Diversity Arrays Technology Markers Research Articles

Zinc finger knuckle genes are associated with tolerance to drought and dehydration in chickpea (Cicer arietinum L.).

Chickpea (Cicer arietinum L.) is a very important food legume and needs improved drought tolerance for higher seed production in dry environments. The aim of this study was to determine diversity and genetic polymorphism in zinc finger knuckle genes with CCHC domains and their functional analysis for practical improvement of chickpea breeding. Two CaZF-CCHC genes, Ca04468 and Ca07571, were identified as potentially important candidates associated with plant responses to drought and dehydration. To study these genes, various methods were used including Sanger sequencing, DArT (Diversity array technology) and molecular markers for plant genotyping, gene expression analysis using RT-qPCR, and associations with seed-related traits in chickpea plants grown in field trials. These genes were studied for genetic polymorphism among a set of chickpea accessions, and one SNP was selected for further study from four identified SNPs between the promoter regions of each of the two genes. Molecular markers were developed for the SNP and verified using the ASQ and CAPS methods. Genotyping of parents and selected breeding lines from two hybrid populations, and SNP positions on chromosomes with haplotype identification, were confirmed using DArT microarray analysis. Differential expression profiles were identified in the parents and the hybrid populations under gradual drought and rapid dehydration. The SNP-based genotypes were differentially associated with seed weight per plant but not with 100 seed weight. The two developed and verified SNP molecular markers for both genes, Ca04468 and Ca07571, respectively, could be used for marker-assisted selection in novel chickpea cultivars with improved tolerance to drought and dehydration.

Effectiveness of DArTseq markers application in genetic diversity and population structure of indigenous chickens in Eastern Province of Rwanda

BackgroundThe application of biotechnologies which make use of genetic markers in chicken breeding is developing rapidly. Diversity Array Technology (DArT) is one of the current Genotyping-By-Sequencing techniques allowing the discovery of whole genome sequencing. In livestock, DArT has been applied in cattle, sheep, and horses. Currently, there is no study on the application of DArT markers in chickens. The aim was to study the effectiveness of DArTSeq markers in the genetic diversity and population structure of indigenous chickens (IC) and SASSO in the Eastern Province of Rwanda.MethodsIn total 87 blood samples were randomly collected from 37 males and 40 females of indigenous chickens and 10 females of SASSO chickens purposively selected from 5 sites located in two districts of the Eastern Province of Rwanda. Genotyping by Sequencing (GBS) using DArTseq technology was employed. This involved the complexity reduction method through digestion of genomic DNA and ligation of barcoded adapters followed by PCR amplification of adapter-ligated fragments.ResultsFrom 45,677 DArTseq SNPs and 25,444 SilicoDArTs generated, only 8,715 and 6,817 respectively remained for further analysis after quality control. The average call rates observed, 0.99 and 0.98 for DArTseq SNPs and SilicoDArTs respectively were quite similar. The polymorphic information content (PIC) from SilicoDArTs (0.33) was higher than that from DArTseq SNPs (0.22). DArTseq SNPs and SilicoDArTs had 34.4% and 34% of the loci respectively mapped on chromosome 1. DArTseq SNPs revealed distance averages of 0.17 and 0.15 within IC and SASSO chickens respectively while the respective averages observed with SilicoDArTs were 0.42 and 0.36. The average genetic distance between IC and SASSO chickens was moderate for SilicoDArTs (0.120) compared to that of DArTseq SNPs (0.048). The PCoA and population structure clustered the chicken samples into two subpopulations (1 and 2); 1 is composed of IC and 2 by SASSO chickens. An admixture was observed in subpopulation 2 with 12 chickens from subpopulation 1.ConclusionsThe application of DArTseq markers have been proven to be effective and efficient for genetic relationship between IC and separated IC from exotic breed used which indicate their suitability in genomic studies. However, further studies using all chicken genetic resources available and large big sample sizes are required.

