Improvements in Genomic Technologies: Application to Crop Genomics

Glutaredoxin regulation of primary root growth is associated with early drought stress tolerance in pearl millet

Seedling root traits impact plant establishment under challenging environments. Pearl millet is one of the most heat and drought tolerant cereal crops that provides a vital food source across the sub-Saharan Sahel region. Pearl millet's early root system features a single fast-growing primary root which we hypothesize is an adaptation to the Sahelian climate. Using crop modeling, we demonstrate that early drought stress is an important constraint in agrosystems in the Sahel where pearl millet was domesticated. Furthermore, we show that increased pearl millet primary root growth is correlated with increased early water stress tolerance in field conditions. Genetics including genome-wide association study and quantitative trait loci (QTL) approaches identify genomic regions controlling this key root trait. Combining gene expression data, re-sequencing and re-annotation of one of these genomic regions identified a glutaredoxin-encoding gene PgGRXC9 as the candidate stress resilience root growth regulator. Functional characterization of its closest Arabidopsis homolog AtROXY19 revealed a novel role for this glutaredoxin (GRX) gene clade in regulating cell elongation. In summary, our study suggests a conserved function for GRX genes in conferring root cell elongation and enhancing resilience of pearl millet to its Sahelian environment.

De novo assembly and annotation of the singing mouse genome

BACKGROUND

Developing genomic resources for a diverse range of species is an important step towards understanding the mechanisms underlying complex traits. Specifically, organisms that exhibit unique and accessible phenotypes-of-interest allow researchers to address questions that may be ill-suited to traditional model organisms. We sequenced the genome and transcriptome of Alston's singing mouse (Scotinomys teguina), an emerging model for social cognition and vocal communication. In addition to producing advertisement songs used for mate attraction and male-male competition, these rodents are diurnal, live at high-altitudes, and are obligate insectivores, providing opportunities to explore diverse physiological, ecological, and evolutionary questions.

RESULTS

Using PromethION, Illumina, and PacBio sequencing, we produced an annotated genome and transcriptome, which were validated using gene expression and functional enrichment analyses. To assess the usefulness of our assemblies, we performed single nuclei sequencing on cells of the orofacial motor cortex, a brain region implicated in song coordination, identifying 12 cell types.

CONCLUSIONS

These resources will provide the opportunity to identify the molecular basis of complex traits in singing mice as well as to contribute data that can be used for large-scale comparative analyses.

Genomic prediction for complex traits across multiples harvests in alfalfa (Medicago sativa L.) is enhanced by enviromics

Breeding for dry matter yield and persistence in alfalfa (Medicago sativa L.) can take several years as these traits must be evaluated under multiple harvests. Therefore, genotype-by-harvest interaction should be incorporated into genomic prediction models to explore genotypes' adaptability and stability. In this study, we investigated how enviromics could help to predict the genotypic performance under multiharvest alfalfa breeding trials by evaluating 177 families across 11 harvests under four cross-validation scenarios. All scenarios were analyzed using six models in a Bayesian mixed model framework. Our results demonstrate that models accounting to the enviromics information led to an increase of genetic variance and a decrease in the error variance, indicating better biological explanation when the enviromic information was incorporated. Furthermore, models that accounted for enviromic data led to higher predictive ability (PA) in a reduced number of harvests used in the training data set. The best enviromic models (M2 and M3) outperformed the base model (GBLUP model-M0) for predicting adaptability and persistence across all cross-validation scenarios. Incorporating environmental covariates also provided higher PA for persistence compared with the base model, as predictions increased from 0 to 0.16, 0.20, 0.56, and 0.46 for CV00, CV1, CV0, and CV2. The results also demonstrate that GBLUP without enviromics term has low power to predict persistence, thus the adoption of enviromics is a cheap and efficient alternative to increase accuracy and biological meaning.

Breeding crops for drought-affected environments and improved climate resilience

Breeding climate-resilient crops with improved levels of abiotic and biotic stress resistance as a response to climate change presents both opportunities and challenges. Applying the framework of the "breeder's equation," which is used to predict the response to selection for a breeding program cycle, we review methodologies and strategies that have been used to successfully breed crops with improved levels of drought resistance, where the target population of environments (TPEs) is a spatially and temporally heterogeneous mixture of drought-affected and favorable (water-sufficient) environments. Long-term improvement of temperate maize for the US corn belt is used as a case study and compared with progress for other crops and geographies. Integration of trait information across scales, from genomes to ecosystems, is needed to accurately predict yield outcomes for genotypes within the current and future TPEs. This will require transdisciplinary teams to explore, identify, and exploit novel opportunities to accelerate breeding program outcomes; both improved germplasm resources and improved products (cultivars, hybrids, clones, and populations) that outperform and replace the products in use by farmers, in combination with modified agronomic management strategies suited to their local environments.

