Connecting genome structural variation with complex traits in crop plants

Improvement of crop production in controlled environment agriculture through breeding

Controlled environment agriculture (CEA) represents one of the fastest-growing sectors of horticulture. Production in controlled environments ranges from highly controlled indoor environments with 100% artificial lighting (vertical farms or plant factories) to high-tech greenhouses with or without supplemental lighting, to simpler greenhouses and high tunnels. Although food production occurs in the soil inside high tunnels, most CEA operations use various hydroponic systems to meet crop irrigation and fertility needs. The expansion of CEA offers promise as a tool for increasing food production in and near urban systems as these systems do not rely on arable agricultural land. In addition, CEA offers resilience to climate instability by growing inside protective structures. Products harvested from CEA systems tend to be of high quality, both internal and external, and are sought after by consumers. Currently, CEA producers rely on cultivars bred for production in open-field agriculture. Because of high energy and other production costs in CEA, only a limited number of food crops have proven themselves to be profitable to produce. One factor contributing to this situation may be a lack of optimized cultivars. Indoor growing operations offer opportunities for breeding cultivars that are ideal for these systems. To facilitate breeding these specialized cultivars, a wide range of tools are available for plant breeders to help speed this process and increase its efficiency. This review aims to cover breeding opportunities and needs for a wide range of horticultural crops either already being produced in CEA systems or with potential for CEA production. It also reviews many of the tools available to breeders including genomics-informed breeding, marker-assisted selection, precision breeding, high-throughput phenotyping, and potential sources of germplasm suitable for CEA breeding. The availability of published genomes and trait-linked molecular markers should enable rapid progress in the breeding of CEA-specific food crops that will help drive the growth of this industry.

Pan-genome analyses of 11 Fraxinus species provide insights into salt adaptation in ash trees

Ash trees (Fraxinus) exhibit rich genetic diversity and wide adaptation to various ecological environments, and several species are highly salt tolerant. Dissecting the genomic basis of salt adaptation in Fraxinus is vital for its resistance breeding. Here, we present 11 high-quality chromosome-level genome assemblies for Fraxinus species, which reveal two unequal subgenome compositions and two recent whole-genome triplication events in their evolutionary history. A Fraxinus pan-genome was constructed on the basis of structural variations and revealed that presence-absence variations (PAVs) of transmembrane transport genes have likely contributed to salt adaptation in Fraxinus. Through whole-genome resequencing of an F1 population from an interspecies cross of F. velutina 'Lula 3' (salt tolerant) with F. pennsylvanica 'Lula 5' (salt sensitive), we mapped salt-tolerance PAV-based quantitative trait loci (QTLs) and pinpointed two PAV-QTLs and candidate genes associated with Fraxinus salt tolerance. Mechanistically, FvbHLH85 enhances salt tolerance by mediating reactive oxygen species and Na+/K+ homeostasis, whereas FvSWEET5 enhances salt tolerance by mediating osmotic homeostasis. Collectively, these findings provide valuable genomic resources for Fraxinus salt-resistance breeding and the research community.

Grapevine pangenome facilitates trait genetics and genomic breeding

Grapevine breeding is hindered by a limited understanding of the genetic basis of complex agronomic traits. This study constructs a graph-based pangenome reference (Grapepan v.1.0) from 18 newly generated phased telomere-to-telomere assemblies and 11 published assemblies. Using Grapepan v.1.0, we build a variation map with 9,105,787 short variations and 236,449 structural variations (SVs) from the resequencing data of 466 grapevine cultivars. Integrating SVs into a genome-wide association study, we map 148 quantitative trait loci for 29 agronomic traits (50.7% newly identified), with 12 traits significantly contributed by SVs. The estimated heritability improves by 22.78% on average when including SVs. We discovered quantitative trait locus regions under divergent artificial selection in metabolism and berry development between wine and table grapes, respectively. Moreover, significant genetic correlations were detected among the 29 traits. Under a polygenic model, we conducted genomic predictions for each trait. In general, our study facilitates the breeding of superior cultivars via the genomic selection of multiple traits.

Unlocking diversity from wild relatives of perennial fruit crops in the pan-genomics era

Crop wild relatives of perennial fruit crops have a wealth of untapped genetic diversity that can be utilized for cultivar development. However, barriers such as linkage drag, long juvenility, and high heterozygosity have hindered their utilization. Advancements in genome sequencing technologies and assembly methods, combined with the integration of chromosome conformation capture have made it possible to construct high-quality reference genomes. These genome assemblies can be combined into pan-genomes, capturing inter- and intraspecific variations across coding and non-coding regions. Pan-genomes of perennial fruit crops are being developed to identify the genetic basis of traits. This will help overcome breeding challenges, enabling faster and more targeted development of new cultivars with novel traits through breeding and biotechnology.

Integrating dynamic high-throughput phenotyping and genetic analysis to monitor growth variation in foxtail millet

BACKGROUND

Foxtail millet [Setaria italica (L.) Beauv] is a C4 graminoid crop cultivated mainly in the arid and semiarid regions of China for more than 7000 years. Its grain highly nutritious and is rich in starch, protein, essential vitamins such as carotenoids, folate, and minerals. To expand the utilisation of foxtail millet, efficient and precise methods for dynamic phenotyping of its growth stages are needed. Traditional foxtail millet monitoring methods have high labour costs and are inefficient and inaccurate, impeding the precise evaluation of foxtail millet genotypic variation.

RESULTS

This study introduces a high-throughput imaging system (HIS) with advanced image processing techniques to enhance monitoring efficiency and data quality. The HIS can accurately extract a range of key growth feature parameters, such as plant height (PH), convex hull area (CHA), side projected area (SPA) and colour distribution, from foxtail millet images. Compared with traditional manual measurements, this HIS improved data quality and phenotyping of the key foxtail millet growth traits. High-throughput phenotyping combined with a genome-wide association study (GWAS) revealed genetic loci associated with dynamic growth traits, particularly plant height (PH), in foxtail millet. The loci were linked to genes involved in the gibberellic acid (GA) synthesis pathway related to PH.

CONCLUSION

The HIS developed in this study enables the efficient and dynamic monitoring of foxtail millet phenotypic traits. It significantly improves the quality of data obtained for phenotyping key growth traits. The integration of high-throughput phenotyping with GWAS provides new insights into the genetic underpinnings of dynamic growth traits, particularly plant height, by identifying associated genetic loci in the GA synthesis pathway. This methodological advancement opens new avenues for the precise phenotyping and exploration of genetic resources in foxtail millet, potentially enhancing its utilisation.

The story of a decade: Genomics, functional genomics, and molecular breeding in Brassica napus

Rapeseed (Brassica napus L.) is one of the major global sources of edible vegetable oil and is also used as a feed and pioneer crop and for sightseeing and industrial purposes. Improvements in genome sequencing and molecular marker technology have fueled a boom in functional genomic studies of major agronomic characters such as yield, quality, flowering time, and stress resistance. Moreover, introgression and pyramiding of key functional genes have greatly accelerated the genetic improvement of important traits. Here we summarize recent progress in rapeseed genomics and genetics, and we discuss effective molecular breeding strategies by exploring these findings in rapeseed. These insights will extend our understanding of the molecular mechanisms and regulatory networks underlying agronomic traits and facilitate the breeding process, ultimately contributing to more sustainable agriculture throughout the world.

Genome-wide association mapping for pre-harvest sprouting in European winter wheat detects novel resistance QTL, pleiotropic effects, and structural variation in multiple genomes

Pre-harvest sprouting (PHS), germination of seeds before harvest, is a major problem in global wheat (Triticum aestivum L.) production, and leads to reduced bread-making quality in affected grain. Breeding for PHS resistance can prevent losses under adverse conditions. Selecting resistant lines in years lacking pre-harvest rain, requires challenging of plants in the field or in the laboratory or using genetic markers. Despite the availability of a wheat reference and pan-genome, linking markers, genes, allelic, and structural variation, a complete understanding of the mechanisms underlying various sources of PHS resistance is still lacking. Therefore, we challenged a population of European wheat varieties and breeding lines with PHS conditions and phenotyped them for PHS traits, grain quality, phenological and agronomic traits to conduct genome-wide association mapping. Furthermore, we compared these marker-trait associations to previously reported PHS loci and evaluated their usefulness for breeding. We found markers associated with PHS on all chromosomes, with strong evidence for novel quantitative trait locus/loci (QTL) on chromosome 1A and 5B. The QTL on chromosome 1A lacks pleiotropic effect, for the QTL on 5B we detected pleiotropic effects on phenology and grain quality. Multiple peaks on chromosome 4A co-located with the major resistance locus Phs-A1, for which two causal genes, TaPM19 and TaMKK3, have been proposed. Mapping markers and genes to the pan-genome and chromosomal alignments provide evidence for structural variation around this major PHS-resistance locus. Although PHS is controlled by many loci distributed across the wheat genome, Phs-A1 on chromosome 4A seems to be the most effective and widely deployed source of resistance, in European wheat varieties.

