Genome-Wide Association Study of Genetic Control of Seed Fatty Acid Biosynthesis in Brassica napus

Hello darkness, my old friend: 3-KETOACYL-COENZYME A SYNTHASE4 is a branch point in the regulation of triacylglycerol synthesis in Arabidopsis thaliana

Plant lipids are important as alternative sources of carbon and energy when sugars or starch are limited. Here, we applied combined heat and darkness or extended darkness to a panel of ∼300 Arabidopsis (Arabidopsis thaliana) accessions to study lipid remodeling under carbon starvation. Natural allelic variation at 3-KETOACYL-COENZYME A SYNTHASE4 (KCS4), a gene encoding an enzyme involved in very long chain fatty acid (VLCFA) synthesis, underlies the differential accumulation of polyunsaturated triacylglycerols (puTAGs) under stress. Ectopic expression of KCS4 in yeast and plants proved that KCS4 is a functional enzyme localized in the endoplasmic reticulum with specificity for C22 and C24 saturated acyl-CoA. Allelic mutants and transient overexpression in planta revealed the differential role of KCS4 alleles in VLCFA synthesis and leaf wax coverage, puTAG accumulation, and biomass. Moreover, the region harboring KCS4 is under high selective pressure and allelic variation at KCS4 correlates with environmental parameters from the locales of Arabidopsis accessions. Our results provide evidence that KCS4 plays a decisive role in the subsequent fate of fatty acids released from chloroplast membrane lipids under carbon starvation. This work sheds light on both plant response mechanisms and the evolutionary events shaping the lipidome under carbon starvation.

Identification of candidate genes for LepR1 resistance against Leptosphaeria maculans in Brassica napus

Utilising resistance (R) genes, such as LepR1, against Leptosphaeria maculans, the causal agent of blackleg in canola (Brassica napus), could help manage the disease in the field and increase crop yield. Here we present a genome wide association study (GWAS) in B. napus to identify LepR1 candidate genes. Disease phenotyping of 104 B. napus genotypes revealed 30 resistant and 74 susceptible lines. Whole genome re-sequencing of these cultivars yielded over 3 million high quality single nucleotide polymorphisms (SNPs). GWAS in mixed linear model (MLM) revealed a total of 2,166 significant SNPs associated with LepR1 resistance. Of these SNPs, 2108 (97%) were found on chromosome A02 of B. napus cv. Darmor bzh v9 with a delineated LepR1_mlm1 QTL at 15.11-26.08 Mb. In LepR1_mlm1, there are 30 resistance gene analogs (RGAs) (13 nucleotide-binding site-leucine rich repeats (NLRs), 12 receptor-like kinases (RLKs), and 5 transmembrane-coiled-coil (TM-CCs)). Sequence analysis of alleles in resistant and susceptible lines was undertaken to identify candidate genes. This research provides insights into blackleg resistance in B. napus and assists identification of the functional LepR1 blackleg resistance gene.

Identification of candidate genes in cotton associated with specific seed traits and their initial functional characterization in Arabidopsis

Oilseed crops are used to produce vegetable oil to satisfy the requirements of humans and livestock. Cotton (Gossypium spp.) is of great economic value because it is used as both an important textile commodity and a nutrient-rich resource. Cottonseed oil is rich in polyunsaturated fatty acids and does not contain trans fatty acids; hence, it is considered a healthy vegetable oil. However, research on the genetic basis for cottonseed protein content, oil production, and fatty acid composition is lacking. Here, we investigated the protein content, oil content, and fatty acid composition in terms of oleic acid (C18:1) and linoleic acid (C18:2) in mature cottonseeds from 318 Gossypium hirsutum accessions. Moreover, we examined the dynamic change of protein content and lipid composition including palmitic acid (C16:0), stearic acid (C18:0), oleic acid (C18:1), linoleic acid (C18:2), and linolenic acid (C18:3) in developing seeds from 258 accessions at 10 and 20 days post-anthesis. Then, we conducted a genome-wide association study and identified 152 trait-associated loci and 64 candidate genes responsible for protein and oil-related contents in mature cottonseeds and ovules. Finally, six candidate genes were experimentally validated to be involved in the regulation of fatty acid biosynthesis through heterologous expression in Arabidopsis. These results comprise a solid foundation for expanding our understanding of lipid biosynthesis in cotton, which will help breeders manipulate protein and oil contents to make it a fully developed 'fiber, food, and oil crop'.

Genomic Regions Associated With Seed Meal Quality Traits in Brassica napus Germplasm

The defatted Brassica napus (rapeseed) meal can be high-protein feed for livestock as the protein value of rapeseed meal is higher than that of the majority of other vegetable proteins. Extensive work has already been carried out on developing canola rapeseed where the focus was on reducing erucic acid and glucosinolate content, with less consideration to other antinutritional factors such as tannin, phytate, sinapine, crude fiber, etc. The presence of these antinutrients limits the use and marketing of rapeseed meals and a significant amount of it goes unused and ends up as waste. We investigated the genetic architecture of crude protein, methionine, tryptophan, total phenols, β-carotene, glucosinolates (GLSs), phytate, tannins, sinapine, and crude fiber content of defatted seed meal samples by conducting a genome-wide association study (GWAS), using a diversity panel comprising 96 B. napus genotypes. Genotyping by sequencing was used to identify 77,889 SNPs, spread over 19 chromosomes. Genetic diversity and phenotypic variations were generally high for the studied traits. A total of eleven genotypes were identified which showed high-quality protein, high antioxidants, and lower amount of antinutrients. A significant negative correlation between protein and limiting amino acids and a significant positive correlation between GLS and phytic acid were observed. General and mixed linear models were used to estimate the association between the SNP markers and the seed quality traits and quantile-quantile (QQ) plots were generated to allow the best-fit algorithm. Annotation of genomic regions around associated SNPs helped to predict various trait-related candidates such as ASP2 and EMB1027 (amino acid biosynthesis); HEMA2, GLU1, and PGM (tryptophan biosynthesis); MS3, CYSD1, and MTO1 (methionine biosynthesis); LYC (β-carotene biosynthesis); HDR and ISPF (MEP pathway); COS1 (riboflavin synthesis); UGT (phenolics biosynthesis); NAC073 (cellulose and hemicellulose biosynthesis); CYT1 (cellulose biosynthesis); BGLU45 and BGLU46 (lignin biosynthesis); SOT12 and UGT88A1 (flavonoid pathway); and CYP79A2, DIN2, and GSTT2 (GLS metabolism), etc. The functional validation of these candidate genes could confirm key seed meal quality genes for germplasm enhancement programs directed at improving protein quality and reducing the antinutritional components in B. napus.

