DArTseq-Based High-Throughput SilicoDArT and SNP Markers Applied for Association Mapping of Genes Related to Maize Morphology

A comparative study of population structure and genetic diversity of commercial and indigenous chickens from different agro-ecological zones in Ghana using SilicoDArT and SNP markers

Chicken production, both in the local and commercial sectors, contributes significantly to human livelihood and food security. Precise use of diverse genetic resources is primary in breeding programs. The study analyzed the genetic diversity and population structure of commercial chickens and indigenous chicken ecotypes from three different agro-ecological zones (Semi-Deciduous Rainforest Zone, Guinea Savannah, and Coastal Savannah) using SilicoDArT and SNP markers, utilizing whole-genome sequencing and phenotypic data. Phenotypic data were collected from 72 indigenous chicken ecotypes across the three AEZs, and 32 commercial birds kept at the Kwame Nkrumah University of Science and Technology (KNUST). DNA samples used for sequencing were obtained from 88 chickens (62 indigenous chicken ecotypes and 26 commercial chickens). A total of 54,995 SilicoDArT and 85,396 SNPs markers were generated from DArTseq genotyping. After filtering, 44,784 SilicoDArT and 58,353 SNP were used for genetic diversity and population structure analysis. Both markers showed high reproducibility and call rate. Polymorphic information content (PIC) values ranged from 0.00 to 0.50, while ≥ 50 % showed PIC values more than the median. Furthermore, we obtained FST values, Nei's genetic distance, dendrogram analysis, and principal component analysis (PCA) of commercial and indigenous chickens. The FST and Nei's genetic distance showed that there is high genetic diversity between the commercial chickens and the indigenous chicken ecotypes. However, there was low genetic diversity among the indigenous chicken ecotypes. The PCA analysis indicated a clear separation between the commercial and indigenous chicken ecotypes, while no clear separation was observed between the indigenous chicken ecotypes. The phenotypic data and the dendrogram indicated that naked and frizzle genes do not markedly alter the genetics of indigenous and commercial birds, and their influence on economic traits may be solely determined by the prevailing environmental conditions. The results indicate that there is high genetic differentiation between commercial and indigenous chickens based on SilicoDArT and SNP markers. The indigenous chickens from the agro-ecological zones have low genetic diversity and might have a common origin. Naked neck and frizzle genes do not markedly alter the genetic performance of birds in terms of economic traits. Therefore, the superiority of birds carrying these genes in economic traits may be solely due to environmental variation.

Using association mapping and local interval haplotype association analysis to improve the cotton drought stress response

Drought stress has a serious impact on the growth and development of cotton. To explore the relevant molecular mechanism of the drought stress response in cotton, gene mapping based on the QTL interval mapped by simplified genome BSA-seq of the drought-resistance-related RIL population was performed. A QTL region spanning 2.02 Mb on chromosome D07 was selected, and 201 resource materials were genotyped using 9 KASP markers in the interval. After local interval haplotype association analysis, the overlap of the 110 kb peak region confirmed the reliability of this region, and at the same time, the role of GhGF14-30, the only gene in the overlapping region, was modeled in the response of cotton to drought stress. qRTPCR analysis of the materials and population parents proved that this gene plays a role in the drought stress response in cotton. Virus-induced gene silencing proved the importance of this gene in drought-sensitive materials, and drought-resistance-related marker genes also proved that the GhGF14-30 gene may play an important role in the ABA and SOS signaling pathways. This study provides a basis for mining drought stress response functional genes in cotton and lays the foundation for the molecular mechanism of the GhGF14-30 gene in response to drought stress in cotton.

A Comparison of Methods to Estimate Additive-by-Additive-by-Additive of QTL×QTL×QTL Interaction Effects by Monte Carlo Simulation Studies

The goal of the breeding process is to obtain new genotypes with traits improved over the parental forms. Parameters related to the additive effect of genes as well as their interactions (such as epistasis of gene-by-gene interaction effect and additive-by-additive-by-additive of gene-by-gene-by-gene interaction effect) can influence decisions on the suitability of breeding material for this purpose. Understanding the genetic architecture of complex traits is a major challenge in the post-genomic era, especially for quantitative trait locus (QTL) effects, QTL-by-QTL interactions and QTL-by-QTL-by-QTL interactions. With regards to the comparing methods for estimating additive-by-additive-by-additive of QTL×QTL×QTL interaction effects by Monte Carlo simulation studies, there are no publications in the open literature. The parameter combinations assumed in the presented simulation studies represented 84 different experimental situations. The use of weighted regression may be the preferred method for estimating additive-by-additive-by-additive of QTL-QTL-QTL triples interaction effects, as it provides results closer to the true values of total additive-by-additive-by-additive interaction effects than using unweighted regression. This is also indicated by the obtained values of the determination coefficients of the proposed models.

