Genome-wide Association Mapping Studies Research Articles

Leveraging the potential of big genomic and phenotypic data for genome-wide association mapping in wheat

Genome-wide association mapping studies (GWAS) based on Big Data are a potential approach to improve marker-assisted selection in plant breeding. The number of available phenotypic and genomic data sets in which medium-sized populations of several hundred individuals have been studied is rapidly increasing. Combining these data and using them in GWAS could increase both the power of QTL discovery and the accuracy of estimation of underlying genetic effects, but is hindered by data heterogeneity and lack of interoperability. In this study, we used genomic and phenotypic data sets, focusing on Central European winter wheat populations evaluated for heading date. We explored strategies for integrating these data and subsequently the resulting potential for GWAS. Establishing interoperability between data sets was greatly aided by some overlapping genotypes and a linear relationship between the different phenotyping protocols, resulting in high quality integrated phenotypic data. In this context, genomic prediction proved to be a suitable tool to study relevance of interactions between genotypes and experimental series, which was low in our case. Contrary to expectations, fewer associations between markers and traits were found in the larger combined data than in the individual experimental series. However, the predictive power based on the marker-trait associations of the integrated data set was higher across data sets. Therefore, the results show that the integration of medium-sized to Big Data is an approach to increase the power to detect QTL in GWAS. The results encourage further efforts to standardize and share data in the plant breeding community.

A multi-ancestry genome-wide association study in type 1 diabetes.

Type 1 diabetes (T1D) is an autoimmune disease caused by destruction of the pancreatic β-cells. Genome-wide association (GWAS) and fine mapping studies have been conducted mainly in European ancestry (EUR) populations. We performed a multi-ancestry GWAS to identify SNPs and HLA alleles associated with T1D risk and age at onset. EUR families (N = 3223), and unrelated individuals of African (AFR, N = 891) and admixed (Hispanic/Latino) ancestry (AMR, N = 308) were genotyped using the Illumina HumanCoreExome BeadArray, with imputation to the TOPMed reference panel. The Multi-Ethnic HLA reference panel was utilized to impute HLA alleles and amino acid residues. Logistic mixed models (T1D risk) and frailty models (age at onset) were used for analysis. In GWAS meta-analysis, seven loci were associated with T1D risk at genome-wide significance: PTPN22, HLA-DQA1, IL2RA, RNLS, INS, IKZF4-RPS26-ERBB3, and SH2B3, with four associated with T1D age at onset (PTPN22, HLA-DQB1, INS, and ERBB3). AFR and AMR meta-analysis revealed NRP1 as associated with T1D risk and age at onset, although NRP1 variants were not associated in EUR ancestry. In contrast, the PTPN22 variant was significantly associated with risk only in EUR ancestry. HLA alleles and haplotypes most significantly associated with T1D risk in AFR and AMR ancestry differed from that seen in EUR ancestry; in addition, the HLA-DRB1*08:02-DQA1*04:01-DQB1*04:02 haplotype was 'protective' in AMR while HLA-DRB1*08:01-DQA1*04:01-DQB1*04:02 haplotype was 'risk' in EUR ancestry, differing only at HLA-DRB1*08. These results suggest that much larger sample sizes in non-EUR populations are required to capture novel loci associated with T1D risk.

Surveying the genomic landscape of silage-quality traits in maize (Zea mays L.)

Despite the longstanding importance of silage as a critical feed source for ruminants, its quality improvement has been largely overlooked. Although numerous quantitative trait loci (QTL) and genes affecting silage quality in maize have been reported, only a few have been effectively incorporated into breeding programs. Addressing this gap, the present study undertook a comprehensive meta-QTL (MQTL) analysis involving 523 QTL associated with silage-quality traits collected from 14 published studies. Of the 523 QTL, 405 were projected onto a consensus map comprising 62,424 genetic markers, resulting in the identification of 60 MQTL and eight singletons. The average confidence interval (CI) of the MQTL was 3.9-fold smaller than that of the source QTL. Nine of the 60 identified MQTL were classified as breeder’s MQTL owing to their small CIs, involvement of more QTL, and large contribution to phenotypic variation. One-third of the MQTL co-localized with DNA marker-trait associations identified in previous genome-wide association mapping studies. A set of 78 high-confidence candidate genes influencing silage quality were identified in the MQTL regions. These genes and associated markers may advance marker-assisted breeding for maize silage quality.