Detection of Transgene Location in the CYP2A13/2B6/2F1-transgenic Mouse Model using Optical Genome Mapping Technology

Most transgenic mouse models are generated through random integration of the transgene. The location of the transgene provides valuable information for assessing potential effects of the transgenesis on the host and for designing genotyping protocols that can amplify across the integration site, but it is challenging to identify. Here, we report the successful utility of optical genome mapping technology to identify the transgene insertion site in a CYP2A13/2B6/2F1-transgenic mouse model, which produces three human cytochrome P450 (P450) enzymes (CYP2A13, CYP2B6, and CYP2F1) that are encoded by neighboring genes on human chromosome 19. These enzymes metabolize many drugs, respiratory toxicants, and chemical carcinogens. Initial efforts to identify candidate insertion sites by whole genome sequencing was unsuccessful, apparently because the transgene is located in a region of the mouse genome that contains highly repetitive sequences. Subsequent utility of the optical genome mapping approach, which compares genome-wide marker distribution between the transgenic mouse genome and a reference mouse (GRCm38) or human (GRCh38) genome, localized the insertion site to mouse chromosome 14, between two marker positions at 4451324 base pair and 4485032 base pair. A transgene-mouse genome junction sequence was further identified through long-polymerase chain reaction amplification and DNA sequencing at GRCm38 Chr.14:4484726. The transgene insertion (∼2.4 megabase pair) contained 5-7 copies of the human transgenes, which replaced a 26.9-33.4 kilobase pair mouse genomic region, including exons 1-4 of Gm3182, a predicted and highly redundant gene. Finally, the sequencing results enabled the design of a new genotyping protocol that can distinguish between hemizygous and homozygous CYP2A13/2B6/2F1-transgenic mice. SIGNIFICANCE STATEMENT: This study characterizes the genomic structure of, and provides a new genotyping method for, a transgenic mouse model that expresses three human P450 enzymes, CYP2A13, CYP2B6, and CYP2F1, that are important in xenobiotic metabolism and toxicity. The demonstrated success in applying the optical genome mapping technology for identification of transgene insertion sites should encourage others to do the same for other transgenic models generated through random integration, including most of the currently available human P450 transgenic mouse models.

Improved pea reference genome and pan-genome highlight genomic features and evolutionary characteristics

Complete and accurate reference genomes and annotations provide fundamental resources for functional genomics and crop breeding. Here we report a de novo assembly and annotation of a pea cultivar ZW6 with contig N50 of 8.98 Mb, which features a 243-fold increase in contig length and evident improvements in the continuity and quality of sequence in complex repeat regions compared with the existing one. Genome diversity of 118 cultivated and wild pea demonstrated that Pisum abyssinicum is a separate species different from P. fulvum and P. sativum within Pisum. Quantitative trait locus analyses uncovered two known Mendel's genes related to stem length (Le/le) and seed shape (R/r) as well as some candidate genes for pod form studied by Mendel. A pan-genome of 116 pea accessions was constructed, and pan-genes preferred in P. abyssinicum and P. fulvum showed distinct functional enrichment, indicating the potential value of them as pea breeding resources in the future.

Applications of Optical Mapping for Plant Genome Assembly and Structural Variation Detection

Optical mapping plays an important role in plant genomics, particularly in plant genome assembly and large-scale structural variation detection. While DNA sequencing provides base-by-base nucleotide information, optical mapping shows the physical locations of selected enzyme restriction sites in a genome. The long single-molecule maps produced by optical mapping make it a useful auxiliary technique to DNA sequencing, which generally cannot span large and complex genomic regions. Although optical mapping, therefore, offers unique advantages to researchers, there are few dedicated tools to assist in optical mapping analyses. In this chapter, we present runBNG2, a successor of runBNG to help optical-mapping data analysis for diverse datasets.