Favorable Loci Identified for Stripe Rust Resistance in Chinese Winter Wheat Accessions via Genome-Wide Association Study.

Stripe rust (or yellow rust), caused by Puccinia striiformis f. sp. tritici (Pst), is one of the most devastating diseases of wheat worldwide. Currently, the utilization of resistant cultivars is the most viable way to reduce yield losses. In this study, a panel of 188 wheat accessions from China was evaluated for stripe rust resistance, and genome-wide association studies were performed using high-quality Diversity Arrays Technology markers. According to the phenotype and genotype data, a total of 26 significant marker-trait associations were identified, representing 18 quantitative trait loci (QTLs) on chromosomes 1B, 2A, 2B, 3A, 3B, 5A, 5B, 6B, 7B, and 7D. Of the 18 QTLs, almost all were associated with adult plant resistance (APR) except QYr.nwsuaf-6B.2, which was associated with all-stage resistance (also known as seedling resistance). Three of the 18 QTLs were mapped far from previously identified Pst resistance genes and QTLs and were considered potentially new loci. The other 15 QTLs were mapped close to known resistance genes and QTLs. Subsequent haplotype analysis for QYr.nwsuaf-2A and QYr.nwsuaf-7B.3 revealed the degrees of resistance of the panel in the APR stage. In summary, the favorable alleles identified in this study may be useful in breeding for disease resistance to stripe rust.

Integrated genome-wide association study and QTL mapping reveals qSa-3A associated with English grain aphid, Sitobion avenae (Fabricius) resistance in wheat.

The English grain aphid, Sitobion avenae (Fabricius), is a devastating pest impacts yield and quality in wheat (Triticum aestivum L.). Breeding resistant wheat varieties and detecting resistance genes are important strategies to control aphid. In this study, we evaluated the number of aphids per spike, the rate of thousand kernel weight decrease and aphid index based on three classic resistance mechanisms (antibiosis, tolerance and antixenosis), and detected SNPs/QTLs for resistance to S. avenae in a natural population of 163 varieties with 20,689 high-quality single-nucleotide polymorphism (SNP) markers and recombinant inbred line (RIL) population of 164 lines with 3,627 diversity arrays technology (DArT) markers. Results showed that 83 loci significantly associated with S. avenae antibiosis and 182 loci significantly associated with S. avenae tolerance were detected by genome-wide association study (GWAS), explaining 6.47-15.82% and 8.36-35.61% of the phenotypic variances, respectively. The wsnp_Ku_c4568_8243646 detected in two periods was localized at 34.52 Mb on chromosome 3AS. Then, we confirmed a stable QSa.haust-3A.2 explained 11.19-20.10% of the phenotypic variances in two periods with S. avenae antixenosis in the physical interval of 37.49-37.50 Mb on chromosome 3A in the RIL population. Therefore, a narrow region in the physical interval of 34.52-37.50 Mb on chromosome 3AS was named as qSa-3A, which was a new locus between wsnp_Ku_c4568_8243646 and QSa.haust-3A.2 associated with S. avenae resistance. We found qSa-3A was a new locus associated with S. avenae resistance. The results could be applied in gene cloning and genetic improvement of S. avenae resistance in wheat.

Validation and marker-assisted selection of DArT-genomic regions associated with wheat yield-related traits under normal and drought conditions.

