Evaluation of Linkage Disequilibrium Pattern and Association Study on Seed Oil Content in Brassica napus Using ddRAD Sequencing

Detection of two homologous major QTLs and development of diagnostic molecular markers for sucrose content in peanut

KEY MESSAGE

We identified two stable and homologous major QTLs for sucrose content in peanut, and developed breeder-friendly molecular markers for marker-assisted selection breeding. Sucrose content is a crucial quality trait for edible peanuts, and increasing sucrose content is a key breeding objective. However, the genetic basis of sucrose content in peanut remains unclear, and major quantitative trait loci (QTLs) for sucrose content have yet to be identified. In this study, a high-density genetic map was constructed based on whole-genome re-sequencing data from a peanut RIL population. This map consisted of 2,042 bins and 24,142 SNP markers, making it one of the most comprehensive maps to date in terms of marker density. Two major QTLs (qSCA06.2 and qSCB06.2) were identified, explaining 31.41% and 24.13% of the phenotypic variance, respectively. Notably, these two QTLs were located in homologous genomic regions between the A and B subgenomes. The elite allele of qSCA06.2 was exclusive to Valencia-type, while the elite allele of qSCB06.2 existed in other peanut types. Importantly, the distribution of alleles from two homologous QTLs in the RIL population and diverse germplasm accessions consistently demonstrated that only the combination of elite allelic genotypes from both QTLs/genes resulted in a significantly dominant phenotype, accompanied by a substantial increase in sucrose content. The newly developed diagnostic markers for these QTLs were confirmed to be reliable and could facilitate future breeding efforts to enhance sucrose content using marker-assisted selection techniques. Overall, this study highlights the co-regulation of sucrose content by two major homologous QTLs/genes and provides valuable insights into the genetic basis of sucrose in peanuts.

A causal inference and Bayesian optimisation framework for modelling multi-trait relationships-Proof-of-concept using Brassica napus seed yield under controlled conditions

The improvement of crop yield is a major breeding target and there is a long history of research that has focussed on unravelling the mechanisms and processes that contribute to yield. Quantitative prediction of the interplay between morphological traits, and the effects of these trait-trait relationships on seed production remains, however, a challenge. Consequently, the extent to which crop varieties optimise their morphology for a given environment is largely unknown. This work presents a new combination of existing methodologies by framing crop breeding as an optimisation problem and evaluates the extent to which existing varieties exhibit optimal morphologies under the test conditions. In this proof-of-concept study using spring and winter oilseed rape plants grown under greenhouse conditions, we employ causal inference to model the hierarchically structured effects of 27 morphological yield traits on each other. We perform Bayesian optimisation of seed yield, to identify and quantify the morphologies of ideotype plants, which are expected to be higher yielding than the varieties in the studied panels. Under the tested growth conditions, we find that existing spring varieties occupy the optimal regions of trait-space, but that potentially high yielding strategies are unexplored in extant winter varieties. The same approach can be used to evaluate trait (morphology) space for any environment.

Machine learning assisted dynamic phenotypes and genomic variants help understand the ecotype divergence in rapeseed

Three ecotypes of rapeseed, winter, spring, and semi-winter, have been formed to enable the plant to adapt to different geographic areas. Although several major loci had been found to contribute to the flowering divergence, the genomic footprints and associated dynamic plant architecture in the vegetative growth stage underlying the ecotype divergence remain largely unknown in rapeseed. Here, a set of 41 dynamic i-traits and 30 growth-related traits were obtained by high-throughput phenotyping of 171 diverse rapeseed accessions. Large phenotypic variation and high broad-sense heritability were observed for these i-traits across all developmental stages. Of these, 19 i-traits were identified to contribute to the divergence of three ecotypes using random forest model of machine learning approach, and could serve as biomarkers to predict the ecotype. Furthermore, we analyzed genomic variations of the population, QTL information of all dynamic i-traits, and genomic basis of the ecotype differentiation. It was found that 213, 237, and 184 QTLs responsible for the differentiated i-traits overlapped with the signals of ecotype divergence between winter and spring, winter and semi-winter, and spring and semi-winter, respectively. Of which, there were four common divergent regions between winter and spring/semi-winter and the strongest divergent regions between spring and semi-winter were found to overlap with the dynamic QTLs responsible for the differentiated i-traits at multiple growth stages. Our study provides important insights into the divergence of plant architecture in the vegetative growth stage among the three ecotypes, which was contributed to by the genetic differentiation, and might contribute to environmental adaption and yield improvement.

Genome-Wide Association Studies of Root-Related Traits in Brassica napus L. under Low-Potassium Conditions

Roots are essential organs for a plant’s ability to absorb water and obtain mineral nutrients, hence they are critical to its development. Plants use root architectural alterations to improve their chances of absorbing nutrients when their supply is low. Nine root traits of a Brassica napus association panel were explored in hydroponic-system studies under low potassium (K) stress to unravel the genetic basis of root growth in rapeseed. The quantitative trait loci (QTL) and candidate genes for root development were discovered using a multilocus genome-wide association study (ML-GWAS). For the nine traits, a total of 453 significant associated single-nucleotide polymorphism (SNP) loci were discovered, which were then integrated into 206 QTL clusters. There were 45 pleiotropic clusters, and qRTA04-4 and qRTC04-7 were linked to TRL, TSA, and TRV at the same time, contributing 5.25–11.48% of the phenotypic variance explained (PVE) to the root traits. Additionally, 1360 annotated genes were discovered by examining genomic regions within 100 kb upstream and downstream of lead SNPs within the 45 loci. Thirty-five genes were identified as possibly regulating root-system development. As per protein–protein interaction analyses, homologs of three genes (BnaC08g29120D, BnaA07g10150D, and BnaC04g45700D) have been shown to influence root growth in earlier investigations. The QTL clusters and candidate genes identified in this work will help us better understand the genetics of root growth traits and could be employed in marker-assisted breeding for rapeseed adaptable to various conditions with low K levels.

