Crop genome sequencing: lessons and rationales

A comparative study of 11 non-linear regression models highlighting autoencoder, DBN, and SVR, enhanced by SHAP importance analysis in soybean branching prediction

To explore a robust tool for advancing digital breeding practices through an artificial intelligence-driven phenotype prediction expert system, we undertook a thorough analysis of 11 non-linear regression models. Our investigation specifically emphasized the significance of Support Vector Regression (SVR) and SHapley Additive exPlanations (SHAP) in predicting soybean branching. By using branching data (phenotype) of 1918 soybean accessions and 42 k SNP (Single Nucleotide Polymorphism) polymorphic data (genotype), this study systematically compared 11 non-linear regression AI models, including four deep learning models (DBN (deep belief network) regression, ANN (artificial neural network) regression, Autoencoders regression, and MLP (multilayer perceptron) regression) and seven machine learning models (e.g., SVR (support vector regression), XGBoost (eXtreme Gradient Boosting) regression, Random Forest regression, LightGBM regression, GPs (Gaussian processes) regression, Decision Tree regression, and Polynomial regression). After being evaluated by four valuation metrics: R2 (R-squared), MAE (Mean Absolute Error), MSE (Mean Squared Error), and MAPE (Mean Absolute Percentage Error), it was found that the SVR, Polynomial Regression, DBN, and Autoencoder outperformed other models and could obtain a better prediction accuracy when they were used for phenotype prediction. In the assessment of deep learning approaches, we exemplified the SVR model, conducting analyses on feature importance and gene ontology (GO) enrichment to provide comprehensive support. After comprehensively comparing four feature importance algorithms, no notable distinction was observed in the feature importance ranking scores across the four algorithms, namely Variable Ranking, Permutation, SHAP, and Correlation Matrix, but the SHAP value could provide rich information on genes with negative contributions, and SHAP importance was chosen for feature selection. The results of this study offer valuable insights into AI-mediated plant breeding, addressing challenges faced by traditional breeding programs. The method developed has broad applicability in phenotype prediction, minor QTL (quantitative trait loci) mining, and plant smart-breeding systems, contributing significantly to the advancement of AI-based breeding practices and transitioning from experience-based to data-based breeding.

Current Progress, Applications and Challenges of Multi-Omics Approaches in Sesame Genetic Improvement

Sesame is one of the important traditional oil crops in the world, and has high economic and nutritional value. Recently, due to the novel high throughput sequencing techniques and bioinformatical methods, the study of the genomics, methylomics, transcriptomics, proteomics and metabonomics of sesame has developed rapidly. Thus far, the genomes of five sesame accessions have been released, including white and black seed sesame. The genome studies reveal the function and structure of the sesame genome, and facilitate the exploitation of molecular markers, the construction of genetic maps and the study of pan-genomes. Methylomics focus on the study of the molecular level changes under different environmental conditions. Transcriptomics provide a powerful tool to study abiotic/biotic stress, organ development, and noncoding RNAs, and proteomics and metabonomics also provide some support in studying abiotic stress and important traits. In addition, the opportunities and challenges of multi-omics in sesame genetics breeding were also described. This review summarizes the current research status of sesame from the perspectives of multi-omics and hopes to provide help for further in-depth research on sesame.

Genetic divergence in transcriptional regulators of defense metabolism: insight into plant domestication and improvement

A number of mutational changes in transcriptional regulators of defense metabolism have occurred during plant domestication and improvement. Plant domestication and improvement entail genetic changes that underlie divergence in development and metabolism, providing a tremendous model of biological evolution. Plant metabolism produces numerous specialized alkaloids, terpenoids, phenolics, and cyanogenic glucosides with indispensable roles in defense against herbivory and microbial infection. Many compounds toxic or deterrent to predators have been eliminated through domestication and breeding. Series of genes involved in defense metabolism are coordinately regulated by transcription factors that specifically recognize cis-regulatory elements in promoter regions of downstream target genes. Recent developments in DNA sequencing technologies and genomic approaches have facilitated studies of the metabolic and genetic changes in chemical defense that have occurred via human-mediated selection, many of which result from mutations in transcriptional regulators of defense metabolism. In this article, we review such examples in almond (Prunus dulcis), cucumber (Cucumis sativus), pepper (Capsicum spp.), potato (Solanum tuberosum), quinoa (Chenopodium quinoa), sorghum (Sorghum bicolor), and related species and discuss insights into the evolution and regulation of metabolic pathways for specialized defense compounds.

Comparative transcriptome analysis reveals the regulation network for fiber strength in cotton

OBJECTIVE

Determine the effect of secondary cell wall (SCW) thickness and microcrystalline cellulose content (MCC) on mature fiber strength (FS) and reveal through comparative transcriptome analysis the molecular regulation network governing FS in cotton.

RESULTS

Transmission electron microscope (TEM) analysis of two parent varieties, Prema with elite FS and 86-1 with weak fiber, revealed significant difference in the SCW but not in MCC. Transcriptome analysis revealed that genes differentially expressed during SCW thickening (20 DPA) are highly related to FS; in particular, up-regulated genes such as UDPG, CESA2, and NAC83 were important in SCW thickening, likely contributing to higher FS. GO and KEGG enrichment analysis revealed the common up-regulated genes to be enriched in carbon metabolism and terms relating to the cell wall.

CONCLUSIONS

We developed two recombinant inbred lines with elite FS, selected from the filial generation of Prema and 86-1. By comparing transcriptomic data, we revealed the gene expression network governing SCW thickness in mature fiber. Our results provide solid insights into the relationship of the SCW and FS.

Mining Grapevine Downy Mildew Susceptibility Genes: A Resource for Genomics-Based Breeding and Tailored Gene Editing

Several pathogens continuously threaten viticulture worldwide. Until now, the investigation on resistance loci has been the main trend to understand the interaction between grapevine and the mildew causal agents. Dominantly inherited gene-based resistance has shown to be race-specific in some cases, to confer partial immunity, and to be potentially overcome within a few years since its introgression. Recently, on the footprint of research conducted in Arabidopsis, putative genes associated with downy mildew susceptibility have been discovered also in the grapevine genome. In this work, we deep-sequenced four putative susceptibility genes-namely VvDMR6.1, VvDMR6.2, VvDLO1, VvDLO2-in 190 genetically diverse grapevine genotypes to discover new sources of broad-spectrum and recessively inherited resistance. Identified Single Nucleotide Polymorphisms were screened in a bottleneck analysis from the genetic sequence to their impact on protein structure. Fifty-five genotypes showed at least one impacting mutation in one or more of the scouted genes. Haplotypes were inferred for each gene and two of them at the VvDMR6.2 gene were found significantly more represented in downy mildew resistant genotypes. The current results provide a resource for grapevine and plant genetics and could corroborate genomic-assisted breeding programs as well as tailored gene editing approaches for resistance to biotic stresses.