Breeding of a new variety of peanut with high-oleic-acid content and high-yield by marker-assisted backcrossing

Peanut (Arachis hypogaea L.) is an important crop used for oil production, and oleic acid is a major factor in determining oil quality. Alterations in the oleic acid content can improve the nutritional quality and oxidative stability and prolong the shelf life of peanut products. The objective of this study was to develop a peanut variety with a high-oleic-acid content and high yield. One elite variety, "huayu22," was hybridized with the high-oleic-acid "KN176" donor and backcrossed for four generations as the recurrent parent using fad2 marker-assisted backcross selection. Based on the Kompetitive allele-specific PCR (KASP) screening of fad2 markers, the oleic acid content of advanced generations derived by selfing was assessed by near-infrared reflectance spectroscopy and gas chromatography. The genetic background recovery rate of four BC4F4 lines showed an average of 92.34% and was confirmed by genotyping using the Axiom_Arachis 58 K SNP array. Across these superior lines in BC4F6 generations, one line with a high-oleic-acid content and high yield was detected and named "YH61." In particular, yield comparison experiments showed that YH61 exhibited high and stable yield at three different locations and was moderately resistant to leaf spot disease. The distinctness, uniformity and stability (DUS) testing for two consecutive years suggested that YH61 reached the standard for variety rights application. The use of the peanut variety YH61 contributed to the expansion of the cultivation area due to its high value in the oleic acid market and the proven economic benefits in China. This study demonstrated that the marker-assisted backcross strategy based on a cost-effective KASP assay and SNP array for the detection of mutations in fad2 and genetic background evaluation can be used to create efficient peanut breeding programs and contribute to oil quality and high-yield stability.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01313-9.

Identification of AhFatB genes through genome-wide analysis and knockout of AhFatB reduces the content of saturated fatty acids in peanut (Arichis hypogaea L.)

Peanut (Arachis hypogaea L.) is an allotetraploid oilseed crop worldwide due to its abundant high-quality oil production. Peanut oil stability and quality are determined by the relative proportions of saturated fatty acids (SFAs) and unsaturated fatty acids (UFAs). The principle approach to minimize the content of SFAs in peanut is to reduce the content of palmitic acid, which is linked to cardiovascular disease. Acyl-acyl carrier protein thioesterases (FATs) determine the types and levels of fatty acids that are exported them from the plastids. Two different classes of FAT have been classified into two families in plants, FatA and FatB. Among them, AhFatB has become the primary objective to genetically reduce the content of palmitic acid in peanut. Here, we identified 18 AhFatB genes in A. hypogaea genome and grouped into four major subfamilies through gene structures and phylogenetic relationships. Expression profiling of AhFatB genes was assessed using the publicly available RNA-seq data and qRT-PCR in 22 tissues. Using the CRISPR/Cas9 system, we designed two sgRNAs to edit the homologs AhFatB genes Arahy.4E7QKU and Arahy.L4EP3N, and identified different types of mutations. Additionally, we discovered mutations at Arahy.4E7QKU exhibited low palmitic acid and high oleic acid phenotypes. The obtained peanut mutants with altered SFAs content have great potential for improving peanut oil quality for human health.

Genomic Regions, Molecular Markers, and Flanking Genes of Metribuzin Tolerance in Wheat (Triticum aestivum L.)

Understanding the genetics of metribuzin (a group C herbicide) tolerance in wheat is vital in developing tolerant cultivars to improve wheat productivity in dryland farming systems. This study investigated metribuzin tolerance in wheat by conducting a Genome-wide Association Studies (GWAS) with a panel of 150 wheat genotypes of diverse genetic backgrounds and genotyped them with the wheat 90 K SNP genotyping assay. The phenotyping was conducted in a temperature-controlled glasshouse at the University of Western Australia (UWA). Genotypes were sprayed with a metribuzin dose of 400 grams of active ingredient (g. a.i.) ha^-1 as pre-emergent in a specialized spraying cabinet and transferred to the glasshouse where the tolerance level of the genotypes was assessed by measuring the relative reduction in chlorophyll content of the leaves. The decrease in chlorophyll content of the treated plants compared to the control was regarded as the phytotoxic effects of metribuzin. GWAS analysis following a mixed linear model revealed 19 genomic regions with significant marker-trait associations (MTAs), including ten on chromosome 6A, three on chromosome 2B, and one on chromosomes 3A, 5B, 6B 6D, 7A, and 7B, respectively. Sequences of the significant markers were blasted against the wheat genome, IWGSC RefSeq V1.0, and candidate genes having annotations related to herbicide tolerance in wheat, especially in pathways reported to be involved in metribuzin tolerance, such as cytochrome P450 pathways and ATP Binding Cassette (ABC) superfamilies, were identified in these genomic regions. These included TraesCS6A01G028800, TraesCS6A02G353700, TraesCS6A01G326200, TraesCS7A02G331000, and TraesCS2B01G465200. These genomic regions were validated on 30 top tolerant and 30 most susceptible genotypes using the five closest SSR makers to the flanked SNPs. Sufficient polymorphism was detected on two markers (wms193 and barc1036) that were found to differentiate between the susceptible and tolerant alleles and a t-test analysis of the phenotypic data shows a significant (value of p < 0.001) difference suggesting that these markers can be used for marker-assisted selection (MAS) in metribuzin studies and wheat breeding programs.