Quantitative trait loci (QTL) is one of the most important steps in marker-assisted selection. Few studies have validated quantitative trait loci for marker-assisted selection of yield traits under drought stress conditions in wheat. A set of 138 highly diverse wheat genotypes were tested under normal and drought stress conditions for 2years. Plant height, heading date, spike length, grain number per spike, grain yield per spike, and 1000-kernel weight were scored. High genetic variation was found among genotypes in all traits scored under both conditions in the 2years. The same panel was genotyped using a diversity-array technology (DArT) marker, and a genome-wide association study was performed to find alleles associated with yield traits under all conditions. A set of 191 significant DArT markers were identified in this study. The results of the genome-wide association study revealed eight common markers in wheat that were significantly associated with the same traits under both conditions in the 2years. Out of the eight markers, seven were located on the D genome except one marker. Four validated markers were located on the 3D chromosome and found in complete linkage disequilibrium. Moreover, these four markers were significantly associated with the heading date under both conditions and the grain yield per spike under drought stress condition in the 2years. This high-linkage disequilibrium genomic region was located within the TraesCS3D02G002400 gene model. Furthermore, of the eight validated markers, seven were previously reported to be associated with yield traits under normal and drought conditions. The results of this study provided very promising DArT markers that can be used for marker-assisted selection to genetically improve yield traits under normal and drought conditions.

QTL cluster analysis and marker development for kernel traits based on DArT markers in spring bread wheat (Triticum aestivum L.).

Genetic dissection of yield component traits including kernel characteristics is essential for the continuous improvement in wheat yield. In the present study, one recombinant inbred line (RIL) F6 population derived from a cross between Avocet and Chilero was used to evaluate the phenotypes of kernel traits of thousand-kernel weight (TKW), kernel length (KL), and kernel width (KW) in four environments at three experimental stations during the 2018-2020 wheat growing seasons. The high-density genetic linkage map was constructed with the diversity arrays technology (DArT) markers and the inclusive composite interval mapping (ICIM) method to identify the quantitative trait loci (QTLs) for TKW, KL, and KW. A total of 48 QTLs for three traits were identified in the RIL population on the 21 chromosomes besides 2A, 4D, and 5B, accounting for 3.00%-33.85% of the phenotypic variances. Based on the physical positions of each QTL, nine stable QTL clusters were identified in the RILs, and among these QTL clusters, TaTKW-1A was tightly linked to the DArT marker interval 3950546-1213099, explaining 10.31%-33.85% of the phenotypic variances. A total of 347 high-confidence genes were identified in a 34.74-Mb physical interval. TraesCS1A02G045300 and TraesCS1A02G058400 were among the putative candidate genes associated with kernel traits, and they were expressed during grain development. Moreover, we also developed high-throughput kompetitive allele-specific PCR (KASP) markers of TaTKW-1A, validated in a natural population of 114 wheat varieties. The study provides a basis for cloning the functional genes underlying the QTL for kernel traits and a practical and accurate marker for molecular breeding.

Genome‐wide association study of variation in cooking time among common bean (Phaseolus vulgaris L.) accessions using Diversity Arrays Technology markers

AbstractStored grains of common bean (Phaseolus vulgaris L.) develop the hard‐to‐cook trait (HTC), which is manifested in a prolonged cooking time, thereby imposing time and energy constraints. The objective of this study was to determine variation in cooking time among common bean genotypes and to identify single nucleotide polymorphism (SNP) markers associated with cooking time.Seeds of 222 common bean accessions sourced from Kenyan institutions were multiplied in the Jomo Kenyatta University of Agriculture and Technology (JKUAT) field in 2019. The freshly harvested seeds and those stored at 35°C and 50% red haricot (RH) for 4 months for accelerated aging were soaked in distilled water for 16 h and evaluated for cooking time using the finger‐pressing method. The accessions were also genotyped to determine variation in SNP markers using Diversity Arrays Technology Sequencing (DArTseq). Genome‐wide association study (GWAS) analysis was conducted to identify SNPs significantly associated with cooking time.The study revealed significant differences (p ≤ 0.05) within and between fresh and aged bean accessions. Fresh seeds had a lower cooking time with a mean of 40.8 min and ranged from 28.1 to 72.2 min, whereas aged seeds had a higher average cooking time of 54.1 min and ranged from 32.1 to 96.3 min. GWAS identified a region in Chromosome 10 to be significantly (p ≤ 0.05) associated with the cooking time of aged seeds. Consequently, two potential candidate genes Phvul.010G038000 and Phvul.010G038100 were revealed. The characterized common bean accessions and the identified SNP markers can be utilized in breeding programs to improve the cooking quality of the common bean.