High-quality de novo assembly of the Eucommia ulmoides haploid genome provides new insights into evolution and rubber biosynthesis

We report the acquisition of a high-quality haploid chromosome-scale genome assembly for the first time in a tree species, Eucommia ulmoides, which is known for its rubber biosynthesis and medicinal applications. The assembly was obtained by applying PacBio and Hi-C technologies to a haploid that we specifically generated. Compared to the initial genome release, this one has significantly improved assembly quality. The scaffold N50 (53.15 MB) increased 28-fold, and the repetitive sequence content (520 Mb) increased by 158.24 Mb, whereas the number of gaps decreased from 104,772 to 128. A total of 92.87% of the 26,001 predicted protein-coding genes identified with multiple strategies were anchored to the 17 chromosomes. A new whole-genome duplication event was superimposed on the earlier γ paleohexaploidization event, and the expansion of long terminal repeats contributed greatly to the evolution of the genome. The more primitive rubber biosynthesis of this species, as opposed to that in Hevea brasiliensis, relies on the methylerythritol-phosphate pathway rather than the mevalonate pathway to synthesize isoprenyl diphosphate, as the MEP pathway operates predominantly in trans-polyisoprene-containing leaves and central peels. Chlorogenic acid biosynthesis pathway enzymes were preferentially expressed in leaves rather than in bark. This assembly with higher sequence contiguity can foster not only studies on genome structure and evolution, gene mapping, epigenetic analysis and functional genomics but also efforts to improve E. ulmoides for industrial and medical uses through genetic engineering.

Genome size, chromosome number determination, and analysis of the repetitive elements in Cissus quadrangularis

Cissus quadrangularis (Vitaceae) is a perennial climber endemic to Africa and is characterized by succulent angular stems. The plant grows in arid and semi-arid regions of Africa especially in the African savanna. The stem of C. quadrangularis has a wide range of applications in both human and animal medicine, but there is limited cytogenetic information available for this species. In this study, the chromosome number, genome size, and genome composition for C. quadrangularis were determined. Flow cytometry results indicated that the genome size of C. quadrangularis is approximately 2C = 1.410 pg. Fluorescence microscopy combined with DAPI stain showed the chromosome numbers to be 2n = 48. It is likely that C. quadrangularis has a tetraploid genome after considering the basic chromosome numbers in Cissus genus (n = 10, 11, or 12). A combination of low-throughput genome sequencing and bioinformatics analysis allowed identification and quantification of repetitive elements that make up about 52% of the C. quadrangularis genome, which was dominated by LTR-retrotransposons. Two LTR superfamilies were identified as Copia and Gypsy, with 24% and 15% of the annotated clusters, respectively. The comparison of repeat elements for C. quadrangularis, Vitis vinifera, and four other selected members in the Cissus genus revealed a high diversity in the repetitive element components, which could suggest recent amplification events in the Cissus genus. Our data provides a platform for further studies on the phylogeny and karyotype evolution in this genus and in the family Vitaceae.

High-throughput phenotyping for crop improvement in the genomics era

Tremendous progress has been made with continually expanding genomics technologies to unravel and understand crop genomes. However, the impact of genomics data on crop improvement is still far from satisfactory, in large part due to a lack of effective phenotypic data; our capacity to collect useful high quality phenotypic data lags behind the current capacity to generate high-throughput genomics data. Thus, the research bottleneck in plant sciences is shifting from genotyping to phenotyping. This article review the current status of efforts made in the last decade to systematically collect phenotypic data to alleviate this 'phenomics bottlenecks' by recording trait data through sophisticated non-invasive imaging, spectroscopy, image analysis, robotics, high-performance computing facilities and phenomics databases. These modern phenomics platforms and tools aim to record data on traits like plant development, architecture, plant photosynthesis, growth or biomass productivity, on hundreds to thousands of plants in a single day, as a phenomics revolution. It is believed that this revolution will provide plant scientists with the knowledge and tools necessary for unlocking information coded in plant genomes. Efforts have been also made to present the advances made in the last 10 years in phenomics platforms and their use in generating phenotypic data on different traits in several major crops including rice, wheat, barley, and maize. The article also highlights the need for phenomics databases and phenotypic data sharing for crop improvement. The phenomics data generated has been used to identify genes/QTL through QTL mapping, association mapping and genome-wide association studies (GWAS) for genomics-assisted breeding (GAB) for crop improvement.

Progress in plant genome sequencing: research directions

Since the first plant genome of Arabidopsis thaliana has been sequenced and published, genome sequencing technologies have undergone significant changes. New algorithms, sequencing technologies and bioinformatic approaches were adopted to obtain genome, transcriptome and exome sequences for model and crop species, which have permitted deep inferences into plant biology. As a result of an improved genome assembly and analysis methods, genome sequencing costs plummeted and the number of high-quality plant genome sequences is constantly growing. Consequently, more than 300 plant genome sequences have been published over the past twenty years. Although many of the published genomes are considered incomplete, they proved to be a valuable tool for identifying genes involved in the formation of economically valuable plant traits, for marker-assisted and genomic selection and for comparative analysis of plant genomes in order to determine the basic patterns of origin of various plant species. Since a high coverage and resolution of a genome sequence is not enough to detect all changes in complex samples, targeted sequencing, which consists in the isolation and sequencing of a specific region of the genome, has begun to develop. Targeted sequencing has a higher detection power (the ability to identify new differences/variants) and resolution (up to one basis). In addition, exome sequencing (the method of sequencing only protein-coding genes regions) is actively developed, which allows for the sequencing of non-expressed alleles and genes that cannot be found with RNA-seq. In this review, an analysis of sequencing technologies development and the construction of “reference” genomes of plants is performed. A comparison of the methods of targeted sequencing based on the use of the reference DNA sequence is accomplished.

Chromosome-based survey sequencing reveals the genome organization of wild wheat progenitor Triticum dicoccoides

Wild emmer wheat (Triticum turgidum ssp. dicoccoides) is the progenitor of wheat. We performed chromosome-based survey sequencing of the 14 chromosomes, examining repetitive sequences, protein-coding genes, miRNA/target pairs and tRNA genes, as well as syntenic relationships with related grasses. We found considerable differences in the content and distribution of repetitive sequences between the A and B subgenomes. The gene contents of individual chromosomes varied widely, not necessarily correlating with chromosome size. We catalogued candidate agronomically important loci, along with new alleles and flanking sequences that can be used to design exome sequencing. Syntenic relationships and virtual gene orders revealed several small-scale evolutionary rearrangements, in addition to providing evidence for the 4AL-5AL-7BS translocation in wild emmer wheat. Chromosome-based sequence assemblies contained five novel miRNA families, among 59 families putatively encoded in the entire genome which provide insight into the domestication of wheat and an overview of the genome content and organization.

Root Phenotyping for Drought Tolerance: A Review

Plant roots play a significant role in plant growth by exploiting soil resources via the uptake of water and nutrients. Root traits such as fine root diameter, specific root length, specific root area, root angle, and root length density are considered useful traits for improving plant productivity under drought conditions. Therefore, understanding interactions between roots and their surrounding soil environment is important, which can be improved through root phenotyping. With the advancement in technologies, many tools have been developed for root phenotyping. Canopy temperature depression (CTD) has been considered a good technique for field phenotyping of crops under drought and is used to estimate crop yield as well as root traits in relation to drought tolerance. Both laboratory and field-based methods for phenotyping root traits have been developed including soil sampling, mini-rhizotron, rhizotrons, thermography and non-soil techniques. Recently, a non-invasive approach of X-ray computed tomography (CT) has provided a break-through to study the root architecture in three dimensions (3-D). This review summarizes methods for root phenotyping. On the basis of this review, it can be concluded that root traits are useful characters to be included in future breeding programs and for selecting better cultivars to increase crop yield under water-limited environments.

