QTL sequencing strategy to map genomic regions associated with resistance to ascochyta blight in chickpea

Assessing the utility of genomic selection to breed for durable Ascochyta blight resistance in chickpea

Ascochyta blight (AB) is one of the most devastating fungal diseases of chickpea (Cicer arietinum L.). Conventional breeding has focused on exploiting and introgressing major genes (qualitative effect) to improve AB resistance in released varieties. However, such approaches are time-consuming and prone to the breakdown of disease resistance due to the fast evolution of AB pathogen. Genomic selection (GS) offers a promising alternative by predicting breeding values using genome-wide single nucleotide polymorphisms (SNPs), regardless of major or minor effects. To our knowledge, this is the first study to develop and implement GS to improve AB resistance in chickpea. Over 4 years, 2790 chickpea lines, representing a broad range of germplasm collections primarily sourced from the Australian Grains Genebank, were evaluated for AB disease response in the field and in an outdoor pot-based facility. Plants were genotyped with the Illumina multispecies pulse 30K SNP array, resulting in 23,239 high-quality SNPs distributed across the genome. Intermediate-to-high genomic prediction accuracies (0.40-0.90) were achieved across validation scenarios. Bayesian modeling identified six major QTL explaining 33% of the genetic variance for AB resistance, with the remaining variance explained by minor effect genes. Using genomic estimated breeding values (GEBVs), 462 lines of the 2790 lines were predicted to have higher resistance compared to the released check varieties, revealing the potential of further improvement of AB resistance for the industry. The desirable genomic prediction accuracy obtained in the study supports the applicability of GS to breed for AB resistance in chickpea.

Amplification-free detection of Ascochyta blight in chickpea using a simple molecular beacon assay

Ascochyta blight is a major biotic stress that limits chickpea production globally. Fungicide application remains one of the effective control measures for the endemic spread. Due to the serious threat that synthetic fungicides pose to crop quality, early diagnosis of the pathogen is imperative. Whilst there have previously been several conventional lab-based diagnostic methods developed for early detection of Ascochyta rabiei, they require long assay times, specialised equipment and facilities, and trained personnel to process the samples. To overcome this challenge, a rapid amplification-free detection assay using a molecular beacon probe was developed. The method consists of a simple assembly assay that accurately detects pathogen within 30 min. The developed assay is species-specific and has a similar sensitivity level as conventional amplification-based methods. Although it is still a lab-based technique, considering the simplicity of the assay, it has a great potential to be developed further as a reliable in-field diagnostic device for early detection and quantification of fungal pathogen spores.

Modern Plant Breeding Techniques in Crop Improvement and Genetic Diversity: From Molecular Markers and Gene Editing to Artificial Intelligence-A Critical Review

With the development of new technologies in recent years, researchers have made significant progress in crop breeding. Modern breeding differs from traditional breeding because of great changes in technical means and breeding concepts. Whereas traditional breeding initially focused on high yields, modern breeding focuses on breeding orientations based on different crops' audiences or by-products. The process of modern breeding starts from the creation of material populations, which can be constructed by natural mutagenesis, chemical mutagenesis, physical mutagenesis transfer DNA (T-DNA), Tos17 (endogenous retrotransposon), etc. Then, gene function can be mined through QTL mapping, Bulked-segregant analysis (BSA), Genome-wide association studies (GWASs), RNA interference (RNAi), and gene editing. Then, at the transcriptional, post-transcriptional, and translational levels, the functions of genes are described in terms of post-translational aspects. This article mainly discusses the application of the above modern scientific and technological methods of breeding and the advantages and limitations of crop breeding and diversity. In particular, the development of gene editing technology has contributed to modern breeding research.

Fine mapping and identification of a Fusarium wilt resistance gene FwS1 in pea

KEY MESSAGE

A Fusarium wilt resistance gene FwS1 on pea chromosome 6 was identified and mapped to a 91.4 kb region by a comprehensive genomic-based approach, and the gene Psat6g003960 harboring NB-ARC domain was identified as the putative candidate gene. Pea Fusarium wilt, incited by Fusarium oxysporum f. sp. pisi (Fop), has always been a devastating disease that causes severe yield losses and economic damage in pea-growing regions worldwide. The utilization of pea cultivars carrying resistance gene is the most efficient approach for managing this disease. In order to finely map resistance gene, F2 populations were established through the cross between Shijiadacaiwan 1 (resistant) and Y4 (susceptible). The resistance genetic analysis indicated that the Fop resistance in Shijiadacaiwan 1 was governed by a single dominant gene, named FwS1. Based on the bulked segregant analysis sequencing analyses, the gene FwS1 was initially detected on chromosome 6 (i.e., linking group II, chr6LG2), and subsequent linkage mapping with 589 F2 individuals fine-mapped the gene FwS1 into a 91.4 kb region. The further functional annotation and haplotype analysis confirmed that the gene Psat6g003960, characterized by a NB-ARC (nucleotide-binding adaptor shared by APAF-1, R proteins, and CED-4) domain, was considered as the most promising candidate gene. The encoding amino acids were altered by a "T/C" single-nucleotide polymorphism (SNP) in the first exon of the Psat6g003960, and based on this SNP locus, the molecular marker A016180 was determined to be a diagnostic marker for FwS1 by validating its specificity in both pea accessions and genetic populations with different genetic backgrounds. The FwS1 with diagnostic KASP marker A016180 could facilitate marker-assisted selection in resistance pea breeding in pea. In addition, a comparison of the candidate gene Psat6g003960 in 74SN3B and SJ1 revealed the same sequences. This finding indicated that 74SN3B carried the candidate gene for FwS1, suggesting that FwS1 and Fwf may be closely linked or an identical resistant gene against Fusarium wilt.

Mapping QTL associated with resistance to Pseudomonas syringae pv. actinidiae in kiwifruit (Actinidia chinensis var. chinensis)

Pseudomonas syringae pv. actinidiae (Psa) is a bacterial pathogen of kiwifruit. This pathogen causes leaf-spotting, cane dieback, wilting, cankers (lesions), and in severe cases, plant death. Families of diploid A. chinensis seedlings grown in the field show a range of susceptibilities to the disease with up to 100% of seedlings in some families succumbing to Psa. But the effect of selection for field resistance to Psa on the alleles that remain in surviving seedlings has not been assessed. The objective of this work was to analyse, the effect of plant removal from Psa on the allele frequency of an incomplete-factorial-cross population. This population was founded using a range of genotypically distinct diploid A. chinensis var. chinensis parents to make 28 F1 families. However, because of the diversity of these families, low numbers of surviving individuals, and a lack of samples from dead individuals, standard QTL mapping approaches were unlikely to yield good results. Instead, a modified bulk segregant analysis (BSA) overcame these drawbacks while reducing the costs of sampling and sample processing, and the complexity of data analysis. Because the method was modified, part one of this work was used to determine the signal strength required for a QTL to be detected with BSA. Once QTL detection accuracy was known, part two of this work analysed the 28 families from the incomplete-factorial-cross population that had multiple individuals removed due to Psa infection. Each family was assigned to one of eight bulks based on a single parent that contributed to the families. DNA was extracted in bulk by grinding sampled leaf discs together before DNA extraction. Each sample bulk was compared against a bulk made up of WGS data from the parents contributing to the sample bulk. The deviation in allele frequency from the expected allele frequency within surviving populations using the modified BSA method was able to identify 11 QTLs for Psa that were present in at least two analyses. The identification of these Psa resistance QTL will enable marker development to selectively breed for resistance to Psa in future kiwifruit breeding programs.

Application of bulk segregant RNA-Seq (BSR-Seq) and allele-specific primers to study soybean powdery mildew resistance

BACKGROUND

Powdery mildew (PM) is one of the important soybean diseases, and host resistance could practically contribute to soybean PM management. To date, only the Rmd locus on chromosome (Chr) 16 was identified through traditional QTL mapping and GWAS, and it remains unclear if the bulk segregant RNA-Seq (BSR-Seq) methodology is feasible to explore additional PM resistance that might exist in other varieties.

RESULTS

BSR-Seq was applied to contrast genotypes and gene expressions between the resistant bulk (R bulk) and the susceptible bulk (S bulk), as well as the parents. The ∆(SNP-index) and G' value identified several QTL and significant SNPs/Indels on Chr06, Chr15, and Chr16. Differentially expressed genes (DEGs) located within these QTL were identified using HISAT2 and Kallisto, and allele-specific primers (AS-primers) were designed to validate the accuracy of phenotypic prediction. While the AS-primers on Chr06 or Chr15 cannot distinguish the resistant and susceptible phenotypes, AS-primers on Chr16 exhibited 82% accuracy prediction with an additive effect, similar to the SSR marker Satt431.

