quantitative traits. In the present study, using a GWAS, we identified robust loci associated with growth trajectories in hybrid Liriodendron populations. We selected 233 hybrid progenies derived from 25 crosses for resequencing, and measured their tree height (H) and diameter at breast height (DBH) for 11 consecutive years; 192 972 high-quality single nucleotide polymorphisms (SNPs) were obtained. The dynamics of the multiyear single-trait GWAS showed that year-specific SNPs predominated, and only five robust SNPs for DBH were identified in at least three different years. Multitrait GWAS analysis with model parameters as latent variables also revealed 62 SNPs for H and 52 for DBH associated with the growth trajectory, displaying different biomass accumulation patterns, among which four SNPs exerted pleiotropic effects. All identified SNPs also exhibited temporal variations in effect sizes and inheritance patterns potentially related to different growth and developmental stages. The haplotypes resulting from these significant SNPs might pyramid favorable loci, benefitting the selection of superior genotypes. The present study provides insights into the genetic architecture of dynamic growth traits and lays a basis for future molecular-assisted breeding.

Genome-wide association study reveals candidate genes controlling root system architecture under low phosphorus supply at seedling stage in Brassica napus

Optimal root system architecture (RSA) is essential for vigorous growth and yield in crops. Plants have evolved adaptive mechanisms in response to low phosphorus (LP) stress, and one of those is changes in RSA. Here, more than five million single-nucleotide polymorphisms (SNPs) obtained from whole-genome re-sequencing data (WGR) of an association panel of 370 oilseed rape (Brassica napus L.) were used to conduct a genome-wide association study (GWAS) of RSA traits of the panel at LP in "pouch and wick" system. Fifty-two SNPs were forcefully associated with lateral root length (LRL), total root length (TRL), lateral root density (LRD), lateral root number (LRN), mean lateral root length (MLRL), and root dry weight (RDW) at LP. There were significant correlations between phenotypic variation and the number of favorable alleles of the associated loci on chromosomes A06 (chrA06_20030601), C03 (chrC03_3535483), and C07 (chrC07_42348561), respectively. Three candidate genes (BnaA06g29270D, BnaC03g07130D, and BnaC07g43230D) were detected by combining transcriptome, candidate gene association analysis, and haplotype analysis. Cultivar carrying "CCGC" at BnaA06g29270DHap1, "CAAT" at BnaC03g07130DHap1, and "ATC" at BnaC07g43230DHap1 had greater LRL, LRN, and RDW than lines carrying other haplotypes at LP supply. The RSA of a cultivar harboring the three favorable haplotypes was further confirmed by solution culture experiments. These findings define exquisite insights into genetic architectures underlying B. napus RSA at LP and provide valuable gene resources for root breeding.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01411-2.

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

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

GWAS across multiple environments and WGCNA suggest the involvement of ZmARF23 in embryonic callus induction from immature maize embryos

Combined GWAS, WGCNA, and gene-based association studies identified the co-expression network and hub genes for maize EC induction. ZmARF23 bound to ZmSAUR15 promoter and regulated its expression, affecting EC induction. Embryonic callus (EC) induction in immature maize embryos shows high genotype dependence, which limits the application of genetic transformation in transgenic breeding and gene function elucidation in maize. Herein, we conducted a genome-wide association mapping (GWAS) for four EC induction-related traits, namely rate of embryonic callus induction (REC), increased callus diameter (ICD), ratio of shoot formation (RSF), and length of shoot (LS) across different environments. A total of 77 SNPs were significantly associated these traits under three environments and using the averages (across environments). Among these significant SNPs, five were simultaneously detected under multiple environments and 11 had respective phenotypic variation explained > 10%. A total of 257 genes were located in the linkage disequilibrium decay of these REC- and ICD-associated SNPs, of which 178 were responsive to EC induction. According to the expression values of the 178 genes, we performed a weighted gene co-expression network analysis (WGCNA) and revealed an EC induction-associated module and five hub genes. Hub gene-based association studies uncovered that the intragenic variations in GRMZM2G105473 and ZmARF23 influenced EC induction efficiency among different maize lines. Dual-luciferase reporter assay indicated that ZmARF23 bound to the promoter of a known causal gene (ZmSAUR15) for EC induction and positively regulated its expression on the transcription level. Our study will deepen the understanding of genetic and molecular mechanisms underlying EC induction and contribute to the use of genetic transformation in maize.

Identification of hub genes regulating isoflavone accumulation in soybean seeds via GWAS and WGCNA approaches

INTRODUCTION

Isoflavones are the secondary metabolites synthesized by the phenylpropanoid biosynthesis pathway in soybean that benefits human and plant health.

METHODS

In this study, we have profiled seed isoflavone content by HPLC in 1551 soybean accessions grown in Beijing and Hainan for two consecutive years (2017 and 2018) and in Anhui for one year (2017).