Genomic approaches for studying crop evolution

Understanding how crop plants evolved from their wild relatives and spread around the world can inform about the origins of agriculture. Here, we review how the rapid development of genomic resources and tools has made it possible to conduct genetic mapping and population genetic studies to unravel the molecular underpinnings of domestication and crop evolution in diverse crop species. We propose three future avenues for the study of crop evolution: establishment of high-quality reference genomes for crops and their wild relatives; genomic characterization of germplasm collections; and the adoption of novel methodologies such as archaeogenetics, epigenomics, and genome editing.

Linked read technology for assembling large complex and polyploid genomes

BACKGROUND

Short read DNA sequencing technologies have revolutionized genome assembly by providing high accuracy and throughput data at low cost. But it remains challenging to assemble short read data, particularly for large, complex and polyploid genomes. The linked read strategy has the potential to enhance the value of short reads for genome assembly because all reads originating from a single long molecule of DNA share a common barcode. However, the majority of studies to date that have employed linked reads were focused on human haplotype phasing and genome assembly.

RESULTS

Here we describe a de novo maize B73 genome assembly generated via linked read technology which contains ~ 172,000 scaffolds with an N50 of 89 kb that cover 50% of the genome. Based on comparisons to the B73 reference genome, 91% of linked read contigs are accurately assembled. Because it was possible to identify errors with > 76% accuracy using machine learning, it may be possible to identify and potentially correct systematic errors. Complex polyploids represent one of the last grand challenges in genome assembly. Linked read technology was able to successfully resolve the two subgenomes of the recent allopolyploid, proso millet (Panicum miliaceum). Our assembly covers ~ 83% of the 1 Gb genome and consists of 30,819 scaffolds with an N50 of 912 kb.

CONCLUSIONS

Our analysis provides a framework for future de novo genome assemblies using linked reads, and we suggest computational strategies that if implemented have the potential to further improve linked read assemblies, particularly for repetitive genomes.

Improvement of Drought Tolerance in Rice (Oryza sativa L.): Genetics, Genomic Tools, and the WRKY Gene Family

Drought tolerance is an important quantitative trait with multipart phenotypes that are often further complicated by plant phenology. Different types of environmental stresses, such as high irradiance, high temperatures, nutrient deficiencies, and toxicities, may challenge crops simultaneously; therefore, breeding for drought tolerance is very complicated. Interdisciplinary researchers have been attempting to dissect and comprehend the mechanisms of plant tolerance to drought stress using various methods; however, the limited success of molecular breeding and physiological approaches suggests that we rethink our strategies. Recent genetic techniques and genomics tools coupled with advances in breeding methodologies and precise phenotyping will likely reveal candidate genes and metabolic pathways underlying drought tolerance in crops. The WRKY transcription factors are involved in different biological processes in plant development. This zinc (Zn) finger protein family, particularly members that respond to and mediate stress responses, is exclusively found in plants. A total of 89 WRKY genes in japonica and 97 WRKY genes in O. nivara (OnWRKY) have been identified and mapped onto individual chromosomes. To increase the drought tolerance of rice (Oryza sativa L.), research programs should address the problem using a multidisciplinary strategy, including the interaction of plant phenology and multiple stresses, and the combination of drought tolerance traits with different genetic and genomics approaches, such as microarrays, quantitative trait loci (QTLs), WRKY gene family members with roles in drought tolerance, and transgenic crops. This review discusses the newest advances in plant physiology for the exact phenotyping of plant responses to drought to update methods of analysing drought tolerance in rice. Finally, based on the physiological/morphological and molecular mechanisms found in resistant parent lines, a strategy is suggested to select a particular environment and adapt suitable germplasm to that environment.

Genome-Wide Analysis of Genetic Variations and the Detection of Rich Variants of NBS-LRR Encoding Genes in Common Wild Rice Lines

Common wild rice (Oryza rufipogon Griff.) is invaluable genetic resource for rice resistance breeding. Whole-genome re-sequencing was conducted to systematically analyze the variations in two new inbred lines (Huaye 3 and Huaye 4) developed from a common wild rice. A total of 4,841,127 SNPs, 1,170,479 InDels, 24,080 structural variations (SVs), and 298 copy number variations (CNVs) were identified in three materials. Approximately 16.24 and 5.64% of the total SNPs and InDels of Huaye 3 and Huaye 4 were located in genic regions, respectively. Together, 12,486 and 15,925 large-effect SNPs, and 12,417 and 14,513 large-effect InDels, which affect the integrity of the encoded protein, were identified in Huaye 3 and Huaye 4, respectively. The distribution map of 194 and 245 NBS-LRR encoding homologs was constructed across 12 rice chromosomes. Further, GO enrichment analysis of the homologs with identical genotype variations in Huaye 3 and Huaye 4 revealed 67, 82, and 58 homologs involved in cell death, response to stress, and both terms, respectively. Comparative analysis displayed that 550 out of 652 SNPs and 129 out of 147 InDels were present in a widely used blast-susceptible rice variety (LTH). Protein-protein interaction analysis revealed a strong interaction between NBS-LRR candidates and several known R genes. One homolog of disease resistance protein (RPM1) was involved in the plant-pathogen interaction pathway. Artificial inoculation of disease/insect displayed resistance phenotypes against rice blast and brown planthopper in two lines. The results will provide allele-specific markers for rice molecular breeding.

The Challenge of Analyzing the Sugarcane Genome

Reference genome sequences have become key platforms for genetics and breeding of the major crop species. Sugarcane is probably the largest crop produced in the world (in weight of crop harvested) but lacks a reference genome sequence. Sugarcane has one of the most complex genomes in crop plants due to the extreme level of polyploidy. The genome of modern sugarcane hybrids includes sub-genomes from two progenitors Saccharum officinarum and S. spontaneum with some chromosomes resulting from recombination between these sub-genomes. Advancing DNA sequencing technologies and strategies for genome assembly are making the sugarcane genome more tractable. Advances in long read sequencing have allowed the generation of a more complete set of sugarcane gene transcripts. This is supporting transcript profiling in genetic research. The progenitor genomes are being sequenced. A monoploid coverage of the hybrid genome has been obtained by sequencing BAC clones that cover the gene space of the closely related sorghum genome. The complete polyploid genome is now being sequenced and assembled. The emerging genome will allow comparison of related genomes and increase understanding of the functioning of this polyploidy system. Sugarcane breeding for traditional sugar and new energy and biomaterial uses will be enhanced by the availability of these genomic resources.