CONCLUSIONS

Evaluation of additional AS-primers in the linkage disequilibrium (LD) block on Chr16 further confirmed the resistant locus, derived from the resistant parental variety 'Kaohsiung 11' ('KS11'), not only overlaps with the Rmd locus with unique up-regulated LRR genes (Glyma.16G213700 and Glyma.16G215100), but also harbors a down-regulated MLO gene (Glyma.16G145600). Accordingly, this study exemplified the feasibility of BSR-Seq in studying biotrophic disease resistance in soybean, and showed the genetic makeup of soybean variety 'KS11' comprising the Rmd locus and one MLO gene.

Genetic Analysis of Partially Resistant and Susceptible Chickpea Cultivars in Response to Ascochyta rabiei Infection

The molecular mechanism involved in chickpea (Cicer arietinum L.) resistance to the necrotrophic fungal pathogen Ascochyta rabiei is not well documented. A. rabiei infection can cause severe damage in chickpea, resulting in significant economic losses. Understanding the resistance mechanism against ascochyta blight can help to define strategies to develop resistant cultivars. In this study, differentially expressed genes from two partially resistant cultivars (CDC Corinne and CDC Luna) and a susceptible cultivar (ICCV 96029) to ascochyta blight were identified in the early stages (24, 48 and 72 h) of A. rabiei infection using RNA-seq. Altogether, 3073 genes were differentially expressed in response to A. rabiei infection across different time points and cultivars. A larger number of differentially expressed genes (DEGs) were found in CDC Corinne and CDC Luna than in ICCV 96029. Various transcription factors including ERF, WRKY, bHLH and MYB were differentially expressed in response to A. rabiei infection. Genes involved in pathogen detection and immune signalings such as receptor-like kinases (RLKs), Leucine-Rich Repeat (LRR)-RLKs, and genes associated with the post-infection defence response were differentially expressed among the cultivars. GO functional enrichment and pathway analysis of the DEGs suggested that the biological processes such as metabolic process, response to stimulus and catalytic activity were overrepresented in both resistant and susceptible chickpea cultivars. The expression patterns of eight randomly selected genes revealed by RNA-seq were confirmed by quantitative PCR (qPCR) analysis. The results provide insights into the complex molecular mechanism of the chickpea defence in response to the A. rabiei infection.

Genome wide association study of genes controlling resistance to Didymella rabiei Pathotype IV through genotyping by sequencing in chickpeas (Cicer arietinum)

Ascochyta blight (AB) is a major disease in chickpeas (Cicer arietinum L.) that can cause a yield loss of up to 100%. Chickpea germplasm collections at the center of origin offer great potential to discover novel sources of resistance to pests and diseases. Herein, 189 Cicer arietinum samples were genotyped via genotyping by sequencing. This chickpea collection was phenotyped for resistance to an aggressive Turkish Didymella rabiei Pathotype IV isolate. Genome-wide association studies based on different models revealed 19 single nucleotide polymorphism (SNP) associations on chromosomes 1, 2, 3, 4, 7, and 8. Although eight of these SNPs have been previously reported, to the best of our knowledge, the remaining ten were associated with AB resistance for the first time. The regions identified in this study can be addressed in future studies to reveal the genetic mechanism underlying AB resistance and can also be utilized in chickpea breeding programs to improve AB resistance in new chickpea varieties.

QTL and PACE analyses identify candidate genes for anthracnose resistance in tomato

Anthracnose, caused by the fungal pathogen Colletotrichum spp., is one of the most significant tomato diseases in the United States and worldwide. No commercial cultivars with anthracnose resistance are available, limiting resistant breeding. Cultivars with genetic resistance would significantly reduce crop losses, reduce the use of fungicides, and lessen the risks associated with chemical application. A recombinant inbred line (RIL) mapping population (N=243) has been made from a cross between the susceptible US28 cultivar and the resistant but semiwild and small-fruited 95L368 to identify quantitative trait loci (QTLs) associated with anthracnose resistance. The RIL population was phenotyped for resistance by inoculating ripe field-harvested tomato fruits with Colletotrichum coccodes for two seasons. In this study, we identified twenty QTLs underlying resistance, with a range of phenotypic variance of 4.5 to 17.2% using a skeletal linkage map and a GWAS. In addition, a QTLseq analysis was performed using deep sequencing of extreme bulks that validated QTL positions identified using traditional mapping and resolved candidate genes underlying various QTLs. We further validated AP2-like ethylene-responsive transcription factor, N-alpha-acetyltransferase (NatA), cytochrome P450, amidase family protein, tetratricopeptide repeat, bHLH transcription factor, and disease resistance protein RGA2-like using PCR allelic competitive extension (PACE) genotyping. PACE assays developed in this study will enable high-throughput screening for use in anthracnose resistance breeding in tomato.

Genomics-assisted genetics of complex region from chickpea chromosome 4 reveals two candidate genes for Ascochyta blight resistance

Ascochyta blight (AB) disease caused by the fungus Ascochyta rabiei is a major threat to global chickpea production. Molecular breeding for improved AB resistance requires the identification of robust fine-mapped QTLs/candidate genes and associated markers. Earlier, we identified three QTLs (qABR4.1, qABR4.2, and qABR4.3) for AB resistance on chickpea chromosome 4 by employing multiple quantitative trait loci sequencing strategy on an intra-specific (FLIP84-92C x PI359075) and an inter-specific (FLIP84-92C x PI599072) crosses derived recombinant inbred lines. Here, we report the identification of AB resistance providing candidate genes under the fine mapped qABR4.2 and qABR4.3 genomic region by combining genetic mapping, haplotype block inheritance, and expression analysis. The qABR4.2 region was narrowed down from 5.94Mb to ~800kb. Among 34 predicted gene models, a secreted class III peroxidase encoding gene showed higher expression in AB resistant parent after A. rabiei conidia inoculation. Under qABR4.3, we identified a frame-shift mutation in a cyclic nucleotide-gated channel CaCNGC1 gene leading to the truncated N-terminal domain in resistant accession of chickpea. This N-terminal domain of CaCNGC1 interacts with chickpea calmodulin. Thus, our analysis has revealed narrowed genomic regions and their associated polymorphic markers, CaNIP43 and CaCNGCPD1. These co-dominant markers significantly associate with AB resistance on qABR4.2 and qABR4.3 regions. Our genetic analysis revealed that the presence of resistant alleles for two major QTLs (qABR4.1 and qABR4.2) together provide AB resistance in the field while minor QTL qABR4.3 determines the degree of resistance. The identified candidate genes and their diagnostic markers will help in biotechnological and AB resistance introgression into farmers adapted local chickpea varieties.

Functional Bph14 from Rathu Heenati promotes resistance to BPH at the early seedling stage of rice (Oryza sativa L.) as revealed by QTL-seq

A QTL associated with BPH resistance at the early seedling stage was identified on chromosome 3. Functional Bph14 in Rathu Heenati was associated with BPH resistance at the early seedling stage. Brown planthopper (BPH; Nilaparvata lugens Stål) is considered the most important rice pest in many Asian countries. Several BPH resistance genes have previously been identified. However, there are few reports of genes specific for BPH resistance at the early seedling stage, a crucial stage for direct-seeding cultivation. In this study, we performed a QTL-seq analysis using two bulks (20 F₂ lines in each bulk) of the F₂ population (n = 300) derived from a cross of Rathu Heenati (RH) × HCS-1 to identify QTL/genes associated with BPH resistance at the early seedling stage. An important QTL was identified on chromosome 3 and Bph14 was identified as a potential candidate gene based on the differences in gene expression and sequence variation when compared with the two parents. All plants in the resistant bulks possessed the functional Bph14 from RH and all plants in the susceptible bulk and HCS-1 contained a large deletion (2703 bp) in Bph14. The functional Bph14 gene of RH appears to be important for BPH resistance at the early seedling stage of rice and could be used in conjunction with other BPH resistance genes in rice breeding programs that confer resistance to BPH at the early and later growth stages.

Inheritance of Early and Late Ascochyta Blight Resistance in Wide Crosses of Chickpea

Chickpea (Cicer arietinum) is a globally important food legume but its yield is negatively impacted by the fungal pathogen Ascochyta blight (Ascochyta rabiei) causing necrotic lesions leading to plant death. Past studies have found that Ascochyta resistance is polygenic. It is important to find new resistance genes from the wider genepool of chickpeas. This study reports the inheritance of Ascochyta blight resistance of two wide crosses between the cultivar Gokce and wild chickpea accessions of C. reticulatum and C. echinospermum under field conditions in Southern Turkey. Following inoculation, infection damage was scored weekly for six weeks. The families were genotyped for 60 SNPs mapped to the reference genome for quantitative locus (QTL) mapping of resistance. Family lines showed broad resistance score distributions. A late responding QTL on chromosome 7 was identified in the C. reticulatum family and three early responding QTLs on chromosomes 2, 3, and 6 in the C. echinospermum family. Wild alleles mostly showed reduced disease severity, while heterozygous genotypes were most diseased. Interrogation of 200k bp genomic regions of the reference CDC Frontier genome surrounding QTLs identified nine gene candidates involved in disease resistance and cell wall remodeling. This study identifies new candidate chickpea Ascochyta blight resistance QTLs of breeding potential.