Improving Bambara Groundnut Production: Insight Into the Role of Omics and Beneficial Bacteria

With the rise in the world population, environmental hazards caused by chemical fertilizers, and a decrease in food supply due to global climate change, food security has become very pertinent. In addition, considerable parts of agriculture lands have been lost to urbanization. It has therefore been projected that at the present rate of population increase coupled with the other mentioned factors, available food will not be enough to feed the world. Hence, drastic approach is needed to improve agriculture output as well as human sustainability. Application of environmentally sustainable approach, such as the use of beneficial microbes, and improved breeding of underutilized legumes are one of the proposed sustainable ways of achieving food security. Microbiome-assisted breeding in underutilized legumes is an untapped area with great capabilities to improve food security. Furthermore, revolution in genomics adaptation to crop improvement has changed the approach from conventional breeding to more advanced genomic-assisted breeding on the host plant and its microbiome. The use of rhizobacteria is very important to improving crop yield, especially rhizobacteria from legumes like Bambara groundnut (BGN). BGN is an important legume in sub-Saharan Africa with high ability to tolerate drought and thrive well in marginalized soils. BGN and its interaction with various rhizobacteria in the soil could play a vital role in crop production and protection. This review focus on the importance of genomics application to BGN and its microbiome with the view of setting a potential blueprint for improved BGN breeding through integration of beneficial bacteria.

Current status of structural variation studies in plants

Structural variations (SVs) including gene presence/absence variations and copy number variations are a common feature of genomes in plants and, together with single nucleotide polymorphisms and epigenetic differences, are responsible for the heritable phenotypic diversity observed within and between species. Understanding the contribution of SVs to plant phenotypic variation is important for plant breeders to assist in producing improved varieties. The low resolution of early genetic technologies and inefficient methods have previously limited our understanding of SVs in plants. However, with the rapid expansion in genomic technologies, it is possible to assess SVs with an ever-greater resolution and accuracy. Here, we review the current status of SV studies in plants, examine the roles that SVs play in phenotypic traits, compare current technologies and assess future challenges for SV studies.

Signal-based optical map alignment

In genomics, optical mapping technology provides long-range contiguity information to improve genome sequence assemblies and detect structural variation. Originally a laborious manual process, Bionano Genomics platforms now offer high-throughput, automated optical mapping based on chips packed with nanochannels through which unwound DNA is guided and the fluorescent DNA backbone and specific restriction sites are recorded. Although the raw image data obtained is of high quality, the processing and assembly software accompanying the platforms is closed source and does not seem to make full use of data, labeling approximately half of the measured signals as unusable. Here we introduce two new software tools, independent of Bionano Genomics software, to extract and process molecules from raw images (OptiScan) and to perform molecule-to-molecule and molecule-to-reference alignments using a novel signal-based approach (OptiMap). We demonstrate that the molecules detected by OptiScan can yield better assemblies, and that the approach taken by OptiMap results in higher use of molecules from the raw data. These tools lay the foundation for a suite of open-source methods to process and analyze high-throughput optical mapping data. The Python implementations of the OptiTools are publicly available through http://www.bif.wur.nl/.

Homeolog expression quantification methods for allopolyploids

Genome duplication with hybridization, or allopolyploidization, occurs in animals, fungi and plants, and is especially common in crop plants. There is an increasing interest in the study of allopolyploids because of advances in polyploid genome assembly; however, the high level of sequence similarity in duplicated gene copies (homeologs) poses many challenges. Here we compared standard RNA-seq expression quantification approaches used currently for diploid species against subgenome-classification approaches which maps reads to each subgenome separately. We examined mapping error using our previous and new RNA-seq data in which a subgenome is experimentally added (synthetic allotetraploid Arabidopsis kamchatica) or reduced (allohexaploid wheat Triticum aestivum versus extracted allotetraploid) as ground truth. The error rates in the two species were very similar. The standard approaches showed higher error rates (>10% using pseudo-alignment with Kallisto) while subgenome-classification approaches showed much lower error rates (<1% using EAGLE-RC, <2% using HomeoRoq). Although downstream analysis may partly mitigate mapping errors, the difference in methods was substantial in hexaploid wheat, where Kallisto appeared to have systematic differences relative to other methods. Only approximately half of the differentially expressed homeologs detected using Kallisto overlapped with those by any other method in wheat. In general, disagreement in low-expression genes was responsible for most of the discordance between methods, which is consistent with known biases in Kallisto. We also observed that there exist uncertainties in genome sequences and annotation which can affect each method differently. Overall, subgenome-classification approaches tend to perform better than standard approaches with EAGLE-RC having the highest precision.

