Association Mapping Studies Research Articles

Genetic diversity, relationships among traits and selection of tropical maize inbred lines for low-P tolerance based on root and shoot traits at seedling stage.

The tropical maize breeding for low-P tolerance and good performance under low-P stress environments can be achieved through selection based on root morphology traits at seedling stage. Here, we assessed the genotypic variation and genetic diversity of a panel of 151 tropical maize inbred lines for root and shoot seedling traits, investigated the relationship among traits and selected a set of promising inbred lines for low-P tolerance and performance. We evaluated the inbred lines at seedling stage in a greenhouse experiment under two conditions: applied P (AP) and non-applied P (NAP). A mixed model approach was used to estimate variance components and predict the genotypic values of each inbred line. The genetic diversity among inbred lines based on root and shoot traits was assessed, and correlations were estimated between tested traits under AP and NAP. Our panel of inbred lines showed huge genetic variability for all traits and presented large genetic diversity under both P conditions. Variance components due to the inbred line × P condition interaction were also highly significant (P < 0.01) for all traits. Root dry weight (RDW) was positively associated with stalk dimeter (SD), shoot dry weight (SDW) and root length, volume, and area under both P conditions. Also, the SD and SDW were associated with most root traits under AP. Based on low-P tolerance and performance indices, we selected a set of top 20 inbred lines to be used in our maize breeding program. We therefore concluded that there is a significant genetic diversity in the tropical maize inbred lines which have the genetic potential to be use in association mapping studies and also to develop improved low-P tolerant and P-efficient hybrids and maize breeding populations for low-P stress environments.

Identification of quantitative trait loci of pod dehiscence in a collection of soybean grown in the southeast of Kazakhstan.

Soybean [Glycine max (L.) Merr.] is one of the important crops that are constantly increasing their cultivation area in Kazakhstan. It is particularly significant in the southeastern regions of the country, which are currently predominant areas for cultivating this crop. One negative trait reducing yield in these dry areas is pod dehiscence (PD). Therefore, it is essential to understand the genetic control of PD to breed new cultivars with high yield potential. In this study, we evaluated 273 soybean accessions from different regions of the world for PD resistance in the conditions of southeastern regions of Kazakhstan in 2019 and 2021. The field data for PD suggested that 12 accessions were susceptible to PD in both studied years, and 32 accessions, in one of the two studied years. The genotyping of the collection using a DNA marker for the Pdh1 gene, a major gene for PD, revealed that 244 accessions had the homozygous R (resistant) allele, 14 had the homozygous S (susceptible) allele, and 15 accessions showed heterozygosity. To identify additional quantitative trait loci (QTLs), we applied an association mapping study using a 6K SNP Illumina iSelect array. The results suggested that in addition to major QTL on chromosome 16, linked to the physical location of Pdh1, two minor QTLs were identified on chromosomes 10 and 13. Both minor QTLs for PD were associated with calmodulin-binding protein, which presumably plays an important role in regulating PD in dry areas. Thus, the current study provided additional insight into PD regulation in soybean. The identified QTLs for PD can be efficiently employed in breeding for high-yield soybean cultivars.

QTL analysis on a lemon population provides novel insights on the genetic regulation of the tolerance to the two-spotted spider mite attack

BackgroundAmong the Citrus species, lemon (Citrus limon Burm f.) is one of the most affected by the two-spotted spider mite (Tetranychus urticae Koch). Moreover, chemical control is hampered by the mite’s ability to develop genetic resistance against acaricides. In this context, the identification of the genetic basis of the host resistance could represent a sustainable strategy for spider mite control. In the present study, a marker-trait association analysis was performed on a lemon population employing an association mapping approach. An inter-specific full-sib population composed of 109 accessions was phenotyped through a detached-leaf assays performed in modified Huffaker cells. Those individuals, complemented with two inter-specific segregating populations, were genotyped using a target-sequencing approach called SPET (Single Primer Enrichment Technology), the resulting SNPs were employed for the generation of an integrated genetic map.ResultsThe percentage of damaged area in the full-sib population showed a quantitative distribution with values ranging from 0.36 to 9.67%. A total of 47,298 SNPs were selected for an association mapping study and a significant marker linked with resistance to spider mite was detected on linkage group 5. In silico gene annotation of the QTL interval enabled the detection of 13 genes involved in immune response to biotic and abiotic stress. Gene expression analysis showed an over expression of the gene encoding for the ethylene-responsive transcription factor ERF098-like, already characterized in Arabidopsis and in rice for its involvement in defense response.ConclusionThe identification of a molecular marker linked to the resistance to spider mite attack can pave the way for the development of marker-assisted breeding plan for the development of novel selection coupling favorable agronomical traits (e.g. fruit quality, yield) with a higher resistance toward the mite.

