Genome-wide detection of genotype environment interactions for flowering time in Brassica napus

Discovering novel genomic regions explaining adaptation of bread wheat to conservation agriculture through GWAS

To sustainably increase wheat yield to meet the growing world population's food demand in the face of climate change, Conservation Agriculture (CA) is a promising approach. Still, there is a lack of genomic studies investigating the genetic basis of crop adaptation to CA. To dissect the genetic architecture of 19 morpho-physiological traits that could be involved in the enhanced adaptation and performance of genotypes under CA, we performed GWAS to identify MTAs under four contrasting production regimes viz., conventional tillage timely sown (CTTS), conservation agriculture timely sown (CATS), conventional tillage late sown (CTLS) and conservation agriculture late sown (CALS) using an association panel of 183 advanced wheat breeding lines along with 5 checks. Traits like Phi2 (Quantum yield of photosystem II; CATS:0.37, CALS: 0.31), RC (Relative chlorophyll content; CATS:55.51, CALS: 54.47) and PS1 (Active photosystem I centers; CATS:2.45, CALS: 2.23) have higher mean values in CA compared to CT under both sowing times. GWAS identified 80 MTAs for the studied traits across four production environments. The phenotypic variation explained (PVE) by these QTNs ranged from 2.15 to 40.22%. Gene annotation provided highly informative SNPs associated with Phi2, NPQ (Quantum yield of non-photochemical quenching), PS1, and RC which were linked with genes that play crucial roles in the physiological adaptation under both CA and CT. A highly significant SNP AX94651261 (9.43% PVE) was identified to be associated with Phi2, while two SNP markers AX94730536 (30.90% PVE) and AX94683305 (16.99% PVE) were associated with NPQ. Identified QTNs upon validation can be used in marker-assisted breeding programs to develop CA adaptive genotypes.

The story of a decade: Genomics, functional genomics, and molecular breeding in Brassica napus

Rapeseed (Brassica napus L.) is one of the major global sources of edible vegetable oil and is also used as a feed and pioneer crop and for sightseeing and industrial purposes. Improvements in genome sequencing and molecular marker technology have fueled a boom in functional genomic studies of major agronomic characters such as yield, quality, flowering time, and stress resistance. Moreover, introgression and pyramiding of key functional genes have greatly accelerated the genetic improvement of important traits. Here we summarize recent progress in rapeseed genomics and genetics, and we discuss effective molecular breeding strategies by exploring these findings in rapeseed. These insights will extend our understanding of the molecular mechanisms and regulatory networks underlying agronomic traits and facilitate the breeding process, ultimately contributing to more sustainable agriculture throughout the world.

Dissection of quantitative trait nucleotides and candidate genes associated with agronomic and yield-related traits under drought stress in rapeseed varieties: integration of genome-wide association study and transcriptomic analysis

Introduction

An important strategy to combat yield loss challenge is the development of varieties with increased tolerance to drought to maintain production. Improvement of crop yield under drought stress is critical to global food security.

Methods

In this study, we performed multiomics analysis in a collection of 119 diverse rapeseed (Brassica napus L.) varieties to dissect the genetic control of agronomic traits in two watering regimes [well-watered (WW) and drought stress (DS)] for 3 years. In the DS treatment, irrigation continued till the 50% pod development stage, whereas in the WW condition, it was performed throughout the whole growing season.

Results

The results of the genome-wide association study (GWAS) using 52,157 single-nucleotide polymorphisms (SNPs) revealed 1,281 SNPs associated with traits. Six stable SNPs showed sequence variation for flowering time between the two irrigation conditions across years. Three novel SNPs on chromosome C04 for plant weight were located within drought tolerance-related gene ABCG16, and their pleiotropically effects on seed weight per plant and seed yield were characterized. We identified the C02 peak as a novel signal for flowering time, harboring 52.77% of the associated SNPs. The 288-kbps LD decay distance analysis revealed 2,232 candidate genes (CGs) associated with traits. The CGs BIG1-D, CAND1, DRG3, PUP10, and PUP21 were involved in phytohormone signaling and pollen development with significant effects on seed number, seed weight, and grain yield in drought conditions. By integrating GWAS and RNA-seq, 215 promising CGs were associated with developmental process, reproductive processes, cell wall organization, and response to stress. GWAS and differentially expressed genes (DEGs) of leaf and seed in the yield contrasting accessions identified BIG1-D, CAND1, and DRG3 genes for yield variation.