Recent advances in Cannabis sativa genomics research

Cannabis (Cannabis sativa L.) is one of the oldest cultivated plants purported to have unique medicinal properties. However, scientific research of cannabis has been restricted by the Single Convention on Narcotic Drugs of 1961, an international treaty that prohibits the production and supply of narcotic drugs except under license. Legislation governing cannabis cultivation for research, medicinal and even recreational purposes has been relaxed recently in certain jurisdictions. As a result, there is now potential to accelerate cultivar development of this multi-use and potentially medically useful plant species by application of modern genomics technologies. Whilst genomics has been pivotal to our understanding of the basic biology and molecular mechanisms controlling key traits in several crop species, much work is needed for cannabis. In this review we provide a comprehensive summary of key cannabis genomics resources and their applications. We also discuss prospective applications of existing and emerging genomics technologies for accelerating the genetic improvement of cannabis.

Can We Harness "Enviromics" to Accelerate Crop Improvement by Integrating Breeding and Agronomy?

The diverse consequences of genotype-by-environment (GxE) interactions determine trait phenotypes across levels of biological organization for crops, challenging our ambition to predict trait phenotypes from genomic information alone. GxE interactions have many implications for optimizing both genetic gain through plant breeding and crop productivity through on-farm agronomic management. Advances in genomics technologies have provided many suitable predictors for the genotype dimension of GxE interactions. Emerging advances in high-throughput proximal and remote sensor technologies have stimulated the development of "enviromics" as a community of practice, which has the potential to provide suitable predictors for the environment dimension of GxE interactions. Recently, several bespoke examples have emerged demonstrating the nascent potential for enhancing the prediction of yield and other complex trait phenotypes of crop plants through including effects of GxE interactions within prediction models. These encouraging results motivate the development of new prediction methods to accelerate crop improvement. If we can automate methods to identify and harness suitable sets of coordinated genotypic and environmental predictors, this will open new opportunities to upscale and operationalize prediction of the consequences of GxE interactions. This would provide a foundation for accelerating crop improvement through integrating the contributions of both breeding and agronomy. Here we draw on our experience from improvement of maize productivity for the range of water-driven environments across the US corn-belt. We provide perspectives from the maize case study to prioritize promising opportunities to further develop and automate "enviromics" methodologies to accelerate crop improvement through integrated breeding and agronomic approaches for a wider range of crops and environmental targets.

Next Generation Sequencing Based Forward Genetic Approaches for Identification and Mapping of Causal Mutations in Crop Plants: A Comprehensive Review

The recent advancements in forward genetics have expanded the applications of mutation techniques in advanced genetics and genomics, ahead of direct use in breeding programs. The advent of next-generation sequencing (NGS) has enabled easy identification and mapping of causal mutations within a short period and at relatively low cost. Identifying the genetic mutations and genes that underlie phenotypic changes is essential for understanding a wide variety of biological functions. To accelerate the mutation mapping for crop improvement, several high-throughput and novel NGS based forward genetic approaches have been developed and applied in various crops. These techniques are highly efficient in crop plants, as it is relatively easy to grow and screen thousands of individuals. These approaches have improved the resolution in quantitative trait loci (QTL) position/point mutations and assisted in determining the functional causative variations in genes. To be successful in the interpretation of NGS data, bioinformatics computational methods are critical elements in delivering accurate assembly, alignment, and variant detection. Numerous bioinformatics tools/pipelines have been developed for such analysis. This article intends to review the recent advances in NGS based forward genetic approaches to identify and map the causal mutations in the crop genomes. The article also highlights the available bioinformatics tools/pipelines for reducing the complexity of NGS data and delivering the concluding outcomes.

Homoeologous Exchanges, Segmental Allopolyploidy, and Polyploid Genome Evolution

Polyploidy is a major force in plant evolution and speciation. In newly formed allopolyploids, pairing between related chromosomes from different subgenomes (homoeologous chromosomes) during meiosis is common. The initial stages of allopolyploid formation are characterized by a spectrum of saltational genomic and regulatory alterations that are responsible for evolutionary novelty. Here we highlight the possible effects and roles of recombination between homoeologous chromosomes during the early stages of allopolyploid stabilization. Homoeologous exchanges (HEs) have been reported in young allopolyploids from across the angiosperms. Although all lineages undergo karyotype change via chromosome rearrangements over time, the early generations after allopolyploid formation are predicted to show an accelerated rate of genomic change. HEs can also cause changes in allele dosage, genome-wide methylation patterns, and downstream phenotypes, and can hence be responsible for speciation and genome stabilization events. Additionally, we propose that fixation of duplication - deletion events resulting from HEs could lead to the production of genomes which appear to be a mix of autopolyploid and allopolyploid segments, sometimes termed "segmental allopolyploids." We discuss the implications of these findings for our understanding of the relationship between genome instability in novel polyploids and genome evolution.