Genomic insight into variations associated with flowering-time and early-maturity in pigeonpea mutant TAT-10 and its wild type parent T21

Pigeonpea [Cajanus cajan (L.) Millspaugh] is an important grain legume crop with a broad range of 90 to 300 days for maturity. To identify the genomic variations associated with the early maturity, we conducted whole-genome resequencing of an early-maturing pigeonpea mutant TAT-10 and its wild type parent T21. A total of 135.67 and 146.34 million sequencing reads were generated for T21 and TAT-10, respectively. From this resequencing data, 1,397,178 and 1,419,904 SNPs, 276,741 and 292,347 InDels, and 87,583 and 92,903 SVs were identified in T21 and TAT-10, respectively. We identified 203 genes in the pigeonpea genome that are homologs of flowering-related genes in Arabidopsis and found 791 genomic variations unique to TAT-10 linked to 94 flowering-related genes. We identified three candidate genes for early maturity in TAT-10; Suppressor of FRI 4 (SUF4), Early Flowering In Short Days (EFS), and Probable Lysine-Specific Demethylase ELF6. The variations in ELF6 were predicted to be possibly damaging and the expression profiles of EFS and ELF6 also supported their probable role during early flowering in TAT-10. The present study has generated information on genomic variations associated with candidate genes for early maturity, which can be further studied and exploited for developing the early-maturing pigeonpea cultivars.

Accurate prediction of quantitative traits with failed SNP calls in canola and maize

In modern plant breeding, genomic selection is becoming the gold standard to select superior genotypes in large breeding populations that are only partially phenotyped. Many breeding programs commonly rely on single-nucleotide polymorphism (SNP) markers to capture genome-wide data for selection candidates. For this purpose, SNP arrays with moderate to high marker density represent a robust and cost-effective tool to generate reproducible, easy-to-handle, high-throughput genotype data from large-scale breeding populations. However, SNP arrays are prone to technical errors that lead to failed allele calls. To overcome this problem, failed calls are often imputed, based on the assumption that failed SNP calls are purely technical. However, this ignores the biological causes for failed calls-for example: deletions-and there is increasing evidence that gene presence-absence and other kinds of genome structural variants can play a role in phenotypic expression. Because deletions are frequently not in linkage disequilibrium with their flanking SNPs, permutation of missing SNP calls can potentially obscure valuable marker-trait associations. In this study, we analyze published datasets for canola and maize using four parametric and two machine learning models and demonstrate that failed allele calls in genomic prediction are highly predictive for important agronomic traits. We present two statistical pipelines, based on population structure and linkage disequilibrium, that enable the filtering of failed SNP calls that are likely caused by biological reasons. For the population and trait examined, prediction accuracy based on these filtered failed allele calls was competitive to standard SNP-based prediction, underlying the potential value of missing data in genomic prediction approaches. The combination of SNPs with all failed allele calls or the filtered allele calls did not outperform predictions with only SNP-based prediction due to redundancy in genomic relationship estimates.

Nanopore sequencing technology and its applications

Since the development of Sanger sequencing in 1977, sequencing technology has played a pivotal role in molecular biology research by enabling the interpretation of biological genetic codes. Today, nanopore sequencing is one of the leading third-generation sequencing technologies. With its long reads, portability, and low cost, nanopore sequencing is widely used in various scientific fields including epidemic prevention and control, disease diagnosis, and animal and plant breeding. Despite initial concerns about high error rates, continuous innovation in sequencing platforms and algorithm analysis technology has effectively addressed its accuracy. During the coronavirus disease (COVID-19) pandemic, nanopore sequencing played a critical role in detecting the severe acute respiratory syndrome coronavirus-2 virus genome and containing the pandemic. However, a lack of understanding of this technology may limit its popularization and application. Nanopore sequencing is poised to become the mainstream choice for preventing and controlling COVID-19 and future epidemics while creating value in other fields such as oncology and botany. This work introduces the contributions of nanopore sequencing during the COVID-19 pandemic to promote public understanding and its use in emerging outbreaks worldwide. We discuss its application in microbial detection, cancer genomes, and plant genomes and summarize strategies to improve its accuracy.

Two complementary genes in a presence-absence variation contribute to indica-japonica reproductive isolation in rice

Understanding the evolutionary forces in speciation is a central goal in evolutionary biology. Asian cultivated rice has two subspecies, indica and japonica, but the underlying mechanism of the partial reproductive isolation between them remains obscure. Here we show a presence-absence variation (PAV) at the Se locus functions as an indica-japonica reproductive barrier by causing hybrid sterility (HS) in indica-japonica crosses. The locus comprises two adjacent genes: ORF3 encodes a sporophytic pollen killer, whereas ORF4 protects pollen in a gametophytic manner. In F₁ of indica-japonica crosses, pollen with the japonica haplotype, which lacks the sequence containing the protective ORF4, is aborted due to the pollen-killing effect of ORF3 from indica. Evolutionary analysis suggests ORF3 is a gene associated with the Asian cultivated rice species complex, and the PAV has contributed to the reproductive isolation between the two subspecies of Asian cultivated rice. Our analyses provide perspectives on rice inter-subspecies post-zygotic isolation, and will promote efforts to overcome reproductive barriers in indica-japonica hybrid rice breeding.

k-mer-Based Genome-Wide Association Studies in Plants: Advances, Challenges, and Perspectives

Genome-wide association studies (GWAS) have allowed the discovery of marker-trait associations in crops over recent decades. However, their power is hampered by a number of limitations, with the key one among them being an overreliance on single-nucleotide polymorphisms (SNPs) as molecular markers. Indeed, SNPs represent only one type of genetic variation and are usually derived from alignment to a single genome assembly that may be poorly representative of the population under study. To overcome this, k-mer-based GWAS approaches have recently been developed. k-mer-based GWAS provide a universal way to assess variation due to SNPs, insertions/deletions, and structural variations without having to specifically detect and genotype these variants. In addition, k-mer-based analyses can be used in species that lack a reference genome. However, the use of k-mers for GWAS presents challenges such as data size and complexity, lack of standard tools, and potential detection of false associations. Nevertheless, efforts are being made to overcome these challenges and a general analysis workflow has started to emerge. We identify the priorities for k-mer-based GWAS in years to come, notably in the development of user-friendly programs for their analysis and approaches for linking significant k-mers to sequence variation.

Patterns, mechanisms, and consequences of homoeologous exchange in allopolyploid angiosperms: a genomic and epigenomic perspective

Allopolyploids result from hybridization between different evolutionary lineages coupled with genome doubling. Homoeologous chromosomes (chromosomes with common shared ancestry) may undergo recombination immediately after allopolyploid formation and continue over successive generations. The outcome of this meiotic pairing behavior is dynamic and complex. Homoeologous exchanges (HEs) may lead to the formation of unbalanced gametes, reduced fertility, and selective disadvantage. By contrast, HEs could act as sources of novel evolutionary substrates, shifting the relative dosage of parental gene copies, generating novel phenotypic diversity, and helping the establishment of neo-allopolyploids. However, HE patterns vary among lineages, across generations, and even within individual genomes and chromosomes. The causes and consequences of this variation are not fully understood, though interest in this evolutionary phenomenon has increased in the last decade. Recent technological advances show promise in uncovering the mechanistic basis of HEs. Here, we describe recent observations of the common patterns among allopolyploid angiosperm lineages, underlying genomic and epigenomic features, and consequences of HEs. We identify critical research gaps and discuss future directions with far-reaching implications in understanding allopolyploid evolution and applying them to the development of important phenotypic traits of polyploid crops.

SVcnn: an accurate deep learning-based method for detecting structural variation based on long-read data

BACKGROUND

Structural variations (SVs) refer to variations in an organism's chromosome structure that exceed a length of 50 base pairs. They play a significant role in genetic diseases and evolutionary mechanisms. While long-read sequencing technology has led to the development of numerous SV caller methods, their performance results have been suboptimal. Researchers have observed that current SV callers often miss true SVs and generate many false SVs, especially in repetitive regions and areas with multi-allelic SVs. These errors are due to the messy alignments of long-read data, which are affected by their high error rate. Therefore, there is a need for a more accurate SV caller method.