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.

Linkage mapping of root shape traits in two carrot populations.

This study investigated the genetic basis of carrot root shape traits using composite interval mapping in two biparental populations (n = 119 and n = 128). The roots of carrot F2:3 progenies were grown over 2 years and analyzed using a digital imaging pipeline to extract root phenotypes that compose market class. Broad-sense heritability on an entry-mean basis ranged from 0.46 to 0.80 for root traits. Reproducible quantitative trait loci (QTL) were identified on chromosomes 2 and 6 on both populations. Colocalization of QTLs for phenotypically correlated root traits was also observed and coincided with previously identified QTLs in published association and linkage mapping studies. Individual QTLs explained between 14 and 27% of total phenotypic variance across traits, while four QTLs for length-to-width ratio collectively accounted for up to 73% of variation. Predicted genes associated with the OFP-TRM (OVATE Family Proteins-TONNEAU1 Recruiting Motif) and IQD (IQ67 domain) pathway were identified within QTL support intervals. This observation raises the possibility of extending the current regulon model of fruit shape to include carrot storage roots. Nevertheless, the precise molecular mechanisms through which this pathway operates in roots characterized by secondary growth originating from cambium layers remain unknown.

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.

Microsatellite markers’ based molecular divergence among the breeding lines of aromatic marigold (Tagetes minuta L.)

Aromatic marigold (Tagetes minuta L.) is an essential oil-bearing plant of industrial value. The essential oil obtained from the plant has high demand in the flavor and perfume industry. The present study investigates the molecular diversity patterns using microsatellite markers in 126 breeding lines representing three groups (higher, intermediate, and lower biomass) based on phenotypic characterization. These lines are being maintained through repeated selfing. A total of 503 alleles with an average of 16.23 alleles per locus were detected at 31 SSR loci over all the genotypes. The average most common and rare alleles were 3.35 and 12.87, respectively, over all the studied loci. The high polymorphic information content (0.88) and genetic diversity (0.89) indicate high allelic diversity among the genotypes studied. Ten genotype-specific markers were identified. Significant molecular variances have been observed among the groups (3 %), among individuals (72 %), and within individuals (26 %). The unweighted neighbor-joining clustering based on a simple matching dissimilarity index grouped all 126 genotypes into five major clusters. The clustering pattern primarily follows the biomass-specific distribution of populations. The principle coordinate analysis depicts considerable variations and again confirms the biomass-specific grouping of genotypes. The highly significant positive association between genotypic and phenotypic distances indicates the importance of these marker loci for future marker-assisted selection and association mapping studies.

Lathyrus sativus Resistance Against the Existing and Emerging Pathogens Erysiphe pisi and E. trifolii: A Case of Commonalities or Total Discrepancy?

Powdery mildew on Lathyrus sativus (grass pea) is commonly caused by Erysiphe pisi, the causal agent of pea powdery mildew. E. trifolii could also pose an additional threat to grass pea, as it does to pea (Pisum sativum). In order to understand the potential threat and the availability of resistance sources, the response to both pathogens was analyzed on a worldwide germplasm collection of 189 grass pea accessions. Infection type and disease severity (DS) of grass pea accessions, independently inoculated with E. pisi and E. trifolii, were evaluated under controlled conditions. A wide range of responses were detected, with the previously uncharacterized partial resistance to E. trifolii in grass pea detected less frequently and uncorrelated with partial resistance against E. pisi. To test for the lack of correlation at the genetic level, an exploratory association mapping study was undertaken by statistically combining grass pea collection DS scores against both pathogens, with 5,651 previously screened genotype-by-sequencing-based single nucleotide polymorphisms (SNP). Mostly different genetic regions in grass pea were identified as being associated with the response to E. trifolii and E. pisi, anticipating an independent genetic basis that requires further validation in larger germplasm collections, with higher SNP densities. This study proposes common and unique partial resistance components against two different powdery mildews, implying the need for complementary approaches to introduce resistance to both pathogens into new grass pea varieties. The identified sources of resistance and predicted genomic targets will assist in breeding for resistance to multiple powdery mildews.