Genetic dissection of seed characteristics in field pennycress via genome-wide association mapping studies

Field pennycress (Thlaspi arvense L.) is a new winter annual cash cover crop with high oil content and seed yield, excellent winter hardiness, early maturation, and resistance to most pests and diseases. It provides living cover on fallow croplands between summer seasons, and in doing so reduces nutrient leaching into water sources, mitigates soil erosion, and suppresses weed growth. The first ever genome-wide association study (GWAS) was conducted on a pennycress diversity panel to identify marker trait associations with important seed size and composition related traits. The entire population was phenotyped in three total environments over 2 yr, and seed area, length, width, thousand grain weight, total oil, and total protein were measured post-harvest with specialized high-throughput imaging and near-infrared spectroscopy. Basic unbiased linear prediction values were calculated for each trait. Seed size traits tended to have higher entry mean reliabilities (0.76-0.79) compared with oil content (0.51) and protein content (0.37). Genotyping-by-sequencing identified 33,606 high quality genome-wide single nucleotide polymorphism (SNPs) that were coupled with phenotypic data to perform GWAS for seed area, length, width, thousand grain weight, total oil, and total protein content. Fifty-nine total marker-trait associations were identified revealing genomic regions controlling each trait. The significant SNPs explained 0.06-0.18% of the total variance for that trait in our population. A list of candidate genes was identified based on their functional annotations and characterization in other species. Our results confirm that GWAS is an efficient strategy to identify significant marker-trait associations that can be incorporated into marker-assisted selection pipelines to accelerate pennycress breeding progress.

Linkage disequilibrium and population structure in a core collection of Brassica napus (L.)

Estimation of genetic diversity in rapeseed is important for sustainable breeding program to provide an option for the development of new breeding lines. The objective of this study was to elucidate the patterns of genetic diversity within and among different structural groups, and measure the extent of linkage disequilibrium (LD) of 383 globally distributed rapeseed germplasm using 8,502 single nucleotide polymorphism (SNP) markers. We divided the germplasm collection into five subpopulations (P1 to P5) according to geographic and growth habit-related patterns. All subpopulations showed moderate genetic diversity (average H = 0.22 and I = 0.34). The pairwise Fst comparison revealed a great degree of divergence (Fst > 0.24) between most of the combinations. The rutabaga type showed highest divergence with spring and winter types. Higher divergence was also found between winter and spring types. Admixture model based structure analysis, principal component and neighbor-joining tree analysis placed all subpopulations into three distinct clusters. Admixed genotype constituted 29.24% of total genotypes, while remaining 70.76% belongs to identified clusters. Overall, mean linkage disequilibrium was 0.03 and it decayed to its half maximum within < 45 kb distance for whole genome. The LD decay was slower in C genome (< 93 kb); relative to the A genome (< 21 kb) which was confirmed by availability of larger haplotype blocks in C genome than A genome. The findings regarding LD pattern and population structure will help to utilize the collection as an important resource for association mapping efforts to identify genes useful in crop improvement as well as for selection of parents for hybrid breeding.

Skim-Based Genotyping by Sequencing Using a Double Haploid Population to Call SNPs, Infer Gene Conversions, and Improve Genome Assemblies

Genotyping by sequencing (GBS) is an emerging technology to rapidly call an abundance of single nucleotide polymorphisms (SNPs) using genome sequencing technology. Several different methodologies and approaches have recently been established, most of these relying on a specific preparation of data. Here we describe our GBS pipeline, which uses high coverage reads from two parents and low coverage reads from their double haploid offspring to call SNPs on a large scale. The upside of this approach is the high resolution and scalability of the method.

Genetic Dissection of Mature Root Characteristics by Genome-Wide Association Studies in Rapeseed (Brassica napus L.)

Roots are complicated quantitative characteristics that play an essential role in absorbing water and nutrients. To uncover the genetic variations for root-related traits in rapeseed, twelve mature root traits of a Brassica napus association panel were investigated in the field within three environments. All traits showed significant phenotypic variation among genotypes, with heritabilities ranging from 55.18% to 79.68%. Genome-wide association studies (GWAS) using 20,131 SNPs discovered 172 marker-trait associations, including 103 significant SNPs (-log10 (p) > 4.30) that explained 5.24-20.31% of the phenotypic variance. With the linkage disequilibrium r² > 0.2, these significant associations were binned into 40 quantitative trait loci (QTL) clusters. Among them, 14 important QTL clusters were discovered in two environments and/or with phenotypic contributions greater than 10%. By analyzing the genomic regions within 100 kb upstream and downstream of the peak SNPs within the 14 loci, 334 annotated genes were found. Among these, 32 genes were potentially associated with root development according to their expression analysis. Furthermore, the protein interaction network using the 334 annotated genes gave nine genes involved in a substantial number of interactions, including a key gene associated with root development, BnaC09g36350D. This research provides the groundwork for deciphering B. napus' genetic variations and improving its root system architecture.