Advances in genomics for diversity studies and trait improvement in temperate fruit and nut crops under changing climatic scenarios.

Genetic improvement of temperate fruit and nut crops through conventional breeding methods is not sufficient alone due to its extreme time-consuming, cost-intensive, and hard-to-handle approach. Again, few other constraints that are associated with these species, viz., their long juvenile period, high heterozygosity, sterility, presence of sexual incompatibility, polyploidy, etc., make their selection and improvement process more complicated. Therefore, to promote precise and accurate selection of plants based on their genotypes, supplement of advanced biotechnological tools, viz., molecular marker approaches along with traditional breeding methods, is highly required in these species. Different markers, especially the molecular ones, enable direct selection of genomic regions governing the trait of interest such as high quality, yield, and resistance to abiotic and biotic stresses instead of the trait itself, thus saving the overall time and space and helping screen fruit quality and other related desired traits at early stages. The availability of molecular markers like SNP (single-nucleotide polymorphism), DArT (Diversity Arrays Technology) markers, and dense molecular genetic maps in crop plants, including fruit and nut crops, led to a revelation of facts from genetic markers, thus assisting in precise line selection. This review highlighted several aspects of the molecular marker approach that opens up tremendous possibilities to reveal valuable information about genetic diversity and phylogeny to boost the efficacy of selection in temperate fruit crops through genome sequencing and thus cultivar improvement with respect to adaptability and biotic and abiotic stress resistance in temperate fruit and nut species.

The 4R QTLs pollen fertility restoration in triticale with CMS Triticum timopheevii

AbstractThe Triticum timopheevii Zhuk. (Tt) cytoplasm is the most exploited cytoplasmic male sterility (CMS) type used in triticale in commercial seed production of hybrid varieties. The present study established a recombinant inbred line (RIL) mapping population to identify genetic loci controlling fertility restoration in triticale with CMS Tt. The trait was evaluated via phenotyping the BC1F1 materials originating from a backcross of maternal line MS 112(15)‐2‐1 (on CMS Tt) and RILs. A genetic map spanning 2293 cM over 21 linkage groups was constructed using 1,170 single nucleotide polymorphisms and silico diversity array technology (DArT) markers generated through DArTseq genotyping. Two quantitative trait loci (QTL) controlling fertility restoration were localized at the 4RL chromosome. They were stable during two vegetative seasons and, depending on the year, explained 17.8 to 37.5 (QRft‐4R.1) and 17.8 to 27.1% (QRft‐4R.2) of phenotypic variance. Bioinformatic analysis was performed to predict genes potentially responsible for the trait. Four markers linked to the trait were successfully converted into a polymerase chain reaction‐based assay to select the pollen fertility QTLs easily. The exact position of QTLs detected previously in the rye and here in the triticale suggests that the same loci might control the trait.

Genomic prediction of drought tolerance during seedling stage in maize using low-cost molecular markers