A re-sequencing-based ultra-dense genetic map reveals a gummy stem blight resistance-associated gene in Cucumis melo

The melon (Cucumis melo) genome and genetic maps with hundreds to thousands of single nucleotide polymorphism markers were recently released. However, a high-resolution genetic map was lacking. Gummy stem blight (Gsb) is a destructive disease responsible for considerable economic losses during melon production. We herein describe the development of an ultra-dense genetic map consisting of 12,932 recombination bin markers covering 1,818 cM, with an average distance of 0.17 cM between adjacent tags. A comparison of the genetic maps for melon, watermelon, and cucumber revealed chromosome-level syntenic relationships and recombination events among the three Cucurbitaceae species. Our genetic map was useful for re-anchoring the genome scaffolds of melon. More than 92% assembly was anchored to 12 pseudo-chromosomes and 90% of them were oriented. Furthermore, 1,135 recombination hotspots revealed an unbalanced recombination rate across the melon genome. Genetic analyses of the Gsb-resistant and -susceptible lines indicated the resistance phenotype is mediated by a single dominant gene. We identified Gsb-resistance gene candidates in a 108-kb region on pseudo-chromosome 4. Our findings verify the utility of an ultra-dense genetic map for mapping a gene of interest, and for identifying new disease resistant genes.

pBACode: a random-barcode-based high-throughput approach for BAC paired-end sequencing and physical clone mapping

Applications that use Bacterial Artificial Chromosome (BAC) libraries often require paired-end sequences and knowledge of the physical location of each clone in plates. To facilitate obtaining this information in high-throughput, we generated pBACode vectors: a pool of BAC cloning vectors, each with a pair of random barcodes flanking its cloning site. In a pBACode BAC library, the BAC ends and their linked barcodes can be sequenced in bulk. Barcode pairs are determined by sequencing the empty pBACode vectors, which allows BAC ends to be paired according to their barcodes. For physical clone mapping, the barcodes are used as unique markers for their linked genomic sequence. After multi-dimensional pooling of BAC clones, the barcodes are sequenced and deconvoluted to locate each clone. We generated a pBACode library of 94,464 clones for the flounder Paralichthys olivaceus and obtained paired-end sequence from 95.4% of the clones. Incorporating BAC paired-ends into the genome preassembly improved its continuity by over 10-fold. Furthermore, we were able to use the barcodes to map the physical locations of each clone in just 50 pools, with up to 11 808 clones per pool. Our physical clone mapping located 90.2% of BAC clones, enabling targeted characterization of chromosomal rearrangements.

The Emerging Oilseed Crop Sesamum indicum Enters the "Omics" Era

Sesame (Sesamum indicum L.) is one of the oldest oilseed crops widely grown in Africa and Asia for its high-quality nutritional seeds. It is well adapted to harsh environments and constitutes an alternative cash crop for smallholders in developing countries. Despite its economic and nutritional importance, sesame is considered as an orphan crop because it has received very little attention from science. As a consequence, it lags behind the other major oil crops as far as genetic improvement is concerned. In recent years, the scenario has considerably changed with the decoding of the sesame nuclear genome leading to the development of various genomic resources including molecular markers, comprehensive genetic maps, high-quality transcriptome assemblies, web-based functional databases and diverse daft genome sequences. The availability of these tools in association with the discovery of candidate genes and quantitative trait locis for key agronomic traits including high oil content and quality, waterlogging and drought tolerance, disease resistance, cytoplasmic male sterility, high yield, pave the way to the development of some new strategies for sesame genetic improvement. As a result, sesame has graduated from an "orphan crop" to a "genomic resource-rich crop." With the limited research teams working on sesame worldwide, more synergic efforts are needed to integrate these resources in sesame breeding for productivity upsurge, ensuring food security and improved livelihood in developing countries. This review retraces the evolution of sesame research by highlighting the recent advances in the "Omics" area and also critically discusses the future prospects for a further genetic improvement and a better expansion of this crop.

Integration of omics approaches to understand oil/protein content during seed development in oilseed crops

Oilseed crops, especially soybean (Glycine max) and canola/rapeseed (Brassica napus), produce seeds that are rich in both proteins and oils and that are major sources of energy and nutrition worldwide. Most of the nutritional content in the seed is accumulated in the embryo during the seed filling stages of seed development. Understanding the metabolic pathways that are active during seed filling and how they are regulated are essential prerequisites to crop improvement. In this review, we summarize various omics studies of soybean and canola/rapeseed during seed filling, with emphasis on oil and protein traits, to gain a systems-level understanding of seed development. Currently, most (80-85%) of the soybean and rapeseed reference genomes have been sequenced (950 and 850 megabases, respectively). Parallel to these efforts, extensive omics datasets from different seed filling stages have become available. Transcriptome and proteome studies have detected preponderance of starch metabolism and glycolysis enzymes to be the possible cause of higher oil in B. napus compared to other crops. Small RNAome studies performed during the seed filling stages have revealed miRNA-mediated regulation of transcription factors, with the suggestion that this interaction could be responsible for transitioning the seeds from embryogenesis to maturation. In addition, progress made in dissecting the regulation of de novo fatty acid synthesis and protein storage pathways is described. Advances in high-throughput omics and comprehensive tissue-specific analyses make this an exciting time to attempt knowledge-driven investigation of complex regulatory pathways.

Oilseed rape: learning about ancient and recent polyploid evolution from a recent crop species

Oilseed rape (Brassica napus) is one of our youngest crop species, arising several times under cultivation in the last few thousand years and completely unknown in the wild. Oilseed rape originated from hybridisation events between progenitor diploid species B. rapa and B. oleracea, both important vegetable species. The diploid progenitors are also ancient polyploids, with remnants of two previous polyploidisation events evident in the triplicated genome structure. This history of polyploid evolution and human agricultural selection makes B. napus an excellent model with which to investigate processes of genomic evolution and selection in polyploid crops. The ease of de novo interspecific hybridisation, responsiveness to tissue culture, and the close relationship of oilseed rape to the model plant Arabidopsis thaliana, coupled with the recent availability of reference genome sequences and suites of molecular cytogenetic and high-throughput genotyping tools, allow detailed dissection of genetic, genomic and phenotypic interactions in this crop. In this review we discuss the past and present uses of B. napus as a model for polyploid speciation and evolution in crop species, along with current and developing analysis tools and resources. We further outline unanswered questions that may now be tractable to investigation.

Computational Tools for Genomic Studies in Plants

In recent years, the genomic sequence of numerous plant species including the main crop species has been determined. Computational tools have been developed to deal with the issue of which plant has been sequenced and where is the sequence hosted. In this mini-review, the databases for genome projects, the databases created to host species/clade projects and the databases developed to perform plant comparative genomics are revised. Because of their importance in modern research, an in-depth analysis of the plant comparative genomics databases has been performed. This comparative analysis is focused in the common and specific computational tools developed to achieve the particular objectives of each database. Besides, emerging high-performance bioinformatics tools specific for plant research are commented. What kind of computational approaches should be implemented in next years to efficiently analyze plant genomes is discussed.

Genomics Approaches For Improving Salinity Stress Tolerance in Crop Plants

Salinity is one of the major factors which reduces crop production worldwide. Plant responses to salinity are highly complex and involve a plethora of genes. Due to its multigenicity, it has been difficult to attain a complete understanding of how plants respond to salinity. Genomics has progressed tremendously over the past decade and has played a crucial role towards providing necessary knowledge for crop improvement. Through genomics, we have been able to identify and characterize the genes involved in salinity stress response, map out signaling pathways and ultimately utilize this information for improving the salinity tolerance of existing crops. The use of new tools, such as gene pyramiding, in genetic engineering and marker assisted breeding has tremendously enhanced our ability to generate stress tolerant crops. Genome editing technologies such as Zinc finger nucleases, TALENs and CRISPR/Cas9 also provide newer and faster avenues for plant biologists to generate precisely engineered crops.