RESULT

We propose a new method-SVcnn, a more accurate deep learning-based method for detecting SVs by using long-read sequencing data. We run SVcnn and other SV callers in three real datasets and find that SVcnn improves the F1-score by 2-8% compared with the second-best method when the read depth is greater than 5×. More importantly, SVcnn has better performance for detecting multi-allelic SVs.

CONCLUSIONS

SVcnn is an accurate deep learning-based method to detect SVs. The program is available at https://github.com/nwpuzhengyan/SVcnn .

Identification of structural variations related to drought tolerance in wheat (Triticum aestivum L.)

Structural variations are common in plant genomes, affecting meiotic recombination and distorted segregation in wheat. And presence/absence variations can significantly affect drought tolerance in wheat. Drought is a major abiotic stress limiting wheat production. Common wheat has a complex genome with three sub-genomes, which host large numbers of structural variations (SVs). SVs play critical roles in understanding the genetic contributions of plant domestication and phenotypic plasticity, but little is known about their genomic characteristics and their effects on drought tolerance. In the present study, high-resolution karyotypes of 180 doubled haploids (DHs) were developed. Signal polymorphisms between the parents involved with 8 presence-absence variations (PAVs) of tandem repeats (TR) distributed on the 7 (2A, 4A, 5A, 7A, 3B, 7B, and 2D) of 21 chromosomes. Among them, PAV on chromosome 2D showed distorted segregation, others transmit normal conforming to a 1:1 segregation ration in the population; and a PAVs recombination occurred on chromosome 2A. Association analysis of PAV and phenotypic traits under different water regimes, we found PAVs on chromosomes 4A, 5A, and 7B showed negative effect on grain length (GL) and grain width (GW); PAV.7A had opposite effect on grain thickness (GT) and spike length (SL), with the effect on traits differing under different water regimes. PAVs on linkage group 2A, 4A, 7A, 2D, and 7B associated with the drought tolerance coefficients (DTCs), and significant negative effect on drought resistance values (D values) were detected in PAV.7B. Additionally, quantitative trait loci (QTL) associated with phenotypic traits using the 90 K SNP array showed QTL for DTCs and grain-related traits in chromosomes 4A, and 5A, 3B were co-localized in differential regions of PAVs. These PAVs can cause the differentiation of the target region of SNP and could be used for genetic improvement of agronomic traits under drought stress via marker-assisted selection (MAS) breeding.

Syntenic Cell Wall QTLs as Versatile Breeding Tools: Intraspecific Allelic Variability and Predictability of Biomass Quality Loci in Target Plant Species

Syntenic cell wall QTLs (SQTLs) can identify genetic determinants of biomass traits in understudied species based on results from model crops. However, their effective use in plant breeding requires SQTLs to display intraspecific allelic variability and to predict causative loci in other populations/species than the ones used for SQTLs identification. In this study, genome assemblies from different accessions of Arabidopsis, rapeseed, tomato, rice, Brachypodium and maize were used to evaluate the intraspecific variability of SQTLs. In parallel, a genome-wide association study (GWAS) on cell wall quality traits was performed in miscanthus to verify the colocalization between GWAS loci and miscanthus SQTLs. Finally, an analogous approach was applied on a set of switchgrass cell wall QTLs retrieved from the literature. These analyses revealed large SQTLs intraspecific genetic variability, ranging from presence-absence gene variation to SNPs/INDELs and changes in coded proteins. Cell wall genes displaying gene dosage regulation, such as PAL and CAD, displayed presence-absence variation in Brachypodium and rapeseed, while protein INDELs were detected for the Brachypodium homologs of the rice brittle culm-like 8 locus, which may likely impact cell wall quality. Furthermore, SQTLs significantly colocalized with the miscanthus and switchgrass QTLs, with relevant cell wall genes being retained in colocalizing regions. Overall, SQTLs are useful tools to screen germplasm for relevant genes and alleles to improve biomass quality and can increase the efficiency of plant breeding in understudied biomass crops.

In it for the long run: perspectives on exploiting long-read sequencing in livestock for population scale studies of structural variants

Studies have demonstrated that structural variants (SV) play a substantial role in the evolution of species and have an impact on Mendelian traits in the genome. However, unlike small variants (< 50 bp), it has been challenging to accurately identify and genotype SV at the population scale using short-read sequencing. Long-read sequencing technologies are becoming competitively priced and can address several of the disadvantages of short-read sequencing for the discovery and genotyping of SV. In livestock species, analysis of SV at the population scale still faces challenges due to the lack of resources, high costs, technological barriers, and computational limitations. In this review, we summarize recent progress in the characterization of SV in the major livestock species, the obstacles that still need to be overcome, as well as the future directions in this growing field. It seems timely that research communities pool resources to build global population-scale long-read sequencing consortiums for the major livestock species for which the application of genomic tools has become cost-effective.

A pangenome analysis pipeline provides insights into functional gene identification in rice

BACKGROUND

A pangenome aims to capture the complete genetic diversity within a species and reduce bias in genetic analysis inherent in using a single reference genome. However, the current linear format of most plant pangenomes limits the presentation of position information for novel sequences. Graph pangenomes have been developed to overcome this limitation. However, bioinformatics analysis tools for graph format genomes are lacking.

RESULTS

To overcome this problem, we develop a novel strategy for pangenome construction and a downstream pangenome analysis pipeline (PSVCP) that captures genetic variants' position information while maintaining a linearized layout. Using PSVCP, we construct a high-quality rice pangenome using 12 representative rice genomes and analyze an international rice panel with 413 diverse accessions using the pangenome as the reference. We show that PSVCP successfully identifies causal structural variations for rice grain weight and plant height. Our results provide insights into rice population structure and genomic diversity. We characterize a new locus (qPH8-1) associated with plant height on chromosome 8 undetected by the SNP-based genome-wide association study (GWAS).

CONCLUSIONS

Our results demonstrate that the pangenome constructed by our pipeline combined with a presence and absence variation-based GWAS can provide additional power for genomic and genetic analysis. The pangenome constructed in this study and the associated genome sequence and genetic variants data provide valuable genomic resources for rice genomics research and improvement in future.

Comparison of structural variants detected by PacBio-CLR and ONT sequencing in pear

BACKGROUND

Structural variations (SVs) have recently become a topic of great interest in the area of genetic diversity and trait regulation. As genomic sequencing technologies have rapidly advanced, longer reads have been used to identify SVs at high resolution and with increased accuracy. It is important to choose a suitable sequencing platform and appropriate sequencing depth for SV detection in the pear genome.

RESULTS

In this study, two types of long reads from sequencing platforms, continuous long reads from Pacific Biosciences (PB-CLR) and long reads from Oxford Nanopore Technologies (ONT), were used to comprehensively analyze and compare SVs in the pear genome. The mapping rate of long reads was higher when the program Minimap2 rather than the other three mapping tools (NGMLR, LRA and Winnowmap2) was used. Three SV detection programs (Sniffles_v2, CuteSV, and Nanovar) were compared, and Nanovar had the highest sensitivity in detecting SVs at low sequencing depth (10-15×). A sequencing depth of 15× was suitable for SV detection in the pear genome using Nanovar. SVs detected by Sniffles_v2 and CuteSV with ONT reads had the high overlap with presence/absence variations (PAVs) in the pear cultivars 'Bartlett' and 'Dangshansuli', both of them with 38% of insertions and 55% of deletions overlapping with PAVs at sequencing depth of 30×. For the ONT sequencing data, over 37,526 SVs spanning ~ 28 Mb were identified by all three software packages for the 'Bartlett' and 'Dangshansuli' genomes. Those SVs were annotated and combined with transcriptome profiles derived from 'Bartlett' and 'Dangshansuli' fruit flesh at 60 days after cross-pollination. Several genes related to levels of sugars, acid, stone cells, and aromatic compounds were identified among the SVs. Transcription factors were then predicted among those genes, and results included bHLH, ERF, and MYB genes.

CONCLUSION

SV detection is of great significance in exploring phenotypic differences between pear varieties. Our study provides a framework for assessment of different SV software packages and sequencing platforms that can be applied in other plant genome studies. Based on these analyses, ONT sequencing data was determined to be more suitable than PB-CLR for SV detection in the pear genome. This analysis model will facilitate screening of genes related to agronomic traits in other crops.