Drought tolerance in maize is a complex and polygenic trait, especially in the seedling stage. In plant breeding, complex genetic traits can be improved by genomic selection (GS), which has become a practical and effective breeding tool. In the present study, a natural maize population named Northeast China core population (NCCP) consisting of 379 inbred lines were genotyped with diversity arrays technology (DArT) and genotyping-by-sequencing (GBS) platforms. Target traits of seedling emergence rate (ER), seedling plant height (SPH), and grain yield (GY) were evaluated under two natural drought stress environments in northeast China. Adequate genetic variations were observed for all the target traits, but they were divergent across environments. Similarly, the heritability of the target trait also varied across years and environments, the heritabilities in 2019 (0.88, 0.82, 0.85 for ER, SPH, GY) were higher than those in 2020 (0.65, 0.53, 0.33) and cross-2-years (0.32, 0.26, 0.33). In total, three marker datasets, 11,865 SilicoDArT markers obtained from the DArT-seq platform, 7837 SNPs obtained from the DArT-seq platform, and 91,003 SNPs obtained from the GBS platform, were used for GS analysis after quality control. The results of phylogenetic trees showed that broad genetic diversity existed in the NCCP population. Genomic prediction results showed that the average prediction accuracies estimated using the DArT SNP dataset under the two-fold cross-validation scheme were 0.27, 0.19, and 0.33, for ER, SPH, and GY, respectively. The result of SilicoDArT is close to the SNPs from DArT-seq, those were 0.26, 0.22, and 0.33. For the trait with lower heritability, the prediction accuracy can be improved using the dataset filtered by linkage disequilibrium. For the same trait, the prediction accuracies estimated with two DArT marker datasets were consistently higher than that estimated with the GBS SNP dataset under the same genotyping cost. The prediction accuracy was improved by controlling population structure and marker quality, even though the marker density was reduced. The prediction accuracies were improved by more than 30% using the significant-associated SNPs. Due to the complexity of drought tolerance under the natural stress environments, multiple years of data need to be accumulated to improve prediction accuracy by reducing genotype-by-environment interaction. Modeling genotype-by-environment interaction into genomic prediction needs to be further developed for improving drought tolerance in maize. The results obtained from the present study provides valuable pathway for improving drought tolerance in maize using GS.

Genetic diversity and population structure of some Nigerian accessions of Bambara groundnut (Vigna subterranea (L.) Verdc.,) using DArT SNP markers

Bambara groundnut is one of the crops with inadequate molecular research to show its full potentials. Previous studies showed morphological diversity with inadequate information to confirm genetic variations. In the quest to reveal the genetic potentials, deoxyribonucleic acid (DNA) of the selected accessions was extracted through leaf samples at 3 weeks old, using Dellaporta Miniprep for Plant DNA Isolation procedure. The high quality DNA was sequenced using Diversity Arrays Technology (DArT) markers to unlock diversity among Bambara groundnut of Nigerian origin. Cluster analysis (neighbor-joining clustering) of the single nucleotide polymorphisms (SNP’s) were used to generate sub-population to show relatedness and differences. Seven sub-populations were generated with 5927 (50.13%) high quality DArT markers out of the 11,821 SNPs generated. This revealed high genetic diversity existed among the selected Bambara groundnut accessions in Nigeria. This also revealed that DArT markers were highly efficient in classifying the accessions based on molecular expressions. This study also identified markers responsible for genetic variation that could facilitate the characterization of larger collections for further utilization of genetic resources and most importantly Bambara groundnut for the purpose of crop improvement.

SilicoDArT and SNP markers for genetic diversity and population structure analysis of Trema orientalis; a fodder species.

Establishing the genetic diversity and population structure of a species can guide the selection of appropriate conservation and sustainable utilization strategies. Next-generation sequencing (NGS) approaches are increasingly being used to generate multi-locus data for genetic structure determination. This study presents the genetic structure of a fodder species -Trema orientalis based on two genome-wide high-throughput diversity array technology (DArT) markers; silicoDArT and single nucleotide polymorphisms (SNPs). Genotyping of 119 individuals generated 40,650 silicoDArT and 4767 SNP markers. Both marker types had a high average scoring reproducibility (>99%). Genetic relationships explored by principal coordinates analysis (PCoA) showed that the first principal coordinate axis explained most of the variation in both the SilicoDArT (34.2%) and SNP (89.6%) marker data. The average polymorphic information content did not highly differ between silicoDArT (0.22) and SNPs (0.17) suggesting minimal differences in informativeness in the two groups of markers. The, mean observed (Ho) and expected (He) heterozygosity were low and differed between the silicoDArT and SNPs respectively, estimated at Ho = 0.08 and He = 0.05 for silicoDArT and Ho = 0.23 and He = 0.19 for SNPs. The population of T. orientalis was moderately differentiated (FST = 0.20–0.53) and formed 2 distinct clusters based on maximum likelihood and principal coordinates analysis. Analysis of molecular variance revealed that clusters contributed more to the variation (46.3–60.8%) than individuals (32.9–31.2%). Overall, the results suggest a high relatedness of the individuals sampled and a threatened genetic potential of T. orientalis in the wild. Therefore, genetic management activities such as ex-situ germplasm management are required for the sustainability of the species. Ex-situ conservation efforts should involve core collection of individuals from different populations to capture efficient diversity. This study demonstrates the importance of silicoDArT and SNP makers in population structure and genetic diversity analysis of Trema orientalis, useful for future genome wide studies in the species.

