Construction of a Quantitative Genomic Map, Identification and Expression Analysis of Candidate Genes for Agronomic and Disease-Related Traits in Brassica napus

Plant Functional Genomics Based on High-Throughput CRISPR Library Knockout Screening: A Perspective

Plant biology studies in the post-genome era have been focused on annotating genome sequences' functions. The established plant mutant collections have greatly accelerated functional genomics research in the past few decades. However, most plant genome sequences' roles and the underlying regulatory networks remain substantially unknown. Clustered, regularly interspaced short palindromic repeat (CRISPR)-associated systems are robust, versatile tools for manipulating plant genomes with various targeted DNA perturbations, providing an excellent opportunity for high-throughput interrogation of DNA elements' roles. This study compares methods frequently used for plant functional genomics and then discusses different DNA multi-targeted strategies to overcome gene redundancy using the CRISPR-Cas9 system. Next, this work summarizes recent reports using CRISPR libraries for high-throughput gene knockout and function discoveries in plants. Finally, this work envisions the future perspective of optimizing and leveraging CRISPR library screening in plant genomes' other uncharacterized DNA sequences.

Meta-analysis of seed weight QTLome using a consensus and highly dense genetic map in Brassica napus L

KEY MESSAGE

We report here the discovery of high-confidence MQTL regions and of putative candidate genes associated with seed weight in B. napus using a highly dense consensus genetic map and by comparing various large-scale multiomics datasets. Seed weight (SW) is a direct determinant of seed yield in Brassica napus and is controlled by many loci. To unravel the main genomic regions associated with this complex trait, we used 13 available genetic maps to construct a consensus and highly dense map, comprising 40,401 polymorphic markers and 9191 genetic bins, harboring a cumulative length of 3047.8 cM. Then, we performed a meta-analysis using 639 projected SW quantitative trait loci (QTLs) obtained from studies conducted since 1999, enabling the identification of 57 meta-QTLS (MQTLs). The confidence intervals of our MQTLs were 9.8 and 4.3 times lower than the average CIs of the original QTLs for the A and C subgenomes, respectively, resulting in the detection of some key genes and several putative novel candidate genes associated with SW. By comparing the genes identified in MQTL intervals with multiomics datasets and coexpression analyses of common genes, we defined a more reliable and shorter list of putative candidate genes potentially involved in the regulation of seed maturation and SW. As an example, we provide a list of promising genes with high expression levels in seeds and embryos (e.g., BnaA03g04230D, BnaC03g08840D, BnaA10g29580D and BnaA03g27410D) that can be more finely studied through functional genetics experiments or that may be useful for MQTL-assisted breeding for SW. The high-density genetic consensus map and the single nucleotide polymorphism (SNP) physical map generated from the latest B. napus cv. Darmor-bzh v10 assembly will be a valuable resource for further mapping and map-based cloning of other important traits.

Genetic dissection of thousand-seed weight in linseed (Linum usitatissimum L.) using multi-locus genome-wide association study

Flaxseed/linseed is an important oilseed crop having applications in the food, nutraceutical, and paint industry. Seed weight is one of the most crucial determinants of seed yield in linseed. Here, quantitative trait nucleotides (QTNs) associated with thousand-seed weight (TSW) have been identified using multi-locus genome-wide association study (ML-GWAS). Field evaluation was carried out in five environments in multi-year-location trials. SNP genotyping information of the AM panel of 131 accessions comprising 68,925 SNPs was employed for ML-GWAS. From the six ML-GWAS methods employed, five methods helped identify a total of 84 unique significant QTNs for TSW. QTNs identified in ≥ 2 methods/environments were designated as stable QTNs. Accordingly, 30 stable QTNs have been identified for TSW accounting up to 38.65% trait variation. Alleles with positive effect on trait were analyzed for 12 strong QTNs with r ² ≥ 10.00%, which showed significant association of specific alleles with higher trait value in three or more environments. A total of 23 candidate genes have been identified for TSW, which included B3 domain-containing transcription factor, SUMO-activating enzyme, protein SCARECROW, shaggy-related protein kinase/BIN2, ANTIAUXIN-RESISTANT 3, RING-type E3 ubiquitin transferase E4, auxin response factors, WRKY transcription factor, and CBS domain-containing protein. In silico expression analysis of candidate genes was performed to validate their possible role in different stages of seed development process. The results from this study provide significant insight and elevate our understanding on genetic architecture of TSW trait in linseed.

Linkage and association mapping of ovule number per ovary (ON) in oilseed rape (Brassica napus L.)

Ovule number (ON) produced during flower development determines the maximum number of seeds per silique and thereby affects crop productivity; however, the genetic basis of ON remains poorly understood in oilseed rape (Brassica napus). In this study, we genetically dissected the ON variations in a double haploid (DH) population and in natural population (NP) by linkage mapping and genome-wide association analysis. Phenotypic analysis showed that ON displayed normal distribution in both populations with the broad-sense heritability of 0.861 (DH population) and 0.930 (natural population). Linkage mapping identified 5 QTLs related to ON, including qON-A03, qON-A07, qON-A07-2, qON-A10, and qON-C06. Genome-wide association studies (GWAS) revealed 214, 48, and 40 significant single-nucleotide polymorphisms (SNPs) by individually using the single-locus model GLM and the multiple-locus model MrMLM and FASTMrMLM. The phenotypic variation explained (PVE) by these QTLs and SNPs ranged from 2.00-17.40% to 5.03-7.33%, respectively. Integration of the results from both strategies identified four consensus genomic regions associated with ON from the chromosomes A03, A07, and A10. Our results preliminarily resolved the genetic basis of ON and provides useful molecular markers for plant yield improvement in B. napus.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01355-7.

Transcriptomic analysis of rapeseed (Brassica napus. L.) seed development in Xiangride, Qinghai Plateau, reveals how its special eco-environment results in high yield in high-altitude areas

As one of the most important oil crops, rapeseed (Brassica napus) is cultivated worldwide to produce vegetable oil, animal feed, and biodiesel. As the population grows and the need for renewable energy increases, the breeding and cultivation of high-yield rapeseed varieties have become top priorities. The formation of a high rapeseed yield is so complex because it is influenced not only by genetic mechanisms but also by many environmental conditions, such as climatic conditions and different farming practices. Interestingly, many high-yield areas are located in special eco-environments, for example, in the high-altitude Xiangride area of the Qinghai Plateau. However, the molecular mechanisms underlying the formation of high yields in such a special eco-environment area remain largely unknown. Here, we conducted field yield analysis and transcriptome analysis in the Xiangride area. Compared with the yield and environmental factors in the Xinning area (a low-yielding area), we found that the relatively longer daylight length is the key to high rapeseed yield in the Xiangride area, which leads up to a 52.1% increase in rapeseed yield, especially the increase in thousand seed weight and silique number (SN). Combined with transcriptome H-cluster analysis and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional analyses, we can assume that the grain development of rapeseed in the Xiangride area is ahead of schedule and lasts for a long time, leading to the high-yield results in the Xiangride area, confirmed by the expression analysis by quantitative real-time polymerase chain reaction (qRT-PCR) of yield-related genes. Our results provide valuable information for further exploring the molecular mechanism underlying high yield in special ecological environments and provide a helpful reference for studying seed development characteristics in special-producing regions for Brassica napus.