Multi-omics revolution to promote plant breeding efficiency

Crop production is the primary goal of agricultural activities, which is always taken into consideration. However, global agricultural systems are coming under increasing pressure from the rising food demand of the rapidly growing world population and changing climate. To address these issues, improving high-yield and climate-resilient related-traits in crop breeding is an effective strategy. In recent years, advances in omics techniques, including genomics, transcriptomics, proteomics, and metabolomics, paved the way for accelerating plant/crop breeding to cope with the changing climate and enhance food production. Optimized omics and phenotypic plasticity platform integration, exploited by evolving machine learning algorithms will aid in the development of biological interpretations for complex crop traits. The precise and progressive assembly of desire alleles using precise genome editing approaches and enhanced breeding strategies would enable future crops to excel in combating the changing climates. Furthermore, plant breeding and genetic engineering ensures an exclusive approach to developing nutrient sufficient and climate-resilient crops, the productivity of which can sustainably and adequately meet the world's food, nutrition, and energy needs. This review provides an overview of how the integration of omics approaches could be exploited to select crop varieties with desired traits.

Homoeologous exchange enables rapid evolution of tolerance to salinity and hyper-osmotic stresses in a synthetic allotetraploid wheat

The link between polyploidy and enhanced adaptation to environmental stresses could be a result of polyploidy itself harbouring higher tolerance to adverse conditions, or polyploidy possessing higher evolvability than diploids under stress conditions. Natural polyploids are inherently unsuitable to disentangle these two possibilities. Using selfed progenies of a synthetic allotetraploid wheat AT3 (AADD) along with its diploid parents, Triticum urartu TMU38 (AA) and Aegilops tauschii TQ27 (DD), we addressed the foregoing issue under abiotic salinity and hyper-osmotic (drought-like) stress. Under short duration of both stresses, euploid plants of AT3 showed intermediate tolerance of diploid parents; under life-long duration of both stresses, tolerant individuals to either stress emerged from selfed progenies of AT3, but not from comparable-sized diploid parent populations. Tolerance to both stresses were conditioned by the same two homoeologous exchanges (HEs; 2DS/2AS and 3DL/3AL), and at least one HE needed to be at the homozygous state. Transcriptomic analyses revealed that hyper-up-regulation of within-HE stress responsive genes of the A sub-genome origin is likely responsible for the dual-stress tolerant phenotypes. Our results suggest that HE-mediated inter-sub-genome rearrangements can be an important mechanism leading to adaptive evolution in allopolyploids as well as a promising target for genetic manipulation in crop improvement.

Comprehensive transcriptional variability analysis reveals gene networks regulating seed oil content of Brassica napus

BACKGROUND

Regulation of gene expression plays an essential role in controlling the phenotypes of plants. Brassica napus (B. napus) is an important source for the vegetable oil in the world, and the seed oil content is an important trait of B. napus.

RESULTS

We perform a comprehensive analysis of the transcriptional variability in the seeds of B. napus at two developmental stages, 20 and 40 days after flowering (DAF). We detect 53,759 and 53,550 independent expression quantitative trait loci (eQTLs) for 79,605 and 76,713 expressed genes at 20 and 40 DAF, respectively. Among them, the local eQTLs are mapped to the adjacent genes more frequently. The adjacent gene pairs are regulated by local eQTLs with the same open chromatin state and show a stronger mode of expression piggybacking. Inter-subgenomic analysis indicates that there is a feedback regulation for the homoeologous gene pairs to maintain partial expression dosage. We also identify 141 eQTL hotspots and find that hotspot87-88 co-localizes with a QTL for the seed oil content. To further resolve the regulatory network of this eQTL hotspot, we construct the XGBoost model using 856 RNA-seq datasets and the Basenji model using 59 ATAC-seq datasets. Using these two models, we predict the mechanisms affecting the seed oil content regulated by hotspot87-88 and experimentally validate that the transcription factors, NAC13 and SCL31, positively regulate the seed oil content.

CONCLUSIONS

We comprehensively characterize the gene regulatory features in the seeds of B. napus and reveal the gene networks regulating the seed oil content of B. napus.

Smart breeding approaches in post-genomics era for developing climate-resilient food crops

Improving the crop traits is highly required for the development of superior crop varieties to deal with climate change and the associated abiotic and biotic stress challenges. Climate change-driven global warming can trigger higher insect pest pressures and plant diseases thus affecting crop production sternly. The traits controlling genes for stress or disease tolerance are economically imperative in crop plants. In this scenario, the extensive exploration of available wild, resistant or susceptible germplasms and unraveling the genetic diversity remains vital for breeding programs. The dawn of next-generation sequencing technologies and omics approaches has accelerated plant breeding by providing the genome sequences and transcriptomes of several plants. The availability of decoded plant genomes offers an opportunity at a glance to identify candidate genes, quantitative trait loci (QTLs), molecular markers, and genome-wide association studies that can potentially aid in high throughput marker-assisted breeding. In recent years genomics is coupled with marker-assisted breeding to unravel the mechanisms to harness better better crop yield and quality. In this review, we discuss the aspects of marker-assisted breeding and recent perspectives of breeding approaches in the era of genomics, bioinformatics, high-tech phonemics, genome editing, and new plant breeding technologies for crop improvement. In nutshell, the smart breeding toolkit in the post-genomics era can steadily help in developing climate-smart future food crops.

An efficient CRISPR-Cas9 enrichment sequencing strategy for characterizing complex and highly duplicated genomic regions. A case study in the Prunus salicina LG3-MYB10 genes cluster

BACKGROUND

Genome complexity is largely linked to diversification and crop innovation. Examples of regions with duplicated genes with relevant roles in agricultural traits are found in many crops. In both duplicated and non-duplicated genes, much of the variability in agronomic traits is caused by large as well as small and middle scale structural variants (SVs), which highlights the relevance of the identification and characterization of complex variability between genomes for plant breeding.

RESULTS

Here we improve and demonstrate the use of CRISPR-Cas9 enrichment combined with long-read sequencing technology to resolve the MYB10 region in the linkage group 3 (LG3) of Japanese plum (Prunus salicina). This region, which has a length from 90 to 271 kb according to the P. salicina genomes available, is associated with fruit color variability in Prunus species. We demonstrate the high complexity of this region, with homology levels between Japanese plum varieties comparable to those between Prunus species. We cleaved MYB10 genes in five plum varieties using the Cas9 enzyme guided by a pool of crRNAs. The barcoded fragments were then pooled and sequenced in a single MinION Oxford Nanopore Technologies (ONT) run, yielding 194 Mb of sequence. The enrichment was confirmed by aligning the long reads to the plum reference genomes, with a mean read on-target value of 4.5% and a depth per sample of 11.9x. From the alignment, 3261 SNPs and 287 SVs were called and phased. A de novo assembly was constructed for each variety, which also allowed detection, at the haplotype level, of the variability in this region.

CONCLUSIONS

CRISPR-Cas9 enrichment is a versatile and powerful tool for long-read targeted sequencing even on highly duplicated and/or polymorphic genomic regions, being especially useful when a reference genome is not available. Potential uses of this methodology as well as its limitations are further discussed.

Genetic and molecular factors in determining grain number per panicle of rice

It was suggested that the most effective way to improve rice grain yield is to increase the grain number per panicle (GN) through the breeding practice in recent decades. GN is a representative quantitative trait affected by multiple genetic and environmental factors. Understanding the mechanisms controlling GN has become an important research field in rice biotechnology and breeding. The regulation of rice GN is coordinately controlled by panicle architecture and branch differentiation, and many GN-associated genes showed pleiotropic effect in regulating tillering, grain size, flowering time, and other domestication-related traits. It is also revealed that GN determination is closely related to vascular development and the metabolism of some phytohormones. In this review, we summarize the recent findings in rice GN determination and discuss the genetic and molecular mechanisms of GN regulators.

Genetic and genomic diversity in the sorghum gene bank collection of Uganda

BACKGROUND

The Plant Genetic Resources Centre at the Uganda National Gene Bank houses has over 3000 genetically diverse landraces and wild relatives of Sorghum bicolor accessions. This genetic diversity resource is untapped, under-utilized, and has not been systematically incorporated into sorghum breeding programs. In this study, we characterized the germplasm collection using whole-genome SNP markers (DArTseq). Discriminant analysis of principal components (DAPC) was implemented to study the racial ancestry of the accessions in comparison to a global sorghum diversity set and characterize the sub-groups present in the Ugandan (UG) germplasm.