High-Density Genetic Linkage Map Construction Using Whole-Genome Resequencing for Mapping QTLs of Resistance to Aspergillus flavus Infection in Peanut

The cultivated peanut (Arachis hypogaea L.), which is rich in edible oil and protein, is widely planted around the world as an oil and cash crop. However, aflatoxin contamination seriously affects the quality safety of peanuts, hindering the development of the peanut industry and threatening the health of consumers. Breeding peanut varieties with resistance to Aspergillus flavus infection is important for the control of aflatoxin contamination, and understanding the genetic basis of resistance is vital to its genetic enhancement. In this study, we reported the quantitative trait locus (QTL) mapping of resistance to A. flavus infection of a well-known resistant variety, J11. A mapping population consisting of 200 recombinant inbred lines (RILs) was constructed by crossing a susceptible variety, Zhonghua 16, with J11. Through whole-genome resequencing, a genetic linkage map was constructed with 2,802 recombination bins and an average inter-bin distance of 0.58 cM. Combined with phenotypic data of an infection index in 4 consecutive years, six novel resistant QTLs with 5.03-10.87% phenotypic variances explained (PVE) were identified on chromosomes A05, A08, B01, B03, and B10. The favorable alleles of five QTLs were from J11, while that of one QTL was from Zhonghua 16. The combination of these favorable alleles significantly improved resistance to A. flavus infection. These results could contribute greatly to the understanding of the genetic basis of A. flavus resistance and could be meaningful in the improvement of further resistance in peanuts.

Genomic insights into the origin, domestication and diversification of Brassica juncea

Despite early domestication around 3000 BC, the evolutionary history of the ancient allotetraploid species Brassica juncea (L.) Czern & Coss remains uncertain. Here, we report a chromosome-scale de novo assembly of a yellow-seeded B. juncea genome by integrating long-read and short-read sequencing, optical mapping and Hi-C technologies. Nuclear and organelle phylogenies of 480 accessions worldwide supported that B. juncea is most likely a single origin in West Asia, 8,000-14,000 years ago, via natural interspecific hybridization. Subsequently, new crop types evolved through spontaneous gene mutations and introgressions along three independent routes of eastward expansion. Selective sweeps, genome-wide trait associations and tissue-specific RNA-sequencing analysis shed light on the domestication history of flowering time and seed weight, and on human selection for morphological diversification in this versatile species. Our data provide a comprehensive insight into the origin and domestication and a foundation for genomics-based breeding of B. juncea.

Genome-wide association study and its applications in the non-model crop Sesamum indicum

BACKGROUND

Sesame is a rare example of non-model and minor crop for which numerous genetic loci and candidate genes underlying features of interest have been disclosed at relatively high resolution. These progresses have been achieved thanks to the applications of the genome-wide association study (GWAS) approach. GWAS has benefited from the availability of high-quality genomes, re-sequencing data from thousands of genotypes, extensive transcriptome sequencing, development of haplotype map and web-based functional databases in sesame.

RESULTS

In this paper, we reviewed the GWAS methods, the underlying statistical models and the applications for genetic discovery of important traits in sesame. A novel online database SiGeDiD ( http://sigedid.ucad.sn/ ) has been developed to provide access to all genetic and genomic discoveries through GWAS in sesame. We also tested for the first time, applications of various new GWAS multi-locus models in sesame.

CONCLUSIONS

Collectively, this work portrays steps and provides guidelines for efficient GWAS implementation in sesame, a non-model crop.

Identification of resistance loci against new pathotypes of Plasmodiophora brassicae in Brassica napus based on genome-wide association mapping

Genetic resistance is a successful strategy for management of clubroot (Plasmodiophora brassicae) of brassica crops, but resistance can break down quickly. Identification of novel sources of resistance is especially important when new pathotypes arise. In the current study, the reaction of 177 accessions of Brassica napus to four new, virulent pathotypes of P. brassicae was assessed. Each accession was genotyped using genotyping by sequencing to identify and map novel sources of clubroot resistance using mixed linear model (MLM) analysis. The majority of accessions were highly susceptible (70–100 DSI), but a few accessions exhibited strong resistance (0–20 DSI) to pathotypes 5X (21 accessions), 3A (8), 2B (7), and 3D (15), based on the Canadian Clubroot Differential system. In total, 301,753 SNPs were mapped to 19 chromosomes. Population structure analysis indicated that the 177 accessions belong to seven major populations. SNPs were associated with resistance to each pathotype using MLM. In total, 13 important SNP loci were identified, with 9 SNPs mapped to the A-genome and 4 to the C-genome. The SNPs were associated with resistance to pathotypes 5X (2 SNPs), 3A (4), 2B (5) and 3D (6). A Blast search of 1.6 Mb upstream and downstream from each SNP identified 13 disease-resistance genes or domains. The distance between a SNP locus and the nearest resistance gene ranged from 0.04 to 0.74 Mb. The resistant lines and SNP markers identified in this study can be used to breed for resistance to the most prevalent new pathotypes of P. brassicae in Canada.

Feral populations of Brassica oleracea along Atlantic coasts in western Europe

There has been growing emphasis on the role that crop wild relatives might play in supporting highly selected agriculturally valuable species in the face of climate change. In species that were domesticated many thousands of years ago, distinguishing wild populations from escaped feral forms can be challenging, but reintroducing variation from either source could supplement current cultivated forms. For economically important cabbages (Brassicaceae: Brassica oleracea), "wild" populations occur throughout Europe but little is known about their genetic variation or potential as resources for breeding more resilient crop varieties. The main aim of this study was to characterize the population structure of geographically isolated wild cabbage populations along the coasts of the UK and Spain, including the Atlantic range edges. Double-digest restriction-site-associated DNA sequencing was used to sample individual cabbage genomes, assess the similarity of plants from 20 populations, and explore environment-genotype associations across varying climatic conditions. Interestingly, there were no indications of isolation by distance; several geographically close populations were genetically more distinct from each other than to distant populations. Furthermore, several distant populations shared genetic ancestry, which could indicate that they were established by escapees of similar source cultivars. However, there were signals of local adaptation to different environments, including a possible relationship between genetic diversity and soil pH. Overall, these results highlight wild cabbages in the Atlantic region as an important genetic resource worthy of further research into their relationship with existing crop varieties.