Genome-wide association study of fiber yield-related traits uncovers the novel genomic regions and candidate genes in Indian upland cotton (Gossypium hirsutum L.).

Upland cotton (Gossypium hirsutum L.) is a major fiber crop that is cultivated worldwide and has significant economic importance. India harbors the largest area for cotton cultivation, but its fiber yield is still compromised and ranks 22nd in terms of productivity. Genetic improvement of cotton fiber yield traits is one of the major goals of cotton breeding, but the understanding of the genetic architecture underlying cotton fiber yield traits remains limited and unclear. To better decipher the genetic variation associated with fiber yield traits, we conducted a comprehensive genome-wide association mapping study using 117 Indian cotton germplasm for six yield-related traits. To accomplish this, we generated 2,41,086 high-quality single nucleotide polymorphism (SNP) markers using genotyping-by-sequencing (GBS) methods. Population structure, PCA, kinship, and phylogenetic analyses divided the germplasm into two sub-populations, showing weak relatedness among the germplasms. Through association analysis, 205 SNPs and 134 QTLs were identified to be significantly associated with the six fiber yield traits. In total, 39 novel QTLs were identified in the current study, whereas 95 QTLs overlapped with existing public domain data in a comparative analysis. Eight QTLs, qGhBN_SCY_D6-1, qGhBN_SCY_D6-2, qGhBN_SCY_D6-3, qGhSI_LI_A5, qGhLI_SI_A13, qGhLI_SI_D9, qGhBW_SCY_A10, and qGhLP_BN_A8 were identified. Gene annotation of these fiber yield QTLs revealed 2,509 unique genes. These genes were predominantly enriched for different biological processes, such as plant cell wall synthesis, nutrient metabolism, and vegetative growth development in the gene ontology (GO) enrichment study. Furthermore, gene expression analysis using RNAseq data from 12 diverse cotton tissues identified 40 candidate genes (23 stable and 17 novel genes) to be transcriptionally active in different stages of fiber, ovule, and seed development. These findings have revealed a rich tapestry of genetic elements, including SNPs, QTLs, and candidate genes, and may have a high potential for improving fiber yield in future breeding programs for Indian cotton.

Genome-wide association mapping and genomic prediction for late blight and potato cyst nematode resistance in potato (Solanum tuberosum L.).

Potatoes are an important source of food for millions of people worldwide. Biotic stresses, notably late blight and potato cyst nematodes (PCN) pose a major threat to potato production worldwide, and knowledge of genes controlling these traits is limited. A genome-wide association mapping study was conducted to identify the genomic regulators controlling these biotic stresses, and the genomic prediction accuracy was worked out using the GBLUP model of genomic selection (GS) in a panel of 222 diverse potato accessions. The phenotype data on resistance to late blight and two PCN species (Globodera pallida and G. rostochiensis) were recorded for three and two consecutive years, respectively. The potato panel was genotyped using genotyping by sequencing (GBS), and 1,20,622 SNP markers were identified. A total of 7 SNP associations for late blight resistance, 9 and 11 for G. pallida and G. rostochiensis, respectively, were detected by additive and simplex dominance models of GWAS. The associated SNPs were distributed across the chromosomes, but most of the associations were found on chromosomes 5, 10 and 11, which have been earlier reported as the hotspots of disease-resistance genes. The GS prediction accuracy estimates were low to moderate for resistance to G. pallida (0.04-0.14) and G. rostochiensis (0.14-0.21), while late blight resistance showed a high prediction accuracy of 0.42-0.51. This study provides information on the complex genetic nature of these biotic stress traits in potatoes and putative SNP markers for resistance breeding.

Genome wide association study to detect genetic regions related to isoflavone content in a mutant soybean population derived from radiation breeding.