Producing High-Quality Single Nucleotide Polymorphism Data for Genome-Wide Association Studies

Single-nucleotide polymorphisms (SNPs) have become the primary type of molecular genetic marker used in a diverse range of genetic and genomic studies. SNPs can be used to identify genomic regions linked to traits such as disease in genome-wide association studies, to understand population structure and diversity, or to understand mechanisms of genome evolution. One of the first steps of any SNP-based workflow, following SNP discovery, is quality control of SNP data. The protocol described here details how to perform quality control on SNP data to minimise errors in downstream analysis.

The Bnapus50K array: a quick and versatile genotyping tool for Brassica napus genomic breeding and research

Rapeseed is a globally cultivated commercial crop, primarily grown for its oil. High-density single nucleotide polymorphism (SNP) arrays are widely used as a standard genotyping tool for rapeseed research, including for gene mapping, genome-wide association studies, germplasm resource analysis, and cluster analysis. Although considerable rapeseed genome sequencing data have been released, DNA arrays are still an attractive choice for providing additional genetic data in an era of high-throughput whole-genome sequencing. Here, we integrated re-sequencing DNA array data (32,216, 304 SNPs) from 505 inbred rapeseed lines, allowing us to develop a sensitive and efficient genotyping DNA array, Bnapus50K, with a more consistent genetic and physical distribution of probes. A total of 42,090 high-quality probes were filtered and synthesized, with an average distance between adjacent SNPs of 8 kb. To improve the practical application potential of this array in rapeseed breeding, we also added 1,618 functional probes related to important agronomic traits such as oil content, disease resistance, male sterility, and flowering time. The additional probes also included those specifically for detecting genetically modified material. These probes show a good detection efficiency and are therefore useful for gene mapping, along with crop variety improvement and identification. The novel Bnapus50K DNA array developed in this study could prove to be a quick and versatile genotyping tool for B. napus genomic breeding and research.

QTL Genetic Mapping Study for Traits Affecting Meal Quality in Winter Oilseed Rape (Brassica Napus L.)

Rapeseed (Brassica napus L.) meal is an important source of protein, but the presence of anti-nutritional compounds, such as fibre and glucosinolates, still limits its use as a livestock feed. Understanding the genetic basis of seed fibre biosynthesis would help to manipulate its content in seeds of oilseed rape. Here, we applied high-resolution skim genotyping by sequencing (SkimGBS) and characterised 187,835 single-nucleotide polymorphism (SNP) markers across a mapping population subsequently used for a genetic mapping study (R/qtl). This approach allowed the identification of 11 stable QTL related to seed quality traits and led to the identification of potential functional genes underlying these traits. Among these, key genes with a known role in carbohydrate metabolic process, cell wall, lignin, and flavonoid biosynthesis, including cellulase GH5, TT10/LAC15, TT4, and SUC2, were found. This study furthers the understanding of the molecular mechanisms underlying seed fibre content and provides new markers for molecular breeding in B. napus.

Candidate Rlm6 resistance genes against Leptosphaeria. maculans identified through a genome-wide association study in Brassica juncea (L.) Czern

One hundred and sixty-seven B. juncea varieties were genotyped on the 90K Brassica assay (42,914 SNPs), which led to the identification of sixteen candidate genes for Rlm6. Brassica species are at high risk of severe crop loss due to pathogens, especially Leptosphaeria maculans (the causal agent of blackleg). Brassica juncea (L.) Czern is an important germplasm resource for canola improvement, due to its good agronomic traits, such as heat and drought tolerance and high blackleg resistance. The present study is the first using genome-wide association studies to identify candidate genes for blackleg resistance in B. juncea based on genome-wide SNPs obtained from the Illumina Infinium 90 K Brassica SNP array. The verification of Rlm6 in B. juncea was performed through a cotyledon infection test. Genotyping 42,914 single nucleotide polymorphisms (SNPs) in a panel of 167 B. juncea lines revealed a total of seven SNPs significantly associated with Rlm6 on chromosomes A07 and B04 in B. juncea. Furthermore, 16 candidate Rlm6 genes were found in these regions, defined as nucleotide binding site leucine-rich-repeat (NLR), leucine-rich repeat RLK (LRR-RLK) and LRR-RLP genes. This study will give insights into the blackleg resistance in B. juncea and facilitate identification of functional blackleg resistance genes which can be used in Brassica breeding.

Identification of Candidate Genes for Drought Tolerance at Maize Seedlings Using Genome-Wide Association

BACKGROUND

Drought stress is a serious threat that limit maize growth and production.

OBJECTIVES

The assessment tolerance level of maize by measuring changes in the main biochemical and physiological indicators under drought stress.

MATERIAL AND METHODS

We performed a genome-wide association analysis of biochemical and physiological indicators using an elite association panel.

RESULTS

The results revealed that eight significant SNPs (p<0.05/N) located in eight genes that are distributed on different chromosomes were associated with drought resistance indices under drought stress. Among these genes, four genes were linked via the associated SNPs with drought-resistance indices of the malondialdehyde activity (MDA), three genes were linked with drought resistance indexes of the superoxide dismutase activity (SOD), and one gene was linked with drought resistance indexes of relative conductivity (REC). The candidate genes functioned as transcription factors, enzymes, and transporters, which included trehalase, the AP2/EREB160 transcription factor, and glutathione S-transferase and also encoded a gene of unknown function. These genes may be directly or indirectly involved in drought resistance. The expression levels of ZmEREB160 responded to ABA and drought stress.

CONCLUSIONS

These results provided good information to understand the genetic basis of variation in drought resistance indices of biochemical and physiological indicators during drought stress.

Integration of miRNAs, Degradome, and Transcriptome Omics Uncovers a Complex Regulatory Network and Provides Insights Into Lipid and Fatty Acid Synthesis During Sesame Seed Development

Sesame (Sesamum indicum L.) has always been known as a health-promoting oilseed crop because of its nutrient-rich oil. In recent years, studies have focused on lipid and fatty acid (FA) biosynthesis in various plants by high-throughput sequencing. Here, we integrated transcriptomics, small RNAs, and the degradome to establish a comprehensive reserve intensive on key regulatory micro RNA (miRNA)-targeting circuits to better understand the transcriptional and translational regulation of the oil biosynthesis mechanism in sesame seed development. Deep sequencing was performed to differentially express 220 miRNAs, including 65 novel miRNAs, in different developmental periods of seeds. GO and integrated KEGG analysis revealed 32 pairs of miRNA targets with negatively correlated expression profiles, of which 12 miRNA-target pairs were further confirmed by RT-PCR. In addition, a regulatory co-expression network was constructed based on the differentially expressed gene (DEG) profiles. The FAD2, LOC10515945, LOC105161564, and LOC105162196 genes were clustered into groups that regulate the accumulation of unsaturated fatty acid (UFA) biosynthesis. The results provide a unique advanced molecular platform for the study of lipid and FA biosynthesis, and this study may serve as a new theoretical reference to obtain increased levels of UFA from higher-quality sesame seed cultivars and other plants.