RESULTS

A broad range of phenotypic variations was observed for individual and total isoflavone (TIF) content. The TIF content ranged from 677.25 to 5823.29 µg g^-1 in the soybean natural population. Using a genome-wide association study (GWAS) based on 6,149,599 single nucleotide polymorphisms (SNPs), we identified 11,704 SNPs significantly associated with isoflavone contents; 75% of them were located within previously reported QTL regions for isoflavone. Two significant regions on chromosomes 5 and 11 were associated with TIF and malonylglycitin across more than 3 environments. Furthermore, the WGCNA identified eight key modules: black, blue, brown, green, magenta, pink, purple, and turquoise. Of the eight co-expressed modules, brown (r = 0.68***), magenta (r = 0.64***), and green (r = 0.51**) showed a significant positive association with TIF, as well as with individual isoflavone contents. By combining the gene significance, functional annotation, and enrichment analysis information, four hub genes Glyma.11G108100, Glyma.11G107100, Glyma.11G106900, and Glyma.11G109100 encoding, basic-leucine zipper (bZIP) transcription factor, MYB4 transcription factor, early responsive to dehydration, and PLATZ transcription factor respectively were identified in brown and green modules. The allelic variation in Glyma.11G108100 significantly influenced individual and TIF accumulation.

DISCUSSION

The present study demonstrated that the GWAS approach, combined with WGCNA, could efficiently identify isoflavone candidate genes in the natural soybean population.

High-Throughput Association Mapping in Brassica napus L.: Methods and Applications

Oil seed rape (Braasica napus L.) is ranked second among oil seed crops cultivated globally for edible oil for human, and seed cake for animal consumption. Recent genetic and genomics advancements highlighted the diversity that exists within B. napus, which is largely discovered using the most promising genetic markers called single nucleotide polymorphism (SNP). Their calling rate is also enhanced to ~100 folds after the continuous advancements in the next generation sequencing (NGS) technologies. As the high throughput of NGS resulted in multi-Giga bases data, the detailed quality control (QC) prior to downstream analyses is a pre-requisite. It mainly involved the removal of false positives, missing proportions, filtering of low-quality SNPs, and adjustments of minor-allele frequency and heterozygosity. After marker-trait association, for conformation of target SNPs, validations of SNPs can be performed using various methods, especially allele-specific PCR assay-based methods have been utilized for SNP genotyping of genes targeting agronomic traits and somaclonal variations occurred during transgenic studies. In the present study, the authors mainly argue on the genotypic progress, and pipelines/methods that are being used for detection, calling, filtering, and validation of SNPs. Also, insight is provided into the application of SNPs in linkage and association mapping, including QTL mapping and genome-wide association studies targeting mainly developmental traits related to the root system and plant architecture, flowering time, silique, and oil quality. Briefly, the present study provides the recent information and recommendations on the SNP genotyping methods and its applications, which can be useful for marker-assisted breeding in B. napus and other crops.

Genetic dissection of branch architecture in oilseed rape (Brassica napus L.) germplasm

Branch architecture is an important factor influencing rapeseed planting density, mechanized harvest, and yield. However, its related genes and regulatory mechanisms remain largely unknown. In this study, branch angle (BA) and branch dispersion degree (BD) were used to evaluate branch architecture. Branch angle exhibited a dynamic change from an increase in the early stage to a gradual decrease until reaching a stable state. Cytological analysis showed that BA variation was mainly due to xylem size differences in the vascular bundle of the branch junction. The phenotypic analysis of 327 natural accessions revealed that BA in six environments ranged from 24.3° to 67.9°, and that BD in three environments varied from 4.20 cm to 21.4 cm, respectively. A total of 115 significant loci were detected through association mapping in three models (MLM, mrMLM, and FarmCPU), which explained 0.53%-19.4% of the phenotypic variations. Of them, 10 loci were repeatedly detected in different environments and models, one of which qBAD.A03-2 was verified as a stable QTL using a secondary segregation population. Totally, 1066 differentially expressed genes (DEGs) were identified between branch adaxial- and abaxial- sides from four extremely large or small BA/BD accessions through RNA sequencing. These DEGs were significantly enriched in the pathways related to auxin biosynthesis and transport as well as cell extension such as indole alkaloid biosynthesis, other glycan degradation, and fatty acid elongation. Four known candidate genes BnaA02g16500D (PIN1), BnaA03g10430D (PIN2), BnaC03g06250D (LAZY1), and BnaC06g20640D (ARF17) were identified by both GWAS and RNA-seq, all of which were involved in regulating the asymmetric distribution of auxins. Our identified association loci and candidate genes provide a theoretical basis for further study of gene cloning and genetic improvement of branch architecture.

