Single-plant GWAS coupled with bulk segregant analysis allows rapid identification and corroboration of plant-height candidate SNPs

Analyzing genetic diversity in luffa and developing a Fusarium wilt-susceptible linked SNP marker through a single plant genome-wide association (sp-GWAS) study

BACKGROUND

Luffa (Luffa spp.) is an economically important crop of the Cucurbitaceae family, commonly known as sponge gourd or vegetable gourd. It is an annual cross-pollinated crop primarily found in the subtropical and tropical regions of Asia, Australia, Africa, and the Americas. Luffa serves not only as a vegetable but also exhibits medicinal properties, including anti-inflammatory, antidiabetic, and anticancer effects. Moreover, the fiber derived from luffa finds extensive applications in various fields such as biotechnology and construction. However, luffa Fusarium wilt poses a severe threat to its production, and existing control methods have proven ineffective in terms of cost-effectiveness and environmental considerations. Therefore, there is an urgent need to develop luffa varieties resistant to Fusarium wilt. Single-plant GWAS (sp-GWAS) has been demonstrated as a promising tool for the rapid and efficient identification of quantitative trait loci (QTLs) associated with target traits, as well as closely linked molecular markers.

RESULTS

In this study, a collection of 97 individuals from 73 luffa accessions including two major luffa species underwent single-plant GWAS to investigate luffa Fusarium wilt resistance. Utilizing the double digest restriction site associated DNA (ddRAD) method, a total of 8,919 high-quality single nucleotide polymorphisms (SNPs) were identified. The analysis revealed the potential for Fusarium wilt resistance in accessions from both luffa species. There are 6 QTLs identified from 3 traits, including the area under the disease progress curve (AUDPC), a putative disease-resistant QTL, was identified on the second chromosome of luffa. Within the region of linkage disequilibrium, a candidate gene homologous to LOC111009722, which encodes peroxidase 40 and is associated with disease resistance in Cucumis melo, was identified. Furthermore, to validate the applicability of the marker associated with resistance from sp-GWAS, an additional set of 21 individual luffa plants were tested, exhibiting 93.75% accuracy in detecting susceptible of luffa species L. aegyptiaca Mill.

CONCLUSION

In summary, these findings give a hint of genome position that may contribute to luffa wild resistance to Fusarium and can be utilized in the future luffa wilt resistant breeding programs aimed at developing wilt-resistant varieties by using the susceptible-linked SNP marker.

Extreme trait GWAS (Et-GWAS): Unraveling rare variants in the 3,000 rice genome

Identifying high-impact, rare genetic variants associated with specific traits is crucial for crop improvement. The 3,010 rice genome (3K RG) dataset offers a valuable resource for discovering genomic regions with potential applications in crop breeding. We used Extreme Trait GWAS (Et-GWAS), employing bulk pooling and allele frequency measurement to efficiently extract rare variants from the 3K RG. This innovative approach facilitates the detection of associations between genetic variants and target traits, concentrating and quantifying rare alleles. In our study, on grain yield under drought stress, Et-GWAS successfully identified five key genes (OsPP2C11, OsK5.2, OsIRO2, OsPEX1, and OsPWA1) known for enhancing yield under drought. In addition, we examined the overlap of our results with previously reported qDTY-QTLs and observed that OsUCH1 and OsUCH2 genes were located within qDTY2.2 We compared Et-GWAS with conventional GWAS, finding it effectively capturing most candidate genes associated with the target trait. Validation with resistant starch showed similar results. To enhance user-friendliness, we developed a GUI for Et-GWAS; https://et-gwas.shinyapps.io/Et-GWAS/.