Enhancing the Nutritional Quality of Major Food Crops Through Conventional and Genomics-Assisted Breeding

Nutritional stress is making over two billion world population malnourished. Either our commercially cultivated varieties of cereals, pulses, and oilseed crops are deficient in essential nutrients or the soils in which these crops grow are becoming devoid of minerals. Unfortunately, our major food crops are poor sources of micronutrients required for normal human growth. To overcome the problem of nutritional deficiency, greater emphasis should be laid on the identification of genes/quantitative trait loci (QTLs) pertaining to essential nutrients and their successful deployment in elite breeding lines through marker-assisted breeding. The manuscript deals with information on identified QTLs for protein content, vitamins, macronutrients, micro-nutrients, minerals, oil content, and essential amino acids in major food crops. These QTLs can be utilized in the development of nutrient-rich crop varieties. Genome editing technologies that can rapidly modify genomes in a precise way and will directly enrich the nutritional status of elite varieties could hold a bright future to address the challenge of malnutrition.

Skim-Sequencing Based Genotyping Reveals Genetic Divergence of the Wild and Domesticated Population of Black Tiger Shrimp (Penaeus monodon) in the Indo-Pacific Region

The domestication of a wild-caught aquatic animal is an evolutionary process, which results in genetic discrimination at the genomic level in response to strong artificial selection. Although black tiger shrimp (Penaeus monodon) is one of the most commercially important aquaculture species, a systematic assessment of genetic divergence and structure of wild-caught and domesticated broodstock populations of the species is yet to be documented. Therefore, we used skim sequencing (SkimSeq) based genotyping approach to investigate the genetic structure of 50 broodstock individuals of P. monodon species, collected from five sampling sites (n = 10 in each site) across their distribution in Indo-Pacific regions. The wild-caught P. monodon broodstock population were collected from Malaysia (MS) and Japan (MJ), while domesticated broodstock populations were collected from Madagascar (MMD), Hawaii, HI, USA (MMO), and Thailand (MT). After various filtering process, a total of 194,259 single nucleotide polymorphism (SNP) loci were identified, in which 4983 SNP loci were identified as putatively adaptive by the pcadapt approach. In both datasets, pairwise F_ST estimates high genetic divergence between wild and domesticated broodstock populations. Consistently, different spatial clustering analyses in both datasets categorized divergent genetic structure into two clusters: (1) wild-caught populations (MS and MJ), and (2) domesticated populations (MMD, MMO and MT). Among 4983 putatively adaptive SNP loci, only 50 loci were observed to be in the coding region. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses suggested that non-synonymous mutated genes might be associated with the energy production, metabolic functions, respiration regulation and developmental rates, which likely act to promote adaptation to the strong artificial selection during the domestication process. This study has demonstrated the applicability of SkimSeq in a highly duplicated genome of P. monodon specifically, across a range of genetic backgrounds and geographical distributions, and would be useful for future genetic improvement program of this species in aquaculture.

Genetic Characterization of Russian Rapeseed Collection and Association Mapping of Novel Loci Affecting Glucosinolate Content

Rapeseed is the second most common oilseed crop worldwide. While the start of rapeseed breeding in Russia dates back to the middle of the 20th century, its widespread cultivation began only recently. In contrast to the world’s rapeseed genetic variation, the genetic composition of Russian rapeseed lines remained unexplored. We have addressed this question by performing genome-wide genotyping of 90 advanced rapeseed accessions provided by the All-Russian Research Institute of Oil Crops (VNIIMK). Genome-wide genetic analysis demonstrated a clear difference between Russian rapeseed varieties and the rapeseed varieties from the rest of the world, including the European ones, indicating that rapeseed breeding in Russia proceeded in its own independent direction. Hence, genetic determinants of agronomical traits might also be different in Russian rapeseed lines. To assess it, we collected the glucosinolate content data for the same 90 genotyped accessions obtained during three years and performed an association mapping of this trait. We indeed found that the loci significantly associated with glucosinolate content variation in the Russian rapeseed collection differ from those previously reported for the non-Russian rapeseed lines.

Towards model-driven characterization and manipulation of plant lipid metabolism

Plant lipids have versatile applications and provide essential fatty acids in human diet. Therefore, there has been a growing interest to better characterize the genetic basis, regulatory networks, and metabolic pathways that shape lipid quantity and composition. Addressing these issues is challenging due to context-specificity of lipid metabolism integrating environmental, developmental, and tissue-specific cues. Here we systematically review the known metabolic pathways and regulatory interactions that modulate the levels of storage lipids in oilseeds. We argue that the current understanding of lipid metabolism provides the basis for its study in the context of genome-wide plant metabolic networks with the help of approaches from constraint-based modeling and metabolic flux analysis. The focus is on providing a comprehensive summary of the state-of-the-art of modeling plant lipid metabolic pathways, which we then contrast with the existing modeling efforts in yeast and microalgae. We then point out the gaps in knowledge of lipid metabolism, and enumerate the recent advances of using genome-wide association and quantitative trait loci mapping studies to unravel the genetic regulations of lipid metabolism. Finally, we offer a perspective on how advances in the constraint-based modeling framework can propel further characterization of plant lipid metabolism and its rational manipulation.

Genomic Prediction and Genetic Correlation of Agronomic, Blackleg Disease, and Seed Quality Traits in Canola (Brassica napus L.)

