SoyMD: a platform combining multi-omics data with various tools for soybean research and breeding.

Advanced multi-omics technologies offer much information that can uncover the regulatory mechanisms from genotype to phenotype. In soybean, numerous multi-omics databases have been published. Although they cover multiple omics, there are still limitations when it comes to the types and scales of omics datasets and analysis methods utilized. This study aims to address these limitations by collecting and integrating a comprehensive set of multi-omics datasets. This includes 38 genomes, transcriptomes from 435 tissue samples, 125 phenotypes from 6686 accessions, epigenome data involving histone modification, transcription factor binding, chromosomal accessibility and chromosomal interaction, as well as genetic variation data from 24 501 soybean accessions. Then, common analysis pipelines and statistical methods were applied to mine information from these multi-omics datasets, resulting in the successful establishment of a user-friendly multi-omics database called SoyMD (https://yanglab.hzau.edu.cn/SoyMD/#/). SoyMD provides researchers with efficient query options and analysis tools, allowing them to swiftly access relevant omics information and conduct comprehensive multi-omics data analyses. Another notable feature of SoyMD is its capability to facilitate the analysis of candidate genes, as demonstrated in the case study on seed oil content. This highlights the immense potential of SoyMD in soybean genetic breeding and functional genomics research.

AnimalMetaOmics: a multi-omics data resources for exploring animal microbial genomes and microbiomes.

The Animal Meta-omics landscape database (AnimalMetaOmics, https://yanglab.hzau.edu.cn/animalmetaomics#/) is a comprehensive and freely available resource that includes metagenomic, metatranscriptomic, and metaproteomic data from various non-human animal species and provides abundant information on animal microbiomes, including cluster analysis of microbial cognate genes, functional gene annotations, active microbiota composition, gene expression abundance, and microbial protein identification. In this work, 55 898 microbial genomes were annotated from 581 animal species, including 42 924 bacterial genomes, 12 336 virus genomes, 496 archaea genomes and 142 fungi genomes. Moreover, 321 metatranscriptomic datasets were analyzed from 31 animal species and 326 metaproteomic datasets from four animal species, as well as the pan-genomic dynamics and compositional characteristics of 679 bacterial species and 13 archaea species from animal hosts. Researchers can efficiently access and acquire the information of cross-host microbiota through a user-friendly interface, such as species, genomes, activity levels, expressed protein sequences and functions, and pan-genome composition. These valuable resources provide an important reference for better exploring the classification, functional diversity, biological process diversity and functional genes of animal microbiota.

CottonMD: a multi-omics database for cotton biological study.

Cotton is an important economic crop, and many loci for important traits have been identified, but it remains challenging and time-consuming to identify candidate or causal genes/variants and clarify their roles in phenotype formation and regulation. Here, we first collected and integrated the multi-omics datasets including 25 genomes, transcriptomes in 76 tissue samples, epigenome data of five species and metabolome data of 768 metabolites from four tissues, and genetic variation, trait and transcriptome datasets from 4180 cotton accessions. Then, a cotton multi-omics database (CottonMD, http://yanglab.hzau.edu.cn/CottonMD/) was constructed. In CottonMD, multiple statistical methods were applied to identify the associations between variations and phenotypes, and many easy-to-use analysis tools were provided to help researchers quickly acquire the related omics information and perform multi-omics data analysis. Two case studies demonstrated the power of CottonMD for identifying and analyzing the candidate genes, as well as the great potential of integrating multi-omics data for cotton genetic breeding and functional genomics research.

Interaction between phenylpropane metabolism and oil accumulation in the developing seed of Brassica napus revealed by high temporal-resolution transcriptomes.

BACKGROUND: Brassica napus is an important oilseed crop providing high-quality vegetable oils for human consumption and non-food applications. However, the regulation between embryo and seed coat for the synthesis of oil and phenylpropanoid compounds remains largely unclear. RESULTS: Here, we analyzed the transcriptomes in developing seeds at 2-day intervals from 14 days after flowering (DAF) to 64 DAF. The 26 high-resolution time-course transcriptomes are clearly clustered into five distinct groups from stage I to stage V. A total of 2217 genes including 136 transcription factors, are specifically expressed in the seed and show high temporal specificity by being expressed only at certain stages of seed development. Furthermore, we analyzed the co-expression networks during seed development, which mainly included master regulatory transcription factors, lipid, and phenylpropane metabolism genes. The results show that the phenylpropane pathway is prominent during seed development, and the key enzymes in the phenylpropane metabolic pathway, including TT5, BAN, and the transporter TT19, were directly or indirectly related to many key enzymes and transcription factors involved in oil accumulation. We identified candidate genes that may regulate seed oil content based on the co-expression network analysis combined with correlation analysis of the gene expression with seed oil content and seed coat content. CONCLUSIONS: Overall, these results reveal the transcriptional regulation between lipid and phenylpropane accumulation during B. napus seed development. The established co-expression networks and predicted key factors provide important resources for future studies to reveal the genetic control of oil accumulation in B. napus seeds.