Genetic mapping of quantitative trait loci and a major locus for resistance to grey leaf spot in maize

The genetic basis of GLS resistance was dissected using two DH populations sharing a common resistant parent. A major QTL repeatedly detected in multiple developmental stages and environments was fine mapped in a backcross population. Grey leaf spot (GLS), caused by Cercospora zeae-maydis or Cercospora zeina, is a highly destructive foliar disease worldwide. However, the mechanism of resistance against GLS is not well understood. To study the inheritance of this resistance, we developed two doubled haploid (DH) populations sharing a common resistant parent. The two DH populations were grown in two locations representing the typical maize-growing mountain area in Southwest China for 2 years. GLS disease severity was investigated 2 or 3 times until maturity in the 2 years, and the area under the disease progress curve was calculated. Two high-density linkage maps were constructed by genotyping-by-sequencing. A total of 22 quantitative trait loci (QTLs) were detected for GLS resistance, with most QTLs being repeatedly detected in different stages, locations and years. The confidence intervals of two major QTLs (qGLS_Y2-2 and qGLS_Z2-1) on chromosome 2 from the two DH populations overlapped with each other and were integrated into one consensus QTL (qGLS_YZ2-1). Using highly resistant and highly susceptible plants from a BC₃ population, we fine mapped this genetic locus to a genomic region of 2.4 Mb. Using a panel of 255 inbred lines from breeding programmes, we detected associations between markers in the qGLS_YZ2-1 region and GLS resistance. The peak marker (ID-B1) will be very useful for marker-assisted breeding for GLS resistance.

Mapping a double flower phenotype-associated gene DcAP2L in Dianthus chinensis

The double flower is a highly important breeding trait that affects the ornamental value in many flowering plants. To get a better understanding of the genetic mechanism of double flower formation in Dianthus chinensis, we have constructed a high-density genetic map using 140 F2 progenies derived from a cross between a single flower genotype and a double flower genotype. The linkage map was constructed using double-digest restriction site-associated DNA sequencing (ddRAD-seq) with 2353 single nucleotide polymorphisms (SNPs). Quantitative trait locus (QTL) mapping analysis was conducted for 12 horticultural traits, and major QTLs were identified for nine of the 12 traits. Among them, two major QTLs accounted for 20.7% and 78.1% of the total petal number variation, respectively. Bulked segregant RNA-seq (BSR-seq) was performed to search accurately for candidate genes associated with the double flower trait. Integrative analysis of QTL mapping and BSR-seq analysis using the reference genome of Dianthus caryophyllus suggested that an SNP mutation in the miR172 cleavage site of the A-class flower organ identity gene APETALA2 (DcAP2L) is responsible for double flower formation in Dianthus through regulating the expression of DcAG genes.

Sacha inchi (Plukenetia volubilis L.)-from lost crop of the Incas to part of the solution to global challenges?

The underutilized, oleaginous crop Plukenetia volubilis L. has a remarkable lipid composition and a large potential for further domestication, alleviation of malnutrition, and integration into sustainable food production systems. Current global challenges include climate change, increasing population size, lack of food security, malnutrition, and degradation of arable lands. In this context, a reformation of our food production systems is imperative. Underutilized crops, or orphan crops, can provide valuable traits for this purpose, e.g., climate change resilience, nutritional benefits, cultivability on marginal lands, and improvement of income opportunities for smallholders. Plukenetia volubilis L. (Euphorbiaceae)-sacha inchi-is a 'lost crop' of the Incas native to the Amazon basin. Its oleaginous seeds are large, with a high content of ω-3, and -6 fatty acids (ca. 50.5, and 34.1%, of the lipid fraction, respectively), protein, and antioxidants. Culinarily, the seeds are nut-like and the crop has been associated with humans since Incan times. Research has particularly been undertaken in seed biochemistry, and to some extent in phylogeny, genetics, and cultivation ecology, but attention has been unevenly distributed, causing knowledge gaps in areas such as ethnobotany, allergenicity, and sustainable cultivation practices. Recently, seed size evolution and molecular drivers of the fatty acid synthesis and composition have been studied, however, further research into the lipid biosynthesis is desirable. Targeted breeding has not been undertaken but might be especially relevant for yield, sensory qualities, and cultivation with low environmental impact. Similarly, studies of integration into sustainable management systems are of highest importance. Here, present knowledge on P. volubilis is reviewed and a general framework for conducting research on underutilized crops with the aim of integration into sustainable food production systems is presented.

Fine mapping and candidate gene analysis of a seed glucosinolate content QTL, qGSL-C2, in rapeseed (Brassica napus L.)