Joint-GWAS, Linkage Mapping, and Transcriptome Analysis to Reveal the Genetic Basis of Plant Architecture-Related Traits in Maize

Plant architecture is one of the key factors affecting maize yield formation and can be divided into secondary traits, such as plant height (PH), ear height (EH), and leaf number (LN). It is a viable approach for exploiting genetic resources to improve plant density. In this study, one natural panel of 226 inbred lines and 150 family lines derived from the offspring of T32 crossed with Qi319 were genotyped by using the MaizeSNP50 chip and the genotyping by sequence (GBS) method and phenotyped under three different environments. Based on the results, a genome-wide association study (GWAS) and linkage mapping were analyzed by using the MLM and ICIM models, respectively. The results showed that 120 QTNs (quantitative trait nucleotides) and 32 QTL (quantitative trait loci) related to plant architecture were identified, including four QTL and 40 QTNs of PH, eight QTL and 41 QTNs of EH, and 20 QTL and 39 QTNs of LN. One dominant QTL, qLN7-2, was identified in the Zhangye environment. Six QTNs were commonly identified to be related to PH, EH, and LN in different environments. The candidate gene analysis revealed that Zm00001d021574 was involved in regulating plant architecture traits through the autophagy pathway, and Zm00001d044730 was predicted to interact with the male sterility-related gene ms26. These results provide abundant genetic resources for improving maize plant architecture traits by using approaches to biological breeding.

Fine mapping of ClLOX, a QTL for powdery mildew resistance in watermelon (Citrullus lanatus L.)

KEY MESSAGE

ClLOX, is located on chromosome 2 and encodes a lipoxygenase gene, which induced watermelon powdery mildew resistance by inhibiting pathogen spread. Powdery mildew is one of the most severe fungal diseases reducing yield and quality of watermelon (Citrullus lanatus L.) and other cucurbit crops. Genes responsible for powdery mildew resistance in watermelon are highly valuable. In this study, we first identified the QTL pm-lox for powdery mildew resistance in watermelon, located within a 0.93 Mb interval of chromosome 2, via XP-GWAS method using two F2 populations. The F2:3 families from one of the F2 populations were then used for fine-mapping the pm-lox locus into a 9,883 bp physical region between 29,581,906 and 29,591,789, containing only two annotated genes. Of these, only ClG42_02g0161300 showed a significant differential expression between the resistant and susceptible lines after powdery mildew inoculation based on RNA sequencing (RNA-seq) and qRT-PCR analysis, and is designated ClLOX. Derived Cleaved Amplified Polymorphic Sequence (dCAPs) markers were developed and validated. In addition, our tests showed that the resistance was anti-spread rather than anti-infection of the pathogen. This study identified a new resistance gene (ClLOX), provided insights into the mechanism of powdery mildew resistance, and developed a molecular marker for watermelon breeding.

Mapping Genetic Variation in Arabidopsis in Response to Plant Growth-Promoting Bacterium Azoarcus olearius DQS-4T

Plant growth-promoting bacteria (PGPB) can enhance plant health by facilitating nutrient uptake, nitrogen fixation, protection from pathogens, stress tolerance and/or boosting plant productivity. The genetic determinants that drive the plant-bacteria association remain understudied. To identify genetic loci highly correlated with traits responsive to PGPB, we performed a genome-wide association study (GWAS) using an Arabidopsis thaliana population treated with Azoarcus olearius DQS-4^T. Phenotypically, the 305 Arabidopsis accessions tested responded differently to bacterial treatment by improving, inhibiting, or not affecting root system or shoot traits. GWA mapping analysis identified several predicted loci associated with primary root length or root fresh weight. Two statistical analyses were performed to narrow down potential gene candidates followed by haplotype block analysis, resulting in the identification of 11 loci associated with the responsiveness of Arabidopsis root fresh weight to bacterial inoculation. Our results showed considerable variation in the ability of plants to respond to inoculation by A. olearius DQS-4^T while revealing considerable complexity regarding statistically associated loci with the growth traits measured. This investigation is a promising starting point for sustainable breeding strategies for future cropping practices that may employ beneficial microbes and/or modifications of the root microbiome.