Advances in optical mapping for genomic research

Recent advances in optical mapping have allowed the construction of improved genome assemblies with greater contiguity. Optical mapping also enables genome comparison and identification of large-scale structural variations. Association of these large-scale genomic features with biological functions is an important goal in plant and animal breeding and in medical research. Optical mapping has also been used in microbiology and still plays an important role in strain typing and epidemiological studies. Here, we review the development of optical mapping in recent decades to illustrate its importance in genomic research. We detail its applications and algorithms to show its specific advantages. Finally, we discuss the challenges required to facilitate the optimization of optical mapping and improve its future development and application.

One fly-one genome: chromosome-scale genome assembly of a single outbred Drosophila melanogaster

A high quality genome assembly is a vital first step for the study of an organism. Recent advances in technology have made the creation of high quality chromosome scale assemblies feasible and low cost. However, the amount of input DNA needed for an assembly project can be a limiting factor for small organisms or precious samples. Here we demonstrate the feasibility of creating a chromosome scale assembly using a hybrid method for a low input sample, a single outbred Drosophila melanogaster. Our approach combines an Illumina shotgun library, Oxford nanopore long reads, and chromosome conformation capture for long range scaffolding. This single fly genome assembly has a N50 of 26 Mb, a length that encompasses entire chromosome arms, contains 95% of expected single copy orthologs, and a nearly complete assembly of this individual's Wolbachia endosymbiont. The methods described here enable the accurate and complete assembly of genomes from small, field collected organisms as well as precious clinical samples.

Comparative analyses of 32 complete plastomes of Tef (Eragrostis tef ) accessions from Ethiopia: phylogenetic relationships and mutational hotspots

Eragrostis tef is an important cereal crop in Ethiopia with excellent storage properties, high–quality food, and the unique ability to thrive in extreme environmental conditions. However, the application of advanced molecular tools for breeding and conservation of these species is extremely limited. Therefore, developing chloroplast genome resources and high-resolution molecular markers are valuable to E. tef population and biogeographic studies. In the current study, we assembled and compared the complete plastomes of 32 E. tef accessions. The size of the plastomes ranged from 134,349 to 134,437 bp with similar GC content (∼38.3%). Genomes annotations revealed 112 individual genes, including 77 protein-coding, 31 tRNA, and 4 rRNA genes. Comparison of E. tef plastomes revealed a low degree of intraspecific sequence variations and no structural differentiations. Furthermore, we found 34 polymorphic sites (13 cpSSRs, 12 InDels, and 9 SNPs) that can be used as valuable DNA barcodes. Among them, the majority (88%) of the polymorphic sites were identified in the noncoding genomic regions. Nonsynonymous (ka) and synonymous (ks) substitution analysis showed that all PCGs were under purifying selection (ka/ks <1). The phylogenetic analyses of the whole plastomes and polymorphic region sequences were able to distinguish the accession from the southern population, indicating its potential to be used as a super-barcode. In conclusion, the newly generated plastomes and polymorphic markers developed here could be a useful genomic resource in molecular breeding, population genetics and the biogeographical study of E. tef.

MapOptics: a light-weight, cross-platform visualization tool for optical mapping alignment

SUMMARY

Bionano optical mapping is a technology that can assist in the final stages of genome assembly by lengthening and ordering scaffolds in a draft assembly by aligning the assembly to a genomic map. However, currently, tools for visualization are limited to use on a Windows operating system or are developed initially for visualizing large-scale structural variation. MapOptics is a lightweight cross-platform tool that enables the user to visualize and interact with the alignment of Bionano optical mapping data and can be used for in depth exploration of hybrid scaffolding alignments. It provides a fast, simple alternative to the large optical mapping analysis programs currently available for this area of research.

AVAILABILITY AND IMPLEMENTATION

MapOptics is implemented in Java 1.8 and released under an MIT licence. MapOptics can be downloaded from https://github.com/FadyMohareb/mapoptics and run on any standard desktop computer equipped with a Java Virtual Machine (JVM).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Miniature inverted-repeat transposable elements (MITEs), derived insertional polymorphism as a tool of marker systems for molecular plant breeding

Plant molecular breeding is expected to give significant gains in cultivar development through development and utilization of suitable molecular marker systems for genetic diversity analysis, rapid DNA fingerprinting, identification of true hybrids, trait mapping and marker-assisted selection. Transposable elements (TEs) are the most abundant component in a genome and being used as genetic markers in the plant molecular breeding. Here, we review on the high copious transposable element belonging to class-II DNA TEs called "miniature inverted-repeat transposable elements" (MITEs). MITEs are ubiquitous, short and non-autonomous DNA transposable elements which have a tendency to insert into genes and genic regions have paved a way for the development of functional DNA marker systems in plant genomes. This review summarises the characteristics of MITEs, principles and methodologies for development of MITEs based DNA markers, bioinformatics tools and resources for plant MITE discovery and their utilization in crop improvement.