Occurrence of simple sequence repeats in cDNA sequences of safflower (Carthamus tinctorius) reveals the importance of SSR-containing genes for cell biology and dynamic response to environmental cues.

Safflower (Carthamus tinctorius) is a diploid crop plant belonging to the family Asteraceae and is well known as one of important oilseed crops due to edible oil containing unsaturated fatty acids. In recent years it is gaining increased attention for food, pharmaceutical and industrial uses, and hence the updating its breeding methods is necessary. Genic simple sequence repeats (SSRs) in addition of being desire molecular markers, are supposed to influence gene function and the respective phenotype. This study aimed to identify SSRs in cDNA sequences and further analysis of the functional features of the SSR-containing genes to elucidate their role in biological and cellular processes. We identified 1,841 SSR regions in 1,667 cDNA sequences. Among all types of repeats, trinucleotide repeats were the most abundant (35.7%), followed by hexanucleotide (29.6%) and dinucleotide repeats (22.0%). Thirty five SSR primer pairs were validated by PCR reaction, detected a high rate of polymorphism (>57%) among safflower accessions, physically mapped on safflower genome and could clearly discriminate the cultivated accessions from wild relatives. The cDNA-derived SSR markers are suitable for evaluation of genetic diversity, linkage and association mapping studies and genome-based breeding programmes. Occurrence of SSR repeats in biologically-important classes of proteins such as kinases, transferases and transcription factors was inferred from functional analyses, which along with variability of their repeat copies, can endow the cell and whole organism the flexibility of facing with continuously changing environment, and indicate a structure-based evolution mechanism of the genome which acts as an up-to-dating tool for the cell and whole origanism, which is realized in GO terms such as involvement of most SSR-containing genes in biological, cellular and metabolic processes, especially in response to stimulus, response to stress, interaction to other organisms and defense responses.

DArTSeq SNP-based genetic diversity and population structure studies among taro [(Colocasia esculenta (L.) Schott] accessions sourced from Nigeria and Vanuatu.

Taro is a valuable staple food crop among resource-poor rural people in countries such as Nigeria and Ghana, among others. Characterization of genetic diversity is a prerequisite for proper management of breeding programs and conservation of genetic resources. Two hundred seventy one taro accessions obtained from Nigeria and Vanuatu were genotyped using DArTseq-based SNP markers with the objectives of investigating the genetic diversity and population structure. In the analysis, 10,391 SNP markers were filtered from the sequence and used. The analysis revealed higher transition than transversion types of SNPs in the ratio of 1.43:1. The polymorphism ranged from 0.26 to 0.29 for the markers, indicating moderate genetic diversity. A model-based Bayesian clustering analysis of taro accessions yielded five subgroups and revealed the admixture situation in 19.19% of all accessions in the study. Vanuatu taro accessions exhibited more genetic diversity than Nigerian taro accessions. The population diversity estimate (PhiPt) was relatively higher (0.52) for accessions originating from Vanuatu than for Nigerian accessions. Analysis of molecular variance (AMOVA) revealed that most variation existed among individuals within a population at 52%. Nei's genetic distance showed that relatedness is based on geographical proximity. Collection of taro genetic resources should give more emphasis to within regions to utilize diversity in taro breeding program. This study also demonstrated the efficiency of DArTseq-based SNP genotyping for large-scale genome analysis in taro. The genotypic markers provided in this study are useful for association mapping studies.

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

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

Comparative Analysis of Multiple GWAS Results Identifies Metabolic Pathways Associated with Resistance to A. flavus Infection and Aflatoxin Accumulation in Maize.