RESULTS

Population structure and phylogenetic analysis revealed the presence of five subgroups among the Ugandan accessions. The samples from the highlands of the southwestern region were genetically distinct as compared to the rest of the population. This subset was predominated by the caudatum race and unique in comparison to the other sub-populations. In this study, we detected QTL for juvenile cold tolerance by genome-wide association studies (GWAS) resulting in the identification of 4 markers associated (-log10p > 3) to survival under cold stress under both field and climate chamber conditions, located on 3 chromosomes (02, 06, 09). To our best knowledge, the QTL on Sb09 with the strongest association was discovered for the first time.

CONCLUSION

This study demonstrates how genebank genomics can potentially facilitate effective and efficient usage of valuable, untapped germplasm collections for agronomic trait evaluation and subsequent allele mining. In face of adverse climate change, identification of genomic regions potentially involved in the adaptation of Ugandan sorghum accessions to cooler climatic conditions would be of interest for the expansion of sorghum production into temperate latitudes.

Plant pan-genomics: recent advances, new challenges, and roads ahead

Pan-genomics can encompass most of the genetic diversity of a species or population and has proved to be a powerful tool for studying genomic evolution and the origin and domestication of species, and for providing information for plant improvement. Plant genomics has greatly progressed because of improvements in sequencing technologies and the rapid reduction of sequencing costs. Nevertheless, pan-genomics still presents many challenges, including computationally intensive assembly methods, high costs with large numbers of samples, ineffective integration of big data, and difficulty in applying it to downstream multi-omics analysis and breeding research. In this review, we summarize the definition and recent achievements of plant pan-genomics, computational technologies used for pan-genome construction, and the applications of pan-genomes in plant genomics and molecular breeding. We also discuss challenges and perspectives for future pan-genomics studies and provide a detailed pipeline for sample selection, genome assembly and annotation, structural variation identification, and construction and application of graph-based pan-genomes. The aim is to provide important guidance for plant pan-genome research and a better understanding of the genetic basis of genome evolution, crop domestication, and phenotypic diversity for future studies.

Recent advancements in CRISPR/Cas technology for accelerated crop improvement

Precise genome engineering approaches could be perceived as a second paradigm for targeted trait improvement in crop plants, with the potential to overcome the constraints imposed by conventional CRISPR/Cas technology. The likelihood of reduced agricultural production due to highly turbulent climatic conditions increases as the global population expands. The second paradigm of stress-resilient crops with enhanced tolerance and increased productivity against various stresses is paramount to support global production and consumption equilibrium. Although traditional breeding approaches have substantially increased crop production and yield, effective strategies are anticipated to restore crop productivity even further in meeting the world's increasing food demands. CRISPR/Cas, which originated in prokaryotes, has surfaced as a coveted genome editing tool in recent decades, reshaping plant molecular biology in unprecedented ways and paving the way for engineering stress-tolerant crops. CRISPR/Cas is distinguished by its efficiency, high target specificity, and modularity, enables precise genetic modification of crop plants, allowing for the creation of allelic variations in the germplasm and the development of novel and more productive agricultural practices. Additionally, a slew of advanced biotechnologies premised on the CRISPR/Cas methodologies have augmented fundamental research and plant synthetic biology toolkits. Here, we describe gene editing tools, including CRISPR/Cas and its imitative tools, such as base and prime editing, multiplex genome editing, chromosome engineering followed by their implications in crop genetic improvement. Further, we comprehensively discuss the latest developments of CRISPR/Cas technology including CRISPR-mediated gene drive, tissue-specific genome editing, dCas9 mediated epigenetic modification and programmed self-elimination of transgenes in plants. Finally, we highlight the applicability and scope of advanced CRISPR-based techniques in crop genetic improvement.

Oxford Nanopore and Bionano Genomics technologies evaluation for plant structural variation detection

BACKGROUND

Structural Variations (SVs) are genomic rearrangements derived from duplication, deletion, insertion, inversion, and translocation events. In the past, SVs detection was limited to cytological approaches, then to Next-Generation Sequencing (NGS) short reads and partitioned assemblies. Nowadays, technologies such as DNA long read sequencing and optical mapping have revolutionized the understanding of SVs in genomes, due to the enhancement of the power of SVs detection. This study aims to investigate performance of two techniques, 1) long-read sequencing obtained with the MinION device (Oxford Nanopore Technologies) and 2) optical mapping obtained with Saphyr device (Bionano Genomics) to detect and characterize SVs in the genomes of the two ecotypes of Arabidopsis thaliana, Columbia-0 (Col-0) and Landsberg erecta 1 (Ler-1).

RESULTS

We described the SVs detected from the alignment of the best ONT assembly and DLE-1 optical maps of A. thaliana Ler-1 against the public reference genome Col-0 TAIR10.1. After filtering (SV > 1 kb), 1184 and 591 Ler-1 SVs were retained from ONT and Bionano technologies respectively. A total of 948 Ler-1 ONT SVs (80.1%) corresponded to 563 Bionano SVs (95.3%) leading to 563 common locations. The specific locations were scrutinized to assess improvement in SV detection by either technology. The ONT SVs were mostly detected near TE and gene features, and resistance genes seemed particularly impacted.

CONCLUSIONS

Structural variations linked to ONT sequencing error were removed and false positives limited, with high quality Bionano SVs being conserved. When compared with the Col-0 TAIR10.1 reference genome, most of the detected SVs discovered by both technologies were found in the same locations. ONT assembly sequence leads to more specific SVs than Bionano one, the latter being more efficient to characterize large SVs. Even if both technologies are complementary approaches, ONT data appears to be more adapted to large scale populations studies, while Bionano performs better in improving assembly and describing specificity of a genome compared to a reference.

Nonhomologous end joining as key to CRISPR/Cas-mediated plant chromosome engineering

Although clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas)-mediated gene editing has revolutionized biology and plant breeding, large-scale, heritable restructuring of plant chromosomes is still in its infancy. Duplications and inversions within a chromosome, and also translocations between chromosomes, can now be achieved. Subsequently, genetic linkages can be broken or can be newly created. Also, the order of genes on a chromosome can be changed. While natural chromosomal recombination occurs by homologous recombination during meiosis, CRISPR/Cas-mediated chromosomal rearrangements can be obtained best by harnessing nonhomologous end joining (NHEJ) pathways in somatic cells. NHEJ can be subdivided into the classical (cNHEJ) and alternative NHEJ (aNHEJ) pathways, which partially operate antagonistically. The cNHEJ pathway not only protects broken DNA ends from degradation but also suppresses the joining of previously unlinked broken ends. Hence, in the absence of cNHEJ, more inversions or translocations can be obtained which can be ascribed to the unrestricted use of the aNHEJ pathway for double-strand break (DSB) repair. In contrast to inversions or translocations, short tandem duplications can be produced by paired single-strand breaks via a Cas9 nickase. Interestingly, the cNHEJ pathway is essential for these kinds of duplications, whereas aNHEJ is required for patch insertions that can also be formed during DSB repair. As chromosome engineering has not only been accomplished in the model plant Arabidopsis (Arabidopsis thaliana) but also in the crop maize (Zea mays), we expect that this technology will soon transform the breeding process.

Genome-wide analysis of deletions in maize population reveals abundant genetic diversity and functional impact

Two read depth methods were jointly used in next-generation sequencing data to identify deletions in maize population. GWAS by deletions were analyzed for gene expression pattern and classical traits, respectively. Many studies have confirmed that structural variation (SV) is pervasive throughout the maize genome. Deletion is one type of SV that may impact gene expression and cause phenotypic changes in quantitative traits. In this study, two read count approaches were used to analyze the deletions in the whole-genome sequencing data of 270 maize inbred lines. A total of 19,754 deletion windows overlapped 12,751 genes, which were unevenly distributed across the genome. The deletions explained population structure well and correlated with genomic features. The deletion proportion of genes was determined to be negatively correlated with its expression. The detection of gene expression quantitative trait loci (eQTL) indicated that local eQTL were fewer but had larger effects than distant ones. The common associated genes were related to basic metabolic processes, whereas unique associated genes with eQTL played a role in the stress or stimulus responses in multiple tissues. Compared with the eQTL detected by SNPs derived from the same sequencing data, 89.4% of the associated genes could be detected by both markers. The effect of top eQTL detected by SNPs was usually larger than that detected by deletions for the same gene. A genome-wide association study (GWAS) on flowering time and plant height illustrated that only a few loci could be consistently captured by SNPs, suggesting that combining deletion and SNP for GWAS was an excellent strategy to dissect trait architecture. Our findings will provide insights into characteristic and biological function of genome-wide deletions in maize.