Bioinformatics Approach in Plant Genomic Research

The advance in genomics technology leads to the dramatic change in plant biology research. Plant biologists now easily access to enormous genomic data to deeply study plant high-density genetic variation at molecular level. Therefore, fully understanding and well manipulating bioinformatics tools to manage and analyze these data are essential in current plant genome research. Many plant genome databases have been established and continued expanding recently. Meanwhile, analytical methods based on bioinformatics are also well developed in many aspects of plant genomic research including comparative genomic analysis, phylogenomics and evolutionary analysis, and genome-wide association study. However, constantly upgrading in computational infrastructures, such as high capacity data storage and high performing analysis software, is the real challenge for plant genome research. This review paper focuses on challenges and opportunities which knowledge and skills in bioinformatics can bring to plant scientists in present plant genomics era as well as future aspects in critical need for effective tools to facilitate the translation of knowledge from new sequencing data to enhancement of plant productivity.

The rubber tree genome reveals new insights into rubber production and species adaptation

The Para rubber tree (Hevea brasiliensis) is an economically important tropical tree species that produces natural rubber, an essential industrial raw material. Here we present a high-quality genome assembly of this species (1.37 Gb, scaffold N50 = 1.28 Mb) that covers 93.8% of the genome (1.47 Gb) and harbours 43,792 predicted protein-coding genes. A striking expansion of the REF/SRPP (rubber elongation factor/small rubber particle protein) gene family and its divergence into several laticifer-specific isoforms seem crucial for rubber biosynthesis. The REF/SRPP family has isoforms with sizes similar to or larger than SRPP1 (204 amino acids) in 17 other plants examined, but no isoforms with similar sizes to REF1 (138 amino acids), the predominant molecular variant. A pivotal point in Hevea evolution was the emergence of REF1, which is located on the surface of large rubber particles that account for 93% of rubber in the latex (despite constituting only 6% of total rubber particles, large and small). The stringent control of ethylene synthesis under active ethylene signalling and response in laticifers resolves a longstanding mystery of ethylene stimulation in rubber production. Our study, which includes the re-sequencing of five other Hevea cultivars and extensive RNA-seq data, provides a valuable resource for functional genomics and tools for breeding elite Hevea cultivars.

ahg12 is a dominant proteasome mutant that affects multiple regulatory systems for germination of Arabidopsis

The ubiquitin-proteasome system is fundamentally involved in myriad biological phenomena of eukaryotes. In plants, this regulated protein degradation system has a pivotal role in the cellular response mechanisms for both internal and external stimuli, such as plant hormones and environmental stresses. Information about substrate selection by the ubiquitination machinery has accumulated, but there is very little information about selectivity for substrates at the proteasome. Here, we report characterization of a novel abscisic acid (ABA)-hypersensitive mutant named ABA hypersensitive germination12 (ahg12) in Arabidopsis. The ahg12 mutant showed a unique pleiotropic phenotype, including hypersensitivity to ABA and ethylene, and hyposensitivity to light. Map-based cloning identified the ahg12 mutation to cause an amino acid conversion in the L23 loop of RPT5a, which is predicted to form the pore structure of the 19S RP complex of the proteasome. Transient expression assays demonstrated that some plant-specific signaling components accumulated at higher levels in the ahg12 mutant. These results suggest that the ahg12 mutation led to changes in the substrate preference of the 26S proteasome. The discovery of the ahg12 mutation thus will contribute to elucidate the characteristics of the regulated protein degradation system.

Improvement of the banana "Musa acuminata" reference sequence using NGS data and semi-automated bioinformatics methods

Background

Recent advances in genomics indicate functional significance of a majority of genome sequences and their long range interactions. As a detailed examination of genome organization and function requires very high quality genome sequence, the objective of this study was to improve reference genome assembly of banana (Musa acuminata).

Results

We have developed a modular bioinformatics pipeline to improve genome sequence assemblies, which can handle various types of data. The pipeline comprises several semi-automated tools. However, unlike classical automated tools that are based on global parameters, the semi-automated tools proposed an expert mode for a user who can decide on suggested improvements through local compromises. The pipeline was used to improve the draft genome sequence of Musa acuminata. Genotyping by sequencing (GBS) of a segregating population and paired-end sequencing were used to detect and correct scaffold misassemblies. Long insert size paired-end reads identified scaffold junctions and fusions missed by automated assembly methods. GBS markers were used to anchor scaffolds to pseudo-molecules with a new bioinformatics approach that avoids the tedious step of marker ordering during genetic map construction. Furthermore, a genome map was constructed and used to assemble scaffolds into super scaffolds. Finally, a consensus gene annotation was projected on the new assembly from two pre-existing annotations. This approach reduced the total Musa scaffold number from 7513 to 1532 (i.e. by 80 %), with an N50 that increased from 1.3 Mb (65 scaffolds) to 3.0 Mb (26 scaffolds). 89.5 % of the assembly was anchored to the 11 Musa chromosomes compared to the previous 70 %. Unknown sites (N) were reduced from 17.3 to 10.0 %.

Conclusion

The release of the Musa acuminata reference genome version 2 provides a platform for detailed analysis of banana genome variation, function and evolution. Bioinformatics tools developed in this work can be used to improve genome sequence assemblies in other species.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2579-4) contains supplementary material, which is available to authorized users.

Metabolomic profiling and genomic analysis of wheat aneuploid lines to identify genes controlling biochemical pathways in mature grain

Metabolomics is becoming an increasingly important tool in plant genomics to decipher the function of genes controlling biochemical pathways responsible for trait variation. Although theoretical models can integrate genes and metabolites for trait variation, biological networks require validation using appropriate experimental genetic systems. In this study, we applied an untargeted metabolite analysis to mature grain of wheat homoeologous group 3 ditelosomic lines, selected compounds that showed significant variation between wheat lines Chinese Spring and at least one ditelosomic line, tracked the genes encoding enzymes of their biochemical pathway using the wheat genome survey sequence and determined the genetic components underlying metabolite variation. A total of 412 analytes were resolved in the wheat grain metabolome, and principal component analysis indicated significant differences in metabolite profiles between Chinese Spring and each ditelosomic lines. The grain metabolome identified 55 compounds positively matched against a mass spectral library where the majority showed significant differences between Chinese Spring and at least one ditelosomic line. Trehalose and branched-chain amino acids were selected for detailed investigation, and it was expected that if genes encoding enzymes directly related to their biochemical pathways were located on homoeologous group 3 chromosomes, then corresponding ditelosomic lines would have a significant reduction in metabolites compared with Chinese Spring. Although a proportion showed a reduction, some lines showed significant increases in metabolites, indicating that genes directly and indirectly involved in biosynthetic pathways likely regulate the metabolome. Therefore, this study demonstrated that wheat aneuploid lines are suitable experimental genetic system to validate metabolomics-genomics networks.

Allele mining and enhanced genetic recombination for rice breeding

Traditional rice varieties harbour a large store of genetic diversity with potential to accelerate rice improvement. For a long time, this diversity maintained in the International Rice Genebank has not been fully used because of a lack of genome information. The publication of the first reference genome of Nipponbare by the International Rice Genome Sequencing Project (IRGSP) marked the beginning of a systematic exploration and use of rice diversity for genetic research and breeding. Since then, the Nipponbare genome has served as the reference for the assembly of many additional genomes. The recently completed 3000 Rice Genomes Project together with the public database (SNP-Seek) provides a new genomic and data resource that enables the identification of useful accessions for breeding. Using disease resistance traits as case studies, we demonstrated the power of allele mining in the 3,000 genomes for extracting accessions from the GeneBank for targeted phenotyping. Although potentially useful landraces can now be identified, their use in breeding is often hindered by unfavourable linkages. Efficient breeding designs are much needed to transfer the useful diversity to breeding. Multi-parent Advanced Generation InterCross (MAGIC) is a breeding design to produce highly recombined populations. The MAGIC approach can be used to generate pre-breeding populations with increased genotypic diversity and reduced linkage drag. Allele mining combined with a multi-parent breeding design can help convert useful diversity into breeding-ready genetic resources.

