Multiple Maize Reference Genomes Impact the Identification of Variants by Genome-Wide Association Study in a Diverse Inbred Panel

Genome-wide association mapping in a sweet cherry germplasm collection (Prunus avium L.) reveals candidate genes for fruit quality traits

In sweet cherry (Prunus avium L.), large variability exists for various traits related to fruit quality. There is a need to discover the genetic architecture of these traits in order to enhance the efficiency of breeding strategies for consumer and producer demands. With this objective, a germplasm collection consisting of 116 sweet cherry accessions was evaluated for 23 agronomic fruit quality traits over 2-6 years, and characterized using a genotyping-by-sequencing approach. The SNP coverage collected was used to conduct a genome-wide association study using two multilocus models and three reference genomes. We identified numerous SNP-trait associations for global fruit size (weight, width, and thickness), fruit cracking, fruit firmness, and stone size, and we pinpointed several candidate genes involved in phytohormone, calcium, and cell wall metabolisms. Finally, we conducted a precise literature review focusing on the genetic architecture of fruit quality traits in sweet cherry to compare our results with potential colocalizations of marker-trait associations. This study brings new knowledge of the genetic control of important agronomic traits related to fruit quality, and to the development of marker-assisted selection strategies targeted towards the facilitation of breeding efforts.

Innovative Advances in Plant Genotyping

Over the past decade, advances in plant genotyping have been critical in enabling the identification of genetic diversity, in understanding evolution, and in dissecting important traits in both crops and native plants. The widespread popularity of single-nucleotide polymorphisms (SNPs) has prompted significant improvements to SNP-based genotyping, including SNP arrays, genotyping by sequencing, and whole-genome resequencing. More recent approaches, including genotyping structural variants, utilizing pangenomes to capture species-wide genetic diversity and exploiting machine learning to analyze genotypic data sets, are pushing the boundaries of what plant genotyping can offer. In this chapter, we highlight these innovations and discuss how they will accelerate and advance future genotyping efforts.

Genome-wide association study of quality traits and starch pasting properties of maize kernels

BACKGROUND

Starch are the main nutritional components of maize (Zea mays L.), and starch pasting properties are widely used as essential indicators for quality estimation. Based on the previous studies, various genes related to pasting properties have been identified in maize. However, the loci underlying variations in starch pasting properties in maize inbred lines remain to be identified.

RESULTS

To investigate the genetic architecture of these traits, the starch pasting properties were examined based on 292 maize inbred lines, which were genotyped with the MaizeSNP50 BeadChip composed of 55,126 evenly spaced, random SNPs. A genome-wide association study (GWAS) implemented in the software package FarmCPU was employed to identify genomic loci for the starch pasting properties. 48 SNPs were found to be associated with pasting properties. Moreover, 37 candidate genes were correlated with pasting properties. Among the candidate genes, GRMZM2G143646 and GRMZM2G166407 were associated with breakdown and final viscosity significantly, and both genes encode PPR (Pentatricopeptide repeat) protein. We used GWAS to explore candidate genes of maize starch pasting properties in this study. The identified candidate genes will be useful for further understanding of the genetic architecture of starch pasting properties in maize.

CONCLUSION

This study showed a complex regulation network about maize quality trait and starch pasting properties. It may provide some useful markers for marker assisted selection and a basis for cloning the genes behind these SNPs.

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.

Integrating advancements in root phenotyping and genome-wide association studies to open the root genetics gateway

Plant adaptation to challenging environmental conditions around the world has made root growth and development an important research area for plant breeders and scientists. Targeted manipulation of root system architecture (RSA) to increase water and nutrient use efficiency can minimize the adverse effects of climate change on crop production. However, phenotyping of RSA is a major bottleneck since the roots are hidden in the soil. Recently the development of 2- and 3D root imaging techniques combined with the genome-wide association studies (GWASs) have opened up new research tools to identify the genetic basis of RSA. These approaches provide a comprehensive understanding of the RSA, by accelerating the identification and characterization of genes involved in root growth and development. This review summarizes the latest developments in phenotyping techniques and GWAS for RSA, which are used to map important genes regulating various aspects of RSA under varying environmental conditions. Furthermore, we discussed about the state-of-the-art image analysis tools integrated with various phenotyping platforms for investigating and quantifying root traits with the highest phenotypic plasticity in both artificial and natural environments which were used for large scale association mapping studies, leading to the identification of RSA phenotypes and their underlying genetics with the greatest potential for RSA improvement. In addition, challenges in root phenotyping and GWAS are also highlighted, along with future research directions employing machine learning and pan-genomics approaches.