Genomic selection accelerates genetic progress in crop breeding through the prediction of future phenotypes of selection candidates based on only their genomic information. Here we report genetic correlations and genomic prediction accuracies in 22 agronomic, disease, and seed quality traits measured across multiple years (2015-2017) in replicated trials under rain-fed and irrigated conditions in Victoria, Australia. Two hundred and two spring canola lines were genotyped for 62,082 Single Nucleotide Polymorphisms (SNPs) using transcriptomic genotype-by-sequencing (GBSt). Traits were evaluated in single trait and bivariate genomic best linear unbiased prediction (GBLUP) models and cross-validation. GBLUP were also expanded to include genotype-by-environment G × E interactions. Genomic heritability varied from 0.31to 0.66. Genetic correlations were highly positive within traits across locations and years. Oil content was positively correlated with most agronomic traits. Strong, not previously documented, negative correlations were observed between average internal infection (a measure of blackleg disease) and arachidic and stearic acids. The genetic correlations between fatty acid traits followed the expected patterns based on oil biosynthesis pathways. Genomic prediction accuracy ranged from 0.29 for emergence count to 0.69 for seed yield. The incorporation of G × E translates into improved prediction accuracy by up to 6%. The genomic prediction accuracies achieved indicate that genomic selection is ready for application in canola breeding.

Identification of Markers Associated with Yield Traits and Morphological Features in Maize (Zea mays L.)

Association mapping is a powerful approach to detect associations between traits of interest and genetic markers based on linkage disequilibrium in molecular plant breeding. The aim of this study was the identification of single nucleotide polymorphisms (SNPs) and SilicoDArT markers associated with yield traits and morphological features in maize. Plant material constituted inbred lines. The field experiment with inbred lines was established on 10 m² plots in a set of complete random blocks in three replicates. We observed 22 quantitative traits. Association mapping was performed in this study using a method based on the mixed linear model with the population structure estimated by eigenanalysis (principal component analysis applied to all markers) and modeled by random effects. As a result of mapping, 969 markers (346 SNPs and 623 SilocoDArT) were selected from 49,911 identified polymorphic molecular markers, which were significantly associated with the analyzed morphological features and yield structure traits. Markers associated with five or six traits were selected during further analyses, including SilicoDArT 4591115 (anthocyanin coloration of anthers, length of main axis above the highest lateral branch, cob length, number of grains per cob, weight of fresh grains per cob and weight of fresh grains per cob at 15% moisture), SilicoDArT 7059939 (anthocyanin coloration of glumes of cob, time of anthesis—50% of flowering plants, time of silk emergence—50% of flowering plants, anthocyanin coloration of anthers and cob diameter), SilicoDArT 5587991 (anthocyanin coloration of glumes of cob, time of anthesis—50% of flowering plants, anthocyanin coloration of anthers, curvature of lateral branches and number of rows of grain). The two genetic similarity dendrograms between the inbred lines were constructed based on all significant SNPs and SilicoDArT markers. On both dendrograms lines clustered according to the kernel structure (flint, dent) and origin. The selected markers may be useful in predicting hybrid formulas in a heterosis culture. The present study demonstrated that molecular SNP and Silico DArT markers could be used in this species to group lines in terms of origin and lines with incomplete origin data. They can also be useful in maize in predicting the hybrid formula and can find applications in the selection of parental components for heterosis crossings.

Multivariate Genome-Wide Association Analyses Reveal the Genetic Basis of Seed Fatty Acid Composition in Oat (Avena sativa L.)

Oat (Avena sativa L.) has a high concentration of oils, comprised primarily of healthful unsaturated oleic and linoleic fatty acids. To accelerate oat plant breeding efforts, we sought to identify loci associated with variation in fatty acid composition, defined as the types and quantities of fatty acids. We genotyped a panel of 500 oat cultivars with genotyping-by-sequencing and measured the concentrations of ten fatty acids in these oat cultivars grown in two environments. Measurements of individual fatty acids were highly correlated across samples, consistent with fatty acids participating in shared biosynthetic pathways. We leveraged these phenotypic correlations in two multivariate genome-wide association study (GWAS) approaches. In the first analysis, we fitted a multivariate linear mixed model for all ten fatty acids simultaneously while accounting for population structure and relatedness among cultivars. In the second, we performed a univariate association test for each principal component (PC) derived from a singular value decomposition of the phenotypic data matrix. To aid interpretation of results from the multivariate analyses, we also conducted univariate association tests for each trait. The multivariate mixed model approach yielded 148 genome-wide significant single-nucleotide polymorphisms (SNPs) at a 10% false-discovery rate, compared to 129 and 73 significant SNPs in the PC and univariate analyses, respectively. Thus, explicit modeling of the correlation structure between fatty acids in a multivariate framework enabled identification of loci associated with variation in seed fatty acid concentration that were not detected in the univariate analyses. Ultimately, a detailed characterization of the loci underlying fatty acid variation can be used to enhance the nutritional profile of oats through breeding.

Transcriptome Profile Analysis of Winter Rapeseed (Brassica napus L.) in Response to Freezing Stress, Reveal Potentially Connected Events to Freezing Stress

Winter rapeseed is not only an important oilseed crop, but also a winter cover crop in Northern China, where its production was severely limited by freezing stress. As an overwinter crop, the production is severely limited by freezing stress. Therefore, understanding the physiological and molecular mechanism of winter rapeseed (Brassica napus L.) in freezing stress responses becomes essential for the improvement and development of freezing-tolerant varieties of Brassica napus. In this study, morphological, physiological, ultrastructure and transcriptome changes in the Brassica napus line "2016TS(G)10" (freezing-tolerance line) that was exposed to -2 °C for 0 h, 1 h, 3 h and 24 h were characterized. The results showed that freezing stress caused seedling dehydration, and chloroplast dilation and degradation. The content of malondialdehyde (MDA), proline, soluble protein and soluble sugars were increased, as well as the relative electrolyte leakage (REL) which was significantly increased at frozen 24 h. Subsequently, RNA-seq analysis revealed a total of 98,672 UniGenes that were annotated in Brassica napus and 3905 UniGenes were identified as differentially expressed genes after being exposed to freezing stress. Among these genes, 2312 (59.21%) were up-regulated and 1593 (40.79%) were down-regulated. Most of these DEGs were significantly annotated in the carbohydrates and energy metabolism, signal transduction, amino acid metabolism and translation. Most of the up-regulated DEGs were especially enriched in plant hormone signal transduction, starch and sucrose metabolism pathways. Transcription factor enrichment analysis showed that the AP2/ERF, WRKY and MYB families were also significantly changed. Furthermore, 20 DEGs were selected to validate the transcriptome profiles via quantitative real-time PCR (qRT-PCR). In conclusion, the results provide an overall view of the dynamic changes in physiology and insights into the molecular regulation mechanisms of winter Brassica napus in response to freezing treatment, expanding our understanding on the complex molecular mechanism in plant response to freezing stress.