SNP-based bulk segregant analysis revealed disease resistance QTLs associated with northern corn leaf blight in maize

Maize (Zea mays L.) is the most important food security crop worldwide. Northern corn leaf blight (NCLB), caused by Exserohilum turcicum, severely reduces production causing millions of dollars in losses worldwide. Therefore, this study aimed to identify significant QTLs associated with NCLB by utilizing next-generation sequencing-based bulked-segregant analysis (BSA). Parental lines GML71 (resistant) and Gui A10341 (susceptible) were used to develop segregating population F₂. Two bulks with 30 plants each were further selected from the segregating population for sequencing along with the parental lines. High throughput sequencing data was used for BSA. We identified 10 QTLs on Chr 1, Chr 2, Chr 3, and Chr 5 with 265 non-synonymous SNPs. Moreover, based on annotation information, we identified 27 candidate genes in the QTL regions. The candidate genes associated with disease resistance include AATP1, At4g24790, STICHEL-like 2, BI O 3-BIO1, ZAR1, SECA2, ABCG25, LECRK54, MKK7, MKK9, RLK902, and DEAD-box ATP-dependent RNA helicase. The annotation information suggested their involvement in disease resistance-related pathways, including protein phosphorylation, cytoplasmic vesicle, protein serine/threonine kinase activity, and ATP binding pathways. Our study provides a substantial addition to the available information regarding QTLs associated with NCLB, and further functional verification of identified candidate genes can broaden the scope of understanding the NCLB resistance mechanism in maize.

Variations of Nutrient and Antinutrient Components of Bambara Groundnut (Vigna subterranea (L.) Verdc.) Seeds

Bambara groundnut (BGN) fits the bill when it comes to an acceptable level of nutrient and mineral composition. BGN is a balanced food that can help eradicate food and nutritional insecurity if it is incorporated into the major food system. However, there is a large degree of variation in nutrient composition and antinutritional factors among BGN accessions. Here, we show the degree of variability of nutrient and antinutrient components such as percentage ash, moisture, protein, fat, tryptophan, tannin, and phytate contents in seeds of 95 accessions of BGN. Data were subjected to analysis of variance (ANOVA), followed by correlation and principal component analysis. Clustering was done to show the relatedness between the accessions in response to the various traits. A high level of heterogeneity was observed among the accessions for the various traits studied. PC1 and PC2 show 41.2% of the total observed variations. Cluster analysis grouped accessions into four main clusters. This study was able to confirm the high level of diversity in the components of nutrients and antinutrients previously reported in BGN. The results of this study are expected to aid in identifying parent lines for improved breeding programs.

Evaluation of nine statistics to identify QTLs in bulk segregant analysis using next generation sequencing approaches

Background

Bulk segregant analysis (BSA) combined with next generation sequencing is a powerful tool to identify quantitative trait loci (QTL). The impact of the size of the study population and the percentage of extreme genotypes analysed have already been assessed. But a good comparison of statistical approaches designed to identify QTL regions using next generation sequencing (NGS) technologies for BSA is still lacking.

Results

We developed an R code to simulate QTLs in bulks of F2 contrasted lines. We simulated a range of recombination rates based on estimations using different crop species. The simulations were used to benchmark the ability of statistical methods identify the exact location of true QTLs. A single QTL led to a shift in allele frequency across a large fraction of the chromosome for plant species with low recombination rate. The smoothed version of all statistics performed best notably the smoothed Euclidean distance-based statistics was always found to be more accurate in identifying the location of QTLs. We propose a simulation approach to build confidence interval statistics for the detection of QTLs.

Conclusion

We highlight the statistical methods best suited for BSA studies using NGS technologies in crops even when recombination rate is low. We also provide simulation codes to build confidence intervals and to assess the impact of recombination for application to other studies. This computational study will help select NGS-based BSA statistics that are useful to the broad scientific community.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08718-y.