Genetic mapping and molecular characterization of the delayed green gene dg in watermelon (Citrullus lanatus)

Leaf color mutants are common in higher plants that can be used as markers in crop breeding and are important tools in understanding regulatory mechanisms of chlorophyll biosynthesis and chloroplast development. Genetic analysis was performed by evaluating F₁, F₂ and BC₁ populations derived from two parental lines (Charleston gray with green leaf color and Houlv with delayed green leaf color), suggesting that a single recessive gene controls the delayed green leaf color. In this study, the delayed green mutant showed a conditional pale green leaf color at the early leaf development but turned to green as the leaf development progressed. Delayed green leaf plants showed reduced pigment content, photosynthetic, chlorophyll fluorescence parameters, and impaired chloroplast development compared with green leaf plants. The delayed green (dg) locus was mapped to 7.48 Mb on chromosome 3 through bulk segregant analysis approach, and the gene controlling delayed green leaf color was narrowed to 53.54 kb between SNP130 and SNP135 markers containing three candidate genes. Sequence alignment of the three genes indicated that there was a single SNP mutation (G/A) in the coding region of ClCG03G010030 in the Houlv parent, which causes an amino acid change from Arginine to Lysine. The ClCG03G010030 gene encoded FtsH extracellular protease protein family is involved in early delayed green leaf development. The expression level of ClCG03G010030 was significantly reduced in delayed green leaf plants than in green leaf plants. These results indicated that the ClCG03G010030 might control watermelon green leaf color and the single SNP variation in ClCG03G010030 may result in early delayed green leaf color development during evolutionary process.

A Global Transcriptome and Co-expression Analysis Reveals Robust Host Defense Pathway Reprogramming and Identifies Key Regulators of Early Phases of Cicer-Ascochyta Interactions

Ascochyta blight (AB) caused by the filamentous fungus Ascochyta rabiei is a major threat to global chickpea production. The mechanisms underlying chickpea response to A. rabiei remain elusive to date. Here, we investigated the comparative transcriptional dynamics of AB-resistant and -susceptible chickpea genotypes upon A. rabiei infection, to understand the early host defense response. Our findings revealed that AB-resistant plants underwent rapid and extensive transcriptional reprogramming compared with a susceptible host. At the early stage (24 h postinoculation [hpi]), mainly cell-wall remodeling and secondary metabolite pathways were highly activated, while differentially expressed genes related to signaling components, such as protein kinases, transcription factors, and hormonal pathways, show a remarkable upsurge at 72 hpi, especially in the resistant genotype. Notably, our data suggest an imperative role of jasmonic acid, ethylene, and abscisic acid signaling in providing immunity against A. rabiei. Furthermore, gene co-expression networks and modules corroborated the importance of cell-wall remodeling, signal transduction, and phytohormone pathways. Hub genes such as MYB14, PRE6, and MADS-SOC1 discovered in these modules might be the master regulators governing chickpea immunity. Overall, we not only provide novel insights for comprehensive understanding of immune signaling components mediating AB resistance and susceptibility at early Cicer-Ascochyta interactions but, also, offer a valuable resource for developing AB-resistant chickpea. [Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Ascochyta rabiei: A threat to global chickpea production

The necrotrophic fungus Ascochyta rabiei causes Ascochyta blight (AB) disease in chickpea. A. rabiei infects all aerial parts of the plant, which results in severe yield loss. At present, AB disease occurs in most chickpea-growing countries. Globally increased incidences of A. rabiei infection and the emergence of new aggressive isolates directed the interest of researchers toward understanding the evolution of pathogenic determinants in this fungus. In this review, we summarize the molecular and genetic studies of the pathogen along with approaches that are helping in combating the disease. Possible areas of future research are also suggested.

TAXONOMY

kingdom Mycota, phylum Ascomycota, class Dothideomycetes, subclass Coelomycetes, order Pleosporales, family Didymellaceae, genus Ascochyta, species rabiei.

PRIMARY HOST

A. rabiei survives primarily on Cicer species.

DISEASE SYMPTOMS

A. rabiei infects aboveground parts of the plant including leaves, petioles, stems, pods, and seeds. The disease symptoms first appear as watersoaked lesions on the leaves and stems, which turn brown or dark brown. Early symptoms include small circular necrotic lesions visible on the leaves and oval brown lesions on the stem. At later stages of infection, the lesions may girdle the stem and the region above the girdle falls off. The disease severity increases at the reproductive stage and rounded lesions with concentric rings, due to asexual structures called pycnidia, appear on leaves, stems, and pods. The infected pod becomes blighted and often results in shrivelled and infected seeds.

DISEASE MANAGEMENT STRATEGIES

Crop failures may be avoided by judicious practices of integrated disease management based on the use of resistant or tolerant cultivars and growing chickpea in areas where conditions are least favourable for AB disease development. Use of healthy seeds free of A. rabiei, seed treatments with fungicides, and proper destruction of diseased stubbles can also reduce the fungal inoculum load. Crop rotation with nonhost crops is critical for controlling the disease. Planting moderately resistant cultivars and prudent application of fungicides is also a way to combat AB disease. However, the scarcity of AB-resistant accessions and the continuous evolution of the pathogen challenges the disease management process.

USEFUL WEBSITES

https://www.ndsu.edu/pubweb/pulse-info/resourcespdf/Ascochyta%20blight%20of%20chickpea.pdf https://saskpulse.com/files/newsletters/180531_ascochyta_in_chickpeas-compressed.pdf http://www.pulseaus.com.au/growing-pulses/bmp/chickpea/ascochyta-blight http://agriculture.vic.gov.au/agriculture/pests-diseases-and-weeds/plant-diseases/grains-pulses-and-cereals/ascochyta-blight-of-chickpea http://www.croppro.com.au/crop_disease_manual/ch05s02.php https://www.northernpulse.com/uploads/resources/722/handout-chickpeaascochyta-nov13-2011.pdf http://oar.icrisat.org/184/1/24_2010_IB_no_82_Host_Plant https://www.crop.bayer.com.au/find-crop-solutions/by-pest/diseases/ascochyta-blight.

Conventional and molecular breeding for disease resistance in chickpea: status and strategies

Chickpea (Cicer arietinum L.) is an important grain legume at the global level. Among different biotic stresses, diseases are the most important factor limiting its production, causing yield losses up to 100% in severe condition. The major diseases that adversely affect yield of chickpea include Fusarium wilt, Ascochyta blight and Botrytis gray mold. However, dry root rot, collar rot, Sclerotinia stem rot, rust, stunt disease and phyllody have been noted as emerging biotic threats to chickpea production in many production regions. Identification and incorporation of different morphological and biochemical traits are required through breeding to enhance genetic gain for disease resistance. In recent years, remarkable progress has been made in the development of trait-specific breeding lines, genetic and genomic resources in chickpea. Advances in genomics technologies have opened up new avenues to introgress genes from secondary and tertiary gene pools for improving disease resistance in chickpea. In this review, we have discussed important diseases, constraints and improvement strategies for enhancing disease resistance in chickpea.

A Locus Controlling Leaf Rolling Degree in Wheat under Drought Stress Identified by Bulked Segregant Analysis

Drought stress frequently occurs, which seriously restricts the production of wheat (Triticum aestivum L.). Leaf rolling is a typical physiological phenomenon of plants during drought stress. To understand the genetic mechanism of wheat leaf rolling, we constructed an F₂ segregating population by crossing the slight-rolling wheat cultivar “Aikang 58” (AK58) with the serious-rolling wheat cultivar ″Zhongmai 36″ (ZM36). A combination of bulked segregant analysis (BSA) with Wheat 660K SNP Array was used to identify molecular markers linked to leaf rolling degree. A major locus for leaf rolling degree under drought stress was detected on chromosome 7A. We named this locus LEAF ROLLING DEGREE 1 (LERD1), which was ultimately mapped to a region between 717.82 and 720.18 Mb. Twenty-one genes were predicted in this region, among which the basic helix-loop-helix (bHLH) transcription factor TraesCS7A01G543300 was considered to be the most likely candidate gene for LERD1. The TraesCS7A01G543300 is highly homologous to the Arabidopsis ICE1 family proteins ICE/SCREAM, SCREAM2 and bHLH093, which control stomatal initiation and development. Two nucleotide variation sites were detected in the promoter region of TraesCS7A01G543300 between the two wheat cultivars. Gene expression assays indicated that TraesCS7A01G543300 was higher expressed in AK58 seedlings than that of ZM36. This research discovered a candidate gene related to wheat leaf rolling under drought stress, which may be helpful for understanding the leaf rolling mechanism and molecular breeding in wheat.