Isoflavones are major secondary metabolites that are exclusively produced by legumes, including soybean. Soy isoflavones play important roles in human health as well as in the plant defense system. The isoflavone content is influenced by minor-effect quantitative trait loci, which interact with polygenetic and environmental factors. It has been difficult to clarify the regulation of isoflavone biosynthesis because of its complex heritability and the influence of external factors. Here, using a genotype-by-sequencing-based genome-wide association mapping study, 189 mutant soybean genotypes (the mutant diversity pool, MDP) were genotyped on the basis of 25,646 high-quality single nucleotide polymorphisms (SNPs) with minor allele frequency of >0.01 except for missing data. All the accessions were phenotyped by determining the contents of 12 isoflavones in the soybean seeds in two consecutive years (2020 and 2021). Then, quantitative trait nucleotides (QTNs) related to isoflavone contents were identified and validated using multi-locus GWAS models. A total of 112 and 46 QTNs related to isoflavone contents were detected by multiple MLM-based models in 2020 and 2021, respectively. Of these, 12 and 5 QTNs were related to more than two types of isoflavones in 2020 and 2021, respectively. Forty-four QTNs were detected within the 441-Kb physical interval surrounding Gm05:38940662. Of them, four QTNs (Gm05:38936166, Gm05:38936167, Gm05:38940662, and Gm05:38940717) were located at Glyma.05g206900 and Glyma.05g207000, which encode glutathione S-transferase THETA 1 (GmGSTT1), as determined from previous quantitative trait loci annotations and the literature. We detected substantial differences in the transcript levels of GmGSTT1 and two other core genes (IFS1 and IFS2) in the isoflavone biosynthetic pathway between the original cultivar and its mutant. The results of this study provide new information about the factors affecting isoflavone contents in soybean seeds and will be useful for breeding soybean lines with high and stable concentrations of isoflavones.

Multiple Genomic Regions Govern Tolerance to Sulfentrazone in Snap Bean (Phaseolus Vulgaris L.)

The availability of effective weed management tools against waterhemp (Amaranthus tuberculatus) is crucial to maintain profitable production of snap bean (Phaseolus vulgaris L.). Preemergence herbicides enable the crop to gain a size advantage over the weed, but the few preemergence herbicides registered in snap bean have poor control of waterhemp. Sulfentrazone, a protoporphyrinogen oxidase (PPO) -inhibiting herbicide, provides significant control of waterhemp and other problematic weeds. However, crop tolerance to the herbicide is poorly known. To quantify snap bean tolerance to sulfentrazone and investigate the underlying tolerance mechanism(s), a genome-wide association mapping study was conducted using field-collected data on a snap bean diversity panel. Response to a preemergence application of sulfentrazone was measured using plant population density and shoot biomass variables. High levels of crop tolerance were found in several entries including Bush Romano 71, Navarro, and Flamata. Snap bean tolerance to sulfentrazone is associated with multiple genomic regions, indicating the trait is likely a non-target site resistance (NTSR). Seed size is partially responsible for the tolerance, thus the genetic factors conditioning sulfentrazone tolerance are likely a combination of those driven indirectly by seed size/weight and those acting directly on the metabolism of the herbicide or ameliorating its damage. In this study, several cytochrome P450 and ABC transporter genes were localized in associated genomic regions. Alleles conditioning snap bean tolerance to sulfentrazone identified in the diversity panel shed light on herbicide metabolism and could be used in snap bean improvement.

Genetic dissection of seed characteristics in field pennycress via genome-wide association mapping studies.

Field pennycress (Thlaspi arvenseL.) is a new winter annual cash cover crop with high oil content and seed yield, excellent winter hardiness, early maturation, and resistance to most pests and diseases. It provides living cover on fallow croplands between summer seasons, and in doing so reduces nutrient leaching into water sources, mitigates soil erosion, and suppresses weed growth. The first ever genome-wide association study (GWAS) was conducted on a pennycress diversity panel to identify marker trait associations with important seed size and composition related traits. The entire population was phenotyped in three total environments over 2 yr, and seed area, length, width, thousand grain weight, total oil, and total protein were measured post-harvest with specialized high-throughput imaging and near-infrared spectroscopy. Basic unbiased linear prediction values were calculated for each trait. Seed size traits tended to have higher entry mean reliabilities (0.76-0.79) compared with oil content (0.51) and protein content (0.37). Genotyping-by-sequencing identified 33,606 high quality genome-wide single nucleotide polymorphism (SNPs) that were coupled with phenotypic data to perform GWAS for seed area, length, width, thousand grain weight, total oil, and total protein content. Fifty-nine total marker-trait associations were identified revealing genomic regions controlling each trait. The significant SNPs explained 0.06-0.18% of the total variance for that trait in our population. A list of candidate genes was identified based on their functional annotations and characterization in other species. Our results confirm that GWAS is an efficient strategy to identify significant marker-trait associations that can be incorporated into marker-assisted selection pipelines to accelerate pennycress breeding progress.