Phenotypic Evaluation and Genetic Analysis of Seedling Emergence in a Global Collection of Wheat Genotypes (Triticum aestivum L.) Under Limited Water Availability

The challenge in establishing an early-sown wheat crop in southern Australia is the need for consistently high seedling emergence when sowing deep in subsoil moisture (>10 cm) or into dry top-soil (4 cm). However, the latter is strongly reliant on a minimum soil water availability to ensure successful seedling emergence. This study aimed to: (1) evaluate 233 Australian and selected international wheat genotypes for consistently high seedling emergence under limited soil water availability when sown in 4 cm of top-soil in field and glasshouse (GH) studies; (2) ascertain genetic loci associated with phenotypic variation using a genome-wide association study (GWAS); and (3) compare across loci for traits controlling coleoptile characteristics, germination, dormancy, and pre-harvest sprouting. Despite significant (P < 0.001) environment and genotype-by-environment interactions within and between field and GH experiments, eight genotypes that included five cultivars, two landraces, and one inbred line had consistently high seedling emergence (mean value > 85%) across nine environments. Moreover, 21 environment-specific quantitative trait loci (QTL) were detected in GWAS analysis on chromosomes 1B, 1D, 2B, 3A, 3B, 4A, 4B, 5B, 5D, and 7D, indicating complex genetic inheritance controlling seedling emergence. We aligned QTL for known traits and individual genes onto the reference genome of wheat and identified 16 QTL for seedling emergence in linkage disequilibrium with coleoptile length, width, and cross-sectional area, pre-harvest sprouting and dormancy, germination, seed longevity, and anthocyanin development. Therefore, it appears that seedling emergence is controlled by multifaceted networks of interrelated genes and traits regulated by different environmental cues.

Deciphering the Genetic Architecture of Plant Virus Resistance by GWAS, State of the Art and Potential Advances

Growing virus resistant varieties is a highly effective means to avoid yield loss due to infection by many types of virus. The challenge is to be able to detect resistance donors within plant species diversity and then quickly introduce alleles conferring resistance into elite genetic backgrounds. Until now, mainly monogenic forms of resistance with major effects have been introduced in crops. Polygenic resistance is harder to map and introduce in susceptible genetic backgrounds, but it is likely more durable. Genome wide association studies (GWAS) offer an opportunity to accelerate mapping of both monogenic and polygenic resistance, but have seldom been implemented and described in the plant-virus interaction context. Yet, all of the 48 plant-virus GWAS published so far have successfully mapped QTLs involved in plant virus resistance. In this review, we analyzed general and specific GWAS issues regarding plant virus resistance. We have identified and described several key steps throughout the GWAS pipeline, from diversity panel assembly to GWAS result analyses. Based on the 48 published articles, we analyzed the impact of each key step on the GWAS power and showcase several GWAS methods tailored to all types of viruses.

High-quality reference genome and annotation aids understanding of berry development for evergreen blueberry (Vaccinium darrowii)

Vaccinium darrowii Camp (2n = 2x = 24) is a native North American blueberry species and an important source of traits such as low chill requirement in commercial southern highbush blueberry breeding (Vaccinium corymbosum, 2n = 4x = 48). We present a chromosomal-scale genome of V. darrowii generated by the combination of PacBio sequencing and high throughput chromatin conformation capture (Hi-C) scaffolding technologies, yielding a total length of 1.06 Gigabases (Gb). Over 97.8% of the genome sequences are scaffolded into 24 chromosomes representing the two haplotypes. The primary haplotype assembly of V. darrowii contains 34,809 protein-coding genes. Comparison to a V. corymbosum haplotype assembly reveals high collinearity between the two genomes with small intrachromosomal rearrangements in eight chromosome pairs. With small RNA sequencing, the annotation was further expanded to include more than 200,000 small RNA loci and 638 microRNAs expressed in berry tissues. Transcriptome analysis across fruit development stages indicates that genes involved in photosynthesis are downregulated, while genes involved in flavonoid and anthocyanin biosynthesis are significantly increased at the late stage of berry ripening. A high-quality reference genome and accompanying annotation of V. darrowii is a significant new resource for assessing the evergreen blueberry contribution to the breeding of southern highbush blueberries.

Intergenic spaces: a new frontier to improving plant health

To more sustainably mitigate the impact of crop diseases on plant health and productivity, there is a need for broader spectrum, long-lasting resistance traits. Defense response (DR) genes, located throughout the genome, participate in cellular and system-wide defense mechanisms to stave off infection by diverse pathogens. This multigenic resistance avoids rapid evolution of a pathogen to overcome host resistance. DR genes reside within resistance-associated quantitative trait loci (QTL), and alleles of DR genes in resistant varieties are more active during pathogen attack relative to susceptible haplotypes. Differential expression of DR genes results from polymorphisms in their regulatory regions, that includes cis-regulatory elements such as transcription factor binding sites as well as features that influence epigenetic structural changes to modulate chromatin accessibility during infection. Many of these elements are found in clusters, known as cis-regulatory modules (CRMs), which are distributed throughout the host genome. Regulatory regions involved in plant-pathogen interactions may also contain pathogen effector binding elements that regulate DR gene expression, and that, when mutated, result in a change in the plants' response. We posit that CRMs and the multiple regulatory elements that comprise them are potential targets for marker-assisted breeding for broad-spectrum, durable disease resistance.

Chromosome identification in oil palm (Elaeis guineensis) using in situ hybridization with massive pools of single copy oligonucleotides and transferability across Arecaceae species

Chromosome identification is essential for linking sequence and chromosomal maps, verifying sequence assemblies, showing structural variations and tracking inheritance or recombination of chromosomes and chromosomal segments during evolution and breeding programs. Unfortunately, identification of individual chromosomes and chromosome arms has been a major challenge for some economically important crop species with a near-continuous chromosome size range and similar morphology. Here, we developed oligonucleotide-based chromosome-specific probes that enabled us to establish a reference chromosome identification system for oil palm (Elaeis guineensis Jacq., 2n = 32). Massive oligonucleotide sequence pools were anchored to individual chromosome arms using dual and triple fluorescent in situ hybridization (EgOligoFISH). Three fluorescently tagged probe libraries were developed to contain, in total 52,506 gene-rich single-copy 47-mer oligonucleotides spanning each 0.2-0.5 Mb across strategically placed chromosome regions. They generated 19 distinct FISH signals and together with rDNA probes enabled identification of all 32 E. guineensis chromosome arms. The probes were able to identify individual homoeologous chromosome regions in the related Arecaceae palm species: American oil palm (Elaeis oleifera), date palm (Phoenix dactylifera) and coconut (Cocos nucifera) showing the comparative organization and concerted evolution of genomes in the Arecaceae. The oligonucleotide probes developed here provide a valuable approach to chromosome arm identification and allow tracking chromosome transfer in hybridization and breeding programs in oil palm, as well as comparative studies within Arecaceae.

Analyses of open-access multi-omics data sets reveal genetic and expression characteristics of maize ZmCCT family genes

Flowering in maize (Zea mays) is influenced by photoperiod. The CO, CO-like/COL and TOC1 (CCT) domain protein-encoding genes in maize, ZmCCTs, are particularly important for photoperiod sensitivity. However, little is known about CCT protein-encoding gene number across plant species or among maize inbred lines. Therefore, we analysed CCT protein-encoding gene number across plant species, and characterized ZmCCTs in different inbred lines, including structural variations (SVs), copy number variations (CNVs), expression under stresses, dark-dark (DD) and dark-light (DL) cycles, interaction network and associations with maize quantitative trait loci (QTLs) by referring to the latest v4 genome data of B73. Gene number varied greatly across plant species, more in polyploids than in diploids. The numbers of ZmCCTs identified were 58 in B73, 59 in W22, 48 in Mo17, and 57 in Huangzao4 for temperate maize inbred lines, and 68 in tropical maize inbred line SK. Some ZmCCTs underwent duplications and presented chromosome collinearity. Structural variations and CNVs were found but they had no germplasm specificity. Forty-two ZmCCTs responded to stresses. Expression of 37 ZmCCTs in embryonic leaves during seed germination of maize under DD and DL cycles was roughly divided into five patterns of uphill pattern, downhill-pattern, zigzag-pattern, └-pattern and ⅃-pattern, indicating some of them have a potential to perceive dark and/or dark-light transition. Thirty-three ZmCCTs were co-expressed with 218 other maize genes; and 24 ZmCCTs were associated with known QTLs. The data presented in this study will help inform further functions of ZmCCTs.