Harnessing the potential of bulk segregant analysis sequencing and its related approaches in crop breeding

Most plant traits are governed by polygenes including both major and minor genes. Linkage mapping and positional cloning have contributed greatly to mapping genomic loci controlling important traits in crop species. However, they are low-throughput, time-consuming, and have low resolution due to which their efficiency in crop breeding is reduced. In this regard, the bulk segregant analysis sequencing (BSA-seq) and its related approaches, viz., quantitative trait locus (QTL)-seq, bulk segregant RNA-Seq (BSR)-seq, and MutMap, have emerged as efficient methods to identify the genomic loci/QTLs controlling specific traits at high resolution, accuracy, reduced time span, and in a high-throughput manner. These approaches combine BSA with next-generation sequencing (NGS) and enable the rapid identification of genetic loci for qualitative and quantitative assessments. Many previous studies have shown the successful identification of the genetic loci for different plant traits using BSA-seq and its related approaches, as discussed in the text with details. However, the efficiency and accuracy of the BSA-seq depend upon factors like sequencing depth and coverage, which enhance the sequencing cost. Recently, the rapid reduction in the cost of NGS together with the expected cost reduction of third-generation sequencing in the future has further increased the accuracy and commercial applicability of these approaches in crop improvement programs. This review article provides an overview of BSA-seq and its related approaches in crop breeding together with their merits and challenges in trait mapping.

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.

The GmSNAP11 Contributes to Resistance to Soybean Cyst Nematode Race 4 in Glycine max

Soybean cyst nematode (SCN) has devastating effects on soybean production, making it crucial to identify genes conferring SCN resistance. Here we employed next-generation sequencing-based bulked segregant analysis (BSA) to discover genomic regions, candidate genes, and diagnostic markers for resistance to SCN race 4 (SCN4) in soybean. Phenotypic analysis revealed highly significant differences among the reactions of 145 recombinant inbred lines (RILs) to SCN4. In combination with euclidean distance (ED) and Δsingle-nucleotide polymorphism (SNP)-index analyses, we identified a genomic region on Gm11 (designated as rhg1-paralog) associated with SCN4 resistance. Overexpression and RNA interference analyzes of the two candidate genes identified in this region (GmPLAC8 and GmSNAP11) revealed that only GmSNAP11 significantly contributes to SCN4 resistance. We developed a diagnostic marker for GmSNAP11. Using this marker, together with previously developed markers for SCN-resistant loci, rhg1 and Rhg4, we evaluated the relationship between genotypes and SCN4 resistance in 145 RILs and 30 soybean accessions. The results showed that all the SCN4-resistant lines harbored all the three loci, however, some lines harboring the three loci were still susceptible to SCN4. This suggests that these three loci are necessary for the resistance to SCN4, but they alone cannot confer full resistance. The GmSNAP11 and the diagnostic markers developed could be used in genomic-assisted breeding to develop soybean varieties with increased resistance to SCN4.

BSA-seq Identifies a Major Locus on Chromosome 6 for Root-Knot Nematode (Meloidogyne graminicola) Resistance From Oryza glaberrima

Root-knot nematode (Meloidogyne graminicola) is one of the emerging threats to rice production worldwide that causes substantial yield reductions. There is a progressive shift of the cropping system from traditional transplanting to direct-seeded water-saving rice production that favored the development of M. graminicola. Scouting and deploying new resistance genes is an economical approach to managing the root-knot nematodes. Here, we report that the inheritance of root-knot nematode resistance in Oryza glaberrima acc. IRGC102206 is governed by a single dominant gene. Traditional mapping coupled with BSA-seq is used to map nematode resistance gene(s) using the BC₁F₁ population derived from a cross of O. sativa cv. PR121 (S) and O. glaberrima acc. IRGC102206 (R). One major novel genomic region spanning a 3.0-Mb interval on chromosome 6 and two minor QTLs on chromosomes 2 and 4 are the potential genomic regions associated with rice root-knot nematode resistance. Within the QTL regions, 19 putative candidate genes contain 81 non-synonymous variants. The detected major candidate region could be fine mapped to accelerate marker-assisted breeding for root-knot nematode resistance in rice.

Identification of Sclerotinia stem rot resistance quantitative trait loci in a chickpea (Cicer arietinum) recombinant inbred line population

Sclerotinia stem rot (SSR), caused by Sclerotinia sclerotiorum , is one of the most economically devastating diseases in chickpea (Cicer arietinum L.). No complete resistance is available in chickpea to this disease, and the inheritance of partial resistance is not understood. Two hundred F7 recombinant inbred lines (RILs) derived from a cross between a partially resistant variety PBA HatTrick, and a highly susceptible variety Kyabra were characterised for their responses to SSR inoculation. Quantitative trait locus (QTL) analysis was conducted for the area under the disease progress curve (AUDPC) after RIL infection with S. sclerotiorum . Four QTLs on chromosomes, Ca4 (qSSR4-1, qSSR4-2), Ca6 (qSSR6-1) and Ca7 (qSSR7-1), individually accounted for between 4.2 and 15.8% of the total estimated phenotypic variation for the response to SSR inoculation. Candidate genes located in these QTL regions are predicted to be involved in a wide range of processes, including phenylpropanoid biosynthesis, plant-pathogen interaction, and plant hormone signal transduction. This is the first study investigating the inheritance of resistance to S. sclerotiorum in chickpea. Markers associated with the identified QTLs could be employed for marker-assisted selection in chickpea breeding.

Detection of a major QTL and development of KASP markers for seed weight by combining QTL-seq, QTL-mapping and RNA-seq in peanut

Combining QTL-seq, QTL-mapping and RNA-seq identified a major QTL and candidate genes, which contributed to the development of KASP markers and understanding of molecular mechanisms associated with seed weight in peanut. Seed weight, as an important component of seed yield, is a significant target of peanut breeding. However, relatively little is known about the quantitative trait loci (QTLs) and candidate genes associated with seed weight in peanut. In this study, three major QTLs on chromosomes A05, B02, and B06 were determined by applying the QTL-seq approach in a recombinant inbred line (RIL) population. Based on conventional QTL-mapping, these three QTL regions were successfully narrowed down through newly developed single nucleotide polymorphism (SNP) and simple sequence repeat markers. Among these three QTL regions, qSWB06.3 exhibited stable expression, contributing mainly to phenotypic variance across environments. Furthermore, differentially expressed genes (DEGs) were identified at the three seed developmental stages between the two parents of the RIL population. It was found that the DEGs were widely distributed in the ubiquitin-proteasome pathway, the serine/threonine-protein pathway, signal transduction of hormones and transcription factors. Notably, DEGs at the early stage were mostly involved in regulating cell division, whereas DEGs at the middle and late stages were primarily involved in cell expansion during seed development. The expression patterns of candidate genes related to seed weight in qSWB06.3 were investigated using quantitative real-time PCR. In addition, the allelic diversity of qSWB06.3 was investigated in peanut germplasm accessions. The marker Ah011475 has higher efficiency for discriminating accessions with different seed weights, and it would be useful as a diagnostic marker in marker-assisted breeding. This study provided insights into the genetic and molecular mechanisms of seed weight in peanut.

Novel Genomic Regions Linked to Ascochyta Blight Resistance in Two Differentially Resistant Cultivars of Chickpea

Ascochyta blight (AB), caused by the fungal pathogen Ascochyta rabiei, is a devastating foliar disease of chickpea (Cicer arietinum L.). The genotyping-by-sequencing (GBS)-based approach was deployed for mapping QTLs associated with AB resistance in chickpea in two recombinant inbred line populations derived from two crosses (AB₃₂₇₉ derived from ILC 1929 × ILC 3279 and AB₄₈₂ derived from ILC 1929 × ILC 482) and tested in six different environments. Twenty-one different genomic regions linked to AB resistance were identified in regions CalG02 and CalG04 in both populations AB₃₂₇₉ and AB₄₈₂. These regions contain 1,118 SNPs significantly associated with AB resistance (p ≤ 0.001), which explained 11.2-39.3% of the phenotypic variation (PVE). Nine of the AB resistance-associated genomic regions were newly detected in this study, while twelve regions were known from previous AB studies. The proposed physical map narrows down AB resistance to consistent genomic regions identified across different environments. Gene ontology (GO) assigned these QTLs to 319 genes, many of which were associated with stress and disease resistance, and with most important genes belonging to resistance gene families such as leucine-rich repeat (LRR) and transcription factor families. Our results indicate that the flowering-associated gene GIGANTEA is a possible key factor in AB resistance in chickpea. The results have identified AB resistance-associated regions on the physical genetic map of chickpea and allowed for the identification of associated markers that will help in breeding of AB-resistant varieties.