Genome wide association mapping of yield and other agronomic traits in rice: Narrative literature review

Based on previous recombination actions and LD (linkage disequilibrium) throughout the genome, genome wide association mapping studies often are employed to find Quantitative trait locus in varied collections of crop germplasm. Generally, diverse panel’s genotyped using high density Single nucleotide polymorphism (SNP) panels are used to test a broad variety of haplotypes and alleles, as well as to track recombination divisions throughout the genome. GWAS, on the other hand, have rarely been used in breeding populations. We studied association mapping for agricultural parameters such as yield and its constituents in a breeding inhabitants of top irrigated tropical rice progenies so that the findings could be used to breeding more directly than those from a diverse panel. GWAS was undertaken with the specific purpose of accelerating selection in the breeding population, and the sample was genotyped with 71,710 Single nucleotide polymorphisms using genotyping-by-sequencing. We found 52 Quantitative trait locus QTL for 11 agronomic characteristics using this breeding panel, including substantial impact Quantitative trait loci (QTLs) for flowering period as well as grain width, grain length, grain length-breadth ratio. Furthermore we discovered haplotypes that may be applied to choose plants for our population with smaller stature (plant height), fast blooming time, with high yield, demonstrating the value of association mapping for advising breeding choices in breeding populations. Furthermore, we explore at how genomic-assisted selection models might be built using the newly discovered important Single nucleotide polymorphisms (SNPs) and deep insight into the genetic structure of these quantitative traits.

Genome-Wide Association Mapping of Seedling Vigor and Regrowth Vigor in Winter Wheat

Seedling vigor and regrowth ability are important traits for the forage production of winter wheat. The objectives of this study were to map quantitative trait loci (QTL) associated with seedling vigor and regrowth vigor traits using a genome-wide association mapping study (GWAS). Seedling vigor and regrowth vigor were evaluated with shoot length, the number of shoots per plant and shoot dry weight per plant 45 days after planting and 15 days after cutting. A large phenotypic variation was observed for all the traits studied. In total, 12 significant QTL for seedling vigor and 16 for regrowth vigor traits were detected on various chromosomes. Four QTL on chromosomes 2B, 4B, 5A and 7A for seedling vigor co-localized with QTL for regrowth vigor due to significant correlations between corresponding traits of the initial growth and regrowth. A BLAST search using DNA sequences of the significant loci revealed candidate genes playing roles in vegetative and reproductive development in different crop species. The QTL and single-nucleotide polymorphism (SNP) markers identified in this study will be further validated and used for marker-assisted selection of the traits during forage wheat breeding.

Genomics and Marker-Assisted Improvement of Vegetable Crops

Vegetables are an integral part of the human diet worldwide. Traditional breeding approaches have been used extensively to develop new cultivars of vegetables with desirable characteristics, including resistance/tolerance to biotic and abiotic stresses, high yield, and an elevated content of compounds beneficial to human health. The technological progress since the early 1980s has revolutionized our ability to study and manipulate genetic variation in crop plants. The development of high-throughput sequencing platforms and accompanying analytical methods have led to sequencing and assembly of a large number of plant genomes, construction of dense and ultra-dense molecular linkage maps, identification of structural variants, and application of molecular markers in breeding programs. Linkage mapping and genome-wide association mapping studies have been used to identify chromosomal locations of genes and QTLs associated with plant phenotypic variations important for crop improvement. This review provides up-to-date information on the status of genomics and marker-assisted improvement of vegetable crops with the focus on tomato, pepper, eggplant, lettuce, spinach, cucumber, and chicory. For each vegetable crop, we present the most recent information on genetic resources, mapping populations, genetic maps, genome sequences, mapped genes and QTLs, the status of marker-assisted selection and genomic selection, and discuss future research prospects and application of novel techniques and approaches.