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.

A setback into a success: what can batch effects tell us about best practices in genomics?

The increasing access to high-throughput sequencing is certainly one of the major changes that molecular ecology has gone through over the last decade. With the positive trend towards more open science, most sequencing datasets are now available on public databases, which holds amazing potential, but also risks of introducing batch effects in studies combining datasets. In this issue of Molecular Ecology Resources, Lou & Therkildsen (2022) offer a timely discussion on the matter by analyzing an imperfect low-coverage Whole Genome Sequencing dataset, in which they test the effects of differences in sequencing choices, DNA degradation, and read depth on routine population genomics analyses. Through a series of diagnostic tools, they uncover multiple factors producing technical artefacts that can bias estimates of genetic diversity, inference of population structure, and selection scans. For each confounding factor, they demonstrate the effectiveness of mitigation approaches and suggest other avenues to deal with the issue. In this perspective, we highlight considerations regarding (1) effects that arise from differences between batches of sequencing, (2) unavoidable heterogeneity within datasets, and (3) more general concerns around the use of next-generation sequencing in population genomics. Altogether, by exploring what may have appeared at first glimpse as a "failed" sequencing project, Lou & Therkildsen (2022) end up setting a standard of best practices to make the most of heterogeneous whole-genome sequences, opening a promising avenue towards efficient reuse of published datasets.

Quantitative Resistance Loci to Southern Rust Mapped in a Temperate Maize Diversity Panel

Southern rust is a severe foliar disease of maize (Zea mays) resulting from infection with the obligate biotrophic fungus Puccinia polysora. This disease reduces photosynthetic productivity, which in turn reduces yields, with the greatest yield losses (up to 50%) associated with earlier onset infections. P. polysora urediniospores overwinter only in tropical and subtropical regions but cause outbreaks when environmental conditions favor initial infection. Increased temperatures and humidity during the growing season combined with an increased frequency of moderate winters are likely to increase the frequency of severe southern rust outbreaks in the U.S. Corn Belt. In summer 2020, a severe outbreak of southern rust was observed in eastern Nebraska, United States. We scored a replicated maize association panel planted in Lincoln, NE for disease severity and found that disease incidence and severity showed significant variation among maize genotypes. Genome-wide association studies identified four loci associated with significant quantitative variation in disease severity. These loci were associated with candidate genes with plausible links to quantitative disease resistance. A transcriptome-wide association study identified additional genes associated with disease severity. Together, these results indicate that substantial diversity in resistance to southern rust exists among current temperate-adapted maize germplasm, including several candidate loci that may explain the observed variation in resistance to southern rust.[Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Pangenomes as a Resource to Accelerate Breeding of Under-Utilised Crop Species

Pangenomes are a rich resource to examine the genomic variation observed within a species or genera, supporting population genetics studies, with applications for the improvement of crop traits. Major crop species such as maize (Zea mays), rice (Oryza sativa), Brassica (Brassica spp.), and soybean (Glycine max) have had pangenomes constructed and released, and this has led to the discovery of valuable genes associated with disease resistance and yield components. However, pangenome data are not available for many less prominent crop species that are currently under-utilised. Despite many under-utilised species being important food sources in regional populations, the scarcity of genomic data for these species hinders their improvement. Here, we assess several under-utilised crops and review the pangenome approaches that could be used to build resources for their improvement. Many of these under-utilised crops are cultivated in arid or semi-arid environments, suggesting that novel genes related to drought tolerance may be identified and used for introgression into related major crop species. In addition, we discuss how previously collected data could be used to enrich pangenome functional analysis in genome-wide association studies (GWAS) based on studies in major crops. Considering the technological advances in genome sequencing, pangenome references for under-utilised species are becoming more obtainable, offering the opportunity to identify novel genes related to agro-morphological traits in these species.