Breeding and Genomics Interventions for Developing Ascochyta Blight Resistant Grain Legumes

Grain legumes are a key food source for ensuring global food security and sustaining agriculture. However, grain legume production is challenged by growing disease incidence due to global climate change. Ascochyta blight (AB) is a major disease, causing substantial yield losses in grain legumes worldwide. Harnessing the untapped reserve of global grain legume germplasm, landraces, and crop wild relatives (CWRs) could help minimize yield losses caused by AB infection in grain legumes. Several genetic determinants controlling AB resistance in various grain legumes have been identified following classical genetic and conventional breeding approaches. However, the advent of molecular markers, biparental quantitative trait loci (QTL) mapping, genome-wide association studies, genomic resources developed from various genome sequence assemblies, and whole-genome resequencing of global germplasm has revealed AB-resistant gene(s)/QTL/genomic regions/haplotypes on various linkage groups. These genomics resources allow plant breeders to embrace genomics-assisted selection for developing/transferring AB-resistant genomic regions to elite cultivars with great precision. Likewise, advances in functional genomics, especially transcriptomics and proteomics, have assisted in discovering possible candidate gene(s) and proteins and the underlying molecular mechanisms of AB resistance in various grain legumes. We discuss how emerging cutting-edge next-generation breeding tools, such as rapid generation advancement, field-based high-throughput phenotyping tools, genomic selection, and CRISPR/Cas9, could be used for fast-tracking AB-resistant grain legumes to meet the increasing demand for grain legume-based protein diets and thus ensuring global food security.

Optimization of BSA-seq experiment for QTL mapping

Deep sequencing-based bulked segregant analysis (BSA-seq) has become a popular approach for quantitative trait loci (QTL) mapping in recent years. Effective statistical methods for BSA-seq have been developed, but how to design a suitable experiment for BSA-seq remains unclear. In this paper, we show in theory how the major experimental factors (including population size, pool proportion, pool balance, and generation) and the intrinsic factors of a QTL (including heritability and degree of dominance) affect the power of QTL detection and the precision of QTL mapping in BSA-seq. Increasing population size can improve the power and precision, depending on the QTL heritability. The best proportion of each pool in the population is around 0.25. So, 0.25 is generally applicable in BSA-seq. Small pool proportion can greatly reduce the power and precision. Imbalance of pool pair in size also causes decrease of the power and precision. Additive effect is more important than dominance effect for QTL mapping. Increasing the generation of filial population produced by selfing can significantly increase the power and precision, especially from F2 to F3. These findings enable researchers to optimize the experimental design for BSA-seq. A web-based program named BSA-seq Design Tool is available at http://124.71.74.135/BSA-seqDesignTool/ and https://github.com/huanglikun/BSA-seqDesignTool.

Genome-Wide Association Analyses Track Genomic Regions for Resistance to Ascochyta rabiei in Australian Chickpea Breeding Germplasm

Ascochyta blight (AB), caused by a necrotrophic fungus, Ascochyta rabiei (syn. Phoma rabiei) has the potential to destroy the chickpea industry worldwide, due to limited sources of genetic resistance in the cultivated gene pool, high evolutionary potential of the pathogen and challenges with integrated disease management. Therefore, the deployment of stable genetic resistance in new cultivars could provide an effective disease control strategy. To investigate the genetic basis of AB resistance, genotyping-by-sequencing based DArTseq-single nucleotide polymorphism (SNP) marker data along with phenotypic data of 251 advanced breeding lines and chickpea cultivars were used to perform genome-wide association (GWAS) analysis. Host resistance was evaluated seven weeks after sowing using two highly aggressive single spore isolates (F17191-1 and TR9571) of A. rabiei. GWAS analyses based on single-locus and multi-locus mixed models and haplotyping trend regression identified twenty-six genomic regions on Ca1, Ca4, and Ca6 that showed significant association with resistance to AB. Two haplotype blocks (HB) on chromosome Ca1; HB5 (992178-1108145 bp), and HB8 (1886221-1976301 bp) were associated with resistance against both isolates. Nine HB on the chromosome, Ca4, spanning a large genomic region (14.9-56.6 Mbp) were also associated with resistance, confirming the role of this chromosome in providing resistance to AB. Furthermore, trait-marker associations in two F₃ derived populations for resistance to TR9571 isolate at the seedling stage under glasshouse conditions were also validated. Eighty-nine significantly associated SNPs were located within candidate genes, including genes encoding for serine/threonine-protein kinase, Myb protein, quinone oxidoreductase, and calmodulin-binding protein all of which are implicated in disease resistance. Taken together, this study identifies valuable sources of genetic resistance, SNP markers and candidate genes underlying genomic regions associated with AB resistance which may enable chickpea breeding programs to make genetic gains via marker-assisted/genomic selection strategies.

Combining QTL-seq and linkage mapping to uncover the genetic basis of single vs. paired spikelets in the advanced populations of two-ranked maize×teosinte

BACKGROUND

Teosinte ear bears single spikelet, whereas maize ear bears paired spikelets, doubling the number of grains in each cupulate during maize domestication. In the past 20 years, genetic analysis of single vs. paired spikelets (PEDS) has been stagnant. A better understanding of genetic basis of PEDS could help fine mapping of quantitative trait loci (QTL) and cloning of genes.

RESULTS

In this study, the advanced mapping populations (BC₃F₂ and BC₄F₂) of maize × teosinte were developed by phenotypic recurrent selection. Four genomic regions associated with PEDS were detected using QTL-seq, located on 194.64-299.52 Mb, 0-162.80 Mb, 12.82-97.17 Mb, and 125.06-157.01 Mb of chromosomes 1, 3, 6, and 8, respectively. Five QTL for PEDS were identified in the regions of QTL-seq using traditional QTL mapping. Each QTL explained 1.12-38.05% of the phenotypic variance (PVE); notably, QTL qPEDS3.1 with the average PVE of 35.29% was identified in all tests. Moreover, 14 epistatic QTL were detected, with the total PVE of 47.57-66.81% in each test. The QTL qPEDS3.1 overlapped with, or was close to, one locus of 7 epistatic QTL. Near-isogenic lines (NILs) of QTL qPEDS1.1, qPEDS3.1, qPEDS6.1, and qPEDS8.1 were constructed. All individuals of NIL-qPEDS6.1(MT1) and NIL-qPEDS8.1(MT1) showed paired spikelets (PEDS = 0), but the flowering time was 7 days shorter in the NIL-qPEDS8.1(MT1). The ratio of plants with PEDS > 0 was low (1/18 to 3/18) in the NIL-qPEDS1.1(MT1) and NIL-qPEDS3.1(MT1), maybe due to the epistatic effect.

CONCLUSION

Our results suggested that major QTL, minor QTL, epistasis and photoperiod were associated with the variation of PEDS, which help us better understand the genetic basis of PEDS and provide a genetic resource for fine mapping of QTL.

Bulk analysis by resequencing and RNA-seq identifies candidate genes for maintaining leaf water content under water deficit in maize

Drought is one of the main abiotic stresses adversely affecting maize growth and grain yield. Identifying drought tolerance-related genes and breeding varieties with enhanced tolerance are effective strategies for minimizing the effects of drought stress. In this study, the leaf relative water content (LRWC) was used for evaluating drought tolerance. QTL-seq analysis of 419 F₂ individuals from a cross between ZhengT22 (the drought-tolerant line with high LRWC) and ZhengA88 (the drought-sensitive line with low LRWC) revealed four LRWC-related QTLs (qLRWC2, qLRWC10a, qLRWC10b, and qLRWC10c) in maize seedlings under water deficit. Of these QTLs, qLRWC2 was located in a 2.03-Mb interval on chromosome 2, whereas qLRWC10a, qLRWC10b, and qLRWC10c were located in 2.85-, 3.99-, and 2.05-Mb intervals, respectively, on chromosome 10, and the 93 genes contained the variation loci locating in the four QTLs regions. To identify the candidate genes within the QTLs, an RNA-seq analysis was performed for the parents exposed to water deficit. Seven genes with effective variation loci showed significant difference in expression either in ZhengA88 or ZhengT22 in response to water deficit. Moreover, among the genes, ZmPrx64, ZmCIPK, HSP90, and ABCG34 have all been shown to be related to water stress in the previous studies. Thus, they are primary considered as the potential candidate genes controlling LRWC under water deficit at the seeding stage of maize in this study. These findings will help clarify the molecular basis of drought tolerance in maize seedlings and may be relevant for future functional analysis and for breeding drought-tolerant maize varieties.

Identification and Validation of a QTL for Bacterial Leaf Streak Resistance in Rice (Oryza sativa L.) against Thai Xoc Strains

Rice is one of the most important food crops in the world and is of vital importance to many countries. Various diseases caused by fungi, bacteria and viruses constantly threaten rice plants and cause yield losses. Bacterial leaf streak disease (BLS) caused by Xanthomonas oryzae pv. oryzicola (Xoc) is one of the most devastating rice diseases. However, most modern rice varieties are susceptible to BLS. In this study, we applied the QTL-seq approach using an F2 population derived from the cross between IR62266 and Homcholasit (HSC) to rapidly identify the quantitative trait loci (QTL) that confers resistance to BLS caused by a Thai Xoc isolate, SP7-5. The results showed that a single genomic region at the beginning of chromosome 5 was highly associated with resistance to BLS. The gene xa5 was considered a potential candidate gene in this region since most associated single nucleotide polymorphisms (SNPs) were within this gene. A Kompetitive Allele-Specific PCR (KASP) marker was developed based on two consecutive functional SNPs in xa5 and validated in six F2 populations inoculated with another Thai Xoc isolate, 2NY2-2. The phenotypic variance explained by this marker (PVE) ranged from 59.04% to 70.84% in the six populations. These findings indicate that xa5 is a viable candidate gene for BLS resistance and may help in breeding programs for BLS resistance.