Genome-wide association study (GWAS) of leaf cuticular wax components in Camelina sativa identifies genetic loci related to intracellular wax transport

BACKGROUND

It is important to explore renewable alternatives (e.g. biofuels) that can produce energy sources to help reduce reliance on fossil oils, and reduce greenhouse gases and waste solids resulted from fossil oils consumption. Camelina sativa is an oilseed crop which has received increasing attention due to its short life cycle, broader adaptation regions, high oil content, high level of omega-3 unsaturated fatty acids, and low-input requirements in agriculture practices. To expand its Camelina production areas into arid regions, there is a need to breed for new drought-tolerant cultivars. Leaf cuticular wax is known to facilitate plant development and growth under water-limited conditions. Dissecting the genetic loci underlying leaf cuticular waxes is important to breed for cultivars with improved drought tolerance.

RESULTS

Here we combined phenotypic data and single nucleotide polymorphism (SNP) data from a spring C. sativa diversity panel using genotyping-by-sequencing (GBS) technology, to perform a large-scale genome-wide association study (GWAS) on leaf wax compositions. A total of 42 SNP markers were significantly associated with 15 leaf wax traits including major wax components such as total primary alcohols, total alkanes, and total wax esters as well as their constituents. The vast majority of significant SNPs were associated with long-chain carbon monomers (carbon chain length longer than C28), indicating the important effects of long-chain carbon monomers on leaf total wax biosynthesis. These SNP markers are located on genes directly or indirectly related to wax biosynthesis such as maintaining endoplasmic reticulum (ER) morphology and enabling normal wax secretion from ER to plasma membrane or Golgi network-mediated transport.

CONCLUSIONS

These loci could potentially serve as candidates for the genetic control involved in intracellular wax transport that might directly or indirectly facilitate leaf wax accumulation in C. sativa and can be used in future marker-assisted selection (MAS) to breed for the cultivars with high wax content to improve drought tolerance.

Evolutionary aspects of direct or indirect selection for seed size and seed metabolites in Brassica juncea and diploid progenitor species

Seed size and seed metabolites have been the targets of direct or indirect selection during domestication and subsequent crop breeding. Understanding these traits and associated genetics can prove very useful for plant translational research. Large germplasm assemblage (235) of Brassica juncea and its progenitor species (B. rapa and B. nigra) was evaluated to establish seed trait variations for seed size and seed metabolites. Seeds were smallest in B. nigra and largest in B. juncea. Australian B. juncea and Indian B. rapa var brown sarson types averaged more seed oil content. Seed size and oil content were generally higher in modern cultivars in comparison to the land races. Allelic diversity for known associated genes for seed-size and oil-content (AP2, ARF2, TTG2, GRF2, GL2, CYP78A5, CYP78A6, MINI3, IKU2, IKU1, BRI1, DGAT, GPDH, LPAAT, GPAT and DA1) was studied so as to infer the effect of domestication on seed traits. Three genes (IKU1, IKU2, AP2) in B. rapa, two (TTG2 and GL2) in B. nigra and two (IKU1 and GRF2) in natural B. juncea were identified as targets of selection on the basis of Fst outlier and/or sequence diversity tests. We report parallel divergence for seed traits between B. juncea and B. rapa. Directional selection appeared stronger for seed-size as compared to correlated seed metabolites. Positive selection on seed-size is likely to have played a significant role in structuring regional variation in the germplasm.

Genome-Wide Association Study Identifies Candidate Genes Related to Seed Oil Composition and Protein Content in Gossypium hirsutum L

Cotton (Gossypium spp.) is a leading natural fiber crop and an important source of vegetable protein and oil for humans and livestock. To investigate the genetic architecture of seed nutrients in upland cotton, a genome-wide association study (GWAS) was conducted in a panel of 196 germplasm resources under three environments using a CottonSNP80K chip of 77,774 loci. Relatively high genetic diversity (average gene diversity being 0.331) and phenotypic variation (coefficient of variation, CV, exceeding 3.9%) were detected in this panel. Correlation analysis revealed that the well-documented negative association between seed protein (PR) and oil may be to some extent attributable to the negative correlation between oleic acid (OA) and PR. Linkage disequilibrium (LD) was unevenly distributed among chromosomes and subgenomes. It ranged from 0.10-0.20 Mb (Chr19) to 5.65-5.75 Mb (Chr25) among the chromosomes and the range of Dt-subgenomes LD decay distances was smaller than At-subgenomes. This panel was divided into two subpopulations based on the information of 41,815 polymorphic single-nucleotide polymorphism (SNP) markers. The mixed linear model considering both Q-matrix and K-matrix [MLM(Q+K)] was employed to estimate the association between the SNP markers and the seed nutrients, considering the false positives caused by population structure and the kinship. A total of 47 SNP markers and 28 candidate quantitative trait loci (QTLs) regions were found to be significantly associated with seven cottonseed nutrients, including protein, total fatty acid, and five main fatty acid compositions. In addition, the candidate genes in these regions were analyzed, which included three genes, Gh_D12G1161, Gh_D12G1162, and Gh_D12G1165 that were most likely involved in the control of cottonseed protein concentration. These results improved our understanding of the genetic control of cottonseed nutrients and provided potential molecular tools to develop cultivars with high protein and improved fatty acid compositions in cotton breeding programs through marker-assisted selection.

