Integrated QTL mapping, gene expression and nucleotide variation analyses to investigate complex quantitative traits: a case study with the soybean-Phytophthora sojae interaction

Functional characterization of four soybean C2H2 zinc-finger genes in Phytophthora resistance

Soybean (Glycine max) is one of the most important industrial and oilseed crops; however, the yield is threatened by the invasion of various pathogens. Soybean stem and root rot, caused by Phytophthora sojae, is a destructive disease that significantly damages soybean production worldwide. C2H2 zinc finger protein (C2H2-ZFP) is a large transcription factor family in plants that plays crucial roles in stress response and hormone signal transduction. Given its importance, we analyzed the expression patterns of C2H2-ZFP family genes in response to P. sojae infection and selected four candidate genes to explore their molecular characteristics and functions related to P. sojae resistance. Subcellular localization analysis indicated that three ZFPs (GmZFP2, GmZFP3, and GmZFP4) were localized in the nucleus, while GmZFP1 was found in both the nucleus and plasma membrane. Dual-luciferase transient expression analysis revealed that all four ZFPs possessed transcriptional repression activation. Further transient expression in N. benthamiana leaves demonstrated that GmZFP2 induced significant cell death and reactive oxygen species (ROS) accumulation. GmZFP2 significantly enhanced the resistance to Phytophthora pathogens in N. benthamiana leaves and soybean hairy roots. This study provides insights in to the functional characterization of soybean ZFPs in Phytophthora resistance and demonstrates that GmZFP2 plays a positive role in P. sojae resistance in soybeans.

Integrating targeted genetic markers to genotyping-by-sequencing for an ultimate genotyping tool

New selection methods, using trait-specific markers (marker-assisted selection (MAS)) and/or genome-wide markers (genomic selection (GS)), are becoming increasingly widespread in breeding programs. This new era requires innovative and cost-efficient solutions for genotyping. Reduction in sequencing cost has enhanced the use of high-throughput low-cost genotyping methods such as genotyping-by-sequencing (GBS) for genome-wide single-nucleotide polymorphism (SNP) profiling in large breeding populations. However, the major weakness of GBS methodologies is their inability to genotype targeted markers. Conversely, targeted methods, such as amplicon sequencing (AmpSeq), often face cost constraints, hindering genome-wide genotyping across a large cohort. Although GBS and AmpSeq data can be generated from the same sample, an efficient method to achieve this is lacking. In this study, we present the Genome-wide & Targeted Amplicon (GTA) genotyping platform, an innovative way to integrate multiplex targeted amplicons into the GBS library preparation to provide an all-in-one cost-effective genotyping solution to breeders and research communities. Custom primers were designed to target 23 and 36 high-value markers associated with key agronomical traits in soybean and barley, respectively. The resulting multiplex amplicons were compatible with the GBS library preparation enabling both GBS and targeted genotyping data to be produced efficiently and cost-effectively. To facilitate data analysis, we have introduced Fast-GBS.v3, a user-friendly bioinformatic pipeline that generates comprehensive outputs from data obtained following sequencing of GTA libraries. This high-throughput low-cost approach will greatly facilitate the application of DNA markers as it provides required markers for both MAS and GS in a single assay.

3D-GBS: a universal genotyping-by-sequencing approach for genomic selection and other high-throughput low-cost applications in species with small to medium-sized genomes

Despite the increased efficiency of sequencing technologies and the development of reduced-representation sequencing (RRS) approaches allowing high-throughput sequencing (HTS) of multiplexed samples, the per-sample genotyping cost remains the most limiting factor in the context of large-scale studies. For example, in the context of genomic selection (GS), breeders need genome-wide markers to predict the breeding value of large cohorts of progenies, requiring the genotyping of thousands candidates. Here, we introduce 3D-GBS, an optimized GBS procedure, to provide an ultra-high-throughput and ultra-low-cost genotyping solution for species with small to medium-sized genome and illustrate its use in soybean. Using a combination of three restriction enzymes (PstI/NsiI/MspI), the portion of the genome that is captured was reduced fourfold (compared to a "standard" ApeKI-based protocol) while reducing the number of markers by only 40%. By better focusing the sequencing effort on limited set of restriction fragments, fourfold more samples can be genotyped at the same minimal depth of coverage. This GBS protocol also resulted in a lower proportion of missing data and provided a more uniform distribution of SNPs across the genome. Moreover, we investigated the optimal number of reads per sample needed to obtain an adequate number of markers for GS and QTL mapping (500-1000 markers per biparental cross). This optimization allows sequencing costs to be decreased by ~ 92% and ~ 86% for GS and QTL mapping studies, respectively, compared to previously published work. Overall, 3D-GBS represents a unique and affordable solution for applications requiring extremely high-throughput genotyping where cost remains the most limiting factor.