Aflatoxins are carcinogenic secondary metabolites produced by several species of Aspergillus, including Aspergillus flavus, an important ear rot pathogen in maize. Most commercial corn hybrids are susceptible to infection by A. flavus, and aflatoxin contaminated grain causes economic damage to farmers. The creation of inbred lines resistant to Aspergillus fungal infection or the accumulation of aflatoxins would be aided by knowing the pertinent alleles and metabolites associated with resistance in corn lines. Multiple Quantitative Trait Loci (QTL) and association mapping studies have uncovered several dozen potential genes, but each with a small effect on resistance. Metabolic pathway analysis, using the Pathway Association Study Tool (PAST), was performed on aflatoxin accumulation resistance using data from four Genome-wide Association Studies (GWAS). The present research compares the outputs of these pathway analyses and seeks common metabolic mechanisms underlying each. Genes, pathways, metabolites, and mechanisms highlighted here can contribute to improving phenotypic selection of resistant lines via measurement of more specific and highly heritable resistance-related traits and genetic gain via marker assisted or genomic selection with multiple SNPs linked to resistance-related pathways.

Genome-Wide SNP Markers Accelerate Perennial Forest Tree Breeding Rate for Disease Resistance through Marker-Assisted and Genome-Wide Selection.

The ecological and economic importance of forest trees is evident and their survival is necessary to provide the raw materials needed for wood and paper industries, to preserve the diversity of associated animal and plant species, to protect water and soil, and to regulate climate. Forest trees are threatened by anthropogenic factors and biotic and abiotic stresses. Various diseases, including those caused by fungal pathogens, are one of the main threats to forest trees that lead to their dieback. Genomics and transcriptomics studies using next-generation sequencing (NGS) methods can help reveal the architecture of resistance to various diseases and exploit natural genetic diversity to select elite genotypes with high resistance to diseases. In the last two decades, QTL mapping studies led to the identification of QTLs related to disease resistance traits and gene families and transcription factors involved in them, including NB-LRR, WRKY, bZIP and MYB. On the other hand, due to the limitation of recombination events in traditional QTL mapping in families derived from bi-parental crosses, genome-wide association studies (GWAS) that are based on linkage disequilibrium (LD) in unstructured populations overcame these limitations and were able to narrow down QTLs to single genes through genotyping of many individuals using high-throughput markers. Association and QTL mapping studies, by identifying markers closely linked to the target trait, are the prerequisite for marker-assisted selection (MAS) and reduce the breeding period in perennial forest trees. The genomic selection (GS) method uses the information on all markers across the whole genome, regardless of their significance for development of a predictive model for the performance of individuals in relation to a specific trait. GS studies also increase gain per unit of time and dramatically increase the speed of breeding programs. This review article is focused on the progress achieved in the field of dissecting forest tree disease resistance architecture through GWAS and QTL mapping studies. Finally, the merit of methods such as GS in accelerating forest tree breeding programs is also discussed.

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.

Association genetics of early season cold and late season frost tolerance in Sorghum bicolor

AbstractSorghum [Sorghum bicolor (L.) Moench] is a multipurpose crop that is highly susceptible to low temperature stress. Early season cold (ESC) greatly affects seed germination, seedling vigor, and root architecture, whereas late‐season frost (LSF) reduces fertility, yield, and nutrition quality and content in sorghum. Here, an association mapping study was conducted to delineate the genetics of ESC and LSF tolerance in sorghum. A total of 10 single nucleotide polymorphisms (SNPs) and 17 quantitative trait loci (QTL) were identified for ESC, and 40 SNPs were identified for LSF. The diversity panel exhibited extensive variation for plant traits measured for their association with ESC and LSF tolerance. Two QTL colocalized with the classical tannin genes Tan1 (S4_61580203) and Tan2 (S2_7777693) were identified for ESC tolerance. We also identified additional putative candidate genes such as Sobic.001G157100 (Nonphototropic hypocotyl 3, NPH3), Sobic.001G156600 (Lectin receptor‐like serine/threonine kinase), and Sobic.006G061100 (Sucrose nonfermenting 1 related protein kinase 1, SnRK1) for ESC tolerance and Sobic.006G139900 (UDP‐glucoronosyl and UDP‐glucosyl transferase), Sobic.002G187400 (Serine/threonine protein kinase), and Sobic.004G333700 (Ca2+/calmodulin‐dependent protein phosphatase) for LSF tolerance. Tan1 and Tan2 play a major role in seed dormancy and induce resistance against soil‐borne pathogens under cold and wet soil conditions. Seed tannin content may be used as an indirect selection marker for identifying cold tolerant germplasm for breeding. NPH3 and SnRK1 regulate seed germinability under cold stress in various crops. Candidates identified in this study could be further exploited to develop low temperature tolerant cultivars as proxies in marker‐assisted breeding, genomic selection, and genetic engineering.

