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Wykorzystanie technologii NGS, mapowania asocjacyjnego i fizycznego w celu identyfikacji genów kandydujących związanych z plonem kukurydzy
The Use of DArTseq Technology to Identify New SNP and SilicoDArT Markers Related to the Yield-Related Traits Components in Maize
In the last decade, many scientists have used molecular biology methods in their research to locate the grain-yield-determining loci and yield structure characteristics in maize. Large-scale molecular analyses in maize do not only focus on the identification of new markers and quantitative trait locus (QTL) regions. DNA analysis in the selection of parental components for heterotic crosses is a very important tool for breeders. The aim of this research was to identify and select new markers for maize (SNP and SilicoDArT) linked to genes influencing the size of the yield components in maize. The plant material used for the research was 186 inbred maize lines. The field experiment was established in twolocations. The yield and six yield components were analyzed. For identification of SNP and SilicoDArT markers related to the yield and yield components, next-generation sequencing was used. As a result of the biometric measurements analysis, differentiation in the average elevation of the analyzed traits for the lines in both locations was found. The above-mentioned results indicate the existence of genotype–environment interactions. The analysis of variance for the observed quality between genotypes indicated a statistically significant differentiation between genotypes and a statistically significant differentiation for all the observed properties betweenlocations. A canonical variable analysis was applied to present a multi-trait assessment of the similarity of the tested maize genotypes in a lower number of dimensions with the lowest possible loss of information. No grouping of lines due to the analyzed was observed. As a result of next-generation sequencing, the molecular markers SilicoDArT (53,031) and SNP (28,571) were obtained. The genetic distance between the analyzed lines was estimated on the basis of these markers. Out of 81,602 identified SilicoDArT and SNP markers, 15,409 (1559 SilicoDArT and 13,850 SNPs) significantly related to the analyzed yield components were selected as a result of association mapping. The greatest numbers of molecular markers were associated with cob length (1203), cob diameter (1759), core length (1201) and core diameter (2326). From 15,409 markers significantly related to the analyzed traits of the yield components, 18 DArT markers were selected, which were significant for the same four traits (cob length, cob diameter, core length, core diameter) in both Kobierzyce and Smolice. These markers were used for physical mapping. As a result of the analyses, it was found that 6 out of 18 (1818; 14,506; 2317; 3233; 11,657; 12,812) identified markers are located inside genes. These markers are located on chromosomes 8, 9, 7, 3, 5, and 1, respectively.
Evaluation of Drought Tolerance in Oat × Maize Addition Lines Through Biochemical and Yield Traits
Oat × maize addition lines (OMAs) are plants of oat (Avena sativa L.) obtained by wide crossing with maize (Zea mays L.) that retained one or more maize chromosomes in the oat genome, which can result in morphological and physiological changes. The aim of the study was to determine the relationship between phenolics, pigments, sugars, and yield components in 14 OMAs and oat cv. Bingo under soil drought. The plants were sown in pots in a vegetation tunnel. The pots were watered to the level of 70% field water capacity (FWC) and then drought treated to 20% FWC for 2 weeks. Analysis of variance (ANOVA) showed that genotype and treatment significantly influenced the measured parameters. Out of 14 OMAs, lines 9 and 78b showed the highest grain weight and number, with the least amount of biomass loss under drought. These OMAs were the only two to equal or surpass the oat cv. Bingo under drought and control conditions. On average, soil drought caused decrease in biomass and the number and mass of grains (30%, 44%, 46%, respectively). Soil drought increased the amount of sugars by 15% and phenolics by 9% but decreased pigment contents by 8%. According to Pearson’s correlation coefficients, fifteen pairs of traits were positively and statistically significantly correlated in control and drought conditions. Significant relationships were found between the yield components and biochemical parameters on the fourteenth day of drought. A positive correlation occurred between the number and weight of kernels and the content of soluble sugars, chlorophyll a, b, and the sum of a and b. A negative correlation was found between all analyzed yield components and the content of phenolics. The results suggest the possibility of using such biochemical parameters as a quick physiological indicator of plant tolerance to soil drought. Variation in studied OMA lines reveals substantial differences in drought response, offering promising opportunities for targeted selection and breeding strategies.
Transcriptomic Characterization of Genes Harboring Markers Linked to Maize Yield
Background: It is currently believed that breeding priorities, including maize breeding, should focus on introducing varieties with greater utility value, specifically higher yields, into production. Global modern maize breeding relies on various molecular genetics techniques. Using the above mentioned technologies, we can identify regions of the genome that are associated with various phenotypic traits, including yield, which is of fundamental importance for understanding and manipulating these regions. Objectives: The aim of the study was to analyze the expression of candidate genes associated with maize yield. To better understand the function of the analyzed genes in increasing maize yield, their expression in different organs and tissues was also assessed using publicly available transcriptome data. Methods: RT-qPCR analyses were performed using iTaq Universal SYBR Green Supermix (Bio-Rad, Hercules, CA, USA) and CFX96 Touch Real-Time PCR Detection System (Bio-Rad, Hercules, CA, USA). Each of the performed RT-qPCR experiments consisted of three biological replicates and three technical replicates, the results of which were averaged. Results: The research results allowed us to select three out of six candidate genes (cinnamoyl-CoA reductase 1—CCR1, aspartate aminotransferase—AAT and sucrose transporter 1—SUT1), which can significantly affect grain yield in maize. Not only our studies but also literature reports clearly indicate the participation of CCR1, AAT and SUT1 in the formation of yield. Identified molecular markers located within these genes can be used in breeding programs to select high yielding maize genotypes.