Opportunities and challenges in long-read sequencing data analysis

Long-read technologies are overcoming early limitations in accuracy and throughput, broadening their application domains in genomics. Dedicated analysis tools that take into account the characteristics of long-read data are thus required, but the fast pace of development of such tools can be overwhelming. To assist in the design and analysis of long-read sequencing projects, we review the current landscape of available tools and present an online interactive database, long-read-tools.org, to facilitate their browsing. We further focus on the principles of error correction, base modification detection, and long-read transcriptomics analysis and highlight the challenges that remain.

Super-Pangenome by Integrating the Wild Side of a Species for Accelerated Crop Improvement

The pangenome provides genomic variations in the cultivated gene pool for a given species. However, as the crop's gene pool comprises many species, especially wild relatives with diverse genetic stock, here we suggest using accessions from all available species of a given genus for the development of a more comprehensive and complete pangenome, which we refer to as a super-pangenome. The super-pangenome provides a complete genomic variation repertoire of a genus and offers unprecedented opportunities for crop improvement. This opinion article focuses on recent developments in crop pangenomics, the need for a super-pangenome that should include wild species, and its application for crop improvement.

Long-read sequencing in deciphering human genetics to a greater depth

Through four decades' development, DNA sequencing has inched into the era of single-molecule sequencing (SMS), or the third-generation sequencing (TGS), as represented by two distinct technical approaches developed independently by Pacific Bioscience (PacBio) and Oxford Nanopore Technologies (ONT). Historically, each generation of sequencing technologies was marked by innovative technological achievements and novel applications. Long reads (LRs) are considered as the most advantageous feature of SMS shared by both PacBio and ONT to distinguish SMS from next-generation sequencing (NGS, or the second-generation sequencing) and Sanger sequencing (the first-generation sequencing). Long reads overcome the limitations of NGS and drastically improves the quality of genome assembly. Besides, ONT also contributes several unique features including ultra-long reads (ULRs) with read length above 300 kb and some close to 1 million bp, direct RNA sequencing and superior portability as made possible by pocket-sized MinION sequencer. Here, we review the history of DNA sequencing technologies and associated applications, with a special focus on the advantages as well as the limitations of ULR sequencing in genome assembly.

Tools and Strategies for Long-Read Sequencing and De Novo Assembly of Plant Genomes

The commercial release of third-generation sequencing technologies (TGSTs), giving long and ultra-long sequencing reads, has stimulated the development of new tools for assembling highly contiguous genome sequences with unprecedented accuracy across complex repeat regions. We survey here a wide range of emerging sequencing platforms and analytical tools for de novo assembly, provide background information for each of their steps, and discuss the spectrum of available options. Our decision tree recommends workflows for the generation of a high-quality genome assembly when used in combination with the specific needs and resources of a project.

Modern technologies and algorithms for scaffolding assembled genomes

The computational reconstruction of genome sequences from shotgun sequencing data has been greatly simplified by the advent of sequencing technologies that generate long reads. In the case of relatively small genomes (e.g., bacterial or viral), complete genome sequences can frequently be reconstructed computationally without the need for further experiments. However, large and complex genomes, such as those of most animals and plants, continue to pose significant challenges. In such genomes, assembly software produces incomplete and fragmented reconstructions that require additional experimentally derived information and manual intervention in order to reconstruct individual chromosome arms. Recent technologies originally designed to capture chromatin structure have been shown to effectively complement sequencing data, leading to much more contiguous reconstructions of genomes than previously possible. Here, we survey these technologies and the algorithms used to assemble and analyze large eukaryotic genomes, placed within the historical context of genome scaffolding technologies that have been in existence since the dawn of the genomic era.