Genetic resources and breeding of maize for Striga resistance: a review

The potential yield of maize (Zea mays L.) and other major crops is curtailed by several biotic, abiotic, and socio-economic constraints. Parasitic weeds, Striga spp., are major constraints to cereal and legume crop production in sub-Saharan Africa (SSA). Yield losses reaching 100% are reported in maize under severe Striga infestation. Breeding for Striga resistance has been shown to be the most economical, feasible, and sustainable approach for resource-poor farmers and for being environmentally friendly. Knowledge of the genetic and genomic resources and components of Striga resistance is vital to guide genetic analysis and precision breeding of maize varieties with desirable product profiles under Striga infestation. This review aims to present the genetic and genomic resources, research progress, and opportunities in the genetic analysis of Striga resistance and yield components in maize for breeding. The paper outlines the vital genetic resources of maize for Striga resistance, including landraces, wild relatives, mutants, and synthetic varieties, followed by breeding technologies and genomic resources. Integrating conventional breeding, mutation breeding, and genomic-assisted breeding [i.e., marker-assisted selection, quantitative trait loci (QTL) analysis, next-generation sequencing, and genome editing] will enhance genetic gains in Striga resistance breeding programs. This review may guide new variety designs for Striga-resistance and desirable product profiles in maize.

The Use of DArTseq Technology to Identify Markers Related to the Heterosis Effects in Selected Traits in Maize

Spectacular scientific advances in the area of molecular biology and the development of modern biotechnological tools have had a significant impact on the development of maize heterosis breeding. One technology based on next-generation sequencing is DArTseq. The plant material used for the research consisted of 13 hybrids resulting from the crossing of inbred maize lines. A two-year field experiment was established at two Polish breeding stations: Smolice and Łagiewniki. Nine quantitative traits were observed: cob length, cob diameter, core length, core diameter, number of rows of grain, number of grains in a row, mass of grain from the cob, weight of one thousand grains, and yield. The isolated DNA was subjected to DArTseq genotyping. Association mapping was performed using a method based on the mixed linear model. A total of 81602 molecular markers (28571 SNPs and 53031 SilicoDArTs) were obtained as a result of next-generation sequencing. Out of 81602, 15409 (13850 SNPs and 1559 SilicoDArTs) were selected for association analysis. The 105 molecular markers (8 SNPs and 97 SilicoDArTs) were associated with the heterosis effect of at least one trait in at least one environment. A total of 186 effects were observed. The number of statistically significant relationships between the molecular marker and heterosis effect varied from 8 (for cob length) and 9 (for yield) to 42 (for the number of rows of grain). Of particular note were three markers (2490222, 2548691 and 7058267), which were significant in 17, 8 and 6 cases, respectively. Two of them (2490222 and 7058267) were associated with the heterosis effects of yield in three of the four environments.

The Use of DArTseq Technology to Identify Markers Linked to Genes Responsible for Seed Germination and Seed Vigor in Maize

Seed vigor and seed germination are very important traits, determined by several factors including genetic and physical purity, mechanical damage, and physiological condition, characterized by maintaining a high seed vigor and stable content after storage. The search for molecular markers related to improvement in seed vigor under adverse condition is an important issue in maize breeding currently. Higher sowing quality of seeds is necessary for the development of the agriculture production and better ability to resist all kinds of adversity in the seeds’ storage. Condition is a very important factor affecting the yield of plants, thanks to the construction of their vitality. Identification of molecular markers associated with seed germination and seed vigor may prove to be very important in the selection of high-yielding maize varieties. The aim of this study was to identify and select new markers for maize (SNP and SilicoDArT) linked to genes influencing the seed germination and seed vigor in inbred lines of maize (Zea mays L.). The plant material used for the research was 152 inbred maize lines. The seed germination and seed vigor were analyzed. For identification of SNP and SilicoDArT markers related to the seed germination and seed vigor, the SilicoDarT technique developed by Diversity Arrays Technology was used. The analysis of variance indicated a statistically significant differentiation between genotypes for both observed traits. Positive (r = 0.41) correlation (p < 0.001) between seed germination and seed vigor was observed. As a result of next-generation sequencing, the molecular markers SilicoDArT (53,031) and SNP (28,571) were obtained. Out of 81,602 identified SilicoDArT and SNP markers, 15,409 (1559 SilicoDArT and 13,850 SNP) were selected as a result of association mapping, which showed them to be significantly related to the analyzed traits. The 890 molecular markers were associated with seed vigor, and 1323 with seed germination. Fifty-six markers (47 SilicoDArT and nine SNP) were significant for both traits. Of these 56 markers, the 20 most significant were selected (five of these markers were significant at the level of 0.001 for seed vigor and at the level of 0.05 for seed germination, another five markers were significant at the level of 0.001 for seed germination and at the level of 0.05 for seed vigor, five markers significant at the level of 0.001 only for seed vigor and five significant at the level of 0.001 only for seed germination also selected). These markers were used for physical mapping to determine their location on the genetic map. Finally, it was found that six of these markers (five silicoDArT—2,435,784, 4,772,587, 4,776,334, 2,507,310, 25,981,291, and one SNP—2,386,217) are located inside genes, the action of which may affect both seed germination and seed vigor. These markers can be used to select genotypes with high vigor and good seed germination.