Identification of Pathogenicity Loci in Magnaporthe oryzae Using GWAS with Neck Blast Phenotypic Data

Magnaporthae oryzae (M. oryzae) is the most destructive disease of rice worldwide. In this study, one hundred and two isolates of M. oryzae were collected from rice (Oryzae sativa L.) from 2001 to 2017, and six rice varieties with resistance genes Pizt, Pish, Pik, Pib, and Pi2 were used in a genome-wide association study to identify pathogenicity loci in M. oryzae. Genome-wide association analysis was performed using 5338 single nucleotide polymorphism (SNPs) and phenotypic data of neck blast screening by TASSEL software together with haplotype block and SNP effect analysis. Twenty-seven significant SNPs were identified on chromosomes 1, 2, 3, 4, 5, 6, and 7. Many predicted genes (820 genes) were found in the target regions of six rice varieties. Most of these genes are described as putative uncharacterized proteins, however, some genes were reported related to virulence in M. oryzae. Moreover, this study revealed that R genes, Pik, Pish, and Pi2, were broad-spectrum resistant against neck blast disease caused by Thai blast isolate. Haplotype analysis revealed that the combination of the favorable alleles causing reduced virulence of isolates against IRBLz5-CA carrying Pi2 gene contributes 69% of the phenotypic variation in pathogenicity. The target regions and information are useful to develop marker-specific genes to classify blast fungal isolates and select appropriate resistance genes for rice cultivation and improvement.

Fine Mapping and Functional Analysis of the Gene PcTYR, Involved in Control of Cap Color of Pleurotus cornucopiae

Oyster mushrooms have a high biological efficiency and are easy to cultivate, which is why they are produced all over the world. Cap color is an important commercial trait for oyster mushrooms. Little is known about the genetic mechanism of the cap color trait in oyster mushrooms, which limits molecular breeding for the improvement of cap color-type cultivars. In this study, a 0.8-Mb major quantitative trait locus (QTL) region controlling cap color in the oyster mushroom Pleurotus cornucopiae was mapped on chromosome 7 through bulked-segregant analysis sequencing (BSA-seq) and extreme-phenotype genome-wide association studies (XP-GWAS). Candidate genes were further selected by comparative transcriptome analysis, and a tyrosinase gene (PcTYR) was identified as the highest-confidence candidate gene. Overexpression of PcTYR resulted in a significantly darker cap color, while the cap color of RNA interference (RNAi) strains for this gene was significantly lighter than that of the wild-type (WT) strains, suggesting that PcTYR plays an essential role in cap color formation. This is the first report about fine mapping and functional verification of a gene controlling cap color in oyster mushrooms. This will enhance our understanding of the genetic basis for cap color formation in oyster mushrooms and will facilitate molecular breeding for cap color. IMPORTANCE Oyster mushrooms are widely cultivated and consumed over the world for their easy cultivation and high biological efficiency (mushroom fresh weight/substrate dry weight × 100%). Fruiting bodies with dark caps are more and more popular according to consumer preferences, but dark varieties are rarely seen on the market. Little is known about the genetic mechanism of the cap color trait in oyster mushrooms, which limits molecular breeding for the improvement of cap color-type cultivars. A major QTL of cap color in oyster mushroom P. cornucopiae was fine mapped by using bulked-segregant analysis (BSA) and extreme-phenotype genome-wide association study (XP-GWAS) analysis. A candidate gene PcTYR coding tyrosinase was further identified with the help of comparative transcriptome analysis. qPCR analysis and genetic transformation tests proved that PcTYR played an essential role in cap color formation. This study will contribute to revealing the genetic mechanism of cap color formation in mushrooms, thereby facilitating molecular breeding for cap color trait.

GWAS identifies genetic loci underlying nitrogen responsiveness in the climate resilient C4 model Setaria italica (L.)

INTRODUCTION

N responsiveness is the capacity to perceive and induce morpho-physiological adaptation to external and internal Nitrogen (N). Crop productivity is propelled by N fertilizer and requires the breeding/selection of cultivars with intrinsically high N responsiveness. This trait has many advantages in being more meaningful in commercial/environmental context, facilitating in-season N management and not being inversely correlated with N availability over processes regulating NUE. Current lack of its understanding at the physio-genetic basis is an impediment to select for cultivars with a predictably high N response.