Elucidating the genetics of grain yield and stress-resilience in bread wheat using a large-scale genome-wide association mapping study with 55,568 lines

Wheat grain yield (GY) improvement using genomic tools is important for achieving yield breakthroughs. To dissect the genetic architecture of wheat GY potential and stress-resilience, we have designed this large-scale genome-wide association study using 100 datasets, comprising 105,000 GY observations from 55,568 wheat lines evaluated between 2003 and 2019 by the International Maize and Wheat Improvement Center and national partners. We report 801 GY-associated genotyping-by-sequencing markers significant in more than one dataset and the highest number of them were on chromosomes 2A, 6B, 6A, 5B, 1B and 7B. We then used the linkage disequilibrium (LD) between the consistently significant markers to designate 214 GY-associated LD-blocks and observed that 84.5% of the 58 GY-associated LD-blocks in severe-drought, 100% of the 48 GY-associated LD-blocks in early-heat and 85.9% of the 71 GY-associated LD-blocks in late-heat, overlapped with the GY-associated LD-blocks in the irrigated-bed planting environment, substantiating that simultaneous improvement for GY potential and stress-resilience is feasible. Furthermore, we generated the GY-associated marker profiles and analyzed the GY favorable allele frequencies for a large panel of 73,142 wheat lines, resulting in 44.5 million datapoints. Overall, the extensive resources presented in this study provide great opportunities to accelerate breeding for high-yielding and stress-resilient wheat varieties.

Genetic variation associated with PPO-inhibiting herbicide tolerance in sorghum.

Herbicide application is crucial for weed management in most crop production systems, but for sorghum herbicide options are limited. Sorghum is sensitive to residual protoporphyrinogen oxidase (PPO)-inhibiting herbicides, such as fomesafen, and a long re-entry period is required before sorghum can be planted after its application. Improving sorghum for tolerance to such residual herbicides would allow for increased sorghum production and the expansion of herbicide options for growers. In this study, we observed sorghum tolerance to residual fomesafen. To investigate the underlying tolerance mechanism a genome-wide association mapping study was conducted using field-collected sorghum biomass panel (SBP) data, and a greenhouse assay was developed to confirm the field phenotypes. A total of 26 significant SNPs (FDR<0.05), spanning a 215.3 kb region on chromosome 3, were detected. The ten most significant SNPs included two in genic regions (Sobic.003G136800, and Sobic.003G136900) and eight SNPs in the intergenic region encompassing the genes Sobic.003G136700, Sobic.003G136800, Sobic.003G137000, Sobic.003G136900, and Sobic.003G137100. The gene Sobic.003G137100 (PPXI), which encodes the PPO1 enzyme, one of the targets of PPO-inhibiting herbicides, was located 12kb downstream of the significant SNP S03_13152838. We found that PPXI is highly conserved in sorghum and expression does not significantly differ between tolerant and sensitive sorghum lines. Our results suggest that PPXI most likely does not underlie the observed herbicide tolerance. Instead, the mechanism underlying herbicide tolerance in the SBP is likely metabolism-based resistance, possibly regulated by the action of multiple genes. Further research is necessary to confirm candidate genes and their functions.

Genome-wide association mapping for wheat blast resistance in CIMMYT\u2019s international screening nurseries evaluated in Bolivia and Bangladesh

Wheat blast caused by the fungus Magnaporthe oryzae pathotype Triticum (MoT) is an emerging threat to wheat production. To identify genomic regions associated with blast resistance against MoT isolates in Bolivia and Bangladesh, we performed a large genome-wide association mapping study using 8607 observations on 1106 lines from the International Maize and Wheat Improvement Centre’s International Bread Wheat Screening Nurseries (IBWSNs) and Semi-Arid Wheat Screening Nurseries (SAWSNs). We identified 36 significant markers on chromosomes 2AS, 3BL, 4AL and 7BL with consistent effects across panels or site-years, including 20 markers that were significant in all the 49 datasets and tagged the 2NS translocation from Aegilops ventricosa. The mean blast index of lines with and without the 2NS translocation was 2.7 ± 4.5 and 53.3 ± 15.9, respectively, that substantiates its strong effect on blast resistance. Furthermore, we fingerprinted a large panel of 4143 lines for the 2NS translocation that provided excellent insights into its frequency over years and indicated its presence in 94.1 and 93.7% of lines in the 2019 IBWSN and SAWSN, respectively. Overall, this study reinforces the effectiveness of the 2NS translocation for blast resistance and emphasizes the urgent need to identify novel non-2NS sources of blast resistance.