Necrotrophic Exploitation and Subversion of Plant Defense: A Lifestyle or Just a Phase, and Implications in Breeding Resistance

Breeding disease-resistant plants is a critical, environmentally friendly component of any strategy to sustainably feed and clothe the 9.8 billion people expected to live on Earth by 2050. Here, I review current literature detailing plant defense responses as they relate to diverse biological outcomes; disease resistance, susceptibility, and establishment of mutualistic plant-microbial relationships. Of particular interest is the degree to which these outcomes are a function of plant-associated microorganisms' lifestyles; biotrophic, hemibiotrophic, necrotrophic, or mutualistic. For the sake of brevity, necrotrophic pathogens and the necrotrophic phase of pathogenicity are emphasized in this review, with special attention given to the host-specific pathogens that exploit defense. Defense responses related to generalist necrotrophs and mutualists are discussed in the context of excellent reviews by others. In addition, host evolutionary trade-offs of disease resistance with other desirable traits are considered in the context of breeding for durable disease resistance.

Next-Generation Sequencing Accelerates Crop Gene Discovery

The identification and isolation of genes underlying quantitative trait loci (QTLs) associated with agronomic traits in crops have been recently accelerated thanks to next-generation sequencing (NGS)-based technologies combined with plant genetics. With NGS, various revisited genetic approaches, which benefited from higher marker density, have been elaborated. These approaches improved resolution in QTL position and assisted in determining functional causative variations in genes. Examples of QTLs/genes associated with agronomic traits in crops and identified using different strategies based on whole-genome sequencing (WGS)/whole-genome resequencing (WGR) or RNA-seq are presented and discussed in this review. More specifically, we summarize and illustrate how NGS boosted bulk-segregant analysis (BSA), expression profiling, and the construction of polymorphism databases to facilitate the detection of QTLs and causative genes.

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.

Bottlenecks for genome-edited crops on the road from lab to farm

Gene discovery and government regulation are bottlenecks for the widespread adoption of genome-edited crops. We propose a culture of sharing and integrating crop data to accelerate the discovery and prioritization of candidate genes, as well as a strong engagement with governments and the public to address environmental and health concerns and to achieve appropriate regulatory standards.

Legume genetic resources and transcriptome dynamics under abiotic stress conditions

Grain legumes are an important source of nutrition and income for billions of consumers and farmers around the world. However, the low productivity of new legume varieties, due to the limited genetic diversity available for legume breeding programmes and poor policymaker support, combined with an increasingly unpredictable global climate is resulting in a large gap between current yields and the increasing demand for legumes as food. Hence, there is a need for novel approaches to develop new high-yielding legume cultivars that are able to cope with a range of environmental stressors. Next-generation technologies are providing the tools that could enable the more rapid and cost-effective genomic and transcriptomic studies for most major crops, allowing the identification of key functional and regulatory genes involved in abiotic stress resistance. In this review, we provide an overview of the recent achievements regarding abiotic stress resistance in a wide range of legume crops and highlight the transcriptomic and miRNA approaches that have been used. In addition, we critically evaluate the availability and importance of legume genetic resources with desirable abiotic stress resistance traits.

De novo genome assembly and annotation of Australia's largest freshwater fish, the Murray cod (Maccullochella peelii), from Illumina and Nanopore sequencing read

One of the most iconic Australian fish is the Murray cod, Maccullochella peelii (Mitchell 1838), a freshwater species that can grow to ∼1.8 metres in length and live to age ≥48 years. The Murray cod is of a conservation concern as a result of strong population contractions, but it is also popular for recreational fishing and is of growing aquaculture interest. In this study, we report the whole genome sequence of the Murray cod to support ongoing population genetics, conservation, and management research, as well as to better understand the evolutionary ecology and history of the species. A draft Murray cod genome of 633 Mbp (N₅₀ = 109 974bp; BUSCO and CEGMA completeness of 94.2% and 91.9%, respectively) with an estimated 148 Mbp of putative repetitive sequences was assembled from the combined sequencing data of 2 fish individuals with an identical maternal lineage; 47.2 Gb of Illumina HiSeq data and 804 Mb of Nanopore data were generated from the first individual while 23.2 Gb of Illumina MiSeq data were generated from the second individual. The inclusion of Nanopore reads for scaffolding followed by subsequent gap-closing using Illumina data led to a 29% reduction in the number of scaffolds and a 55% and 54% increase in the scaffold and contig N₅₀, respectively. We also report the first transcriptome of Murray cod that was subsequently used to annotate the Murray cod genome, leading to the identification of 26 539 protein-coding genes. We present the whole genome of the Murray cod and anticipate this will be a catalyst for a range of genetic, genomic, and phylogenetic studies of the Murray cod and more generally other fish species of the Percichthydae family.