Progress and prospectus in genetics and genomics of Phytophthora root and stem rot resistance in soybean (Glycine max L.)

Soybean is one of the largest sources of protein and oil in the world and is also considered a "super crop" due to several industrial advantages. However, enhanced acreage and adoption of monoculture practices rendered the crop vulnerable to several diseases. Phytophthora root and stem rot (PRSR) caused by Phytophthora sojae is one of the most prevalent diseases adversely affecting soybean production globally. Deployment of genetic resistance is the most sustainable approach for avoiding yield losses due to this disease. PRSR resistance is complex in nature and difficult to address by conventional breeding alone. Genetic mapping through a cost-effective sequencing platform facilitates identification of candidate genes and associated molecular markers for genetic improvement against PRSR. Furthermore, with the help of novel genomic approaches, identification and functional characterization of Rps (resistance to Phytophthora sojae) have also progressed in the recent past, and more than 30 Rps genes imparting complete resistance to different PRSR pathotypes have been reported. In addition, many genomic regions imparting partial resistance have also been identified. Furthermore, the adoption of emerging approaches like genome editing, genomic-assisted breeding, and genomic selection can assist in the functional characterization of novel genes and their rapid introgression for PRSR resistance. Hence, in the near future, soybean growers will likely witness an increase in production by adopting PRSR-resistant cultivars. This review highlights the progress made in deciphering the genetic architecture of PRSR resistance, genomic advances, and future perspectives for the deployment of PRSR resistance in soybean for the sustainable management of PRSR disease.

Breeding for disease resistance in soybean: a global perspective

KEY MESSAGE

This review provides a comprehensive atlas of QTLs, genes, and alleles conferring resistance to 28 important diseases in all major soybean production regions in the world. Breeding disease-resistant soybean [Glycine max (L.) Merr.] varieties is a common goal for soybean breeding programs to ensure the sustainability and growth of soybean production worldwide. However, due to global climate change, soybean breeders are facing strong challenges to defeat diseases. Marker-assisted selection and genomic selection have been demonstrated to be successful methods in quickly integrating vertical resistance or horizontal resistance into improved soybean varieties, where vertical resistance refers to R genes and major effect QTLs, and horizontal resistance is a combination of major and minor effect genes or QTLs. This review summarized more than 800 resistant loci/alleles and their tightly linked markers for 28 soybean diseases worldwide, caused by nematodes, oomycetes, fungi, bacteria, and viruses. The major breakthroughs in the discovery of disease resistance gene atlas of soybean were also emphasized which include: (1) identification and characterization of vertical resistance genes reside rhg1 and Rhg4 for soybean cyst nematode, and exploration of the underlying regulation mechanisms through copy number variation and (2) map-based cloning and characterization of Rps11 conferring resistance to 80% isolates of Phytophthora sojae across the USA. In this review, we also highlight the validated QTLs in overlapping genomic regions from at least two studies and applied a consistent naming nomenclature for these QTLs. Our review provides a comprehensive summary of important resistant genes/QTLs and can be used as a toolbox for soybean improvement. Finally, the summarized genetic knowledge sheds light on future directions of accelerated soybean breeding and translational genomics studies.

RXLR effector gene Avr3a from Phytophthora sojae is recognized by Rps8 in soybean

The use of resistance genes in elite soybean cultivars is one of the most widely used methods to manage Phytophthora sojae. This method relies on effector-triggered immunity, where a Resistant to P. sojae (Rps) gene product from the plant recognizes a specific effector from the pathogen, encoded by an avirulence (Avr) gene. Many Avr genes from P. sojae have been identified in the last decade, allowing a better exploitation of this type of resistance. The objective of the present study was to identify the Avr gene triggering immunity derived from the soybean resistance gene Rps8. The analysis of a segregating F2 progeny coupled with a genotyping-by-sequencing approach led to the identification of a putative Avr8 locus. The investigation of this locus using whole-genome sequencing data from 31 isolates of P. sojae identified Avr3a as the likely candidate for Avr8. Long-read sequencing also revealed that P. sojae isolates can carry up to five copies of the Avr3a gene, compared to the four previously reported. Haplotype and transcriptional analyses showed that amino acid changes and absence of Avr3a transcripts from P. sojae isolates caused changes in virulence towards Rps8. Functional analyses using CRISPR/Cas9 knockout and constitutive expression demonstrated that Rps8 interacted with Avr3a. We also showed that a specific allele of Avr3a is recognized by Rps3a but not Rps8. While Rps3a and Rps8 have been previously described as closely linked, this is the first report of a clear distinction hitherto undefined between these two resistance genes.