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.

Comparative transcriptome profiling reveals the multiple levels of crosstalk in phytohormone networks in Brassica napus.

Plant hormones are the intrinsic factors that control plant development. The integration of different phytohormone pathways in a complex network of synergistic, antagonistic and additive interactions has been elucidated in model plants. However, the systemic level of transcriptional responses to hormone crosstalk in Brassica napus is largely unknown. Here, we present an in-depth temporal-resolution study of the transcriptomes of the seven hormones in B. napus seedlings. Differentially expressed gene analysis revealed few common target genes that co-regulated (up- and down-regulated) by seven hormones; instead, different hormones appear to regulate distinct members of protein families. We then constructed the regulatory networks between the seven hormones side by side, which allowed us to identify key genes and transcription factors that regulate the hormone crosstalk in B. napus. Using this dataset, we uncovered a novel crosstalk between gibberellin and cytokinin in which cytokinin homeostasis was mediated by RGA-related CKXs expression. Moreover, the modulation of gibberellin metabolism by the identified key transcription factors was confirmed in B. napus. Furthermore, all data were available online from http://yanglab.hzau.edu.cn/BnTIR/hormone. Our study reveals an integrated hormone crosstalk network in Brassica napus, which also provides a versatile resource for future hormone studies in plant species.

High-throughput phenotyping-based quantitative trait loci mapping reveals the genetic architecture of the salt stress tolerance of Brassica napus.

Salt stress is a major limiting factor that severely affects the survival and growth of crops. It is important to understand the salt stress tolerance ability of Brassica napus and explore the underlying related genetic resources. We used a high-throughput phenotyping platform to quantify 2111 image-based traits (i-traits) of a natural population under three different salt stress conditions and an intervarietal substitution line (ISL) population under nine different stress conditions to monitor and evaluate the salt stress tolerance of B. napus over time. We finally identified 928 high-quality i-traits associated with the salt stress tolerance of B. napus. Moreover, we mapped the salt stress-related loci in the natural population via a genome-wide association study and performed a linkage analysis associated with the ISL population, respectively. These results revealed 234 candidate genes associated with salt stress response, and two novel candidate genes, BnCKX5 and BnERF3, were experimentally verified to regulate the salt stress tolerance of B. napus. This study demonstrates the feasibility of using high-throughput phenotyping-based quantitative trait loci mapping to accurately and comprehensively quantify i-traits associated with B. napus. The mapped loci could be used for genomics-assisted breeding to genetically improve the salt stress tolerance of B. napus.

Plant-ImputeDB: an integrated multiple plant reference panel database for genotype imputation.

Genotype imputation is a process that estimates missing genotypes in terms of the haplotypes and genotypes in a reference panel. It can effectively increase the density of single nucleotide polymorphisms (SNPs), boost the power to identify genetic association and promote the combination of genetic studies. However, there has been a lack of high-quality reference panels for most plants, which greatly hinders the application of genotype imputation. Here, we developed Plant-ImputeDB (http://gong_lab.hzau.edu.cn/Plant_imputeDB/), a comprehensive database with reference panels of 12 plant species for online genotype imputation, SNP and block search and free download. By integrating genotype data and whole-genome resequencing data of plants from various studies and databases, the current Plant-ImputeDB provides high-quality reference panels of 12 plant species, including ∼69.9 million SNPs from 34 244 samples. It also provides an easy-to-use online tool with the option of two popular tools specifically designed for genotype imputation. In addition, Plant-ImputeDB accepts submissions of different types of genomic variations, and provides free and open access to all publicly available data in support of related research worldwide. In general, Plant-ImputeDB may serve as an important resource for plant genotype imputation and greatly facilitate the research on plant genetic research.

Calling large indels in 1047 Arabidopsis with IndelEnsembler.