OBJECTIVES

To dissect physio-genetic basis of N responsiveness in 142 diverse population of foxtail millet, Setaria italica (L.) by employing contrasting N fertilizer nutrition regimes.

METHODS

We phenotyped S. italica accessions for major yield related traits under low (N10, N25) and optimal (N100) growth conditions and genotyped them to subsequently perform a genome-wide association study to identify genetic loci associated with nitrogen responsiveness trait. Groups of accessions showing contrasting trait performance and allelic forms of specific linked genetic loci (showing haplotypes) were further accessed for N dependent transcript abundances of their proximal genes.

RESULTS

Our study show that N dependent yield rise in S. italica is driven by grain number whose responsiveness to N availability is genetically underlined. We identify 22 unique SNP loci strongly associated with this trait out of which six exhibit haplotypes and consistent allelic variation between lines with contrasting N dependent grain number response and panicle architectures. Furthermore, differential transcript abundances of specific genes proximally linked to these SNPs in same lines is indicative of their N dependence in a genotype specific manner.

CONCLUSION

The study demonstrates the value/ potential of N responsiveness as a selection trait and identifies key genetic components underlying the trait in S. italica. This has major implications for improving crop N sustainability and food security.

Multi-locus genome-wide association mapping for spike-related traits in bread wheat (Triticum aestivum L.)

BACKGROUND

Bread wheat (Triticum aestivum L.) is one of the most important cereal food crops for the global population. Spike-layer uniformity (the consistency of the spike distribution in the vertical space)-related traits (SLURTs) are quantitative and have been shown to directly affect yield potential by modifying the plant architecture. Therefore, these parameters are important breeding targets for wheat improvement. The present study is the first genome-wide association study (GWAS) targeting SLURTs in wheat. In this study, a set of 225 diverse spring wheat accessions were used for multi-locus GWAS to evaluate SLURTs, including the number of spikes per plant (NSPP), spike length (SL), number of spikelets per spike (NSPS), grain weight per spike (GWPS), lowest tiller height (LTH), spike-layer thickness (SLT), spike-layer number (SLN) and spike-layer uniformity (SLU).

RESULTS

In total, 136 significant marker trait associations (MTAs) were identified when the analysis was both performed individually and combined for two environments. Twenty-nine MTAs were detected in environment one, 48 MTAs were discovered in environment two and 59 MTAs were detected using combined data from the two environments. Altogether, 15 significant MTAs were found for five traits in one of the two environments, and four significant MTAs were detected for the two traits, LTH and SLU, in both environments i.e. E1, E2 and also in combined data from the two environments. In total, 279 candidate genes (CGs) were identified, including Chaperone DnaJ, ABC transporter-like, AP2/ERF, SWEET sugar transporter, as well as genes that have previously been associated with wheat spike development, seed development and grain yield.

CONCLUSIONS

The MTAs detected through multi-locus GWAS will be useful for improving SLURTs and thus yield in wheat production through marker-assisted and genomic selection.

Single-trait, multi-locus and multi-trait GWAS using four different models for yield traits in bread wheat

A genome-wide association study (GWAS) for 10 yield and yield component traits was conducted using an association panel comprising 225 diverse spring wheat genotypes. The panel was genotyped using 10,904 SNPs and evaluated for three years (2016-2019), which constituted three environments (E1, E2 and E3). Heritability for different traits ranged from 29.21 to 97.69%. Marker-trait associations (MTAs) were identified for each trait using data from each environment separately and also using BLUP values. Four different models were used, which included three single trait models (CMLM, FarmCPU, SUPER) and one multi-trait model (mvLMM). Hundreds of MTAs were obtained using each model, but after Bonferroni correction, only 6 MTAs for 3 traits were available using CMLM, and 21 MTAs for 4 traits were available using FarmCPU; none of the 525 MTAs obtained using SUPER could qualify after Bonferroni correction. Using BLUP, 20 MTAs were available, five of which also figured among MTAs identified for individual environments. Using mvLMM model, after Bonferroni correction, 38 multi-trait MTAs, for 15 different trait combinations were available. Epistatic interactions involving 28 pairs of MTAs were also available for seven of the 10 traits; no epistatic interactions were available for GNPS, PH, and BYPP. As many as 164 putative candidate genes (CGs) were identified using all the 50 MTAs (CMLM, 3; FarmCPU, 9; mvLMM, 6, epistasis, 21 and BLUP, 11 MTAs), which ranged from 20 (CMLM) to 66 (epistasis) CGs. In-silico expression analysis of CGs was also conducted in different tissues at different developmental stages. The information generated through the present study proved useful for developing a better understanding of the genetics of each of the 10 traits; the study also provided novel markers for marker-assisted selection (MAS) to be utilized for the development of wheat cultivars with improved agronomic traits.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01240-1.