Comparative Analysis of Genotyping by Sequencing and Whole-Genome Sequencing Methods in Diversity Studies of Olea europaea L

Olive, Olea europaea L., is a tree of great economic and cultural importance in the Mediterranean basin. Thousands of cultivars have been described, of which around 1200 are conserved in the different olive germplasm banks. The genetic characterisation of these cultivars can be performed in different ways. Whole-genome sequencing (WGS) provides more information than the reduced representation methods such as genotype by sequencing (GBS), but at a much higher cost. This may change as the cost of sequencing continues to drop, but, currently, genotyping hundreds of cultivars using WGS is not a realistic goal for most research groups. Our aim is to systematically compare both methodologies applied to olive genotyping and summarise any possible recommendations for the geneticists and molecular breeders of the olive scientific community. In this work, we used a selection of 24 cultivars from an olive core collection from the World Olive Germplasm Collection of the Andalusian Institute of Agricultural and Fisheries Research and Training (WOGBC), which represent the most of the cultivars present in cultivated fields over the world. Our results show that both methodologies deliver similar results in the context of phylogenetic analysis and popular population genetic analysis methods such as clustering. Furthermore, WGS and GBS datasets from different experiments can be merged in a single dataset to perform these analytical methodologies with proper filtering. We also tested the influence of the different olive reference genomes in this type of analysis, finding that they have almost no effect when estimating genetic relationships. This work represents the first comparative study between both sequencing techniques in olive. Our results demonstrate that the use of GBS is a perfectly viable option for replacing WGS and reducing research costs when the goal of the experiment is to characterise the genetic relationship between different accessions. Besides this, we show that it is possible to combine variants from GBS and WGS datasets, allowing the reuse of publicly available data.

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.

Genomic variation within the maize stiff-stalk heterotic germplasm pool

The stiff-stalk heterotic group in Maize (Zea mays L.) is an important source of inbreds used in U.S. commercial hybrid production. Founder inbreds B14, B37, B73, and, to a lesser extent, B84, are found in the pedigrees of a majority of commercial seed parent inbred lines. We created high-quality genome assemblies of B84 and four expired Plant Variety Protection (ex-PVP) lines LH145 representing B14, NKH8431 of mixed descent, PHB47 representing B37, and PHJ40, which is a Pioneer Hi-Bred International (PHI) early stiff-stalk type. Sequence was generated using long-read sequencing achieving highly contiguous assemblies of 2.13-2.18 Gbp with N50 scaffold lengths >200 Mbp. Inbred-specific gene annotations were generated using a core five-tissue gene expression atlas, whereas transposable element (TE) annotation was conducted using de novo and homology-directed methodologies. Compared with the reference inbred B73, synteny analyses revealed extensive collinearity across the five stiff-stalk genomes, although unique components of the maize pangenome were detected. Comparison of this set of stiff-stalk inbreds with the original Iowa Stiff Stalk Synthetic breeding population revealed that these inbreds represent only a proportion of variation in the original stiff-stalk pool and there are highly conserved haplotypes in released public and ex-Plant Variety Protection inbreds. Despite the reduction in variation from the original stiff-stalk population, substantial genetic and genomic variation was identified supporting the potential for continued breeding success in this pool. The assemblies described here represent stiff-stalk inbreds that have historical and commercial relevance and provide further insight into the emerging maize pangenome.