Large indels greatly impact the observable phenotypes in different organisms including plants and human. Hence, extracting large indels with high precision and sensitivity is important. Here, we developed IndelEnsembler to detect large indels in 1047 Arabidopsis whole-genome sequencing data. IndelEnsembler identified 34 093 deletions, 12 913 tandem duplications and 9773 insertions. Our large indel dataset was more comprehensive and accurate compared with the previous dataset of AthCNV (1). We captured nearly twice of the ground truth deletions and on average 27% more ground truth duplications compared with AthCNV, though our dataset has less number of large indels compared with AthCNV. Our large indels were positively correlated with transposon elements across the Arabidopsis genome. The non-homologous recombination events were the major formation mechanism of deletions in Arabidopsis genome. The Neighbor joining (NJ) tree constructed based on IndelEnsembler's deletions clearly divided the geographic subgroups of 1047 Arabidopsis. More importantly, our large indels represent a previously unassessed source of genetic variation. Approximately 49% of the deletions have low linkage disequilibrium (LD) with surrounding single nucleotide polymorphisms. Some of them could affect trait performance. For instance, using deletion-based genome-wide association study (DEL-GWAS), the accessions containing a 182-bp deletion in AT1G11520 had delayed flowering time and all accessions in north Sweden had the 182-bp deletion. We also found the accessions with 65-bp deletion in the first exon of AT4G00650 (FRI) flowered earlier than those without it. These two deletions cannot be detected in AthCNV and, interestingly, they do not co-occur in any Arabidopsis thaliana accession. By SNP-GWAS, surrounding SNPs of these two deletions do not correlate with flowering time. This example demonstrated that existing large indel datasets miss phenotypic variations and our large indel dataset filled in the gap.

R gene triplication confers European fodder turnip with improved clubroot resistance.

Clubroot is one of the most important diseases for many important cruciferous vegetables and oilseed crops worldwide. Different clubroot resistance (CR) loci have been identified from only limited species in Brassica, making it difficult to compare and utilize these loci. European fodder turnip ECD04 is considered one of the most valuable resources for CR breeding. To explore the genetic and evolutionary basis of CR in ECD04, we sequenced the genome of ECD04 using de novo assembly and identified 978 candidate R genes. Subsequently, the 28 published CR loci were physically mapped to 15 loci in the ECD04 genome, including 62 candidate CR genes. Among them, two CR genes, CRA3.7.1 and CRA8.2.4, were functionally validated. Phylogenetic analysis revealed that CRA3.7.1 and CRA8.2.4 originated from a common ancestor before the whole-genome triplication (WGT) event. In clubroot susceptible Brassica species, CR-gene homologues were affected by transposable element (TE) insertion, resulting in the loss of CR function. It can be concluded that the current functional CR genes in Brassica rapa and non-functional CR genes in other Brassica species were derived from a common ancestral gene before WGT. Finally, a hypothesis for CR gene evolution is proposed for further discussion.

Multi-Group Gorilla Troops Optimizer with Multi-Strategies for 3D Node Localization of Wireless Sensor Networks.

The localization problem of nodes in wireless sensor networks is often the focus of many researches. This paper proposes an opposition-based learning and parallel strategies Artificial Gorilla Troop Optimizer (OPGTO) for reducing the localization error. Opposition-based learning can expand the exploration space of the algorithm and significantly improve the global exploration ability of the algorithm. The parallel strategy divides the population into multiple groups for exploration, which effectively increases the diversity of the population. Based on this parallel strategy, we design communication strategies between groups for different types of optimization problems. To verify the optimized effect of the proposed OPGTO algorithm, it is tested on the CEC2013 benchmark function set and compared with Particle Swarm Optimization (PSO), Sine Cosine Algorithm (SCA), Whale Optimization Algorithm (WOA) and Artificial Gorilla Troops Optimizer (GTO). Experimental studies show that OPGTO has good optimization ability, especially on complex multimodal functions and combinatorial functions. Finally, we apply OPGTO algorithm to 3D localization of wireless sensor networks in the real terrain. Experimental results proved that OPGTO can effectively reduce the localization error based on Time Difference of Arrival (TDOA).

Development and screening of EMS mutants with altered seed oil content or fatty acid composition in Brassica napus.

Brassica napus is an important oilseed crop in the world, and the mechanism of seed oil biosynthesis in B. napus remains unclear. In order to study the mechanism of oil biosynthesis and generate germplasms for breeding, an ethyl methanesulfonate (EMS) mutant population with ~100 000 M2 lines was generated using Zhongshuang 11 as the parent line. The EMS-induced genome-wide mutations in M2-M4 plants were assessed. The average number of mutations including single nucleotide polymorphisms and insertion/deletion in M2-M4 was 21 177, 28 675 and 17 915, respectively. The effects of the mutations on gene function were predicted in M2-M4 mutants, respectively. We screened the seeds from 98 113 M2 lines, and 9415 seed oil content and fatty acid mutants were identified. We further confirmed 686 mutants with altered seed oil content and fatty acid in advanced generation (M4 seeds). Five representative M4 mutants with increased oleic acid were re-sequenced, and the potential causal variations in FAD2 and ROD1 genes were identified. This study generated and screened a large scale of B. napus EMS mutant population, and the identified mutants could provide useful genetic resources for the study of oil biosynthesis and genetic improvement of seed oil content and fatty acid composition of B. napus in the future.