Genetic Diversity and Population Structure of Didymella rabiei Affecting Chickpea in Ethiopia

Ascochyta blight, also known as chickpea blight, which is caused by the fungal pathogen, Didymella rabiei, is an important disease affecting chickpea (Cicer arietinum L.) in many countries. We studied the genetic diversity and population structure of 96 D. rabiei isolates collected from three geographic populations in Ethiopia using simple sequence repeat (SSR) markers. We confirmed the genetic identity of 89 of the D. rabiei isolates by sequencing their rRNA internal transcribed spacer region genes. The chickpea blight pathogen isolates were genetically diverse, with a total of 51 alleles identified across 6 polymorphic SSR loci, which varied from 3 to 18 (average 8.5) alleles per SSR marker. The observed heterozygosity and expected heterozygosity ranged from 0.01 to 0.92 and 0.19 to 0.86, respectively. The mean polymorphic information content value of the D. rabiei populations was 0.58, with a mean gene diversity of 0.61 among loci. Gene flow (Nm = number of migrants) for the three populations of D. rabiei isolates ranged from 1.51 to 24.10 (average 6.2) migrants/cluster. However, the genetic variation between the D. rabiei populations was small (8%), with most of the variation occurring within populations (92%). Principal component analysis to visualize genetic variation showed that the D. rabiei isolates obtained from most of the chickpea samples formed roughly three groups on a two-dimensional coordinate plane. Similarly, the clustering of individuals into populations based on multi-locus genotypes (using Clumpak) grouped isolates into three clusters but with individual isolate admixtures. Hence, no clear geographic origin-based structuring of populations could be identified. To our knowledge, this is the first report of D. rabiei diversity in Ethiopia. Virulence studies should be conducted to develop chickpea varieties that are resistant to more aggressive pathogen populations.

The Sequencing-Based Mapping Method for Effectively Cloning Plant Mutated Genes

A forward genetic approach is a powerful tool for identifying the genes underlying the phenotypes of interest. However, the conventional map-based cloning method is lengthy, requires a large mapping population and confirmation of many candidate genes in a broad genetic region to clone the causal variant. The whole-genome sequencing method clones the variants with a certain failure probability for multiple reasons, especially for heterozygotes, and could not be used to clone the mutation of epigenetic modifications. Here, we applied the highly complementary characteristics of these two methods and developed a sequencing-based mapping method (SBM) for identifying the location of plant variants effectively with a small population and low cost, which is very user-friendly for most popular laboratories. This method used the whole-genome sequencing data of two pooled populations to screen out enough markers. These markers were used to identify and narrow the candidate region by analyzing the marker-indexes and recombinants. Finally, the possible mutational sites were identified using the whole-genome sequencing data and verified in individual mutants. To elaborate the new method, we displayed the cloned processes in one Arabidopsis heterozygous mutant and two rice homozygous mutants. Thus, the sequencing-based mapping method could clone effectively different types of plant mutations and was a powerful tool for studying the functions of plant genes in the species with known genomic sequences.

Understanding Omics Driven Plant Improvement and de novo Crop Domestication: Some Examples

In the current era, one of biggest challenges is to shorten the breeding cycle for rapid generation of a new crop variety having high yield capacity, disease resistance, high nutrient content, etc. Advances in the "-omics" technology have revolutionized the discovery of genes and bio-molecules with remarkable precision, resulting in significant development of plant-focused metabolic databases and resources. Metabolomics has been widely used in several model plants and crop species to examine metabolic drift and changes in metabolic composition during various developmental stages and in response to stimuli. Over the last few decades, these efforts have resulted in a significantly improved understanding of the metabolic pathways of plants through identification of several unknown intermediates. This has assisted in developing several new metabolically engineered important crops with desirable agronomic traits, and has facilitated the de novo domestication of new crops for sustainable agriculture and food security. In this review, we discuss how "omics" technologies, particularly metabolomics, has enhanced our understanding of important traits and allowed speedy domestication of novel crop plants.

Introgression of "QTL-hotspot" region enhances drought tolerance and grain yield in three elite chickpea cultivars

With an aim of enhancing drought tolerance using a marker-assisted backcrossing (MABC) approach, we introgressed the "QTL-hotspot" region from ICC 4958 accession that harbors quantitative trait loci (QTLs) for several drought-tolerance related traits into three elite Indian chickpea (Cicer arietinum L.) cultivars: Pusa 372, Pusa 362, and DCP 92-3. Of eight simple sequence repeat (SSR) markers in the QTL-hotspot region, two to three polymorphic markers were used for foreground selection with respective cross-combinations. A total of 47, 53, and 46 SSRs were used for background selection in case of introgression lines (ILs) developed in genetic backgrounds of Pusa 372, Pusa 362, and DCP 92-3, respectively. In total, 61 ILs (20 BC₃ F₃ in Pusa 372; 20 BC₂ F₃ in Pusa 362, and 21 BC₃ F₃ in DCP 92-3), with >90% recurrent parent genome recovery were developed. Six improved lines in different genetic backgrounds (e.g. BGM 10216 in Pusa 372; BG 3097 and BG 4005 in Pusa 362; IPC(L4-14), IPC(L4-16), and IPC(L19-1) in DCP 92-3) showed better performance than their respective recurrent parents. BGM 10216, with 16% yield gain over Pusa 372, has been released as Pusa Chickpea 10216 by the Central Sub-Committees on Crop Standards, Notification and Release of Varieties of Agricultural Crops, Ministry of Agriculture and Farmers Welfare, Government of India, for commercial cultivation in India. In summary, this study reports introgression of the QTL-hotspot for enhancing yield under rainfed conditions, development of several introgression lines, and release of Pusa Chickpea 10216 developed through molecular breeding in India.

QTL-Seq and Transcriptome Analysis Disclose Major QTL and Candidate Genes Controlling Leaf Size in Sesame (Sesamum indicum L.)

Leaf size is a crucial component of sesame (Sesamum indicum L.) plant architecture and further influences yield potential. Despite that it is well known that leaf size traits are quantitative traits controlled by large numbers of genes, quantitative trait loci (QTL) and candidate genes for sesame leaf size remain poorly understood. In the present study, we combined the QTL-seq approach and SSR marker mapping to identify the candidate genomic regions harboring QTL controlling leaf size traits in an RIL population derived from a cross between sesame varieties Zhongzhi No. 13 (with big leaves) and ZZM2289 (with small leaves). The QTL mapping revealed 56 QTL with phenotypic variation explained (PVE) from 1.87 to 27.50% for the length and width of leaves at the 1/3 and 1/2 positions of plant height. qLS15-1, a major and environmentally stable pleiotropic locus for both leaf length and width explaining 5.81 to 27.50% phenotypic variation, was located on LG15 within a 408-Kb physical genomic region flanked by the markers ZMM6185 and ZMM6206. In this region, a combination of transcriptome analysis with gene annotations revealed three candidate genes SIN_1004875, SIN_1004882, and SIN_1004883 associated with leaf growth and development in sesame. These findings provided insight into the genetic characteristics and variability for sesame leaf and set up the foundation for future genomic studies on sesame leaves and will serve as gene resources for improvement of sesame plant architecture.

Rapid Mining of Candidate Genes for Verticillium Wilt Resistance in Cotton Based on BSA-Seq Analysis

Cotton is a globally important cash crop. Verticillium wilt (VW) is commonly known as "cancer" of cotton and causes serious loss of yield and fiber quality in cotton production around the world. Here, we performed a BSA-seq analysis using an F_2:3 segregation population to identify the candidate loci involved in VW resistance. Two QTLs (qvw-D05-1 and qvw-D05-2) related to VW resistance in cotton were identified using two resistant/susceptible bulks from the F₂ segregation population constructed by crossing the resistant cultivar ZZM2 with the susceptible cultivar J11. A total of 30stop-lost SNPs and 42 stop-gained SNPs, which included 17 genes, were screened in the qvw-D05-2 region by SnpEff analysis. Further analysis of the transcriptome data and qRT-PCR revealed that the expression level of Ghir_D05G037630 (designated as GhDRP) varied significantly at certain time points after infection with V. dahliae. The virus-induced gene silencing of GhDRP resulted in higher susceptibility of the plants to V. dahliae than the control, suggesting that GhDRP is involved in the resistance to V. dahlia infection. This study provides a method for rapid mining of quantitative trait loci and screening of candidate genes, as well as enriches the genomic information and gene resources for the molecular breeding of disease resistance in cotton.