Using a Hybrid Mapping Population to Identify Genomic Regions of Pyrenophora teres Associated With Virulence.

Net blotches caused by Pyrenophora teres are important foliar fungal diseases of barley and result in significant yield losses of up to 40%. The two types of net blotch, net-form net blotch and spot-form net blotch, are caused by P. teres f. teres (Ptt) and P. teres f. maculata (Ptm), respectively. This study is the first to use a cross between Ptt and Ptm to identify quantitative trait loci (QTL) associated with virulence and leaf symptoms. A genetic map consisting of 1,965 Diversity Arrays Technology (DArT) markers was constructed using 351 progenies of the Ptt/Ptm cross. Eight barley cultivars showing differential reactions to the parental isolates were used to phenotype the hybrid progeny isolates. Five QTL associated with virulence and four QTL associated with leaf symptoms were identified across five linkage groups. Phenotypic variation explained by these QTL ranged from 6 to 16%. Further phenotyping of selected progeny isolates on 12 more barley cultivars revealed that three progeny isolates are moderately to highly virulent across these cultivars. The results of this study suggest that accumulation of QTL in hybrid isolates can result in enhanced virulence.

Genome wide association study for stripe rust resistance in spring bread wheat (Triticum aestivum L.)

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst) is one of the most destructive diseases of wheat (Triticum aestivum L.) worldwide causing huge yield losses every year. Development and deployment of resistant varieties is the most economical and environment friendly approach for controlling this disease. However, because of the continuous evolution of the pathogen, resistant genes are easily overcome by new virulent Pst races, which necessitates a continuous identification and introgression of resistance genes to develop resistant wheat varieties. To identify effective source of resistance, a genome-wide association study was performed using 426 elite bread wheat genotypes based on 5176 polymorphic Diversity Arrays Technology (DArT) markers. Adult-plant-resistance was evaluated under field conditions for yellow rust resistance for two consecutive years (2014 and 2015) at ICARDA Merchouch station, Morocco. Out of the 426 genotypes, 51.17% were highly resistant with 5–10% level of severity to yellow rust. Genome wide association studies (GWAS) using a mixed linear model (MLM) identified three DArT markers on chromosomes 1B, 2B and 7B which are significantly associated with stripe rust resistance at false discovery rate p ≤ 0.05. BLAST analysis confirmed that the marker 412,394 in chromosome 2B overlapped with two previously reported QTLs (QYrlu.cau-2BS1 Luke and QYrid.ui-2B.1_IDO444). However, the two other markers 542,318 (1B) and 583,038 (5B) were not mapped within any of the previously reported gene/QTL regions; therefore, these markers may represent novel resistance loci for yellow rust. The highly resistant elite genotypes and linked molecular markers are recommended for further gene introgression and pyramiding purposes in the wheat breeding programs after validation.