Large scale SNP unearthing and genetic architecture analysis in sea-captured and cultured populations of Cynoglossus semilaevis

Knowledge on population structure and genetic diversity is a focal point for association mapping studies and genomic selection. Genotyping by sequencing (GBS) represents an innovative method for large scale SNP detection and genotyping of genetic resources. Here we used the GBS approach for the genome-wide identification of SNPs in a collection of Cynoglossus semilaevis and for the assessment of the level of genetic diversity in C. semilaevis genotypes. GBS analysis generated a total of 55.12 Gb high-quality sequence data, with an average of 0.63 Gb per sample. The total number of SNP markers was 563, 109. In order to explore the genetic diversity of C. semilaevis and to select a minimal core set representing most of the total genetic variation with minimum redundancy, C. semilaevis sequences were analyzed using high quality SNPs. Based on hierarchical clustering, it was possible to divide the collection into 2 clusters. The marine fishing populations were clustered and clearly separated from the cultured populations, and the cultured populations from Hebei was also distinct from the other two local populations. These analyses showed that genotypes were clustered based on species-related features. Differential significant SNPs were also captured and validated by GBS and SNaPshot, with linkage disequilibrium and haplotype analysis, seven SNPs have been confirmed to have obvious differentiation in two populations, which may be used as the characteristic evaluation sites of sea-captured and cultured Cynoglossus semilaevis populations. And SNP markers and information on population structure developed in this study will undoubtedly support genome-wide association mapping studies and marker-assisted selection programs. These differential SNPs could be also employed as the characteristic evaluation sites of sea-captured and cultured Cynoglossus semilaevis populations in future.

In-depth genome diversity, population structure and linkage disequilibrium analysis of worldwide diverse safflower (Carthamus tinctorius L.) accessions using NGS data generated by DArTseq technology.

Safflower (Carthamus tinctorius L.) is one of the most important oilseed crops for its seed oil rich in unsaturated fatty acids. Precise utilization of diverse genetic resources is fundamental in breeding programs to improve high yield genotypes with desirable traits. In this study, for the first time we report successful application of DArTseq technology; an efficient genotyping-by-sequencing (NGS); to analysis genetic diversity and population structure of 89 safflower accessions from worldwide origins. Totally, 19,639 DArTseq markers (10,130 SilicoDArTs and 9509 SNPs) generated through DArTseq genotyping. After filtering the data, 3431 polymorphic DArTseq markers (1136 SilicoDArTs and 2295 SNPs) used for genetic diversity, population structure and linkage disequilibrium analysis in safflower genotypes. All the SilicoDArT and SNP markers showed high reproducibility and call rate. Polymorphism information content (PIC) values ranged from 0.1 to 0.5, while ≥ 0.50% of SilicoDArTs and ≥ 0.64% SNPs showed PIC values more than median. Genotypes grouping using DArTseq markers resulted in three distinct clusters. Results showed weak correlation between safflower diversity pattern and origins. Analysis of molecular variance revealed that the majority of genetic variation was attributed to the differences among varieties within cluster populations and there was no significant molecular variance between origins. However, safflower of accessions belonged to Iran, Turkey, Pakistan and India indeed appear to be genetically similar and grouped close in referred cluster, while the accessions from Near East (Afghanistan, China) being distinct. Our results were in agreement with hypothesis that safflower domesticated in somewhere west of Fertile Crescent and then expanded through Africa and Europe. Present study using a panel of globally diverse safflower accessions and large number of DArTseq markers set the stage for future analysis of safflower domestication using large germplasm from proposed domestication centers. Also, studied germplasm in this study can be used as a valuable source for future genomic studies in safflower for mapping desirable traits through genome-wide association mapping studies.

Method for Characterization of Root Traits in Chickpea Germplasm for Legume Genomics and Breeding.

A semi-hydroponic phenotyping platform was constructed using inexpensive and easily obtained materials for characterizing root trait variability in a large set of chickpea (Cicer arietinum) germplasm. The system was designed to accommodate a large number of plants in a small area allowing relatively deeper root development, and thus serves as a high-throughput phenotyping tool for studying root dynamic growth. The root trait quantitative platform could provide accurate phenotyping data for parameterizing root models and for genome-wide association analysesor mapping studies of quantitative trait loci.

Genome-Wide Association Mapping of Resistance to Septoria Nodorum Leaf Blotch in a Nordic Spring Wheat Collection.