The SoyaGen Project: Putting Genomics to Work for Soybean Breeders

The SoyaGen project was a collaborative endeavor involving Canadian soybean researchers and breeders from academia and the private sector as well as international collaborators. Its aims were to develop genomics-derived solutions to real-world challenges faced by breeders. Based on the needs expressed by the stakeholders, the research efforts were focused on maximizing realized yield through optimization of maturity and improved disease resistance. The main deliverables related to molecular breeding in soybean will be reviewed here. These include: (1) SNP datasets capturing the genetic diversity within cultivated soybean (both within a worldwide collection of > 1,000 soybean accessions and a subset of 102 short-season accessions (MG0 and earlier) directly relevant to this group); (2) SNP markers for selecting favorable alleles at key maturity genes as well as loci associated with increased resistance to key pathogens and pests (Phytophthora sojae, Heterodera glycines, Sclerotinia sclerotiorum); (3) diagnostic tools to facilitate the identification and mapping of specific pathotypes of P. sojae; and (4) a genomic prediction approach to identify the most promising combinations of parents. As a result of this fruitful collaboration, breeders have gained new tools and approaches to implement molecular, genomics-informed breeding strategies. We believe these tools and approaches are broadly applicable to soybean breeding efforts around the world.

Comprehensive Analysis of Cytochrome P450 Monooxygenases Reveals Insight Into Their Role in Partial Resistance Against Phytophthora sojae in Soybean

Cytochrome P450 monooxygenases (P450) participate in the catalytic conversion of biological compounds in a plethora of metabolic pathways, such as the biosynthesis of alkaloids, terpenoids, phenylpropanoids, and hormones in plants. Plants utilize these metabolites for growth and defense against biotic and abiotic stress. In this study, we identified 346 P450 (GmP450) enzymes encoded by 317 genes in soybean where 26 GmP450 genes produced splice variants. The genome-wide comparison of both A-type and non-A-type GmP450s for their motifs composition, gene structure, tissue-specific expression, and their chromosomal distribution were determined. Even though conserved P450 signature motifs were found in all GmP450 families, larger variation within a specific motif was observed in the non-A-type GmP450s as compared with the A-type. Here, we report that the length of variable region between two conserved motifs is exact in the members of the same family in majority of the A-type GmP450. Analyses of the transcriptomic datasets from soybean-Phytophthora sojae interaction studies, quantitative trait loci (QTL) associated with P. sojae resistance, and co-expression analysis identified some GmP450s that may be, in part, play an important role in partial resistance against P. sojae. The findings of our CYPome study provides novel insights into the functions of GmP450s and their involvements in metabolic pathways in soybean. Further experiments will elucidate their roles in general and legume-specific function.

Mapping of partial resistance to Phytophthora sojae in soybean PIs using whole-genome sequencing reveals a major QTL

In the last decade, more than 70 quantitative trait loci (QTL) related to soybean [Glycine max (L.) Merr.] partial resistance (PR) against Phytophthora sojae have been identified by genome-wide association studies (GWAS). However, most of them have either a minor effect on the resistance level or are specific to a single phenotypic variable or one isolate, thereby limiting their use in breeding programs. In this study, we have used an analytical approach combining (a) the phenotypic characterization of a diverse panel of 357 soybean accessions for resistance to P. sojae captured through a single variable, corrected dry weight; (b) a new hydroponic assay allowing the inoculation of a combination of P. sojae isolates covering the spectrum of commercially relevant Rps genes; and (c) exhaustive genotyping through whole-genome resequencing (WGS). This led to the identification of a novel P. sojae resistance QTL with a relatively major effect compared with the previously reported QTL. The QTL interval, spanning ∼500 kb on chromosome (Chr) 15, does not colocalize with previously reported QTL for P. sojae resistance. Plants carrying the favorable allele at this QTL were 60% more resistant. Eight genes were found to reside in the linkage disequilibrium (LD) block containing the peak single-nucleotide polymorphism (SNP) including Glyma.15G217100, which encodes a major latex protein (MLP)-like protein, with a functional annotation related to pathogen resistance. Expression analysis of Glyma.15G217100 indicated that it was nearly eight times more highly expressed in a group of plant introductions (PIs) carrying the resistant (R) allele compared with those carrying the susceptible (S) allele within a short period after inoculation. These results offer new and valuable options to develop improved soybean cultivars with broad resistance to P. sojae through marker-assisted selection.