Genomic interventions for sustainable agriculture

Agricultural production faces a Herculean challenge to feed the increasing global population. Food production systems need to deliver more with finite land and water resources while exerting the least negative influence on the ecosystem. The unpredictability of climate change and consequent changes in pests/pathogens dynamics aggravate the enormity of the challenge. Crop improvement has made significant contributions towards food security, and breeding climate-smart cultivars are considered the most sustainable way to accelerate food production. However, a fundamental change is needed in the conventional breeding framework in order to respond adequately to the growing food demands. Progress in genomics has provided new concepts and tools that hold promise to make plant breeding procedures more precise and efficient. For instance, reference genome assemblies in combination with germplasm sequencing delineate breeding targets that could contribute to securing future food supply. In this review, we highlight key breakthroughs in plant genome sequencing and explain how the presence of these genome resources in combination with gene editing techniques has revolutionized the procedures of trait discovery and manipulation. Adoption of new approaches such as speed breeding, genomic selection and haplotype-based breeding could overcome several limitations of conventional breeding. We advocate that strengthening varietal release and seed distribution systems will play a more determining role in delivering genetic gains at farmer's field. A holistic approach outlined here would be crucial to deliver steady stream of climate-smart crop cultivars for sustainable agriculture.

Prospects of next generation sequencing in lentil breeding

Lentil is an important food legume crop that has large and complex genome. During past years, considerable attention has been given on the use of next generation sequencing for enriching the genomic resources including identification of SSR and SNP markers, development of unigenes, transcripts, and identification of candidate genes for biotic and abiotic stresses, analysis of genetic diversity and identification of genes/ QTLs for agronomically important traits. However, in other crops including pulses, next generation sequencing has revolutionized the genomic research and helped in genomic assisted breeding rapidly and cost effectively. The present review discuss current status and future prospects of the use NGS based breeding in lentil.

Fine mapping and gene cloning in the post-NGS era: advances and prospects

Improvement in traits of agronomic importance is the top breeding priority of crop improvement programs. Majority of these agronomic traits show complex quantitative inheritance. Identification of quantitative trait loci (QTLs) followed by fine mapping QTLs and cloning of candidate genes/QTLs is central to trait analysis. Advances in genomic technologies revolutionized our understanding of genetics of complex traits, and genomic regions associated with traits were employed in marker-assisted breeding or cloning of QTLs/genes. Next-generation sequencing (NGS) technologies have enabled genome-wide methodologies for the development of ultra-high-density genetic linkage maps in different crops, thus allowing placement of candidate loci within few kbs in genomes. In this review, we compare the marker systems used for fine mapping and QTL cloning in the pre- and post-NGS era. We then discuss how different NGS platforms in combination with advanced experimental designs have improved trait analysis and fine mapping. We opine that efficient genotyping/sequencing assays may circumvent the need for cumbersome procedures that were earlier used for fine mapping. A deeper understanding of the trait architectures of agricultural significance will be crucial to accelerate crop improvement.

Integrating genomics for chickpea improvement: achievements and opportunities

Integration of genomic technologies with breeding efforts have been used in recent years for chickpea improvement. Modern breeding along with low cost genotyping platforms have potential to further accelerate chickpea improvement efforts. The implementation of novel breeding technologies is expected to contribute substantial improvements in crop productivity. While conventional breeding methods have led to development of more than 200 improved chickpea varieties in the past, still there is ample scope to increase productivity. It is predicted that integration of modern genomic resources with conventional breeding efforts will help in the delivery of climate-resilient chickpea varieties in comparatively less time. Recent advances in genomics tools and technologies have facilitated the generation of large-scale sequencing and genotyping data sets in chickpea. Combined analysis of high-resolution phenotypic and genetic data is paving the way for identifying genes and biological pathways associated with breeding-related traits. Genomics technologies have been used to develop diagnostic markers for use in marker-assisted backcrossing programmes, which have yielded several molecular breeding products in chickpea. We anticipate that a sequence-based holistic breeding approach, including the integration of functional omics, parental selection, forward breeding and genome-wide selection, will bring a paradigm shift in development of superior chickpea varieties. There is a need to integrate the knowledge generated by modern genomics technologies with molecular breeding efforts to bridge the genome-to-phenome gap. Here, we review recent advances that have led to new possibilities for developing and screening breeding populations, and provide strategies for enhancing the selection efficiency and accelerating the rate of genetic gain in chickpea.

Ethylene-responsive factor 4 is associated with the desirable rind hardness trait conferring cracking resistance in fresh fruits of watermelon

Fruit rind plays a pivotal role in alleviating water loss and disease and particularly in cracking resistance as well as the transportability, storability and shelf-life quality of the fruit. High susceptibility to cracking due to low rind hardness is largely responsible for severe annual yield losses of fresh fruits such as watermelon in the field and during the postharvest process. However, the candidate gene controlling the rind hardness phenotype remains unclear to date. Herein, we report, for the first time, an ethylene-responsive transcription factor 4 (ClERF4) associated with variation in rind hardness via a combinatory genetic map with bulk segregant analysis (BSA). Strikingly, our fine-mapping approach revealed an InDel of 11 bp and a neighbouring SNP in the ClERF4 gene on chromosome 10, conferring cracking resistance in F₂ populations with variable rind hardness. Furthermore, the concomitant kompetitive/competitive allele-specific PCR (KASP) genotyping data sets of 104 germplasm accessions strongly supported candidate ClERF4 as a causative gene associated with fruit rind hardness variability. In conclusion, our results provide new insight into the underlying mechanism controlling rind hardness, a desirable trait in fresh fruit. Moreover, the findings will further enable the molecular improvement of fruit cracking resistance in watermelon via precisely targeting the causative gene relevant to rind hardness, ClERF4.

Next-generation sequencing identified genomic region and diagnostic markers for resistance to bacterial wilt on chromosome B02 in peanut (Arachis hypogaea L.)

Bacterial wilt, caused by Ralstonia solanacearum, is a devastating disease affecting over 350 plant species. A few peanut cultivars were found to possess stable and durable bacterial wilt resistance (BWR). Genomics-assisted breeding can accelerate the process of developing resistant cultivars by using diagnostic markers. Here, we deployed sequencing-based trait mapping approach, QTL-seq, to discover genomic regions, candidate genes and diagnostic markers for BWR in a recombination inbred line population (195 progenies) of peanut. The QTL-seq analysis identified one candidate genomic region on chromosome B02 significantly associated with BWR. Mapping of newly developed single nucleotide polymorphism (SNP) markers narrowed down the region to 2.07 Mb and confirmed its major effects and stable expressions across three environments. This candidate genomic region had 49 nonsynonymous SNPs affecting 19 putative candidate genes including seven putative resistance genes (R-genes). Two diagnostic markers were successfully validated in diverse breeding lines and cultivars and could be deployed in genomics-assisted breeding of varieties with enhanced BWR.

Construction, characteristics and high throughput molecular screening methodologies in some special breeding populations: a horticultural perspective

Advanced marker technologies are widely used for evaluation of genetic diversity in cultivated crops, wild ancestors, landraces or any special plant genotypes. Developing agricultural cultivars requires the following steps: (i) determining desired characteristics to be improved, (ii) screening genetic resources to help find a superior cultivar, (iii) intercrossing selected individuals, (iv) generating genetically hybrid populations and screening them for agro-morphological or molecular traits, (v) evaluating the superior cultivar candidates, (vi) testing field performance at different locations, and (vii) certifying. In the cultivar development process valuable genes can be identified by creating special biparental or multiparental populations and analysing their association using suitable markers in given populations. These special populations and advanced marker technologies give us a deeper knowledge about the inherited agronomic characteristics. Unaffected by the changing environmental conditions, these provide a higher understanding of genome dynamics in plants. The last decade witnessed new applications for advanced molecular techniques in the area of breeding,with low costs per sample. These, especially, include next-generation sequencing technologies like reduced representation genome sequencing (genotyping by sequencing, restriction site-associated DNA). These enabled researchers to develop new markers, such as simple sequence repeat and single- nucleotide polymorphism, for expanding the qualitative and quantitative information onpopulation dynamics. Thus, the knowledge acquired from novel technologies is a valuable asset for the breeding process and to better understand the population dynamics, their properties, and analysis methods.

Genome-wide SNP discovery for development of high-density genetic map and QTL mapping of ascochyta blight resistance in chickpea (Cicer arietinum L.)