Genotyping-by-sequencing map permits identification of clubroot resistance QTLs and revision of the reference genome assembly in cabbage (Brassica oleracea L.)

Clubroot is a devastating disease caused by Plasmodiophora brassicae and results in severe losses of yield and quality in Brassica crops. Many clubroot resistance genes and markers are available in Brassica rapa but less is known in Brassica oleracea. Here, we applied the genotyping-by-sequencing (GBS) technique to construct a high-resolution genetic map and identify clubroot resistance (CR) genes. A total of 43,821 SNPs were identified using GBS data for two parental lines, one resistant and one susceptible lines to clubroot, and 18,187 of them showed >5× coverage in the GBS data. Among those, 4,103 were credibly genotyped for all 78 F₂ individual plants. These markers were clustered into nine linkage groups spanning 879.9 cM with an average interval of 1.15 cM. Quantitative trait loci (QTLs) survey based on three rounds of clubroot resistance tests using F_2:3 progenies revealed two and single major QTLs for Race 2 and Race 9 of P. brassicae, respectively. The QTLs show similar locations to the previously reported CR loci for Race 4 in B. oleracea but are in different positions from any of the CR loci found in B. rapa. We utilized two reference genome sequences in this study. The high-resolution genetic map developed herein allowed us to reposition 37 and 2 misanchored scaffolds in the 02–12 and TO1000DH genome sequences, respectively. Our data also support additional positioning of two unanchored 3.3 Mb scaffolds into the 02–12 genome sequence.

Application of Population Sequencing (POPSEQ) for Ordering and Imputing Genotyping-by-Sequencing Markers in Hexaploid Wheat

The advancement of next-generation sequencing technologies in conjunction with new bioinformatics tools enabled fine-tuning of sequence-based, high-resolution mapping strategies for complex genomes. Although genotyping-by-sequencing (GBS) provides a large number of markers, its application for association mapping and genomics-assisted breeding is limited by a large proportion of missing data per marker. For species with a reference genomic sequence, markers can be ordered on the physical map. However, in the absence of reference marker order, the use and imputation of GBS markers is challenging. Here, we demonstrate how the population sequencing (POPSEQ) approach can be used to provide marker context for GBS in wheat. The utility of a POPSEQ-based genetic map as a reference map to create genetically ordered markers on a chromosome for hexaploid wheat was validated by constructing an independent de novo linkage map of GBS markers from a Synthetic W7984 × Opata M85 recombinant inbred line (SynOpRIL) population. The results indicated that there is strong agreement between the independent de novo linkage map and the POPSEQ mapping approach in mapping and ordering GBS markers for hexaploid wheat. After ordering, a large number of GBS markers were imputed, thus providing a high-quality reference map that can be used for QTL mapping for different traits. The POPSEQ-based reference map and whole-genome sequence assemblies are valuable resources that can be used to order GBS markers and enable the application of highly accurate imputation methods to leverage the application GBS markers in wheat.

Physical Mapping of Bread Wheat Chromosome 5A: An Integrated Approach

The huge size, redundancy, and highly repetitive nature of the bread wheat [Triticum aestivum (L.)] genome, makes it among the most difficult species to be sequenced. To overcome these limitations, a strategy based on the separation of individual chromosomes or chromosome arms and the subsequent production of physical maps was established within the frame of the International Wheat Genome Sequence Consortium (IWGSC). A total of 95,812 bacterial artificial chromosome (BAC) clones of short-arm chromosome 5A (5AS) and long-arm chromosome 5A (5AL) arm-specific BAC libraries were fingerprinted and assembled into contigs by complementary analytical approaches based on the FingerPrinted Contig (FPC) and Linear Topological Contig (LTC) tools. Combined anchoring approaches based on polymerase chain reaction (PCR) marker screening, microarray, and sequence homology searches applied to several genomic tools (i.e., genetic maps, deletion bin map, neighbor maps, BAC end sequences (BESs), genome zipper, and chromosome survey sequences) allowed the development of a high-quality physical map with an anchored physical coverage of 75% for 5AS and 53% for 5AL with high portions (64 and 48%, respectively) of contigs ordered along the chromosome. In the genome of grasses, Brachypodium [Brachypodium distachyon (L.) Beauv.], rice (Oryza sativa L.), and sorghum [Sorghum bicolor (L.) Moench] homologs of genes on wheat chromosome 5A were separated into syntenic blocks on different chromosomes as a result of translocations and inversions during evolution. The physical map presented represents an essential resource for fine genetic mapping and map-based cloning of agronomically relevant traits and a reference for the 5A sequencing projects.

Point Mutations in Centromeric Histone Induce Post-zygotic Incompatibility and Uniparental Inheritance

The centromeric histone 3 variant (CENH3, aka CENP-A) is essential for the segregation of sister chromatids during mitosis and meiosis. To better define CENH3 functional constraints, we complemented a null allele in Arabidopsis with a variety of mutant alleles, each inducing a single amino acid change in conserved residues of the histone fold domain. Many of these transgenic missense lines displayed wild-type growth and fertility on self-pollination, but exhibited frequent post-zygotic death and uniparental inheritance when crossed with wild-type plants. The failure of centromeres marked by these missense mutation in the histone fold domain of CENH3 reproduces the genome elimination syndromes described with chimeric CENH3 and CENH3 from diverged species. Additionally, evidence that a single point mutation is sufficient to generate a haploid inducer provide a simple one-step method for the identification of non-transgenic haploid inducers in existing mutagenized collections of crop species. As proof of the extreme simplicity of this approach to create haploid-inducing lines, we performed an in silico search for previously identified point mutations in CENH3 and identified an Arabidopsis line carrying the A86V substitution within the histone fold domain. This A87V non-transgenic line, while fully fertile on self-pollination, produced postzygotic death and uniparental haploids when crossed to wild type.

The centromeric histone protein, CENH3, plays an important role in chromosome segregation during mitosis and meiosis. Here we show that single amino acid changes in CENH3, while producing no obvious effect on mitosis or meiosis, affect segregation postzygotically upon outcrossing to plants carrying wild-type centromeres. This results in uniparental inheritance among some progeny, and seed death in a larger fraction of progeny. Interestingly, changes competent to induce haploid in Arabidopsis existed in a TILLING population and in unrelated plant species. Our findings have two major consequences. First, uniparental inheritance facilitates the production of haploid plants that can easily be doubled to produce completely homozygous lines in a single generation. Secondly, our findings suggest that natural variation in CENH3 may result in partial reproductive isolation, because chromosomes of the mutant parent from F1 hybrid progeny are culled during embryonic development, while no reproductive defects are observed in self-pollinated plants. We do not know if the same mutations are haploid-inducing in other species, but uniparental chromosome loss, and the seed abortion that accompanies it results in an outcrossing-specific penalty that could potentially be involved in reproductive isolation.