Cis-element amplified polymorphism (CEAP), a novel promoter- and gene-targeted molecular marker of plants

In this study, we selected eight cis-elements: AAAG, ACGTG, CCGA, ACTCAT, GGTCA, TATCC, TGAC and GATAA, which are closely related to plant growth and development, signal transduction and stress response. The CEAP primers were 18 nucleotides long and consisted of a central cis-element nucleotide core flanked by a filler sequence at the 5' end and di- or tri-nucleotides at the 3' end. A total of two hundred and twenty-four primers were developed, and the PCR procedure consisted of 5 cycles of low-temperature annealing and 35 subsequent cycles of annealing at 50°C. The PCR products are electrophoretically separated by 1.8-2.3% agarose. The polymorphism of the CEAP marker was amplified in eight mango (Mangifera indica L.) species. The results showed that the CEAP primers could amplify clear, repeatable bands in mango and combine at least four cis-elements from which a large number of bands were amplified and six highly polymorphic primers for each cis-element can reach an accurate clustering result. The results of CEAP marker assays compared with ISSR, CBDP and iPBS marker assays showed that CEAP marker was better than the other three markers in the number of fragment bands, H and I indexes. In addition, we also tested the CEAP markers in rice, tomato, potato, wax gourd, citrus and longan and the results showed that the CEAP marker assay could amplify clear polymorphic bands in different species. Our results indicate that the CEAP markers could be universally used in different species for genetic diversity analysis, relationship analysis, and marker-assisted selection for breeding.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-022-01212-5.

Unraveling the Genetic Basis of Key Agronomic Traits of Wrinkled Vining Pea (Pisum sativum L.) for Sustainable Production

Estimating the allelic variation and exploring the genetic basis of quantitatively inherited complex traits are the two foremost breeding scenarios for sustainable crop production. The current study utilized 188 wrinkled vining pea genotypes comprising historical varieties and breeding lines to evaluate the existing genetic diversity and to detect molecular markers associated with traits relevant to vining pea production, such as wrinkled vining pea yield (YTM100), plant height (PH), earliness (ERL), adult plant resistance to downy mildew (DM), pod length (PDL), numbers of pods per plant (PDP), number of peas per pod (PPD), and percent of small wrinkled vining peas (PSP). Marker-trait associations (MTAs) were conducted using 6902 quality single nucleotide polymorphism (SNP) markers generated from the diversity arrays technology sequencing (DArTseq) and Genotyping-by-sequencing (GBS) sequencing methods. The best linear unbiased prediction (BLUP) values were estimated from the two-decades-long (1999-2020) unbalanced phenotypic data sets recorded from two private breeding programs, the Findus and the Birds eye, now owned by Nomad Foods. Analysis of variance revealed a highly significant variation between genotypes and genotype-by-environment interactions for the ten traits. The genetic diversity and population structure analyses estimated an intermediate level of genetic variation with two optimal sub-groups within the current panel. A total of 48 significant (P < 0.0001) MTAs were identified for eight different traits, including five for wrinkled vining pea yield on chr2LG1, chr4LG4, chr7LG7, and scaffolds (two), and six for adult plant resistance to downy mildew on chr1LG6, chr3LG5 (two), chr6LG2, and chr7LG7 (two). We reported several novel MTAs for different crucial traits with agronomic importance in wrinkled vining pea production for the first time, and these candidate markers could be easily validated and integrated into the active breeding programs for marker-assisted selection.