Integrating omics approaches to discover and prioritize candidate genes involved in oil biosynthesis in soybean

Soybean is a major source of edible protein and oil. Oil content is a quantitative trait that is significantly determined by genetic and environmental factors. Over the past 30 years, a large volume of soybean genetic, genomic, and transcriptomic data have been accumulated. Nevertheless, integrative analyses of such data remain scarce, in spite of their importance for crop improvement. We hypothesized that the co-occurrence of genomic regions for oil-related traits in different studies may reveal more stable regions encompassing important genetic determinants of oil content and quality in soybean. We integrated publicly available data, obtained with distinct techniques, to discover and prioritize candidate genes involved in oil biosynthesis and regulation in soybean. We detected key fatty acid biosynthesis genes (e.g., BCCP2 and ACCase, FADs, KAS family proteins) and several transcription factors, which are likely regulators of oil biosynthesis. In addition, we identified new candidates for seed oil accumulation and quality, such as Glyma.03G213300 and Glyma.19G160700, which encode a translocator protein homolog and a histone acetyltransferase, respectively. Further, oil and protein genomic hotspots are strongly associated with breeding and not with domestication, suggesting that soybean domestication prioritized other traits. The genes identified here are promising targets for breeding programs and for the development of soybean lines with increased oil content and quality.

Identification and candidate gene screening of qCIR9.1, a novel QTL associated with anther culturability in rice (Oryza sativa L.)

A novel QTL, qCIR9.1, that controls callus induction rate in anther culture was identified on chromosome 9 in rice, and based on RNA-seq data, Os09g0551600 was the most promising candidate gene. Anther culture, a doubled haploid (DH) technique, has become an important technology in many plant-breeding programmes. Although anther culturability is the key factor in this technique, its genetic mechanisms in rice remain poorly understood. In this study, we mapped quantitative trait loci (QTLs) responsible for anther culturability by using 192 recombinant inbred lines (RILs) derived from YZX (Oryza sativa ssp. indica) × 02428 (Oryza sativa ssp. japonica) and a high-density bin map. A total of eight QTLs for anther culturability were detected in three environments. Among these QTLs, a novel major QTL for callus induction rate (CIR) named qCIR9.1 was repeatedly mapped to a ~ 100 kb genomic interval on chromosome 9 and explained 8.39-14.14% of the phenotypic variation. Additionally, RNA sequencing (RNA-seq) was performed for the parents (YZX and 02428), low- (L-Pool) and high-CIR RILs (H-Pool) after 16 and 26 days of culture. By using the RNA of the bulked RILs for background normalization, the number of differentially expressed genes (DEGs) both between the parents and between the bulked RILs after 26 days of culture was drastically reduced to only 78. Among these DEGs, only one gene, Os09g0551600, encoding a high-mobility group (HMG) protein, was located in the candidate region of qCIR9.1. qRT-PCR analysis of Os09g0551600 showed the same results as RNA-seq, and the expression of this gene was decreased in the low-callus-induction parent (YZX) and L-Pool. Our results provide a foundational step for further cloning of qCIR9.1 and will be very useful for improving anther culturability in rice.

A High-Throughput Phenotyping Tool to Identify Field-Relevant Anthracnose Resistance in White Lupin

The seed- and air-borne pathogen Colletotrichum lupini, the causal agent of lupin anthracnose, is the most important disease in white lupin (Lupinus albus) worldwide and can cause total yield loss. The aims of this study were to establish a reliable high-throughput phenotyping tool to identify anthracnose resistance in white lupin germplasm and to evaluate a genomic prediction model, accounting for previously reported resistance quantitative trait loci, on a set of independent lupin genotypes. Phenotyping under controlled conditions, performing stem inoculation on seedlings, showed to be applicable for high throughput, and its disease score strongly correlated with field plot disease assessments (r = 0.95, P < 0.0001) and yield (r = -0.64, P = 0.035). Traditional one-row field disease phenotyping showed no significant correlation with field plot disease assessments (r = 0.31, P = 0.34) and yield (r = -0.45, P = 0.17). Genomically predicted resistance values showed no correlation with values observed under controlled or field conditions, and the parental lines of the recombinant inbred line population used for constructing the prediction model exhibited a resistance pattern opposite to that displayed in the original (Australian) environment used for model construction. Differing environmental conditions, inoculation procedures, or population structure may account for this result. Phenotyping a diverse set of 40 white lupin accessions under controlled conditions revealed eight accessions with improved resistance to anthracnose. The standardized area under the disease progress curves (sAUDPC) ranged from 2.1 to 2.8, compared with the susceptible reference accession with a sAUDPC of 3.85. These accessions can be incorporated into white lupin breeding programs. In conclusion, our data support stem inoculation-based disease phenotyping under controlled conditions as a time-effective approach to identify field-relevant resistance, which can now be applied to further identify sources of resistance and their underlying genetics.