QTL mapping and candidate gene analysis indicate that allelic variations in BnaC2.MYB28 resulted from homeologous exchange and determine difference in seed glucosinolate content. A low seed glucosinolate content has long been an important breeding objective in rapeseed improvement. However, the molecular mechanisms underlying seed GSL content variations remain to be elucidated in allotetraploid Brassica napus. Here, we developed a double haploid population from a cross between two B. napus accessions that possess relatively low, but significantly different seed GSL contents and identified a major QTL, qGSL-C2, on chromosome C02 that explains 30.88-72.87% of the phenotypic variation observed in five environments. Using near-isogenic lines, we further delimited qGSL-C2 to a physical region of 49 kb on the B. rapa chromosome A02 which is highly homologous to the target C02 interval. Among five candidate genes, BnaC2.MYB28, a homologue of the Arabidopsis MYB28 encoding a putative R2R3-MYB-type transcription factor functioning in aliphatic methionine-derived GSL synthesis, was most likely to be the target gene underlying the QTL. Sequence analysis revealed multiple insertion/deletion and SNP variations in the genomic region between the alleles of the NILs. Furthermore, the allelic variations in BnaC2.MYB28 in the natural B. napus population were significantly associated with seed GSL content. Remarkably, the phylogenetic analysis and sequence comparison suggested that while the BnaC2.MYB28 allele from the parental line G120 was inherited from B. oleracea BolC2.MYB28, its counterpart from the other parent, 9172, most likely evolved from B. rapa BraA2.MYB28 via possible homeologous exchange. Our study promotes greater understanding of the molecular regulation of seed GSL content and provides useful molecular markers for seed GSL improvement in B. napus.

Strong temporal dynamics of QTL action on plant growth progression revealed through high-throughput phenotyping in canola

A major challenge of plant biology is to unravel the genetic basis of complex traits. We took advantage of recent technical advances in high-throughput phenotyping in conjunction with genome-wide association studies to elucidate genotype-phenotype relationships at high temporal resolution. A diverse Brassica napus population from a commercial breeding programme was analysed by automated non-invasive phenotyping. Time-resolved data for early growth-related traits, including estimated biovolume, projected leaf area, early plant height and colour uniformity, were established and complemented by fresh and dry weight biomass. Genome-wide SNP array data provided the framework for genome-wide association analyses. Using time point data and relative growth rates, multiple robust main effect marker-trait associations for biomass and related traits were detected. Candidate genes involved in meristem development, cell wall modification and transcriptional regulation were detected. Our results demonstrate that early plant growth is a highly complex trait governed by several medium and many small effect loci, most of which act only during short phases. These observations highlight the importance of taking the temporal patterns of QTL/allele actions into account and emphasize the need for detailed time-resolved analyses to effectively unravel the complex and stage-specific contributions of genes affecting growth processes that operate at different developmental phases.

Genome-Wide Mapping of Loci Associated With Resistance to Clubroot in Brassica napus ssp. napobrassica (Rutabaga) Accessions From Nordic Countries

Rutabaga [Brassica napus ssp. napobrassica (L.) Hanelt] is reported to be an excellent source of clubroot (Plasmodiophora brassicae) resistance genes. In this study, 124 rutabaga accessions from the Nordic countries (Norway, Sweden, Finland, Denmark, and Iceland) were evaluated for their reaction to five single-spore isolates representing P. brassicae pathotypes 2F, 3H, 5I, 6M, and 8N and 12 field isolates representing pathotypes 2B, 3A, 3O, 5C, 5G, 5K, 5L, 5X (two isolates, L-G2 and L-G3), 8E, 8J, and 8P. The accessions were also genotyped using a 15K Brassica SNP array and 60 PCR-based primers linked to previously identified clubroot resistance genes. Six thousand eight hundred sixty-one SNP markers were retained after filtering with TASSEL 5.0, and used to evaluate four general linear models (GLM) and four mixed linear models (MLM). The PCA + K and Q + K MLM models gave the minimal deviance of the observed from the expected distribution in quantile-quantile plots, and hence were used for SNP-clubroot association analyses. In addition, 108 alleles derived from the PCR-based markers and the phenotypic data were analyzed with the PCA + K model. Forty-five SNPs and four PCR-based markers were identified to be associated strongly with resistance to isolates representing 13 pathotypes (2F, 3H, 5I, 6M, 8N, 2B, 3A, 3O, 5C, 5G, 5K, 5L, and 8P). These markers revealed the top and bottom segments of rutabaga chromosome A03 and the middle segment of chromosome A08 as genomic hotspots associated with resistance to the different P. brassicae pathotypes.

Utilizing field collected insects for next generation sequencing: Effects of sampling, storage, and DNA extraction methods

DNA sequencing technologies continue to advance the biological sciences, expanding opportunities for genomic studies of non-model organisms for basic and applied questions. Despite these opportunities, many next generation sequencing protocols have been developed assuming a substantial quantity of high molecular weight DNA (>100 ng), which can be difficult to obtain for many study systems. In particular, the ability to sequence field-collected specimens that exhibit varying levels of DNA degradation remains largely unexplored. In this study we investigate the influence of five traditional insect capture and curation methods on Double-Digest Restriction Enzyme Associated DNA (ddRAD) sequencing success for three wild bee species. We sequenced a total of 105 specimens (between 7-13 specimens per species and treatment). We additionally investigated how different DNA quality metrics (including pre-sequence concentration and contamination) predicted downstream sequencing success, and also compared two DNA extraction methods. We report successful library preparation for all specimens, with all treatments and extraction methods producing enough highly reliable loci for population genetic analyses. Although results varied between species, we found that specimens collected by net sampling directly into 100% EtOH, or by passive trapping followed by 100% EtOH storage before pinning tended to produce higher quality ddRAD assemblies, likely as a result of rapid specimen desiccation. Surprisingly, we found that specimens preserved in propylene glycol during field sampling exhibited lower-quality assemblies. We provide recommendations for each treatment, extraction method, and DNA quality assessment, and further encourage researchers to consider utilizing a wider variety of specimens for genomic analyses.