First genome-wide association mapping of adult plant Septoria nodorum blotch resistance. Some adult plant resistance loci were shared with seedling resistance loci. Other adult plant resistance loci were significant across environments. Resistant haplotypes were identified, which can be used for breeding. Parastagonospora nodorum is the causal agent of Septoria nodorum leaf blotch (SNB) in wheat (Triticum aestivum L.). It is the most important leaf blotch pathogen in Norwegian spring wheat. Several quantitative trait loci (QTL) for SNB susceptibility have been identified. Some of these QTL are the result of underlying gene-for-gene interactions involving necrotrophic effectors (NEs) and corresponding sensitivity (Snn) genes. A collection of diverse spring wheat lines was evaluated for SNB resistance and susceptibility over seven growing seasons in the field. In addition, wheat seedlings were inoculated and infiltrated with culture filtrates (CFs) from four single spore isolates and infiltrated with semipurified NEs (SnToxA, SnTox1, and SnTox3) under greenhouse conditions. In adult plants, the most stable SNB resistance QTL were located on chromosomes 2B, 2D, 4A, 4B, 5A, 6B, 7A, and 7B. The QTL on chromosome 2D was effective most years in the field. At the seedling stage, the most significant QTL after inoculation were located on chromosomes 1A, 1B, 3A, 4B, 5B, 6B, 7A, and 7B. The QTL on chromosomes 3A and 6B were significant both after inoculation and CF infiltration, indicating the presence of novel NE-Snn interactions. The QTL on chromosomes 4B and 7A were significant in both seedlings and adult plants. Correlations between SnToxA sensitivity and disease severity in the field were significant. To our knowledge, this is the first genome-wide association mapping study (GWAS) to investigate SNB resistance at the adult plant stage under field conditions.

Next generation sequencing technologies for the development of molecular markers and the analysis of genome diversity in Capsicum spp.

The accessibility and use of natural genetic variability in crops is essential for the management of genetic resources and the establishment of innovative breeding programs. Nuclear whole-genome sequences of several cultivated and wild peppers have been recently generated in order to provide crucial information on the evolution, domestication and divergence of pepper species (Capsicum spp.). Despite next generation sequencing (NGS) technologies providing a significant advance in generation of high throughput data, the analysis of a large-scale data and of individuals is still a challenging task. An alternative strategy to Whole Genome Sequencing is to generate a reduced representation of the genome using target enrichment strategies. Among them, genotyping-by-sequencing (GBS) provides a rapid, highly informative, cost-effective tool for exploring genetic diversity on a genome-wide scale. We applied GBS for SNP marker discovery in nuclear genomes and population structure analysis in a collection of cultivated and domesticated peppers. Information generated in this study represents a first step towards future genome-wide association mapping studies and marker-assisted selection programs. In addition, results from this analysis can be used to gain a better understanding of the genetic relationships within the Capsicum genus. In order to provide a further contribution to that issue, we also determined the complete chloroplast DNA (cpDNA) sequence of 11 Capsicum accessions for a total of 8 species generally included in the C. annuum (7), C. baccatum (3) or C. pubescens/eximium complex (1). We performed comparative analysis and identified potential molecular markers able to discriminate among Capsicum species.

Linkage disequilibrium and past effective population size in native Tunisian cattle.

To carry out effective genome-wide association studies, information about linkage disequilibrium (LD) is essential. Here, we used medium-density SNP chips to provide estimates of LD in native Tunisian cattle. The two measures of LD that were used, mean r2 and D’, decreased from 0.26 to 0.05 and from 0.73 to 0.40, respectively, when the distance between markers increased from less than 20 Kb to 200 Kb. The decay in LD over physical distance occurred at a faster rate than that reported for European and other indigenous breeds, and reached background levels at less than 500 Kb distance. This is consistent with the absence of strong selective pressure within the Tunisian population and suggests that, in order to be effective, any potential genome-wide association mapping studies will need to use chips with higher marker density. An analysis of effective population size (Ne) based on LD data showed a decline in past Ne, with a sudden drop starting about eight generations ago. This finding, combined with the high levels of recent inbreeding revealed by runs of homozygosity (ROH) analysis, indicate that this population is endangered and may be in urgent need of a conservation plan that includes a well-designed genetic management program.