Discussion

The results of our study provide insights into the genetic control of drought tolerance and the improvement of marker-assisted selection (MAS) for breeding high-yield and drought-tolerant varieties.

Multi-locus genome-wide association studies reveal the dynamic genetic architecture of flowering time in chrysanthemum

KEY MESSAGE

The dynamic genetic architecture of flowering time in chrysanthemum was elucidated by GWAS. Thirty-six known genes and 14 candidate genes were identified around the stable QTNs and QEIs, among which ERF-1 was highlighted. Flowering time (FT) adaptation is one of the major breeding goals in chrysanthemum, a multipurpose ornamental plant. In order to reveal the dynamic genetic architecture of FT in chrysanthemum, phenotype investigation of ten FT-related traits was conducted on 169 entries in 2 environments. The broad-sense heritability of five non-conditional FT traits, i.e., budding (FBD), visible coloring (VC), early opening (EO), full-bloom (OF) and decay period (DP), ranged from 56.93 to 84.26%, which were higher than that of the five derived conditional FT traits (38.51-75.13%). The phenotypic variation coefficients of OF_EO and DP_OF were relatively large ranging from 30.59 to 36.17%. Based on 375,865 SNPs, the compressed variance component mixed linear model 3VmrMLM was applied for a multi-locus genome-wide association study (GWAS). As a result, 313 quantitative trait nucleotides (QTNs) were identified for the non-conditional FT traits in single-environment analysis, while 119 QTNs and 67 QTN-by-environment interactions (QEIs) were identified in multi-environment analysis. As for the conditional traits, 343 QTNs were detected in single-environment analysis, and 119 QTNs and 83 QEIs were identified in multi- environment analysis. Among the genes around stable QTNs and QEIs, 36 were orthologs of known FT genes in Arabidopsis and other plants; 14 candidates were mined by combining the transcriptomics data and functional annotation, including ERF-1, ACA10, and FOP1. Furthermore, the haplotype analysis of ERF-1 revealed six elite accessions with extreme FBD. Our findings contribute to the understanding of dynamic genetic architecture of FT and provide valuable resources for future chrysanthemum molecular breeding programs.

Trade-offs between root-secreted acid phosphatase and root morphology traits, and their contribution to phosphorus acquisition in Brassica napus

Oilseed rape (Brassica napus) is one of the most important oil crops in the world and shows sensitivity to low phosphorus (P) availability. In many soils, organic P (Po) is the main component of the soil P pool. Po must be mineralised to Pi through phosphatases, and then taken up by plants. However, the relationship between root-secreted acid phosphatases (APase) and root morphology traits, two important P-acquisition strategies in response to P deficiency, is unclear among B. napus genotypes. This study aimed to understand their relationship and how they affect P acquisition, which is crucial for the sustainable utilisation of agricultural P resources. This study showed significant genotypic variations in root-secreted APase activity per unit root fresh weight (SAP) and total root-secreted APase activity per plant (total SAP) among 350 B. napus genotypes. Seed yield was positively correlated with total SAP but not significantly correlated with SAP. Six root traits of 18 B. napus genotypes with contrasting root biomass were compared under normal Pi, low Pi and Po. Genotypes with longer total root length (TRL) reduced SAP, but those with shorter TRL increased SAP under P deficiency. Additionally, TRL was important in P-acquisition under three P treatments, and total SAP was also important in P-acquisition under Po treatment. In conclusion, trade-offs existed between the two P-acquisition strategies among B. napus genotypes under P-deficient conditions. Total SAP was an important root trait under Po conditions. These results might help to breed B. napus with greater P-acquisition ability under low P availability conditions.

Functional genomics of Brassica napus: Progresses, challenges, and perspectives

Brassica napus, commonly known as rapeseed or canola, is a major oil crop contributing over 13% to the stable supply of edible vegetable oil worldwide. Identification and understanding the gene functions in the B. napus genome is crucial for genomic breeding. A group of genes controlling agronomic traits have been successfully cloned through functional genomics studies in B. napus. In this review, we present an overview of the progress made in the functional genomics of B. napus, including the availability of germplasm resources, omics databases and cloned functional genes. Based on the current progress, we also highlight the main challenges and perspectives in this field. The advances in the functional genomics of B. napus contribute to a better understanding of the genetic basis underlying the complex agronomic traits in B. napus and will expedite the breeding of high quality, high resistance and high yield in B. napus varieties.