Genome-Wide Analyses Reveal Footprints of Divergent Selection and Drought Adaptive Traits in Synthetic-Derived Wheats

Crop-wild introgressions have long been exploited without knowing the favorable recombination points. Synthetic hexaploid wheats are one of the most exploited genetic resources for bread wheat improvement. However, despite some QTL with major effects, much less is known about genome-wide patterns of introgressions and their effects on phenotypes. We used two genome-wide association approaches: SNP-GWAS and haplotype-GWAS to identify SNPs and haplotypes associated with productivity under water-limited conditions in a synthetic-derived wheat (SYN-DER) population. Haplotype-GWAS further enriched and identified 20 more genomic regions associated with drought adaptability that did not overlap with SNP-GWAS. Since GWAS is biased to the phenotypes in the study and may fail to detect important genetic diversity during breeding, we used five complementary analytical approaches (t-test, Tajima’s D, nucleotide diversity (π), Fst, and EigenGWAS) to identify divergent selections in SYN-DER compared to modern bread wheat. These approaches consistently pinpointed 89 ‘selective sweeps’, out of which 30 selection loci were identified on D-genome. These key selections co-localized with important functional genes of adaptive traits such as TaElf3-D1 (1D) for earliness per se (Eps), TaCKX-D1 (3D), TaGS1a (6D) and TaGS-D1 (7D) for grain size, weight and morphology, TaCwi-D1 (5D) influencing drought tolerance, and Vrn-D3 (7D) for vernalization. Furthermore, 55 SNPs and 23 haplotypes of agronomic and physiological importance such as grain yield, relative water content and thousand grain weight in SYN-DER, were among the top 5% of divergent selections contributed by synthetic hexaploid wheats. These divergent selections associated with improved agronomic performance carry new alleles that have been introduced to wheat. Our results demonstrated that GWAS and selection sweep analyses are powerful approaches for investigating favorable introgressions under strong selection pressure and the use of crop-wild hybridization to assist the improvement of wheat yield and productivity under moisture limiting environments.

Reconstituting the genome of a young allopolyploid crop, Brassica napus, with its related species

Brassica napus (Aⁿ Aⁿ Cⁿ Cⁿ ) is an important worldwide oilseed crop, but it is a young allotetraploid with a short evolutionary history and limited genetic diversity. To significantly broaden its genetic diversity and create a novel heterotic population for sustainable rapeseed breeding, this study reconstituted the genome of B. napus by replacing it with the subgenomes from 122 accessions of Brassica rapa (A^r A^r ) and 74 accessions of Brassica carinata (B^c B^c C^c C^c ) and developing a novel gene pool of B. napus through five rounds of extensive recurrent selection. When compared with traditional B. napus using SSR markers and high-throughput SNP/Indel markers through genotyping by sequencing, the newly developed gene pool and its homozygous progenies exhibited a large genetic distance, rich allelic diversity, new alleles and exotic allelic introgression across all 19 AC chromosomes. In addition to the abundant genomic variation detected in the AC genome, we also detected considerable introgression from the eight chromosomes of the B genome. Extensive trait variation and some genetic improvements were present from the early recurrent selection to later generations. This novel gene pool produced equally rich phenotypic variation and should be valuable for rapeseed genetic improvement. By reconstituting the genome of B. napus by introducing subgenomic variation within and between the related species using intense selection and recombination, the whole genome could be substantially reorganized. These results serve as an example of the manipulation of the genome of a young allopolyploid and provide insights into its rapid genome evolution affected by interspecific and intraspecific crosses.

From markers to genome-based breeding in wheat

Recent technological advances in wheat genomics provide new opportunities to uncover genetic variation in traits of breeding interest and enable genome-based breeding to deliver wheat cultivars for the projected food requirements for 2050. There has been tremendous progress in development of whole-genome sequencing resources in wheat and its progenitor species during the last 5 years. High-throughput genotyping is now possible in wheat not only for routine gene introgression but also for high-density genome-wide genotyping. This is a major transition phase to enable genome-based breeding to achieve progressive genetic gains to parallel to projected wheat production demands. These advances have intrigued wheat researchers to practice less pursued analytical approaches which were not practiced due to the short history of genome sequence availability. Such approaches have been successful in gene discovery and breeding applications in other crops and animals for which genome sequences have been available for much longer. These strategies include, (i) environmental genome-wide association studies in wheat genetic resources stored in genbanks to identify genes for local adaptation by using agroclimatic traits as phenotypes, (ii) haplotype-based analyses to improve the statistical power and resolution of genomic selection and gene mapping experiments, (iii) new breeding strategies for genome-based prediction of heterosis patterns in wheat, and (iv) ultimate use of genomics information to develop more efficient and robust genome-wide genotyping platforms to precisely predict higher yield potential and stability with greater precision. Genome-based breeding has potential to achieve the ultimate objective of ensuring sustainable wheat production through developing high yielding, climate-resilient wheat cultivars with high nutritional quality.