Reveel: large-scale population genotyping using low-coverage sequencing data

MOTIVATION

Population low-coverage whole-genome sequencing is rapidly emerging as a prominent approach for discovering genomic variation and genotyping a cohort. This approach combines substantially lower cost than full-coverage sequencing with whole-genome discovery of low-allele frequency variants, to an extent that is not possible with array genotyping or exome sequencing. However, a challenging computational problem arises of jointly discovering variants and genotyping the entire cohort. Variant discovery and genotyping are relatively straightforward tasks on a single individual that has been sequenced at high coverage, because the inference decomposes into the independent genotyping of each genomic position for which a sufficient number of confidently mapped reads are available. However, in low-coverage population sequencing, the joint inference requires leveraging the complex linkage disequilibrium (LD) patterns in the cohort to compensate for sparse and missing data in each individual. The potentially massive computation time for such inference, as well as the missing data that confound low-frequency allele discovery, need to be overcome for this approach to become practical.

RESULTS

Here, we present Reveel, a novel method for single nucleotide variant calling and genotyping of large cohorts that have been sequenced at low coverage. Reveel introduces a novel technique for leveraging LD that deviates from previous Markov-based models, and which is aimed at computational efficiency as well as accuracy in capturing LD patterns present in rare haplotypes. We evaluate Reveel's performance through extensive simulations as well as real data from the 1000 Genomes Project, and show that it achieves higher accuracy in low-frequency allele discovery and substantially lower computation cost than previous state-of-the-art methods.

AVAILABILITY AND IMPLEMENTATION

http://reveel.stanford.edu/

CONTACT

: serafim@cs.stanford.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Application of whole genome re-sequencing data in the development of diagnostic DNA markers tightly linked to a disease-resistance locus for marker-assisted selection in lupin (Lupinus angustifolius)

BACKGROUND

Molecular marker-assisted breeding provides an efficient tool to develop improved crop varieties. A major challenge for the broad application of markers in marker-assisted selection is that the marker phenotypes must match plant phenotypes in a wide range of breeding germplasm. In this study, we used the legume crop species Lupinus angustifolius (lupin) to demonstrate the utility of whole genome sequencing and re-sequencing on the development of diagnostic markers for molecular plant breeding.

RESULTS

Nine lupin cultivars released in Australia from 1973 to 2007 were subjected to whole genome re-sequencing. The re-sequencing data together with the reference genome sequence data were used in marker development, which revealed 180,596 to 795,735 SNP markers from pairwise comparisons among the cultivars. A total of 207,887 markers were anchored on the lupin genetic linkage map. Marker mining obtained an average of 387 SNP markers and 87 InDel markers for each of the 24 genome sequence assembly scaffolds bearing markers linked to 11 genes of agronomic interest. Using the R gene PhtjR conferring resistance to phomopsis stem blight disease as a test case, we discovered 17 candidate diagnostic markers by genotyping and selecting markers on a genetic linkage map. A further 243 candidate diagnostic markers were discovered by marker mining on a scaffold bearing non-diagnostic markers linked to the PhtjR gene. Nine out from the ten tested candidate diagnostic markers were confirmed as truly diagnostic on a broad range of commercial cultivars. Markers developed using these strategies meet the requirements for broad application in molecular plant breeding.

CONCLUSIONS

We demonstrated that low-cost genome sequencing and re-sequencing data were sufficient and very effective in the development of diagnostic markers for marker-assisted selection. The strategies used in this study may be applied to any trait or plant species. Whole genome sequencing and re-sequencing provides a powerful tool to overcome current limitations in molecular plant breeding, which will enable plant breeders to precisely pyramid favourable genes to develop super crop varieties to meet future food demands.

Single Nucleotide Polymorphism Identification in Polyploids: A Review, Example, and Recommendations

Understanding the relationship between genotype and phenotype is a major biological question and being able to predict phenotypes based on molecular genotypes is integral to molecular breeding. Whole-genome duplications have shaped the history of all flowering plants and present challenges to elucidating the relationship between genotype and phenotype, especially in neopolyploid species. Although single nucleotide polymorphisms (SNPs) have become popular tools for genetic mapping, discovery and application of SNPs in polyploids has been difficult. Here, we summarize common experimental approaches to SNP calling, highlighting recent polyploid successes. To examine the impact of software choice on these analyses, we called SNPs among five peanut genotypes using different alignment programs (BWA-mem and Bowtie 2) and variant callers (SAMtools, GATK, and Freebayes). Alignments produced by Bowtie 2 and BWA-mem and analyzed in SAMtools shared 24.5% concordant SNPs, and SAMtools, GATK, and Freebayes shared 1.4% concordant SNPs. A subsequent analysis of simulated Brassica napus chromosome 1A and 1C genotypes demonstrated that, of the three software programs, SAMtools performed with the highest sensitivity and specificity on Bowtie 2 alignments. These results, however, are likely to vary among species, and we therefore propose a series of best practices for SNP calling in polyploids.

Getting the 'MOST' out of crop improvement

Unraveling the function of genes affecting agronomic traits is accelerating due to progress in DNA sequencing and other high-throughput genomic approaches. Characterized genes can be exploited by plant breeders by using either marker-aided selection (MAS) or transgenic procedures. Here, we propose a third 'outlet', 'molecular strengthening' (MOST), as alternative option for exploiting detailed molecular understanding of trait expression, which is comparable to the pharmaceutical treatment of human diseases. MOST treatments can be used to enhance yield stability. Alternatively, they can be used to control traits temporally, such as flowering time to facilitate crosses for plant breeders. We also discuss the essence for developing MOST treatments, their prospects, and limitations.

Decoding the oak genome: public release of sequence data, assembly, annotation and publication strategies

The 1.5 Gbp/2C genome of pedunculate oak (Quercus robur) has been sequenced. A strategy was established for dealing with the challenges imposed by the sequencing of such a large, complex and highly heterozygous genome by a whole-genome shotgun (WGS) approach, without the use of costly and time-consuming methods, such as fosmid or BAC clone-based hierarchical sequencing methods. The sequencing strategy combined short and long reads. Over 49 million reads provided by Roche 454 GS-FLX technology were assembled into contigs and combined with shorter Illumina sequence reads from paired-end and mate-pair libraries of different insert sizes, to build scaffolds. Errors were corrected and gaps filled with Illumina paired-end reads and contaminants detected, resulting in a total of 17,910 scaffolds (>2 kb) corresponding to 1.34 Gb. Fifty per cent of the assembly was accounted for by 1468 scaffolds (N50 of 260 kb). Initial comparison with the phylogenetically related Prunus persica gene model indicated that genes for 84.6% of the proteins present in peach (mean protein coverage of 90.5%) were present in our assembly. The second and third steps in this project are genome annotation and the assignment of scaffolds to the oak genetic linkage map. In accordance with the Bermuda and Fort Lauderdale agreements and the more recent Toronto Statement, the oak genome data have been released into public sequence repositories in advance of publication. In this presubmission paper, the oak genome consortium describes its principal lines of work and future directions for analyses of the nature, function and evolution of the oak genome.

Transcriptomic analysis of wheat near-isogenic lines identifies PM19-A1 and A2 as candidates for a major dormancy QTL

BACKGROUND

Next-generation sequencing technologies provide new opportunities to identify the genetic components responsible for trait variation. However, in species with large polyploid genomes, such as bread wheat, the ability to rapidly identify genes underlying quantitative trait loci (QTL) remains non-trivial. To overcome this, we introduce a novel pipeline that analyses, by RNA-sequencing, multiple near-isogenic lines segregating for a targeted QTL.