Multi-locus genome-wide association study and genomic prediction for flowering time in chrysanthemum

MAIN CONCLUSION

Multi-locus GWAS detected several known and candidate genes responsible for flowering time in chrysanthemum. The associations could greatly increase the predictive ability of genome selection that accelerates the possible application of GS in chrysanthemum breeding. Timely flowering is critical for successful reproduction and determines the economic value for ornamental plants. To investigate the genetic architecture of flowering time in chrysanthemum, a multi-locus genome-wide association study (GWAS) was performed using a collection of 200 accessions and 330,710 single-nucleotide polymorphisms (SNPs) via 3VmrMLM method. Five flowering time traits including budding (FBD), visible colouring (VC), early opening (EO), full-bloom (OF) and senescing (SF) stages, plus five derived conditional traits were recorded in two environments. Extensive phenotypic variations were observed for these flowering time traits with coefficients of variation ranging from 6.42 to 38.27%, and their broad-sense heritability ranged from 71.47 to 96.78%. GWAS revealed 88 stable quantitative trait nucleotides (QTNs) and 93 QTN-by-environment interactions (QEIs) associated with flowering time traits, accounting for 0.50-8.01% and 0.30-10.42% of the phenotypic variation, respectively. Amongst the genes around these stable QTNs and QEIs, 21 and 10 were homologous to known flowering genes in Arabidopsis; 20 and 11 candidate genes were mined by combining the functional annotation and transcriptomics data, respectively, such as MYB55, FRIGIDA-like, WRKY75 and ANT. Furthermore, genomic selection (GS) was assessed using three models and seven unique marker datasets. We found the prediction accuracy (PA) using significant SNPs identified by GWAS under SVM model exhibited the best performance with PA ranging from 0.90 to 0.95. Our findings provide new insights into the dynamic genetic architecture of flowering time and the identified significant SNPs and candidate genes will accelerate the future molecular improvement of chrysanthemum.

Genome-wide association study of cooking-caused grain expansion in rice (Oryza sativa L.)

Cooking-caused rice grain expansion (CCRGE) is a critical trait for evaluating the cooking quality of rice. Previous quantitative trait locus (QTL) mapping studies on CCRGE have been limited to bi-parental populations, which restrict the exploration of natural variation and mapping resolution. To comprehensively and precisely dissect the genetic basis of CCRGE, we performed a genome-wide association study (GWAS) on three related indices: grain breadth expansion index (GBEI), grain length expansion index (GLEI), and grain length-breadth ratio expansion index (GREI), using 345 rice accessions grown in two years (environments) and 193,582 SNP markers. By analyzing each environment separately using seven different methods (3VmrMLM, mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, pKWmEB, ISIS EM-BLASSO), we identified a total of 32, 19 and 27 reliable quantitative trait nucleotides (QTNs) associated with GBEI, GLEI and GREI, respectively. Furthermore, by jointly analyzing the two environments using 3VmrMLM, we discovered 19, 22 and 25 QTNs, as well as 9, 5 and 7 QTN-by-environment interaction (QEIs) associated with GBEI, GLEI and GREI, respectively. Notably, 12, 9 and 15 QTNs for GBEI, GLEI and GREI were found within the intervals of previously reported QTLs. In the vicinity of these QTNs or QEIs, based on analyses of mutation type, gene ontology classification, haplotype, and expression pattern, we identified five candidate genes that are related to starch synthesis and endosperm development. The five candidate genes, namely, LOC_Os04g53310 (OsSSIIIb, near QTN qGREI-4.5s), LOC_Os05g02070 (OsMT2b, near QTN qGLEI-5.1s), LOC_Os06g04200 (wx, near QEI qGBEI-6.1i and QTNs qGREI-6.1s and qGLEI-6.1t), LOC_Os06g12450 (OsSSIIa, near QTN qGLEI-6.2t), and LOC_Os08g09230 (OsSSIIIa, near QTN qGBEI-8.1t), are predicted to be involved in the process of rice grain starch synthesis and to influence grain expansion after cooking. Our findings provide valuable insights and will facilitate genetic research and improvement of CCRGE.