A high-density linkage map of chickpea using 3430 SNPs was constructed and used to identify QTLs and candidate genes for ascochyta blight resistance in chickpea. Chickpea cultivation in temperate conditions is highly vulnerable to ascochyta blight infection. Cultivation of resistant cultivars in combination with fungicide application within an informed disease management package is the most effective method to control ascochyta blight in chickpeas. Identifying new sources of resistance is critical for continued improvement in ascochyta blight resistance in chickpea. The objective of this study was to identify genetic loci and candidate genes controlling the resistance to ascochyta blight in recombinant inbred lines derived from crossing cultivars Amit and ICCV 96029. The RILs were genotyped using the genotyping-by-sequencing procedure and Illumina^® GoldenGate array. The RILs were evaluated in the field over three site-years and in three independent greenhouse experiments. A genetic map with eight linkage groups was constructed using 3430 SNPs. Eight QTLs for resistance were identified on chromosomes 2, 3, 4, 5 and 6. The QTLs individually explained 7-40% of the phenotypic variations. The QTLs on chromosomes 2 and 6 were associated with the resistance at vegetative stage only. The QTLs on chromosomes 2 and 4 that were previously reported to be conserved across diverse genetic backgrounds and against different isolates of Ascochyta rabiei were confirmed in this study. Candidate genes were identified within the QTL regions. Their co-localization with the underlying QTLs was confirmed by genetic mapping. The candidate gene-based SNP markers would lead to more efficient marker-assisted selection for ascochyta blight resistance and would provide a framework for fine mapping and subsequent cloning of the genes associated with the resistance.

Genetic factors affecting Fusarium head blight resistance improvement from introgression of exotic Sumai 3 alleles (including Fhb1, Fhb2, and Fhb5) in hard red spring wheat

BACKGROUND

Fusarium head blight resistance genes, Fhb1 (for Type-II resistance), Fhb2 (Type-II), and Fhb5 (Type-I plus some Type-II), which originate from Sumai 3, are among the most important that confer resistance in hexaploid wheat. Near-isogenic lines (NILs), in the CDC Alsask (susceptible; n = 32) and CDC Go (moderately susceptible; n = 38) backgrounds, carrying these genes in all possible combinations were developed using flanking microsatellite markers and evaluated for their response to FHB and deoxynivalenol (DON) accumulation in eight environments. NILs were haplotyped with wheat 90 K iSelect assay to elucidate the genomic composition and confirm alleles' presence. Other than evaluating the effects of three major genes in common genetic background, the study elucidated the epistatic gene interactions as they influence FHB measurements; identified loci other than Fhb1, Fhb2, and Fhb5, in both recurrent and donor parents and examined annotated proteins in gene intervals.

RESULTS

Genotyping using 81,857 single nucleotide polymorphism (SNP) markers revealed polymorphism on all chromosomes and that the NILs carried < 3% of alleles from the resistant donor. Significant improvement in field resistance (Type-I + Type-II) resulted only among the CDC Alsask NILs, not the CDC Go NILs. The phenotypic response of NILs carrying combinations of Sumai 3 derived genes suggested non-additive responses and Fhb5 was as good as Fhb1 in conferring field resistance in both populations. In addition to Fhb1, Fhb2, and Fhb5, four to five resistance improving alleles in both populations were identified and three of five in CDC Go were contributed by the susceptible parent. The introgressed chromosome regions carried genes encoding disease resistance proteins, protein kinases, nucleotide-binding and leucine rich repeats' domains. Complex epistatic gene-gene interactions among marker loci (including Fhb1, Fhb2, Fhb5) explained > 20% of the phenotypic variation in FHB measurements.

CONCLUSIONS

Immediate Sumai 3 derivatives carry a number of resistance improving minor effect alleles, other than Fhb1, Fhb2, Fhb5. Results verified that marker-assisted selection is possible for the introgression of exotic FHB resistance genes, however, the genetic background of the recipient line and epistatic interactions can have a strong influence on expression and penetrance of any given gene.

Identification and validation of a novel major QTL for all-stage stripe rust resistance on 1BL in the winter wheat line 20828

A major, likely novel stripe rust resistance QTL for all-stage resistance on chromosome arm 1BL identified in a 1.76-cM interval using a saturated linkage map was validated in four populations with different genetic backgrounds. Stripe rust is a globally important disease of wheat. Identification and utilization of new resistance genes are essential for breeding resistant cultivars. Wheat line 20828 has exhibited high levels of stripe rust resistance for over a decade. However, the genetics of stripe rust resistance in this line has not been studied. A set of 199 recombinant inbred lines (RILs) were developed from a cross between 20828 and a susceptible cultivar Chuannong 16. The RIL population was genotyped with the Wheat55K SNP (single nucleotide polymorphism) array and SSR (simple sequence repeat) markers and evaluated in four environments with current predominant Puccinia striiformis f. sp. tritici t races including CYR32, CYR33 and CYR34. Four stable QTL were located on chromosomes 1B (2 QTL), 4A and 6A. Among them, the major QTL, QYr.sicau-1B.1 (LOD = 23-28, PVE = 16-39%), was localized to a 1.76-cM interval flanked by SSR markers Xwmc216 and Xwmc156 on chromosome 1BL. Eight resistance genes were previously identified in the physical interval of QYr.sicau-1B.1. Compared with previous studies, QYr.sicau-1B.1 is a new gene for resistant to stripe rust. It was further verified by analysis of the closely linked SSR markers Xwmc216 and Xwmc156 in four other populations with different genetic backgrounds. QYr.sicau-1B.1 reduced the stripe rust disease index by up to 82.8%. Three minor stable QTL (located on chromosomes 1B, 4A and 6A, respectively) also added to the resistance level of QYr.sicau-1B.1. Our results provide valuable information for further fine mapping and cloning as well as molecular-assisted breeding with QYr.sicau-1B.1.

Toward the sequence-based breeding in legumes in the post-genome sequencing era

Efficiency of breeding programs of legume crops such as chickpea, pigeonpea and groundnut has been considerably improved over the past decade through deployment of modern genomic tools and technologies. For instance, next-generation sequencing technologies have facilitated availability of genome sequence assemblies, re-sequencing of several hundred lines, development of HapMaps, high-density genetic maps, a range of marker genotyping platforms and identification of markers associated with a number of agronomic traits in these legume crops. Although marker-assisted backcrossing and marker-assisted selection approaches have been used to develop superior lines in several cases, it is the need of the hour for continuous population improvement after every breeding cycle to accelerate genetic gain in the breeding programs. In this context, we propose a sequence-based breeding approach which includes use of independent or combination of parental selection, enhancing genetic diversity of breeding programs, forward breeding for early generation selection, and genomic selection using sequencing/genotyping technologies. Also, adoption of speed breeding technology by generating 4-6 generations per year will be contributing to accelerate genetic gain. While we see a huge potential of the sequence-based breeding to revolutionize crop improvement programs in these legumes, we anticipate several challenges especially associated with high-quality and precise phenotyping at affordable costs, data analysis and management related to improving breeding operation efficiency. Finally, integration of improved seed systems and better agronomic packages with the development of improved varieties by using sequence-based breeding will ensure higher genetic gains in farmers' fields.

Genetic Mapping of Resistance in Hexaploid Wheat for a Quarantine Disease: Karnal Bunt

Karnal bunt (KB) of wheat, caused by Tilletia indica, is one of the greatest challenges to grain industry, not because of yield loss, but quarantine regulations that restrict international movement and trade of affected stocks. Genetic resistance is the best way to manage this disease. Although several different sources of resistance have been identified to date, very few of those have been subjected to genetic analyses. Understanding the genetics of resistance, characterization and mapping of new resistance loci can help in development of improved germplasm. The objective of this study was to identify and characterize resistance loci (QTL) in two independent recombinant inbred lines (RILs) populations utilizing different wheat lines as resistance donors. Elite CIMMYT wheat lines Blouk#1 and Huirivis#1 were used as susceptible female parents and WHEAR/KUKUNA/3/C80.1/3∗BATAVIA//2∗WBLL1 (WKCBW) and Mutus as moderately resistant male parents in Pop1 and Pop2 populations, respectively. Populations were evaluated for KB resistance in 2015-16 and 2016-17 cropping seasons at two seeding dates (total four environments) in Cd. Obregon, Mexico. Two stable QTL from each population were identified in each environment: QKb.cim-2B and QKb.cim-3D (Pop1), QKb.cim-3B1 and QKb.cim-5B2 (Pop2). Other than those four QTL, other QTL were detected in each population which were specific to environments: QKb.cim-5B1, QKb.cim-6A, and QKb.cim-7A (Pop1), QKb.cim-3B2, QKb.cim-4A1, QKb.cim-4A2, QKb.cim-4B, QKb.cim-5A1, QKb.cim-5A2, and QKb.cim-7A2 (Pop2). Among the four stable QTL, all but QKb.cim-3B1 were derived from the resistant parent. QKb.cim-2B and QKb.cim-3D in Pop1 and QKb.cim-3B1 and QKb.cim-5B2 in Pop2 explained 5.0-11.4% and 3.3-7.1% phenotypic variance, respectively. A combination of two stable QTL in each population reduced KB infection by 24-33%, respectively. Transgressive resistant segregants lines derived with resistance alleles from both parents in each population were identified. Single nucleotide polymorphism (SNP) markers flanking these QTL regions may be amenable to marker-assisted selection. The best lines from both populations (in agronomy, end-use quality and KB resistance) carrying resistance alleles at all identified loci, may be used for inter-crossing and selection of improved germplasm in future. Markers flanking these QTL may assist in selection of such lines.