The reuse of public datasets in the life sciences: potential risks and rewards

The 'big data' revolution has enabled novel types of analyses in the life sciences, facilitated by public sharing and reuse of datasets. Here, we review the prodigious potential of reusing publicly available datasets and the associated challenges, limitations and risks. Possible solutions to issues and research integrity considerations are also discussed. Due to the prominence, abundance and wide distribution of sequencing data, we focus on the reuse of publicly available sequence datasets. We define 'successful reuse' as the use of previously published data to enable novel scientific findings. By using selected examples of successful reuse from different disciplines, we illustrate the enormous potential of the practice, while acknowledging the respective limitations and risks. A checklist to determine the reuse value and potential of a particular dataset is also provided. The open discussion of data reuse and the establishment of this practice as a norm has the potential to benefit all stakeholders in the life sciences.

Comparisons of sampling methods for assessing intra- and inter-accession genetic diversity in three rice species using genotyping by sequencing

To minimize the cost of sample preparation and genotyping, most genebank genomics studies in self-pollinating species are conducted on a single individual to represent an accession, which may be heterogeneous with larger than expected intra-accession genetic variation. Here, we compared various population genetics parameters among six DNA (leaf) sampling methods on 90 accessions representing a wild species (O. barthii), cultivated and landraces (O. glaberrima, O. sativa), and improved varieties derived through interspecific hybridizations. A total of 1,527 DNA samples were genotyped with 46,818 polymorphic single nucleotide polymorphisms (SNPs) using DArTseq. Various statistical analyses were performed on eleven datasets corresponding to 5 plants per accession individually and in a bulk (two sets), 10 plants individually and in a bulk (two sets), all 15 plants individually (one set), and a randomly sampled individual repeated six times (six sets). Overall, we arrived at broadly similar conclusions across 11 datasets in terms of SNP polymorphism, heterozygosity/heterogeneity, diversity indices, concordance among genetic dissimilarity matrices, population structure, and genetic differentiation; there were, however, a few discrepancies between some pairs of datasets. Detailed results of each sampling method, the concordance in their outputs, and the technical and cost implications of each method were discussed.

Prospects for the Study and Improvement of Abiotic Stress Tolerance in Date Palms in the Post-genomics Era

Date palm (Phoenix dactylifera L.) is a socio-economically important crop in the Middle East and North Africa and a major contributor to food security in arid regions of the world. P. dactylifera is both drought and salt tolerant, but recent water shortages and increases in groundwater and soil salinity have threatened the continued productivity of the crop. Recent studies of date palm have begun to elucidate the physiological mechanisms of abiotic stress tolerance and the genes and biochemical pathways that control the response to these stresses. Here we review recent studies on tolerance of date palm to salinity and drought stress, the role of the soil and root microbiomes in abiotic stress tolerance, and highlight recent findings of omic-type studies. We present a perspective on future research of abiotic stress in date palm that includes improving existing genome resources, application of genetic mapping to determine the genetic basis of variation in tolerances among cultivars, and adoption of gene-editing technologies to the study of abiotic stress in date palms. Development of necessary resources and application of the proposed methods will provide a foundation for future breeders and genetic engineers aiming to develop more stress-tolerant cultivars of date palm.