RESULTS

We use this approach to characterize a major and widely utilized seed dormancy QTL located on chromosome 4AL. It exploits the power and mapping resolution afforded by large multi-parent mapping populations, whilst reducing complexity by using multi-allelic contrasts at the targeted QTL region. Our approach identifies two adjacent candidate genes within the QTL region belonging to the ABA-induced Wheat Plasma Membrane 19 family. One of them, PM19-A1, is highly expressed during grain maturation in dormant genotypes. The second, PM19-A2, shows changes in sequence causing several amino acid alterations between dormant and non-dormant genotypes. We confirm that PM19 genes are positive regulators of seed dormancy.

CONCLUSIONS

The efficient identification of these strong candidates demonstrates the utility of our transcriptomic pipeline for rapid QTL to gene mapping. By using this approach we are able to provide a comprehensive genetic analysis of the major source of grain dormancy in wheat. Further analysis across a diverse panel of bread and durum wheats indicates that this important dormancy QTL predates hexaploid wheat. The use of these genes by wheat breeders could assist in the elimination of pre-harvest sprouting in wheat.

Sequencing consolidates molecular markers with plant breeding practice

Plenty of molecular markers have been developed by contemporary sequencing technologies, whereas few of them are successfully applied in breeding, thus we present a review on how sequencing can facilitate marker-assisted selection in plant breeding. The growing global population and shrinking arable land area require efficient plant breeding. Novel strategies assisted by certain markers have proven effective for genetic gains. Fortunately, cutting-edge sequencing technologies bring us a deluge of genomes and genetic variations, enlightening the potential of marker development. However, a large gap still exists between the potential of molecular markers and actual plant breeding practices. In this review, we discuss marker-assisted breeding from a historical perspective, describe the road from crop sequencing to breeding, and highlight how sequencing facilitates the application of markers in breeding practice.

High-throughput physical map anchoring via BAC-pool sequencing

BACKGROUND

Physical maps created from large insert DNA libraries, typically cloned in BAC vector, are valuable resources for map-based cloning and de novo genome sequencing. The maps are most useful if contigs of overlapping DNA clones are anchored to chromosome(s), and ordered along them using molecular markers. Here we present a novel approach for anchoring physical maps, based on sequencing three-dimensional pools of BAC clones from minimum tilling path.

RESULTS

We used physical map of wheat chromosome arm 3DS to validate the method with two different DNA sequence datasets. The first comprised 567 genes ordered along the chromosome arm based on syntenic relationship of wheat with the sequenced genomes of Brachypodium, rice and sorghum. The second dataset consisted of 7,136 SNP-containing sequences, which were mapped genetically in Aegilops tauschii, the donor of the wheat D genome. Mapping of sequence reads from individual BAC pools to the first and the second datasets enabled unambiguous anchoring 447 and 311 3DS-specific sequences, respectively, or 758 in total.

CONCLUSIONS

We demonstrate the utility of the novel approach for BAC contig anchoring based on mass parallel sequencing of three-dimensional pools prepared from minimum tilling path of physical map. The existing genetic markers as well as any other DNA sequence could be mapped to BAC clones in a single in silico experiment. The approach reduces significantly the cost and time needed for anchoring and is applicable to any genomic project involving the construction of anchored physical map.

New insights into the wheat chromosome 4D structure and virtual gene order, revealed by survey pyrosequencing

Survey sequencing of the bread wheat (Triticum aestivum L.) genome (AABBDD) has been approached through different strategies delivering important information. However, the current wheat sequence knowledge is not complete. The aim of our study is to provide different and complementary set of data for chromosome 4D. A survey sequence was obtained by pyrosequencing of flow-sorted 4DS (7.2×) and 4DL (4.1×) arms. Single ends (SE) and long mate pairs (LMP) reads were assembled into contigs (223Mb) and scaffolds (65Mb) that were aligned to Aegilops tauschii draft genome (DD), anchoring 34Mb to chromosome 4. Scaffolds annotation rendered 822 gene models. A virtual gene order comprising 1973 wheat orthologous gene loci and 381 wheat gene models was built. This order was largely consistent with the scaffold order determined based on a published high density map from the Ae. tauschii chromosome 4, using bin-mapped 4D ESTs as a common reference. The virtual order showed a higher collinearity with homeologous 4B compared to 4A. Additionally, a virtual map was constructed and ∼5700 genes (∼2200 on 4DS and ∼3500 on 4DL) predicted. The sequence and virtual order obtained here using the 454 platform were compared with the Illumina one used by the IWGSC, giving complementary information.

Networks controlling seed size in Arabidopsis

Key message: Overview of seed size control. Human and livestock nutrition is largely based on calories derived from seeds, in particular cereals and legumes. Unveiling the control of seed size is therefore of remarkable importance in the frame of developing new strategies for crop improvement. The networks controlling the development of the seed coat, the endosperm and the embryo, as well as their interplay, have been described in Arabidopsis thaliana. In this review, we provide a comprehensive description of the current knowledge regarding the molecular mechanisms controlling seed size in Arabidopsis.

A whole-genome shotgun approach for assembling and anchoring the hexaploid bread wheat genome

Polyploid species have long been thought to be recalcitrant to whole-genome assembly. By combining high-throughput sequencing, recent developments in parallel computing, and genetic mapping, we derive, de novo, a sequence assembly representing 9.1 Gbp of the highly repetitive 16 Gbp genome of hexaploid wheat, Triticum aestivum, and assign 7.1 Gb of this assembly to chromosomal locations. The genome representation and accuracy of our assembly is comparable or even exceeds that of a chromosome-by-chromosome shotgun assembly. Our assembly and mapping strategy uses only short read sequencing technology and is applicable to any species where it is possible to construct a mapping population.

A whole-genome shotgun approach for assembling and anchoring the hexaploid bread wheat genome

Polyploid species have long been thought to be recalcitrant to whole-genome assembly. By combining high-throughput sequencing, recent developments in parallel computing, and genetic mapping, we derive, de novo, a sequence assembly representing 9.1 Gbp of the highly repetitive 16 Gbp genome of hexaploid wheat, Triticum aestivum, and assign 7.1 Gb of this assembly to chromosomal locations. The genome representation and accuracy of our assembly is comparable or even exceeds that of a chromosome-by-chromosome shotgun assembly. Our assembly and mapping strategy uses only short read sequencing technology and is applicable to any species where it is possible to construct a mapping population.

Next Generation Sequencing Technologies: The Doorway to the Unexplored Genomics of Non-Model Plants

Non-model plants i.e., the species which have one or all of the characters such as long life cycle, difficulty to grow in the laboratory or poor fecundity, have been schemed out of sequencing projects earlier, due to high running cost of Sanger sequencing. Consequently, the information about their genomics and key biological processes are inadequate. However, the advent of fast and cost effective next generation sequencing (NGS) platforms in the recent past has enabled the unearthing of certain characteristic gene structures unique to these species. It has also aided in gaining insight about mechanisms underlying processes of gene expression and secondary metabolism as well as facilitated development of genomic resources for diversity characterization, evolutionary analysis and marker assisted breeding even without prior availability of genomic sequence information. In this review we explore how different Next Gen Sequencing platforms, as well as recent advances in NGS based high throughput genotyping technologies are rewarding efforts on de-novo whole genome/transcriptome sequencing, development of genome wide sequence based markers resources for improvement of non-model crops that are less costly than phenotyping.