Identification and Functional Analysis of Two New Mutant BnFAD2 Alleles That Confer Elevated Oleic Acid Content in Rapeseed

Rapeseed (Brassica napus L.) is a vital oil crop worldwide. High oleic acid content is a desirable quality trait for rapeseed oil, which makes it more beneficial to human health. However, many germplasm resources with high oleic acid content in rapeseed have not been evaluated with regard to their genotypes, making it difficult to select the best strains with this trait for the breeding of high oleic acid rapeseed variety. This work was to explore the gene-regulation mechanism of this trait using a new super-high oleic acid content (∼85%) line N1379T as genetic material. In this study, the sequences of four homologous fatty acid desaturase (BnFAD2) genes were compared between super-high (∼85%, N1379T) and normal (∼63%) oleic acid content lines. Results showed that there were two single-nucleotide polymorphisms (SNPs) in BnFAD2-1 and BnFAD2-2, respectively, which led to the amino acid changes (E106K and G303E) in the corresponding proteins. Functional analysis of both genes in yeast confirmed that these SNPs were loss-of-function mutations, thus limiting the conversion of oleic acid to linoleic acid and resulting in the considerable accumulation of oleic acid. Moreover, two specific cleaved amplified polymorphic sequences (CAPS) markers for the two SNPs were developed to identify genotypes of each line in the F₂ and BC₁ populations. Furthermore, these two mutant loci of BnFAD2-1 and BnFAD2-2 genes were positively associated with elevated oleic acid levels and had a similar effect with regard to the increase of oleic acid content. Taken together, these two novel SNPs in two different BnFAD2 genes jointly regulated the high oleic acid trait in this special germplasm. The study provided insight into the genetic regulation involved in oleic acid accumulation and highlighted the use of new alleles of BnFAD2-1 and BnFAD2-2 in breeding high oleic acid rapeseed varieties.

Unconditional and conditional QTL analyses of seed fatty acid composition in Brassica napus L

BACKGROUND

The fatty acid composition of B. napus' seeds determines the oil's nutritional and industrial values, and affects seed germination. Many studies have reported correlations among C16:0, C18:0, C18:1, C18:2 and C18:3 based on phenotypic data; however, the genetic basis of the fatty acid composition in B. napus is still not well understood.

RESULTS

In this study, unconditional and conditional quantitative trail locus (QTL) mapping analyses were conducted using a recombinant inbred line in six environments. In total, 21 consensus QTLs each for C16:0, C18:0 and C18:2, 16 for C18:1 and 22 for C18:3 were detected by unconditional mapping. The QTLs with overlapping confidence intervals were integrated into 71 pleiotropically unique QTLs by meta-analysis. Two major QTLs, uuqA5-6 and uuqA5-7, simultaneously affected the fatty acids, except C18:0, in most of environments, with the homologous genes fatty acid desaturase 2 (FAD2) and glycerol-3-phosphate sn-2-acyltransferase 5 (GPAT5) occurring in the confidence interval of uuqA5-6, while phosphatidic acid phosphohydrolase 1 (PAH1) was assigned to uuqA5-7. Moreover, 49, 30, 48, 60 and 45 consensus QTLs were detected for C16:0, C18:0, C18:1, C18:2 and C18:3, respectively, by the conditional mapping analysis. In total, 128 unique QTLs were subsequently integrated from the 232 conditional consensus QTLs. A comparative analysis revealed that 63 unique QTLs could be identified by both mapping methodologies, and 65 additional unique QTLs were only identified in conditional mapping.

CONCLUSIONS

Thus, conditional QTL mapping for fatty acids may uncover numerous additional QTLs that were inhibited by the effects of other traits. These findings provide useful information for better understanding the genetic relationships among fatty acids at the QTL level.

Genome-wide association study reveals candidate genes influencing lipids and diterpenes contents in Coffea arabica L

Lipids, including the diterpenes cafestol and kahweol, are key compounds that contribute to the quality of coffee beverages. We determined total lipid content and cafestol and kahweol concentrations in green beans and genotyped 107 Coffea arabica accessions, including wild genotypes from the historical FAO collection from Ethiopia. A genome-wide association study was performed to identify genomic regions associated with lipid, cafestol and kahweol contents and cafestol/kahweol ratio. Using the diploid Coffea canephora genome as a reference, we identified 6,696 SNPs. Population structure analyses suggested the presence of two to three groups (K = 2 and K = 3) corresponding to the east and west sides of the Great Rift Valley and an additional group formed by wild accessions collected in western forests. We identified 5 SNPs associated with lipid content, 4 with cafestol, 3 with kahweol and 9 with cafestol/kahweol ratio. Most of these SNPs are located inside or near candidate genes related to metabolic pathways of these chemical compounds in coffee beans. In addition, three trait-associated SNPs showed evidence of directional selection among cultivated and wild coffee accessions. Our results also confirm a great allelic richness in wild accessions from Ethiopia, especially in accessions originating from forests in the west side of the Great Rift Valley.

Integrated QTL and eQTL Mapping Provides Insights and Candidate Genes for Fatty Acid Composition, Flowering Time, and Growth Traits in a F2 Population of a Novel Synthetic Allopolyploid Brassica napus

Brassica napus (B. napus, AACC), is an economically important allotetraploid crop species that resulted from hybridization between two diploid species, Brassica rapa (AA) and Brassica olereacea (CC). We have created one new synthetic B. napus genotype Da-Ae (AACC) and one introgression line Da-Ol-1 (AACC), which were used to generate an F₂ mapping population. Plants in this F₂ mapping population varied in fatty acid content, flowering time, and growth-related traits. Using quantitative trait locus (QTL) mapping, we aimed to determine if Da-Ae and Da-Ol-1 provided novel genetic variation beyond what has already been found in B. napus. Making use of the genotyping information generated from RNA-seq data of these two lines and their F₂ mapping population of 166 plants, we constructed a genetic map consisting of 2,021 single nucleotide polymorphism markers that spans 2,929 cM across 19 linkage groups. Besides the known major QTL identified, our high resolution genetic map facilitated the identification of several new QTL contributing to the different fatty acid levels, flowering time, and growth-related trait values. These new QTL probably represent novel genetic variation that existed in our new synthetic B. napus strain. By conducting genome-wide expression variation analysis in our F₂ mapping population, genetic regions that potentially regulate many genes across the genome were revealed. A FLOWERING LOCUS C gene homolog, which was identified as a candidate regulating flowering time and multiple growth-related traits, was found underlying one of these regions. Integrated QTL and expression QTL analyses also helped us identified candidate causative genes associated with various biological traits through expression level change and/or possible protein function modification.