Genetic dissection of the natural variation of ovule number per ovary in oilseed rape germplasm (Brassica napus L.)

Oilseed rape is one of the world's largest oil and industrial crops, providing humans with various products, such as vegetable oil and biofuel. Ovules are the direct precursors of seeds, and ovule number per ovary (ONPO) largely determines seed number per fruit that affects both yield and fitness of seed crops. The ONPO shows wide variation in oilseed rape, whereas the underlying genes and mechanisms are poorly known. The present study performed the genetic, physiological and transcriptomic analyses of ovule number per ovary using an association panel and the extreme lines. The ONPO of 327 accessions planted in four environments showed a large variation from 19.2 to 43.8, indicating a great potential for the further genetic improvement of ovule number. The genome-wide association study (GWAS) identified a total of 43 significant SNP markers. Further, these SNPs were integrated into 18 association loci, which were distributed on chromosomes A01, A03, A06, A07, A09, C01, C03, C06, C07, and C09, explaining 4.3-11.5% of the phenotypic variance. The ONPO decreased as their appearance order on the inflorescence and was associated with the level of several types of endogenous phytohormones but not related to leaf area and photosynthetic rate. Comparative transcriptomic analysis identified a total of 4,449 DEGs enriched in 30 classes, including DNA, RNA, protein, signaling, transport, development, cell wall, lipid metabolism, and secondary metabolism. Nearly half of DEGs were involved in the known pathways in regulating ovule number, of which 12 were homologous to know ovule number regulating genes, indicating a strong link between the identified DEGs and ovule number. A total of 73 DEGs were located within the genomic regions of association loci, of which six were identified as candidates based on functional annotation. These results provide useful information for the further genetic improvement of ovule and seed number in oilseed rape.

Quantitative trait loci mapping reveals important genomic regions controlling root architecture and shoot biomass under nitrogen, phosphorus, and potassium stress in rapeseed (Brassica napus L.)

Plants rely on root systems for nutrient uptake from soils. Marker-assisted selection helps breeders to select desirable root traits for effective nutrient uptake. Here, 12 root and biomass traits were investigated at the seedling stage under low nitrogen (LN), low phosphorus (LP), and low potassium (LK) conditions, respectively, in a recombinant inbred line (RIL) population, which was generated from Brassica napus L. Zhongshuang11 and 4D122 with significant differences in root traits and nutrient efficiency. Significant differences for all the investigated traits were observed among RILs, with high heritabilities (0.43-0.74) and high correlations between the different treatments. Quantitative trait loci (QTL) mapping identified 57, 27, and 36 loci, explaining 4.1-10.9, 4.6-10.8, and 4.9-17.4% phenotypic variances under LN, LP, and LK, respectively. Through QTL-meta analysis, these loci were integrated into 18 significant QTL clusters. Four major QTL clusters involved 25 QTLs that could be repeatedly detected and explained more than 10% phenotypic variances, including two NPK-common and two specific QTL clusters (K and NK-specific), indicating their critical role in cooperative nutrients uptake of N, P, and K. Moreover, 264 genes within the four major QTL clusters having high expressions in roots and SNP/InDel variations between two parents were identified as potential candidate genes. Thirty-eight of them have been reported to be associated with root growth and development and/or nutrient stress tolerance. These key loci and candidate genes lay the foundation for deeper dissection of the NPK starvation response mechanisms in B. napus.

Deciphering the Genetic Basis of Root and Biomass Traits in Rapeseed (Brassica napus L.) through the Integration of GWAS and RNA-Seq under Nitrogen Stress

An excellent root system is responsible for crops with high nitrogen-use efficiency (NUE). The current study evaluated the natural variations in 13 root- and biomass-related traits under a low nitrogen (LN) treatment in a rapeseed association panel. The studied traits exhibited significant phenotypic differences with heritabilities ranging from 0.53 to 0.66, and most of the traits showed significant correlations with each other. The genome-wide association study (GWAS) found 51 significant and 30 suggestive trait–SNP associations that integrated into 14 valid quantitative trait loci (QTL) clusters and explained 5.7–21.2% phenotypic variance. In addition, RNA sequencing was performed at two time points to examine the differential expression of genes (DEGs) between high and low NUE lines. In total, 245, 540, and 399 DEGs were identified as LN stress-specific, high nitrogen (HN) condition-specific, and HNLN common DEGs, respectively. An integrated analysis of GWAS, weighted gene co-expression network, and DEGs revealed 16 genes involved in rapeseed root development under LN stress. Previous studies have reported that the homologs of seven out of sixteen potential genes control root growth and NUE. These findings revealed the genetic basis underlying nitrogen stress and provided worthwhile SNPs/genes information for the genetic improvement of NUE in rapeseed.

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.

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.

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.