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

Integration of QTL and transcriptome approaches for the identification of genes involved in tomato response to nitrogen deficiency

Optimizing plant nitrogen (N) usage and inhibiting N leaching loss in the soil-crop system is crucial to maintaining crop yield and reducing environmental pollution. This study aimed at identifying quantitative trait loci (QTLs) and differentially expressed genes (DEGs) between two N treatments in order to list candidate genes related to nitrogen-related contrasting traits in tomato varieties. We characterized a genetic diversity core-collection (CC) and a multi-parental advanced generation intercross (MAGIC) tomato population grown in a greenhouse under two nitrogen levels and assessed several N-related traits and mapped QTLs. Transcriptome response under the two N conditions was also investigated through RNA sequencing of fruit and leaves in four parents of the MAGIC population. Significant differences in response to N input reduction were observed at the phenotypic level for biomass and N-related traits. Twenty-seven QTLs were detected for three target traits (leaf N content, leaf nitrogen balance index, and petiole NO3- content), 10 and six in the low and high N condition, respectively, while 19 QTLs were identified for plasticity traits. At the transcriptome level, 4752 and 2405 DEGs were detected between the two N conditions in leaves and fruits, respectively, among which 3628 (50.6%) in leaves and 1717 (71.4%) in fruit were genotype specific. When considering all the genotypes, 1677 DEGs were shared between organs or tissues. Finally, we integrated DEG and QTL analyses to identify the most promising candidate genes. The results highlighted a complex genetic architecture of N homeostasis in tomato and novel putative genes useful for breeding tomato varieties requiring less N input.

Transcriptomic profiling and discovery of key transcription factors involved in adventitious roots formation from root cuttings of mulberry

ARs plays a crucial role in plant morphogenesis and development. The limited and inefficient rooting of scions poses a significant challenge to the efficiency and quality of clonal propagation of forest trees in silvicultural practices. Building on previous research conducted by our team, we found that applying IBA at a concentration of 1000 mg/L significantly enhanced mulberry rooting. This study aims to uncover the molecular mechanisms underlying this effect by analyzing RNA sequencing data from mulberry phloem before and after treatment with IBA over time intervals of 10, 20, 30, and 40 days. We identified 5226 DEGs, which were then classified into GO terms and KEGG pathways, showing significant enrichment in hormone signaling processes. Using WGCNA, we identified eight co-expression modules, two of which were significantly correlated with the IBA treatment. Additionally, 18 transcription factors that potentially facilitate ARs formation in mulberry were identified, and an exploratory analysis on the cis-regulatory elements associated with these transcription factors was conducted. The findings of this study provide a comprehensive understanding of the mechanisms of ARs in mulberry and offer theoretical support for the discovery and utilization of exceptional genetic resources within the species.

Research on Plant Genomics and Breeding 2.0

Plant genomics and breeding is one among the several highly regarded disciplines in today's field of biological sciences [...].

Root system architecture change in response to waterlogging stress in a 448 global collection of rapeseeds (Brassica napus L.)

MAIN CONCLUSIONS

A novel image-based screening method for precisely identifying genotypic variations in rapeseed RSA under waterlogging stress was developed. Five key root traits were confirmed as good indicators of waterlogging and might be employed in breeding, particularly when using the MFVW approach. Waterlogging is a vital environmental factor that has detrimental effects on the growth and development of rapeseed (Brassica napus L.). Plant roots suffer from hypoxia under waterlogging, which ultimately confers yield penalty. Therefore, it is crucially important to understand the genetic variation of root system architecture (RSA) in response to waterlogging stress to guide the selection of new tolerant cultivars with favorable roots. This research was conducted to investigate RSA traits using image-based screening techniques to better understand how RSA changes over time during waterlogging at the seedling stage. First, we performed a t-test by comparing the relative root trait value between four tolerant and four sensitive accessions. The most important root characteristics associated with waterlogging tolerance at 12 h are total root length (TRL), total root surface area (TRSA), total root volume (TRV), total number of tips (TNT), and total number of forks (TNF). The root structures of 448 rapeseed accessions with or without waterlogging showed notable genetic diversity, and all traits were generally restrained under waterlogging conditions, except for the total root average diameter. Additionally, according to the evaluation and integration analysis of 448 accessions, we identified that five traits, TRL, TRSA, TRV, TNT, and TNF, were the most reliable traits for screening waterlogging-tolerant accessions. Using analysis of the membership function value (MFVW) and D-value of the five selected traits, 25 extremely waterlogging-tolerant materials were screened out. Waterlogging significantly reduced RSA, inhibiting root growth compared to the control. Additionally, waterlogging increased lipid peroxidation, accompanied by a decrease in the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT). This study effectively improves our understanding of the response of RSA to waterlogging. The image-based screening method developed in this study provides a new scientific guidance for quickly examining the basic RSA changes and precisely predicting waterlogging-tolerant rapeseed germplasms, thus expanding the genetic diversity of waterlogging-tolerant rapeseed germplasm available for breeding.