Dissection of genetic architecture for glucosinolate accumulations in leaves and seeds of Brassica napus by genome-wide association study.

Glucosinolates (GSLs), whose degradation products have been shown to be increasingly important for human health and plant defence, compose important secondary metabolites found in the order Brassicales. It is highly desired to enhance pest and disease resistance by increasing the leaf GSL content while keeping the content low in seeds of Brassica napus, one of the most important oil crops worldwide. Little is known about the regulation of GSL accumulation in the leaves. We quantified the levels of 9 different GSLs and 15 related traits in the leaves of 366 accessions and found that the seed and leaf GSL content were highly correlated (r = 0.79). A total of 78 loci were associated with GSL traits, and five common and eleven tissue-specific associated loci were related to total leaf and seed GSL content. Thirty-six candidate genes were inferred to be involved in GSL biosynthesis. The candidate gene BnaA03g40190D (BnaA3.MYB28) was validated by DNA polymorphisms and gene expression analysis. This gene was responsible for high leaf/low seed GSL content and could explain 30.62% of the total leaf GSL variation in the low seed GSL panel and was not fixed during double-low rapeseed breeding. Our results provide new insights into the genetic basis of GSL variation in leaves and seeds and may facilitate the metabolic engineering of GSLs and the breeding of high leaf/low seed GSL content in B. napus.

Nonspecific phospholipase C6 increases seed oil production in oilseed Brassicaceae plants.

Plant oils are valuable commodities for food, feed, renewable industrial feedstocks and biofuels. To increase vegetable oil production, here we show that the nonspecific phospholipase C6 (NPC6) promotes seed oil production in the Brassicaceae seed oil species Arabidopsis, Camelina and oilseed rape. Overexpression of NPC6 increased seed oil content, seed weight and oil yield both in Arabidopsis and Camelina, whereas knockout of NPC6 decreased seed oil content and seed size. NPC6 is associated with the chloroplasts and microsomal membranes, and hydrolyzes phosphatidylcholine and galactolipids to produce diacylglycerol. Knockout and overexpression of NPC6 decreased and increased, respectively, the flux of fatty acids from phospholipids and galactolipids into triacylglycerol production. Candidate-gene association study in oilseed rape indicates that only BnNPC6.C01 of the four homeologues NPC6s is associated with seed oil content and yield. Haplotypic analysis indicates that the BnNPC6.C01 favorable haplotype can increase both seed oil content and seed yield. These results indicate that NPC6 promotes membrane glycerolipid turnover to accumulate TAG production in oil seeds and that NPC6 has a great application potential for oil yield improvement.

Modifications of fatty acid profile through targeted mutation at BnaFAD2 gene with CRISPR/Cas9-mediated gene editing in Brassica napus.

KEY MESSAGE: Genomic editing with CRISPR/Cas9 system can simultaneously modify multiple copies of theBnaFAD2 gene to develop novel variations in fatty acids profiles in polyploidy rapeseed. Fatty acid composition affects edible and processing quality of vegetable oil and has been one of the primary targets for genetic modification in oilseed crops including rapeseed (Brassica napus). Fatty acid desaturase 2 gene, FAD2, is a key player that affects three major fatty acids, namely oleic, linoleic and linolenic acid, in oilseed plants. Previously, we showed that there are four copies of BnaFAD2 in allotetraploid rapeseed. In this study, we further established spatiotemporal expression pattern of each copy of BnaFAD2 using published RNA-seq data. Genomic editing technology based on CRISPR/Cas9 system was used to mutate all the copies of BnaFAD2 to create novel allelic variations in oleic acid and other fatty acid levels. A number of mutants at two targeting sites were identified, and the phenotypic variation in the mutants was systematically evaluated. The oleic acid content in the seed of the mutants increased significantly with the highest exceeding 80% compared with wild type of 66.43%, while linoleic and linolenic acid contents decreased accordingly. Mutations on BnaFAD2.A5 caused more dramatic changes of fatty acid profile than the mutations on BnaFAD2.C5 alleles that were identified with gene editing technique for the first time. Moreover, combining different mutated alleles of BnaFAD2 can even broaden the variation more dramatically. It was found that effects of different mutation types at BnaFAD2 alleles on oleic levels varied, indicating a possibility to manipulate fatty acid levels by precise mutation at specific region of a gene.