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

Comparative Genomics of Eight Fusarium graminearum Strains with Contrasting Aggressiveness Reveals an Expanded Open Pangenome and Extended Effector Content Signatures

Fusarium graminearum, the primary cause of Fusarium head blight (FHB) in small-grain cereals, demonstrates remarkably variable levels of aggressiveness in its host, producing different infection dynamics and contrasted symptom severity. While the secreted proteins, including effectors, are thought to be one of the essential components of aggressiveness, our knowledge of the intra-species genomic diversity of F. graminearum is still limited. In this work, we sequenced eight European F. graminearum strains of contrasting aggressiveness to characterize their respective genome structure, their gene content and to delineate their specificities. By combining the available sequences of 12 other F. graminearum strains, we outlined a reference pangenome that expands the repertoire of the known genes in the reference PH-1 genome by 32%, including nearly 21,000 non-redundant sequences and gathering a common base of 9250 conserved core-genes. More than 1000 genes with high non-synonymous mutation rates may be under diverse selection, especially regarding the trichothecene biosynthesis gene cluster. About 900 secreted protein clusters (SPCs) have been described. Mostly localized in the fast sub-genome of F. graminearum supposed to evolve rapidly to promote adaptation and rapid responses to the host's infection, these SPCs gather a range of putative proteinaceous effectors systematically found in the core secretome, with the chloroplast and the plant nucleus as the main predicted targets in the host cell. This work describes new knowledge on the intra-species diversity in F. graminearum and emphasizes putative determinants of aggressiveness, providing a wealth of new candidate genes potentially involved in the Fusarium head blight disease.

How the pan-genome is changing crop genomics and improvement

Crop genomics has seen dramatic advances in recent years due to improvements in sequencing technology, assembly methods, and computational resources. These advances have led to the development of new tools to facilitate crop improvement. The study of structural variation within species and the characterization of the pan-genome has revealed extensive genome content variation among individuals within a species that is paradigm shifting to crop genomics and improvement. Here, we review advances in crop genomics and how utilization of these tools is shifting in light of pan-genomes that are becoming available for many crop species.

Genome Size Variation and Comparative Genomics Reveal Intraspecific Diversity in Brassica rapa

Traditionally, reference genomes in crop species rely on the assembly of one accession, thus occulting most of intraspecific diversity. However, rearrangements, gene duplications, and transposable element content may have a large impact on the genomic structure, which could generate new phenotypic traits. Comparing two Brassica rapa genomes recently sequenced and assembled using long-read technology and optical mapping, we investigated structural variants and repetitive content between the two accessions and genome size variation among a core collection. We explored the structural consequences of the presence of large repeated sequences in B. rapa 'Z1' genome vs. the B. rapa 'Chiifu' genome, using comparative genomics and cytogenetic approaches. First, we showed that large genomic variants on chromosomes A05, A06, A09, and A10 are due to large insertions and inversions when comparing B. rapa 'Z1' and B. rapa 'Chiifu' at the origin of important length differences in some chromosomes. For instance, lengths of 'Z1' and 'Chiifu' A06 chromosomes were estimated in silico to be 55 and 29 Mb, respectively. To validate these observations, we compared using fluorescent in situ hybridization (FISH) the two A06 chromosomes present in an F1 hybrid produced by crossing these two varieties. We confirmed a length difference of 17.6% between the A06 chromosomes of 'Z1' compared to 'Chiifu.' Alternatively, using a copy number variation approach, we were able to quantify the presence of a higher number of rDNA and gypsy elements in 'Z1' genome compared to 'Chiifu' on different chromosomes including A06. Using flow cytometry, the total genome size of 12 Brassica accessions corresponding to a B. rapa available core collection was estimated and revealed a genome size variation of up to 16% between these accessions as well as some shared inversions. This study revealed the contribution of long-read sequencing of new accessions belonging to different cultigroups of B. rapa and highlighted the potential impact of differential insertion of repeat elements and inversions of large genomic regions in genome size intraspecific variability.

Pangenomics Comes of Age: From Bacteria to Plant and Animal Applications

The pangenome refers to a collection of genomic sequence found in the entire species or population rather than in a single individual; the sequence can be core, present in all individuals, or accessory (variable or dispensable), found in a subset of individuals only. While pangenomic studies were first undertaken in bacterial species, developments in genome sequencing and assembly approaches have allowed construction of pangenomes for eukaryotic organisms, fungi, plants, and animals, including two large-scale human pangenome projects. Analysis of the these pangenomes revealed key differences, most likely stemming from divergent evolutionary histories, but also surprising similarities.