The Genetic Dissection of Nitrogen Use-Related Traits in Flax (Linum usitatissimum L.) at the Seedling Stage through the Integration of Multi-Locus GWAS, RNA-seq and Genomic Selection

Nitrogen (N), the most important macro-nutrient for plant growth and development, is a key factor that determines crop yield. Yet its excessive applications pollute the environment and are expensive. Hence, studying nitrogen use efficiency (NUE) in crops is fundamental for sustainable agriculture. Here, an association panel consisting of 123 flax accessions was evaluated for 21 NUE-related traits at the seedling stage under optimum N (N+) and N deficiency (N-) treatments to dissect the genetic architecture of NUE-related traits using a multi-omics approach integrating genome-wide association studies (GWAS), transcriptome analysis and genomic selection (GS). Root traits exhibited significant and positive correlations with NUE under N- conditions (r = 0.33 to 0.43, p < 0.05). A total of 359 QTLs were identified, accounting for 0.11% to 23.1% of the phenotypic variation in NUE-related traits. Transcriptomic analysis identified 1034 differentially expressed genes (DEGs) under contrasting N conditions. DEGs involved in N metabolism, root development, amino acid transport and catabolism and others, were found near the QTLs. GS models to predict NUE stress tolerance index (NUE_STI) trait were tested using a random genome-wide SNP dataset and a GWAS-derived QTLs dataset. The latter produced superior prediction accuracy (r = 0.62 to 0.79) compared to the genome-wide SNP marker dataset (r = 0.11) for NUE_STI. Our results provide insights into the QTL architecture of NUE-related traits, identify candidate genes for further studies, and propose genomic breeding tools to achieve superior NUE in flax under low N input.

Genome-Wide Association Study Unravels Quantitative Trait Loci and Genes Associated with Yield-Related Traits in Sugarcane

Sugarcane, a major sugar and energy crop worldwide faces an increasing demand for higher yields. Identifying yield-related markers and candidate genes is valuable for breeding high-yield varieties using molecular techniques. In this work, seven yield-related traits were evaluated in a diversity panel of 159 genotypes, derived from Tripidium arundinaceum, Saccharum spontaneum, and modern sugarcane genotypes. All traits exhibited significant genetic variance with high heritability and high correlations. Genetic diversity analysis reveals a genomic decay of 23 kb and an average single nucleotide polymorphism (SNP) number of 25,429 per genotype. These 159 genotypes were divided into 4 subgroups. Genome-wide association analysis identified 47 SNPs associated with brix, spanning 36 quantitative trait loci (QTLs), and 138 SNPs for other traits across 104 QTLs, covering all 32 chromosomes. Interestingly, 12 stable QTLs associated with yield-related traits were identified, which contained 35 candidate genes. This work provides markers and candidate genes for marker-assisted breeding to improve sugarcane yields.

Research on Plant Genomics and Breeding

In recent years, plant genomics has made significant progress following the development of biotechnology [...].

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.

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.

Integration of GWAS and RNA-Seq Analysis to Identify SNPs and Candidate Genes Associated with Alkali Stress Tolerance at the Germination Stage in Mung Bean

Soil salt-alkalization seriously impacts crop growth and productivity worldwide. Breeding and applying tolerant varieties is the most economical and effective way to address soil alkalization. However, genetic resources for breeders to improve alkali tolerance are limited in mung bean. Here, a genome-wide association study (GWAS) was performed to detect alkali-tolerant genetic loci and candidate genes in 277 mung bean accessions during germination. Using the relative values of two germination traits, 19 QTLs containing 32 SNPs significantly associated with alkali tolerance on nine chromosomes were identified, and they explained 3.6 to 14.6% of the phenotypic variance. Moreover, 691 candidate genes were mined within the LD intervals containing significant trait-associated SNPs. Transcriptome sequencing of alkali-tolerant accession 132-346 under alkali and control conditions after 24 h of treatment was conducted, and 2565 DEGs were identified. An integrated analysis of the GWAS and DEGs revealed six hub genes involved in alkali tolerance responses. Moreover, the expression of hub genes was further validated by qRT-PCR. These findings improve our understanding of the molecular mechanism of alkali stress tolerance and provide potential resources (SNPs and genes) for the genetic improvement of alkali tolerance in mung bean.

Insights on Phytohormonal Crosstalk in Plant Response to Nitrogen Stress: A Focus on Plant Root Growth and Development

Nitrogen (N) is a vital mineral component that can restrict the growth and development of plants if supplied inappropriately. In order to benefit their growth and development, plants have complex physiological and structural responses to changes in their nitrogen supply. As higher plants have multiple organs with varying functions and nutritional requirements, they coordinate their responses at the whole-plant level based on local and long-distance signaling pathways. It has been suggested that phytohormones are signaling substances in such pathways. The nitrogen signaling pathway is closely associated with phytohormones such as auxin (AUX), abscisic acid (ABA), cytokinins (CKs), ethylene (ETH), brassinosteroid (BR), strigolactones (SLs), jasmonic acid (JA), and salicylic acid (SA). Recent research has shed light on how nitrogen and phytohormones interact to modulate physiology and morphology. This review provides a summary of the research on how phytohormone signaling affects root system architecture (RSA) in response to nitrogen availability. Overall, this review contributes to identifying recent developments in the interaction between phytohormones and N, as well as serving as a foundation for further study.