Association between red blood cell distribution width and long-term mortality among patients undergoing percutaneous coronary intervention with previous history of cancer.

Background: The number of patients suffering from coronary heart disease with cancer is rising. There is scarce evidence concerning the biomarkers related to prognosis among patients undergoing percutaneous coronary intervention (PCI) with cancer. Thus, the aim of this study was to investigate the association between red blood cell distribution width (RDW) and prognosis in this population.Methods: A total of 172 patients undergoing PCI with previous history of cancer were enrolled in this retrospective study. The endpoint was long-term all-cause mortality. According to tertiles of RDW, the patients were classified into three groups: Tertile 1 (RDW <12.8%), Tertile 2 (RDW ≥12.8% and <13.5%) and Tertile 3 (RDW ≥13.5%).Results: During an average follow-up period of 33.3 months, 29 deaths occurred. Compared with Tertile 3, mortality of Tertile 1 and Tertile 2 was significantly lower in the Kaplan-Meier analysis. In multivariate Cox regression analysis, RDW remained an independent risk factor of mortality (HR: 1.938, 95% CI: 1.295-2.655, p < 0.001). The all-cause mortality in Tertile 3 was significantly higher than that in Tertile 1 (HR: 5.766; 95% CI: 1.426-23.310, p = 0.014).Conclusions: An elevated RDW level (≥13.5%) was associated with long-term all-cause mortality among patients undergoing PCI with previous history of cancer.

A novel quantitative trait locus on chromosome A9 controlling oleic acid content in Brassica napus.

One of the most important goals in the breeding of oilseed crops, including Brassica napus, is to improve the quality of edible vegetable oil, which is mainly determined by the seed fatty acid composition, particularly the C18:1 content. Previous studies have indicated that the C18:1 content is a polygenic trait, and no stable quantitative trait loci (QTLs) except for FAD2 have been reported. By performing a GWAS using 375 low erucic acid B. napus accessions genotyped with the Brassica 60K SNP array and constructing a high-density SNP-based genetic map of a 150 DH population, we identified a novel QTL on the A9 chromosome. The novel locus could explain 11.25%, 5.72% and 6.29% of phenotypic variation during three consecutive seasons and increased the C18:1 content by approximately 3%-5%. By fine mapping and gene expression analysis, we found three potential candidate genes and verified the fatty acids in a homologous gene mutant of Arabidopsis. A metal ion-binding protein was found to be the most likely candidate gene in the region. Thus, the C18:1 content can be further increased to about 80% with this novel locus together with FAD2 mutant allele without compromise of agronomic performance. A closely linked marker, BnA129, for this novel QTL (OLEA9) was developed so that we can effectively identify materials with high C18:1 content at an early growth stage by marker-assisted selection. Our results may also provide new insight for understanding the complex genetic mechanism of fatty acid metabolism.

Development of iFOX-hunting as a functional genomic tool and demonstration of its use to identify early senescence-related genes in the polyploid Brassica napus.

Functional genomic studies of many polyploid crops, including rapeseed (Brassica napus), are constrained by limited tool sets. Here we report development of a gain-of-function platform, termed 'iFOX (inducible Full-length cDNA OvereXpressor gene)-Hunting', for inducible expression of B. napus seed cDNAs in Arabidopsis. A Gateway-compatible plant gene expression vector containing a methoxyfenozide-inducible constitutive promoter for transgene expression was developed. This vector was used for cloning of random cDNAs from developing B. napus seeds and subsequent Agrobacterium-mediated transformation of Arabidopsis. The inducible promoter of this vector enabled identification of genes upon induction that are otherwise lethal when constitutively overexpressed and to control developmental timing of transgene expression. Evaluation of a subset of the resulting ~6000 Arabidopsis transformants revealed a high percentage of lines with full-length B. napus transgene insertions. Upon induction, numerous iFOX lines with visible phenotypes were identified, including one that displayed early leaf senescence. Phenotypic analysis of this line (rsl-1327) after methoxyfenozide induction indicated high degree of leaf chlorosis. The integrated B. napuscDNA was identified as a homolog of an Arabidopsis acyl-CoA binding protein (ACBP) gene designated BnACBP1-like. The early senescence phenotype conferred by BnACBP1-like was confirmed by constitutive expression of this gene in Arabidopsis and B. napus. Use of the inducible promoter in the iFOX line coupled with RNA-Seq analyses allowed mechanistic clues and a working model for the phenotype associated with BnACBP1-like expression. Our results demonstrate the utility of iFOX-Hunting as a tool for gene discovery and functional characterization of Brassica napus genome.