Association Mapping Analysis of Fatty Acid Content in Different Ecotypic Rapeseed Using mrMLM

Brassica napus L. is a widely cultivated oil crop and provides important resources of edible vegetable oil, and its quality is determined by fatty acid composition and content. To explain the genetic basis and identify more minor loci for fatty acid content, the multi-locus random-SNP-effect mixed linear model (mrMLM) was used to identify genomic regions associated with fatty acid content in a genetically diverse population of 435 rapeseed accessions, including 77 winter-type, 55 spring-type, and 303 semi-winter-type accessions grown in different environments. A total of 149 quantitative trait nucleotides (QTNs) were found to be associated with fatty acid content and composition, including 34 QTNs that overlapped with the previously reported loci, and 115 novel QTNs. Of these, 35 novel QTNs, located on chromosome A01, A02, A03, A05, A06, A09, A10, and C02, respectively, were repeatedly detected across different environments. Subsequently, we annotated 95 putative candidate genes by BlastP analysis using sequences from Arabidopsis thaliana homologs of the identified regions. The candidate genes included 34 environmentally-insensitive genes (e.g., CER4, DGK2, KCS17, KCS18, MYB4, and TT16) and 61 environment-sensitive genes (e.g., FAB1, FAD6, FAD7, KCR1, KCS9, KCS12, and TT1) as well as genes invloved in the fatty acid biosynthesis. Among these, BnaA08g08280D and BnaC03g60080D differed in genomic sequence between the high- and low-oleic acid lines, and might thus be the novel alleles regulating oleic acid content. Furthermore, RT-qPCR analysis of these genes showed differential expression levels during seed development. Our results highlight the practical and scientific value of mrMLM or QTN detection and the accuracy of linking specific QTNs to fatty acid content, and suggest a useful strategy to improve the fatty acid content of B. napus seeds by molecular marker-assisted breeding.

Stable, Environmental Specific and Novel QTL Identification as Well as Genetic Dissection of Fatty Acid Metabolism in Brassica napus

Fatty acid (FA) composition is the typical quantitative trait in oil seed crops, of which study is not only closely related to oil content, but is also more critical for the quality improvement of seed oil. The double haploid (DH) population named KN with a high density SNP linkage map was applied for quantitative trait loci (QTL) analysis of FA composition in this study. A total of 406 identified QTL were detected for eight FA components with an average confidence interval (CI) of 2.92 cM, the explained phenotypic variation (PV) value ranged from 1.49 to 45.05%. Totally, 204 consensus and 91 unique QTL were further obtained via meta-analysis method for the purpose of detecting multiple environment expressed and pleiotropic QTL, respectively. Of which, 74 stable expressed and 22 environmental specific QTL were also revealed, respectively. In order to make clear the genetic mechanism of FA metabolism at individual QTL level, conditional QTL analysis was also conducted and more than two thousand conditional QTL which could not be detected under the unconditional mapping were detected, which indicated the complex interrelationship of the QTL controlling FA content in rapeseed. Through comparative genomic analysis and homologous gene annotation, 61 candidates related to acyl lipid metabolism were identified underlying the CI of FA QTL. To further visualize the genetic mechanism of FA metabolism, an intuitive and meticulous network about acyl lipid metabolism was constructed and some closely related candidates were positioned. This study provided a more accurate localization for stable and pleiotropic QTL, and a deeper dissection of the molecular regulatory mechanism of FA metabolism in rapeseed.

Genetic and Molecular Regulation of Seed Storage Proteins (SSPs) to Improve Protein Nutritional Value of Oilseed Rape (Brassica napus L.) Seeds

The world-wide demand for additional protein sources for human nutrition and animal feed keeps rising due to rapidly growing world population. Oilseed rape is a second important oil producing crop and the by-product of the oil production is a protein rich meal. The protein in rapeseed meal finds its application in animal feed and various industrial purposes, but its improvement is of great interest, especially for non-ruminants and poultry feed. To be able to manipulate the quality and quantity of seed protein in oilseed rape, understanding genetic architecture of seed storage protein (SSPs) synthesis and accumulation in this crop species is of great interest. For this, application of modern molecular breeding tools such as whole genome sequencing, genotyping, association mapping, and genome editing methods implemented in oilseed rape seed protein improvement would be of great interest. This review examines current knowledge and opportunities to manipulate of SSPs in oilseed rape to improve its quality, quantity and digestibility.

Earliness traits in rapeseed (Brassica napus): SNP loci and candidate genes identified by genome-wide association analysis

Life cycle timing is critical for yield and productivity of Brassica napus (rapeseed) cultivars grown in different environments. To facilitate breeding for earliness traits in rapeseed, SNP loci and underlying candidate genes associated with the timing of initial flowering, maturity and final flowering, as well as flowering period (FP) were investigated in two environments in a diversity panel comprising 300 B. napus inbred lines. Genome-wide association studies (GWAS) using 201,817 SNP markers previously developed from SLAF-seq (specific locus amplified fragment sequencing) revealed a total of 131 SNPs strongly linked (P < 4.96E-07) to the investigated traits. Of these 131 SNPs, 40 fell into confidence intervals or were physically adjacent to previously published flowering time QTL or SNPs. Phenotypic effect analysis detected 35 elite allelic variants for early maturing, and 90 for long FP. Candidate genes present in the same linkage disequilibrium blocks (r²>0.6) or in 100 kb regions around significant trait-associated SNPs were screened, revealing 57 B. napus genes (33 SNPs) orthologous to 39 Arabidopsis thaliana flowering time genes. These results support the practical and scientific value of novel large-scale SNP data generation in uncovering the genetic control of agronomic traits in B. napus, and also provide a theoretical basis for molecular marker-assisted selection of earliness breeding in rapeseed.