Evaluation and Recommendations for Routine Genotyping Using Skim Whole Genome Re-sequencing in Canola

Whole genome sequencing offers genome wide, unbiased markers, and inexpensive library preparation. With the cost of sequencing decreasing rapidly, many plant genomes of modest size are amenable to skim whole genome resequencing (skim WGR). The use of skim WGR in diverse sample sets without the use of imputation was evaluated in silico in 149 canola samples representative of global diversity. Fastq files with an average of 10x coverage of the reference genome were used to generate skim samples representing 0.25x, 0.5x, 1x, 2x, 3x, 4x, and 5x sequencing coverage. Applying a pre-defined list of SNPs versus de novo SNP discovery was evaluated. As skim WGR is expected to result in some degree of insufficient allele sampling, all skim coverage levels were filtered at a range of minimum read depths from a relaxed minimum read depth of 2 to a stringent read depth of 5, resulting in 28 list-based SNP sets. As a broad recommendation, genotyping pre-defined SNPs between 1x and 2x coverage with relatively stringent depth filtering is appropriate for a diverse sample set of canola due to a balance between marker number, sufficient accuracy, and sequencing cost, but depends on the intended application. This was experimentally examined in two sample sets with different genetic backgrounds: 1x coverage of 1,590 individuals from 84 Australian spring type four-parent crosses aimed at maximizing diversity as well as one commercial F1 hybrid, and 2x coverage of 379 doubled haploids (DHs) derived from a subset of the four-parent crosses. To determine optimal coverage in a simpler genetic background, the DH sample sequence coverage was further down sampled in silico. The flexible and cost-effective nature of the protocol makes it highly applicable across a range of species and purposes.

Dissection of the genetic architecture of three seed-quality traits and consequences for breeding in Brassica napus

Genome-wide association studies (GWASs) combining high-throughput genome resequencing and phenotyping can accelerate the dissection of genetic architecture and identification of genes for plant complex traits. In this study, we developed a rapeseed genomic variation map consisting of 4 542 011 SNPs and 628 666 INDELs. GWAS was performed for three seed-quality traits, including erucic acid content (EAC), glucosinolate content (GSC) and seed oil content (SOC) using 3.82 million polymorphisms in an association panel. Six, 49 and 17 loci were detected to be associated with EAC, GSC and SOC in multiple environments, respectively. The mean total contribution of these loci in each environment was 94.1% for EAC and 87.9% for GSC, notably higher than that for SOC (40.1%). A high correlation was observed between phenotypic variance and number of favourable alleles for associated loci, which will contribute to breeding improvement by pyramiding these loci. Furthermore, candidate genes were detected underlying associated loci, based on functional polymorphisms in gene regions where sequence variation was found to correlate with phenotypic variation. Our approach was validated by detection of well-characterized FAE1 genes at each of two major loci for EAC on chromosomes A8 and C3, along with MYB28 genes at each of three major loci for GSC on chromosomes A9, C2 and C9. Four novel candidate genes were detected by correlation between GSC and SOC and observed sequence variation, respectively. This study provides insights into the genetic architecture of three seed-quality traits, which would be useful for genetic improvement of B. napus.

Diversity and Genome Analysis of Australian and Global Oilseed Brassica napus L. Germplasm Using Transcriptomics and Whole Genome Re-sequencing

Intensive breeding of Brassica napus has resulted in relatively low diversity, such that B. napus would benefit from germplasm improvement schemes that sustain diversity. As such, samples representative of global germplasm pools need to be assessed for existing population structure, diversity and linkage disequilibrium (LD). Complexity reduction genotyping-by-sequencing (GBS) methods, including GBS-transcriptomics (GBS-t), enable cost-effective screening of a large number of samples, while whole genome re-sequencing (WGR) delivers the ability to generate large numbers of unbiased genomic single nucleotide polymorphisms (SNPs), and identify structural variants (SVs). Furthermore, the development of genomic tools based on whole genomes representative of global oilseed diversity and orientated by the reference genome has substantial industry relevance and will be highly beneficial for canola breeding. As recent studies have focused on European and Chinese varieties, a global diversity panel as well as a substantial number of Australian spring types were included in this study. Focusing on industry relevance, 633 varieties were initially genotyped using GBS-t to examine population structure using 61,037 SNPs. Subsequently, 149 samples representative of global diversity were selected for WGR and both data sets used for a side-by-side evaluation of diversity and LD. The WGR data was further used to develop genomic resources consisting of a list of 4,029,750 high-confidence SNPs annotated using SnpEff, and SVs in the form of 10,976 deletions and 2,556 insertions. These resources form the basis of a reliable and repeatable system allowing greater integration between canola genomics studies, with a strong focus on breeding germplasm and industry applicability.

Revolution in Genotyping Platforms for Crop Improvement

In the past decade, the application of high-throughput sequencing to crop genotyping has given rise to novel platforms capable of genotyping tens of thousands of genome-wide DNA markers. Coupled with the decreasing costs of sequencing, this rapid increase in markers allows accelerated and highly accurate genotyping of entire crop populations and diversity sets using single nucleotide polymorphisms (SNPs). These revolutionary advances accelerate crop improvement by facilitating a more precise connection of phenotype to genotype through association studies, linkage mapping and diversity analysis. The platforms driving the advances in genotyping are array technologies and genotyping by sequencing (GBS) methods, which include both low-coverage whole genome resequencing (skim sequencing) and reduced representation sequencing (RRS) approaches. Here, we outline and compare these genotyping platforms and provide a perspective on the promising future of crop genotyping. While SNP arrays provide high quality, simple handling, and unchallenging analysis, the lower cost of RRS and the greater data volume produced by skim sequencing suggest that use of GBS will become more prevalent in crop genomics as sequencing costs decrease and data analysis becomes more streamlined. Graphical Abstract.