Status and advances in mining for blackleg (Leptosphaeria maculans) quantitative resistance (QR) in oilseed rape (Brassica napus)

KEY MESSAGE

Quantitative resistance (QR) loci discovered through genetic and genomic analyses are abundant in the Brassica napus genome, providing an opportunity for their utilization in enhancing blackleg resistance. Quantitative resistance (QR) has long been utilized to manage blackleg in Brassica napus (canola, oilseed rape), even before major resistance genes (R-genes) were extensively explored in breeding programmes. In contrast to R-gene-mediated qualitative resistance, QR reduces blackleg symptoms rather than completely eliminating the disease. As a polygenic trait, QR is controlled by numerous genes with modest effects, which exerts less pressure on the pathogen to evolve; hence, its effectiveness is more durable compared to R-gene-mediated resistance. Furthermore, combining QR with major R-genes has been shown to enhance resistance against diseases in important crops, including oilseed rape. For these reasons, there has been a renewed interest among breeders in utilizing QR in crop improvement. However, the mechanisms governing QR are largely unknown, limiting its deployment. Advances in genomics are facilitating the dissection of the genetic and molecular underpinnings of QR, resulting in the discovery of several loci and genes that can be potentially deployed to enhance blackleg resistance. Here, we summarize the efforts undertaken to identify blackleg QR loci in oilseed rape using linkage and association analysis. We update the knowledge on the possible mechanisms governing QR and the advances in searching for the underlying genes. Lastly, we lay out strategies to accelerate the genetic improvement of blackleg QR in oilseed rape using improved phenotyping approaches and genomic prediction tools.

High quality haplotype-resolved genome assemblies of Populus tomentosa Carr., a stabilized interspecific hybrid species widespread in Asia

Populus has a wide ecogeographical range spanning the Northern Hemisphere, and interspecific hybrids are common. Populus tomentosa Carr. is widely distributed and cultivated in the eastern region of Asia, where it plays multiple important roles in forestry, agriculture, conservation, and urban horticulture. Reference genomes are available for several Populus species, however, our goals were to produce a very high quality de novo chromosome-level genome assembly in P. tomentosa genome that could serve as a reference for evolutionary and ecological studies of hybrid speciation throughout the genus. Here, combining long-read sequencing and Hi-C scaffolding, we present a high-quality, haplotype-resolved genome assembly. The genome size was 740.2 Mb, with a contig N50 size of 5.47 Mb and a scaffold N50 size of 46.68 Mb, consisting of 38 chromosomes, as expected with the known diploid chromosome number (2n = 2x = 38). A total of 59,124 protein-coding genes were identified. Phylogenomic analyses revealed that P. tomentosa is comprised of two distinct subgenomes, which we deomonstrate is likely to have resulted from hybridization between Populus adenopoda as the female parent and Populus alba var. pyramidalis as the male parent, with an origin of approximately 3.93 Ma. Although highly colinear, significant structural variation was found between the two subgenomes. Our study provides a valuable resource for ecological genetics and forest biotechnology.

Advances in genomics and genome editing for breeding next generation of fruit and nut crops

Fruit tree crops are an essential part of the food production systems and are key to achieve food and nutrition security. Genetic improvement of fruit trees by conventional breeding has been slow due to the long juvenile phase. Advancements in genomics and molecular biology have paved the way for devising novel genetic improvement tools like genome editing, which can accelerate the breeding of these perennial crops to a great extent. In this article, advancements in genomics of fruit trees covering genome sequencing, transcriptome sequencing, genome editing technologies (GET), CRISPR-Cas system based genome editing, potential applications of CRISPR-Cas9 in fruit tree crops improvement, the factors influencing the CRISPR-Cas editing efficiency and the challenges for CRISPR-Cas9 applications in fruit tree crops improvement are reviewed. Besides, base editing, a recently emerging more precise editing system, and the future perspectives of genome editing in the improvement of fruit and nut crops are covered.

Positional-based cloning 'fail-safe' approach is overpowered by wheat chromosome structural variation

Positional-based cloning is a foundational method for understanding the genes and gene networks that control valuable agronomic traits such as grain yield components. In this study, we sought to positionally clone the causal genetic variant of a 1000-grain weight (TGW) quantitative trait loci (QTL) on wheat (Triticum aestivum L.) chromosome arm 5AL. We developed heterogenous inbred families (HIFs) (>5,000 plants) for enhanced genotypic resolution and fine-mapped the QTL to a 10-Mbp region. The transcriptome of developing grains from positive and negative control HIF haplotypes revealed presence-absence chromosome arm 5AS structural variation and unexpectedly no differential expression of genes within the chromosome arm 5AL candidate region. Evaluation of genomic, transcriptomic, and phenotypic data, and predicted function of genes, identified that the 5AL QTL was the result of strong linkage disequilibrium (LD) with chromosome arm 5AS presence or absence (HIF r² = 0.91). Structural variation is common in wheat, and our results highlight that the redundant polyploid genome's masking of such variation is a significant barrier to positional cloning. We propose recommendations for more efficient and robust detection of structural variation, including transitioning from a single nucleotide polymorphism (SNP) to a haplotype-based approach to identify positional cloning targets. We also present nine candidate genes for grain yield components based on chromosome arm 5AS presence or absence, which may unveil hidden variation of homoeolog dosage-dependent genes across the group five chromosome short arms. Taken together, our discovery demonstrates the phenotypic resiliency of polyploid genomic structural variation and highlights a considerable challenge to routine positional cloning in wheat.

Zea mays RNA-seq estimated transcript abundances are strongly affected by read mapping bias

Background

Genetic variation for gene expression is a source of phenotypic variation for natural and agricultural species. The common approach to map and to quantify gene expression from genetically distinct individuals is to assign their RNA-seq reads to a single reference genome. However, RNA-seq reads from alleles dissimilar to this reference genome may fail to map correctly, causing transcript levels to be underestimated. Presently, the extent of this mapping problem is not clear, particularly in highly diverse species. We investigated if mapping bias occurred and if chromosomal features associated with mapping bias. Zea mays presents a model species to assess these questions, given it has genotypically distinct and well-studied genetic lines.

Results

In Zea mays, the inbred B73 genome is the standard reference genome and template for RNA-seq read assignments. In the absence of mapping bias, B73 and a second inbred line, Mo17, would each have an approximately equal number of regulatory alleles that increase gene expression. Remarkably, Mo17 had 2–4 times fewer such positively acting alleles than did B73 when RNA-seq reads were aligned to the B73 reference genome. Reciprocally, over one-half of the B73 alleles that increased gene expression were not detected when reads were aligned to the Mo17 genome template. Genes at dissimilar chromosomal ends were strongly affected by mapping bias, and genes at more similar pericentromeric regions were less affected. Biased transcript estimates were higher in untranslated regions and lower in splice junctions. Bias occurred across software and alignment parameters.

Conclusions

Mapping bias very strongly affects gene transcript abundance estimates in maize, and bias varies across chromosomal features. Individual genome or transcriptome templates are likely necessary for accurate transcript estimation across genetically variable individuals in maize and other species.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07577-3.

A novel deletion in FLOWERING LOCUS T modulates flowering time in winter oilseed rape

A novel structural variant was discovered in the FLOWERING LOCUS T orthologue BnaFT.A02 by long-read sequencing. Nested association mapping in an elite winter oilseed rape population revealed that this 288 bp deletion associates with early flowering, putatively by modification of binding-sites for important flowering regulation genes. Perfect timing of flowering is crucial for optimal pollination and high seed yield. Extensive previous studies of flowering behavior in Brassica napus (canola, rapeseed) identified mutations in key flowering regulators which differentiate winter, semi-winter and spring ecotypes. However, because these are generally fixed in locally adapted genotypes, they have only limited relevance for fine adjustment of flowering time in elite cultivar gene pools. In crosses between ecotypes, the ecotype-specific major-effect mutations mask minor-effect loci of interest for breeding. Here, we investigated flowering time in a multiparental mapping population derived from seven elite winter oilseed rape cultivars which are fixed for major-effect mutations separating winter-type rapeseed from other ecotypes. Association mapping revealed eight genomic regions on chromosomes A02, C02 and C03 associating with fine modulation of flowering time. Long-read genomic resequencing of the seven parental lines identified seven structural variants coinciding with candidate genes for flowering time within chromosome regions associated with flowering time. Segregation patterns for these variants in the elite multiparental population and a diversity set of winter types using locus-specific assays revealed significant associations with flowering time for three deletions on chromosome A02. One of these was a previously undescribed 288 bp deletion within the second intron of FLOWERING LOCUS T on chromosome A02, emphasizing the advantage of long-read sequencing for detection of structural variants in this size range. Detailed analysis revealed the impact of this specific deletion on flowering-time modulation under extreme environments and varying day lengths in elite, winter-type oilseed rape.