Assessment of genetic diversity in wheat (Triticum aestivum) genotype for cold tolerance, agronomic, and quality traits
Context Wheat (Triticum aestvium) contributes approximately 19% of daily caloric intake and 21% of protein in human diet, and is increasingly threatened by climate change-induced drought, erratic rainfall patterns, disease outbreaks, pest infestations, and cold damage, compounded by disruptions from political conflicts. Exposure to low temperatures induces morphological and physiological changes in plants, with the severity of these alterations depending on the duration of exposure. Aims This study aimed to identify promising genotypes derived from the wheat genotype Kırik that exhibit superior yield, yield components, grain quality, and cold resistance traits. Methods We assessed 186 genotypes from Kırik wheat collections obtained from farmers in the eastern Anatolia region of Türkiye, along with eight standard varieties. These genotypes were cultivated at altitudes exceeding 1850 m during the 2019–2022 production seasons based on an augmented design. Key results Several genotypes showed outstanding agronomic and quality traits: genotype G-56 had superior grain yield and grain weight per spike; G-102 had the highest number of spikes per m2; G-140 had the greatest spike length; G-80 had high wet gluten content, hectolitre (hL) weight, and gluten index; and G-34 had the highest protein content. Conclusions Wheat genotype Kırik is a potential source of genetic material for wheat breeding under adverse environmental and political conditions. Implications The superior genotypes derived from the Kırik genotype exhibit notable agronomic and quality characteristics, suggesting their potential utility as parental lines in pre-breeding programmes aimed at developing high-performing, climate-resilient wheat varieties.
Using Genome-Wide Association Studies to Reveal DArTseq and SNP Loci Associated with Agronomic Traits and Yield in Maize
Next-generation sequencing (NGS) has revolutionized genetic research, enabling the massive, rapid, and relatively inexpensive analysis of the genomes, transcriptomes, and epigenomes of various organisms, including maize. Therefore, this paper uses NGS, association mapping, and physical mapping to identify candidate genes associated with yield structure traits and yield in maize (Zea mays L.). Furthermore, expression analysis of selected candidate genes was performed to confirm their contribution to yield formation. The plant material used for the study was 186 F1 hybrids and 20 reference genotypes (high-yielding and low-yielding). Field experiments were conducted simultaneously in two locations (in Smolice and Kobierzyce). NGS yielded a total of 45,876 molecular markers (24,437 SilicoDArT markers and 21,439 SNP markers) relevant to yield and crop structure. The largest number of markers in both localities (Smolice and Kobierzyce) was related to: the number of grain rows (6960), dry matter content after harvest (6616), the number of grains in a row (6721), mass of grain from the cob (6616), and cob length (6564). The smallest number of markers in both localities was related to yield (t ha−1) (1114) and yield from the plot (1237). To narrow down the number of markers for physical mapping, ten were selected from all the significant ones associated with the same traits in both localities (Kobierzyce and Smolice). Significant markers included eight silicoDArT markers (459199, 2447305, 4768759, 4579916, 4764335, 2448946, 2492509, 4774802) and two SNP markers (9692004, 5587791). These markers were used for physical mapping. These markers are located on chromosomes 7, 8, and 10. Some of these markers are located at a considerable distance from characterized genes or within uncharacterized genes. Two markers caught our attention: SNP 5587791 and silicoDArT 4774802. The first one is located on chromosome 8 inside exon 5 of the LOC100383455 U-box domain-containing protein 7 gene, the second marker is also located on chromosome 8 near (300 bp) the LOC103635953 putative WUSCHEL-related homeobox 2 protein gene. Our own research and literature reports indicate the usefulness of next-generation sequencing, association mapping, and physical mapping for identifying candidate genes associated with economically important traits in maize. Furthermore, two genes characterized in detail in the publication, LOC100383455 U-box domain-containing protein 7 gene and LOC103635953 putative WUSCHEL-related homeobox 2 protein gene, may be involved in processes related to maize yield.
Identification and Analysis of Candidate Genes Associated with Yield Structure Traits and Maize Yield Using Next-Generation Sequencing Technology
The main challenge of agriculture in the 21st century is the continuous increase in food production. In addition to ensuring food security, the goal of modern agriculture is the continued development and production of plant-derived biomaterials. Conventional plant breeding methods do not allow breeders to achieve satisfactory results in obtaining new varieties in a short time. Currently, advanced molecular biology tools play a significant role worldwide, markedly contributing to biological progress. The aim of this study was to identify new markers linked to candidate genes determining grain yield. Next-generation sequencing, gene association, and physical mapping were used to identify markers. An additional goal was to also optimize diagnostic procedures to identify molecular markers on reference materials. As a result of the conducted research, 19 SNP markers significantly associated with yield structure traits in maize were identified. Five of these markers (28629, 28625, 28640, 28649, and 29294) are located within genes that can be considered candidate genes associated with yield traits. For two markers (28639 and 29294), different amplification products were obtained on the electrophorograms. For marker 28629, a specific product of 189 bp was observed for genotypes 1, 4, and 10. For marker 29294, a specific product of 189 bp was observed for genotypes 1 and 10. Both markers can be used for the preliminary selection of well-yielding genotypes.