The Population Structure of a Globe Artichoke Worldwide Collection, as Revealed by Molecular and Phenotypic Analyzes.

The knowledge of the organization of the domesticated gene pool of crop species is an essential requirement to understand crop evolution, to rationalize conservation programs, and to support practical decisions in plant breeding. Here, we integrate simple sequence repeat (SSR) analysis and phenotypic characterization to investigate a globe artichoke collection that comprises most of the varieties cultivated worldwide. We show that the cultivated gene pool of globe artichoke includes five distinct genetic groups associated with the major phenotypic typologies: Catanesi (which based on our analysis corresponds to Violetti di Provenza), Spinosi, Violetti di Toscana, Romaneschi, and Macau. We observed that 17 and 11% of the molecular and phenotypic variance, respectively, is between these groups, while within groups, strong linkage disequilibrium and heterozygote excess are evident. The divergence between groups for quantitative traits correlates with the average broad-sense heritability within the groups. The phenotypic divergence between groups for both qualitative and quantitative traits is strongly and positively correlated with SSR divergence (FST) between groups. All this implies a low population size and strong bottleneck effects, and indicates a long history of clonal propagation and selection during the evolution of the domesticated gene pool of globe artichoke. Moreover, the comparison between molecular and phenotypic population structures suggests that harvest time, plant architecture (i.e., plant height, stem length), leaf spininess, head morphology (i.e., head shape, bract shape, spininess) together with the number of heads per plant were the main targets of selection during the evolution of the cultivated germplasm. We emphasize our findings in light of the potential exploitation of this collection for association mapping studies.

Assessment of Rice Sheath Blight Resistance Including Associations with Plant Architecture, as Revealed by Genome-Wide Association Studies

BackgroundSheath blight (ShB) disease caused by Rhizoctonia solani Kühn, is one of the most economically damaging rice (Oryza sativa L.) diseases worldwide. There are no known major resistance genes, leaving only partial resistance from small-effect QTL to deploy for cultivar improvement. Many ShB-QTL are associated with plant architectural traits detrimental to yield, including tall plants, late maturity, or open canopy from few or procumbent tillers, which confound detection of physiological resistance.ResultsTo identify QTL for ShB resistance, 417 accessions from the Rice Diversity Panel 1 (RDP1), developed for association mapping studies, were evaluated for ShB resistance, plant height and days to heading in inoculated field plots in Arkansas, USA (AR) and Nanning, China (NC). Inoculated greenhouse-grown plants were used to evaluate ShB using a seedling-stage method to eliminate effects from height or maturity, and tiller (TN) and panicle number (PN) per plant. Potted plants were used to evaluate the RDP1 for TN and PN. Genome-wide association (GWA) mapping with over 3.4 million SNPs identified 21 targeted SNP markers associated with ShB which tagged 18 ShB-QTL not associated with undesirable plant architecture traits. Ten SNPs were associated with ShB among accessions of the Indica subspecies, ten among Japonica subspecies accessions, and one among all RDP1 accessions. Across the 18 ShB QTL, only qShB4-1 was not previously reported in biparental mapping studies and qShB9 was not reported in the GWA ShB studies. All 14 PN QTL overlapped with TN QTL, with 15 total TN QTL identified. Allele effects at the five TN QTL co-located with ShB QTL indicated that increased TN does not inevitably increase disease development; in fact, for four ShB QTL that overlapped TN QTL, the alleles increasing resistance were associated with increased TN and PN, suggesting a desirable coupling of alleles at linked genes.ConclusionsNineteen accessions identified as containing the most SNP alleles associated with ShB resistance for each subpopulation were resistant in both AR and NC field trials. Rice breeders can utilize these accessions and SNPs to develop cultivars with enhanced ShB resistance along with increased TN and PN for improved yield potential.