Use of Diversity Arrays Technology (DArT) for detection of QTL underlying plant architecture and yield-related traits in cassava

ABSTRACT Cassava (Manihot esculenta Crantz) is an important starchy root crop representing food security for more than one billion people in the world. Plant architecture (PA) is a key factor underlying yield, and understanding the physiological basis of PA may lead to improved yield plants. In this study, we identified genomic regions controlling several traits associated with plant architecture and productivity in Thai cassava cultivars. The analysis was conducted in an F1 population derived from a cross between “Huay Bong 60” (female parent) and “Hanatee” (male parent). A genetic linkage analysis was undertaken with 167 conventional DArT markers using JoinMap 3.0 software. Plant architecture and productivity were evaluated over four years at the Rayong Field Crops Research Center, Thailand. DArT markers associated with five traits of plant architecture (number of mainstems per plant (NMain), number of apices per plant (NAp), plant height (PH), first branching height (BH), branching level (BL)) as well as two productivity measurements harvest index (HI) and fresh root yield (FRY) were identified by simple interval mapping (SIM) using MapQTL 4.0. Small effects of 22 plant architecture quantitative trait loci (QTL) were detected, with phenotypic contributions varying from 5.1 to 10.9%. Small effects of four QTL of FRY and five QTL of HI were also detected. Additionally, PH showed a significant correlation with FRY. However, this study has limitations from the low density of the markers, therefore additional markers would be necessary for an efficient genetic linkage map and QTL detection.

Association Mapping for Common Bunt Resistance in Wheat Landraces and Cultivars

Common bunt is a seed borne disease of wheat whose importance is likely to increase due to the growing organic seed market, which, in addition to seed phytosanitary measures, relies on genetic resistances towards the disease. Genome wide association studies in wheat have been proven to be a useful tool in the detection of genetic polymorphisms underlying phenotypic trait variation in wheat. Here 248 wheat landraces and cultivars representing 130 years of breeding history were screened for two years in the field for their resistance reactions towards common bunt. The majority of lines exhibited high levels of susceptibility towards common bunt, while 25 accessions had less than 10% infection. Using Diversity Array Technology (DArT) markers for genotyping and correcting for population stratification by using a compressed mixed linear model, we identified two significant marker trait associations (MTA) for common bunt resistance, designated QCbt.cph-2B and QCbt.cph-7A, located on wheat chromosomes 2B and 7A, respectively. This shows that genome wide association studies (GWAS) are applicable in the search for genetic polymorphisms for resistance towards less studied plant diseases such as common bunt in the context of an under representation of resistant lines.

Assessment of the Genetic Structure and Diversity of Soybean (Glycine max L.) Germplasm Using Diversity Array Technology and Single Nucleotide Polymorphism Markers.

Knowledge of the genetic structure and diversity of germplasm collections is crucial for sustainable genetic improvement through hybridization programs and rapid adaptation to changing breeding objectives. The objective of this study was to determine the genetic diversity and population structure of 281 International Institute of Tropical Agriculture (IITA) soybean accessions using diversity array technology (DArT) and single nucleotide polymorphism (SNP) markers for the efficient utilization of these accessions. From the results, the SNP and DArT markers were well distributed across the 20 soybean chromosomes. The cluster and principal component analyses revealed the genetic diversity among the 281 accessions by grouping them into two stratifications, a grouping that was also evident from the population structure analysis, which divided the 281 accessions into two distinct groups. The analysis of molecular variance revealed that 97% and 98% of the genetic variances using SNP and DArT markers, respectively, were within the population. Genetic diversity indices such as Shannon’s diversity index, diversity and unbiased diversity revealed the diversity among the different populations of the soybean accessions. The SNP and DArT markers used provided similar information on the structure, diversity and polymorphism of the accessions, which indicates the applicability of the DArT marker in genetic diversity studies. Our study provides information about the genetic structure and diversity of the IITA soybean accessions that will allow for the efficient utilization of these accessions in soybean improvement programs, especially in Africa.