Single-Cell Genomic Analysis in Plants

Individual cells in an organism are variable, which strongly impacts cellular processes. Advances in sequencing technologies have enabled single-cell genomic analysis to become widespread, addressing shortcomings of analyses conducted on populations of bulk cells. While the field of single-cell plant genomics is in its infancy, there is great potential to gain insights into cell lineage and functional cell types to help understand complex cellular interactions in plants. In this review, we discuss current approaches for single-cell plant genomic analysis, with a focus on single-cell isolation, DNA amplification, next-generation sequencing, and bioinformatics analysis. We outline the technical challenges of analysing material from a single plant cell, and then examine applications of single-cell genomics and the integration of this approach with genome editing. Finally, we indicate future directions we expect in the rapidly developing field of plant single-cell genomic analysis.

Large-Scale Structural Variation Detection in Subterranean Clover Subtypes Using Optical Mapping

We selected two genetically diverse subspecies of the Trifolium model species, subterranean clover cvs. Daliak and Yarloop. The structural variations (SVs) discovered by Bionano optical mapping (BOM) were validated using Illumina short reads. In the analysis, BOM identified 12 large-scale regions containing deletions and 19 regions containing insertions in Yarloop. The 12 large-scale regions contained 71 small deletions when validated by Illumina short reads. The results suggest that BOM could detect the total size of deletions and insertions, but it could not precisely report the location and actual quantity of SVs in the genome. Nucleotide-level validation is crucial to confirm and characterize SVs reported by optical mapping. The accuracy of SV detection by BOM is highly dependent on the quality of reference genomes and the density of selected nickases.

Genome Sequencing and Assembly by Long Reads in Plants

Plant genomes generated by Sanger and Next Generation Sequencing (NGS) have provided insight into species diversity and evolution. However, Sanger sequencing is limited in its applications due to high cost, labor intensity, and low throughput, while NGS reads are too short to resolve abundant repeats and polyploidy, leading to incomplete or ambiguous assemblies. The advent and improvement of long-read sequencing by Third Generation Sequencing (TGS) methods such as PacBio and Nanopore have shown promise in producing high-quality assemblies for complex genomes. Here, we review the development of sequencing, introducing the application as well as considerations of experimental design in TGS of plant genomes. We also introduce recent revolutionary scaffolding technologies including BioNano, Hi-C, and 10× Genomics. We expect that the informative guidance for genome sequencing and assembly by long reads will benefit the initiation of scientists' projects.

Towards CRISPR/Cas crops - bringing together genomics and genome editing

Contents 682 I. 682 II. 683 III. 684 IV. 685 V. 685 VI. 688 VII. 690 VIII. 694 694 References 694 SUMMARY: With the rapid increase in the global population and the impact of climate change on agriculture, there is a need for crops with higher yields and greater tolerance to abiotic stress. However, traditional crop improvement via genetic recombination or random mutagenesis is a laborious process and cannot keep pace with increasing crop demand. Genome editing technologies such as clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein (CRISPR/Cas) allow targeted modification of almost any crop genome sequence to generate novel variation and accelerate breeding efforts. We expect a gradual shift in crop improvement away from traditional breeding towards cycles of targeted genome editing. Crop improvement using genome editing is not constrained by limited existing variation or the requirement to select alleles over multiple breeding generations. However, current applications of crop genome editing are limited by the lack of complete reference genomes, the sparse knowledge of potential modification targets, and the unclear legal status of edited crops. We argue that overcoming technical and social barriers to the application of genome editing will allow this technology to produce a new generation of high-yielding, climate ready crops.

Multiple hybrid de novo genome assembly of finger millet, an orphan allotetraploid crop

Finger millet (Eleusine coracana (L.) Gaertn) is an important crop for food security because of its tolerance to drought, which is expected to be exacerbated by global climate changes. Nevertheless, it is often classified as an orphan/underutilized crop because of the paucity of scientific attention. Among several small millets, finger millet is considered as an excellent source of essential nutrient elements, such as iron and zinc; hence, it has potential as an alternate coarse cereal. However, high-quality genome sequence data of finger millet are currently not available. One of the major problems encountered in the genome assembly of this species was its polyploidy, which hampers genome assembly compared with a diploid genome. To overcome this problem, we sequenced its genome using diverse technologies with sufficient coverage and assembled it via a novel multiple hybrid assembly workflow that combines next-generation with single-molecule sequencing, followed by whole-genome optical mapping using the Bionano Irys® system. The total number of scaffolds was 1,897 with an N50 length >2.6 Mb and detection of 96% of the universal single-copy orthologs. The majority of the homeologs were assembled separately. This indicates that the proposed workflow is applicable to the assembly of other allotetraploid genomes.