Crops of the future: building a climate-resilient plant immune system

A grand challenge facing plant scientists today is to find innovative solutions to increase global crop production in the context of an increasingly warming climate. A major roadblock to global food sufficiency is persistent loss of crops to plant diseases and insect infestations. The United Nations has declared 2020 as the International Year of Plant Health. For historical reasons, molecular studies of plant-biotic interactions in the past several decades have not paid enough attention to how variable climate conditions affect plant-biotic interactions. Here, we highlight a few recent studies that begin to reveal how major climatic drivers impact the plant immune system, particularly secondary messenger and defense hormone signaling, and discuss possible approaches toward engineering climate-resilient plant immunity as part of an ongoing global effort to design 'dream' crops of the future.

Detection of breeding signatures in wheat using a linkage disequilibrium-corrected mapping approach

Marker assisted breeding, facilitated by reference genome assemblies, can help to produce cultivars adapted to changing environmental conditions. However, anomalous linkage disequilibrium (LD), where single markers show high LD with markers on other chromosomes but low LD with adjacent markers, is a serious impediment for genetic studies. We used a LD-correction approach to overcome these drawbacks, correcting the physical position of markers derived from 15 and 135 K arrays in a diversity panel of bread wheat representing 50 years of breeding history. We detected putative mismapping of 11.7% markers and improved the physical alignment of 5.4% markers. Population analysis indicated reduced genetic diversity over time as a result of breeding efforts. By analysis of outlier loci and allele frequency change over time we traced back the 2NS/2AS translocation of Aegilops ventricosa to one cultivar, "Cardos" (registered in 1998) which was the first among the panel to contain this translocation. A "selective sweep" for this important translocation region on chromosome 2AS was found, putatively linked to plant response to biotic stress factors. Our approach helps in overcoming the drawbacks of incorrectly anchored markers on the wheat reference assembly and facilitates detection of selective sweeps for important agronomic traits.

A major quantitative trait locus on chromosome A9, BnaPh1, controls homoeologous recombination in Brassica napus

Ensuring faithful homologous recombination in allopolyploids is essential to maintain optimal fertility of the species. Variation in the ability to control aberrant pairing between homoeologous chromosomes in Brassica napus has been identified. The current study exploited the extremes of such variation to identify genetic factors that differentiate newly resynthesised B. napus, which is inherently unstable, and established B. napus, which has adapted to largely control homoeologous recombination. A segregating B. napus mapping population was analysed utilising both cytogenetic observations and high-throughput genotyping to quantify the levels of homoeologous recombination. Three quantitative trait loci (QTL) were identified that contributed to the control of homoeologous recombination in the important oilseed crop B. napus. One major QTL on BnaA9 contributed between 32 and 58% of the observed variation. This study is the first to assess homoeologous recombination and map associated QTLs resulting from deviations in normal pairing in allotetraploid B. napus. The identified QTL regions suggest candidate meiotic genes that could be manipulated in order to control this important trait and further allow the development of molecular markers to utilise this trait to exploit homoeologous recombination in a crop.

Genomics Armed With Diversity Leads the Way in Brassica Improvement in a Changing Global Environment

Meeting the needs of a growing world population in the face of imminent climate change is a challenge; breeding of vegetable and oilseed Brassica crops is part of the race in meeting these demands. Available genetic diversity constituting the foundation of breeding is essential in plant improvement. Elite varieties, land races, and crop wild species are important resources of useful variation and are available from existing genepools or genebanks. Conservation of diversity in genepools, genebanks, and even the wild is crucial in preventing the loss of variation for future breeding efforts. In addition, the identification of suitable parental lines and alleles is critical in ensuring the development of resilient Brassica crops. During the past two decades, an increasing number of high-quality nuclear and organellar Brassica genomes have been assembled. Whole-genome re-sequencing and the development of pan-genomes are overcoming the limitations of the single reference genome and provide the basis for further exploration. Genomic and complementary omic tools such as microarrays, transcriptomics, epigenetics, and reverse genetics facilitate the study of crop evolution, breeding histories, and the discovery of loci associated with highly sought-after agronomic traits. Furthermore, in genomic selection, predicted breeding values based on phenotype and genome-wide marker scores allow the preselection of promising genotypes, enhancing genetic gains and substantially quickening the breeding cycle. It is clear that genomics, armed with diversity, is set to lead the way in Brassica improvement; however, a multidisciplinary plant breeding approach that includes phenotype = genotype × environment × management interaction will ultimately ensure the selection of resilient Brassica varieties ready for climate change.

CRISPR/Cas-mediated chromosome engineering: opening up a new avenue for plant breeding

The advent of powerful site-specific nucleases, particularly the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas) system, which enables precise genome manipulation, has revolutionized plant breeding. Until recently, the main focus of researchers has been to simply knock-in or knock-out single genes, or to induce single base changes, but constant improvements of this technology have enabled more ambitious applications that aim to improve plant productivity or other desirable traits. One long-standing aim has been the induction of targeted chromosomal rearrangements (crossovers, inversions, or translocations). The feasibility of this technique has the potential to transform plant breeding, because natural rearrangements, like inversions, for example, typically present obstacles to the breeding process. In this way, genetic linkages between traits could be altered to combine or separate favorable and deleterious genes, respectively. In this review, we discuss recent breakthroughs in the field of chromosome engineering in plants and their potential applications in the field of plant breeding. In the future, these approaches might be applicable in shaping plant chromosomes in a directed manner, based on plant breeding needs.

Long-read sequencing reveals widespread intragenic structural variants in a recent allopolyploid crop plant

Genome structural variation (SV) contributes strongly to trait variation in eukaryotic species and may have an even higher functional significance than single-nucleotide polymorphism (SNP). In recent years, there have been a number of studies associating large chromosomal scale SV ranging from hundreds of kilobases all the way up to a few megabases to key agronomic traits in plant genomes. However, there have been little or no efforts towards cataloguing small- (30-10 000 bp) to mid-scale (10 000-30 000 bp) SV and their impact on evolution and adaptation-related traits in plants. This might be attributed to complex and highly duplicated nature of plant genomes, which makes them difficult to assess using high-throughput genome screening methods. Here, we describe how long-read sequencing technologies can overcome this problem, revealing a surprisingly high level of widespread, small- to mid-scale SV in a major allopolyploid crop species, Brassica napus. We found that up to 10% of all genes were affected by small- to mid-scale SV events. Nearly half of these SV events ranged between 100 bp and 1000 bp, which makes them challenging to detect using short-read Illumina sequencing. Examples demonstrating the contribution of such SV towards eco-geographical adaptation and disease resistance in oilseed rape suggest that revisiting complex plant genomes using medium-coverage long-read sequencing might reveal unexpected levels of functional gene variation, with major implications for trait regulation and crop improvement.

GreenPhylDB v5: a comparative pangenomic database for plant genomes

Comparative genomics is the analysis of genomic relationships among different species and serves as a significant base for evolutionary and functional genomic studies. GreenPhylDB (https://www.greenphyl.org) is a database designed to facilitate the exploration of gene families and homologous relationships among plant genomes, including staple crops critically important for global food security. GreenPhylDB is available since 2007, after the release of the Arabidopsis thaliana and Oryza sativa genomes and has undergone multiple releases. With the number of plant genomes currently available, it becomes challenging to select a single reference for comparative genomics studies but there is still a lack of databases taking advantage several genomes by species for orthology detection. GreenPhylDBv5 introduces the concept of comparative pangenomics by harnessing multiple genome sequences by species. We created 19 pangenes and processed them with other species still relying on one genome. In total, 46 plant species were considered to build gene families and predict their homologous relationships through phylogenetic-based analyses. In addition, since the previous publication, we rejuvenated the website and included a new set of original tools including protein-domain combination, tree topologies searches and a section for users to store their own results in order to support community curation efforts.