Identification of Candidate Genes and Genomic Regions Associated with Adult Plant Resistance to Stripe Rust in Spring Wheat

Wheat stripe rust (caused by Puccinia striiformis f. sp. tritici) is a major disease that damages wheat plants and affects wheat yield all over the world. In recent years, stripe rust became a major problem that affects wheat yield in Egypt. New races appeared and caused breakdowns in the resistant genotypes. To improve resistance in the Egyptian genotypes, new sources of resistance are urgently needed. In the recent research, a set of 95 wheat genotypes collected from 19 countries, including Egypt, were evaluated for their resistance against the Egyptian race(s) of stripe rust under field conditions in the two growing seasons 2018/2019 and 2019/2020. A high genetic variation was found among the tested genotypes. Single marker analysis was conducted using a subset of 71 genotypes and 424 diversity array technology (DArT) markers, well distributed across the genome. Out of the tested markers, 13 stable markers were identified that were significantly associated with resistance in both years (p-value ≤ 0.05). By using the sequence of the DArT markers, the chromosomal position of the significant DArT markers was detected, and nearby gene models were identified. Two markers on chromosomes 5A and 5B were found to be located within gene models functionally annotated with disease resistance in plants. These two markers could be used in marker-assisted selection for stripe rust resistance under Egyptian conditions. Two German genotypes were carrying the targeted allele of all the significant DArT markers associated with stripe rust resistance and could be used to improve resistance under Egyptian conditions.

Genetic Diversity and Population Structure of Myanmar Rice (Oryza sativa L.) Varieties Using DArTseq-Based SNP and SilicoDArT Markers.

Myanmar is well known as a primary center of plant genetic resources for rice. A considerable number of genetic diversity studies have been conducted in Myanmar using various DNA markers. However, this is the first report using DArTseq technology for exploring the genetic diversity of Myanmar rice. In our study, two ultra-high-throughput diversity array technology markers were employed to investigate the genetic diversity and population structure of local rice varieties in the Ayeyarwady delta, the major region of rice cultivation. The study was performed using 117 rice genotypes with 7643 SNP and 4064 silicoDArT markers derived from the DArT platform. Genetic variance among the genotypes ranged from 0 to 0.753 in SNPs, and from 0.001 to 0.954 in silicoDArT. Two distinct population groups were identified from SNP data analysis. Cluster analysis with both markers clearly separated traditional Pawsan varieties and modern high-yielding varieties. A significant divergence was found between populations according to the Fst values (0.737) obtained from the analysis of molecular variance, which revealed 74% genetic variation at the population level. These findings support rice researchers in identifying useful DNA polymorphisms in genes and pinpointing specific genes conferring desirable phenotypic traits for further genome-wide association studies and parental selection for recombination breeding to enhance rice varietal development and release.

Population Structure of Pyrenophora teres f. teres Barley Pathogens from Different Continents.

Net form net blotch disease, caused by Pyrenophora teres f. teres, results in significant yield losses to barley industries. Up-to-date knowledge of the genetic diversity and structure of pathogen populations is critical for elucidating the disease epidemiology and unraveling pathogen survival and dispersal mechanisms. Thus, this study investigated long-distance dispersal and adaptation by analyzing the genetic structure of 250 P. teres f. teres isolates collected from Australia, Canada, Hungary, and Republic of South Africa (RSA), and historical isolates from Canada, Denmark, Japan, and Sweden. The population genetic structure detected by discriminant analysis of principal components, with the use of 5,890 Diversity Arrays Technology markers, revealed the presence of four clusters. Two of these contained isolates from all regions, and all isolates from RSA were grouped in these two. Australia and Hungary showed three clusters each. One of the Australian clusters contained only Australian isolates. One of the Hungarian clusters contained only Hungarian isolates and one Danish isolate. STRUCTURE analysis indicated that some isolates from Australia and Hungary shared recent ancestry with RSA, Canada, and historical isolates and were thus admixed. Subdivisions of the neighbor joining network indicated that isolates from distinct countries were closely related, suggesting that multiple introduction events conferred genetic heterogeneity in these countries. Through a neighbor joining analysis and amplification with form-specific DNA markers, we detected two hybrid isolates, CBS 281.31 from Japan and H-919 from Hungary, collected in 1931 and 2018, respectively. These results provide a foundation for exploring improved management of disease incursions and pathogen control through strategic deployment of resistance.