Genetic Properties of a Nested Association Mapping Population Constructed With Semi-Winter and Spring Oilseed Rapes

Nested association mapping (NAM) populations have been widely applied to dissect the genetic basis of complex quantitative traits in a variety of crops. In this study, we developed a Brassica napus NAM (BN-NAM) population consisting of 15 recombination inbred line (RIL) families with 2,425 immortal genotypes. Fifteen high-density genetic linkage maps were constructed by genotyping by sequencing (GBS) based on all RIL families, with further integration into a joint linkage map (JLM) having 30,209 unique markers in common with multiple linkage maps. Furthermore, an ultra-density whole-genome variation map was constructed by projecting 4,444,309 high-quality variants onto the JLM. The NAM population captured a total of 88,542 recombination events (REs). The uneven distribution of recombination rate along chromosomes is positively correlated with the densities of genes and markers, but negatively correlated with the density of transposable elements and linkage disequilibrium (LD). Analyses of population structure and principal components revealed that the BN-NAM population could be divided into three groups with weak stratification. The LD decay distance across genome varied between 170 and 2,400 Kb, with LD decay more rapid in the A than in the C sub-genome. The pericentromeric regions contained large LD blocks, especially in the C sub-genome. This NAM population provides a valuable resource for dissecting the genetic basis of important traits in rapeseed, especially in semi-winter oilseed rape.

Genetic Variation and Association Mapping of Seed-Related Traits in Cultivated Peanut (Arachis hypogaea L.) Using Single-Locus Simple Sequence Repeat Markers

Cultivated peanut (Arachis hypogaea L.) is an allotetraploid (AABB, 2n = 4x = 40), valued for its edible oil and digestible protein. Seed size and weight are important agronomical traits significantly influence the yield and nutritional composition of peanut. However, the genetic basis of seed-related traits remains ambiguous. Association mapping is a powerful approach for quickly and efficiently exploring the genetic basis of important traits in plants. In this study, a total of 104 peanut accessions were used to identify molecular markers associated with seed-related traits using 554 single-locus simple sequence repeat (SSR) markers. Most of the accessions had no or weak relationship in the peanut panel. The linkage disequilibrium (LD) decayed with the genetic distance of 1cM at the genome level and the LD of B subgenome decayed faster than that of the A subgenome. Large phenotypic variation was observed for four seed-related traits in the association panel. Using mixed linear model with population structure and kinship, a total of 30 significant SSR markers were detected to be associated with four seed-related traits (P < 1.81 × 10^-3) in different environments, which explained 11.22-32.30% of the phenotypic variation for each trait. The marker AHGA44686 was simultaneously and repeatedly associated with seed length and hundred-seed weight in multiple environments with large phenotypic variance (26.23 ∼ 32.30%). The favorable alleles of associated markers for each seed-related trait and the optimal combination of favorable alleles of associated markers were identified to significantly enhance trait performance, revealing a potential of utilization of these associated markers in peanut breeding program.

Identification of stable QTLs for seed oil content by combined linkage and association mapping in Brassica napus

Seed oil content is an important agricultural trait in rapeseed breeding. Although numerous quantitative trait locus (QTL) have been identified, most of them cannot be applied in practical breeding mainly due to environmental instability or large confidence intervals. The purpose of this study was to identify and validate high quality and more stable QTLs by combining linkage mapping and genome-wide association study (GWAS). For linkage mapping, we constructed two F₂ populations from crosses of high-oil content (∼50%) lines 6F313 and 61616 with a low-oil content (∼40%) line 51070. Two high density linkage maps spanned 1987cM (1659 bins) and 1856cM (1746 bins), respectively. For GWAS, we developed more than 34,000 high-quality SNP markers based on 227 accessions. Finally, 40 QTLs and 29 associations were established by linkage and association mapping in different environments. After merging the results, 32 consensus QTLs were obtained and 7 of them were identified by both mapping methods. Seven overlapping QTLs covered an average confidence interval of 183kb and explained the phenotypic variation of 10.23 to 24.45%. We further developed allele-specific PCR primers to identify each of the seven QTLs. These stable QTLs should be useful in gene cloning and practical breeding application.

Characterization and Transferable Utility of Microsatellite Markers in the Wild and Cultivated Arachis Species

Microsatellite or simple sequence repeat (SSR) is one of the most widely distributed molecular markers that have been widely utilized to assess genetic diversity and genetic mapping for important traits in plants. However, the understanding of microsatellite characteristics in Arachis species and the currently available amount of high-quality SSR markers remain limited. In this study, we identified 16,435 genome survey sequences SSRs (GSS-SSRs) and 40,199 expressed sequence tag SSRs (EST-SSRs) in Arachis hypogaea and its wild relative species using the publicly available sequence data. The GSS-SSRs had a density of 159.9–239.8 SSRs/Mb for wild Arachis and 1,015.8 SSR/Mb for cultivated Arachis, whereas the EST-SSRs had the density of 173.5–384.4 SSR/Mb and 250.9 SSRs/Mb for wild and cultivated Arachis, respectively. The trinucleotide SSRs were predominant across Arachis species, except that the dinucleotide accounted for most in A. hypogaea GSSs. From Arachis GSS-SSR and EST-SSR sequences, we developed 2,589 novel SSR markers that showed a high polymorphism in six diverse A. hypogaea accessions. A genetic linkage map that contained 540 novel SSR loci and 105 anchor SSR loci was constructed by case of a recombinant inbred lines F₆ population. A subset of 82 randomly selected SSR markers were used to screen 39 wild and 22 cultivated Arachis accessions, which revealed a high transferability of the novel SSRs across Arachis species. Our results provided informative clues to investigate microsatellite patterns across A. hypogaea and its wild relative species and potentially facilitate the germplasm evaluation and gene mapping in Arachis species.