Abstract
Today, agricultural productivity is essential to meet the needs of a growing population, and is also a key tool in coping with climate change. Innovative plant breeding technologies such as molecular markers, phenotyping, genotyping, the CRISPR/Cas method and next-generation sequencing can help agriculture meet the challenges of the 21st century more effectively. Therefore, the aim of the research was to identify single-nucleotide polymorphisms (SNPs) and SilicoDArT markers related to select morphological features determining the yield in maize. The plant material consisted of ninety-four inbred lines of maize of various origins. These lines were phenotyped under field conditions. A total of 14 morphological features was analyzed. The DArTseq method was chosen for genotyping because this technique reduces the complexity of the genome by restriction enzyme digestion. Subsequently, short fragment sequencing was used. The choice of a combination of restrictases allowed the isolation of highly informative low copy fragments of the genome. Thanks to this method, 90% of the obtained DArTseq markers are complementary to the unique sequences of the genome. All the observed features were normally distributed. Analysis of variance indicated that the main effect of lines was statistically significant (p < 0.001) for all 14 traits of study. Thanks to the DArTseq analysis with the use of next-generation sequencing (NGS) in the studied plant material, it was possible to identify 49,911 polymorphisms, of which 33,452 are SilicoDArT markers and the remaining 16,459 are SNP markers. Among those mentioned, two markers associated with four analyzed traits deserved special attention: SNP (4578734) and SilicoDArT (4778900). SNP marker 4578734 was associated with the following features: anthocyanin coloration of cob glumes, number of days from sowing to anthesis, number of days from sowing to silk emergence and anthocyanin coloration of internodes. SilicoDArT marker 4778900 was associated with the following features: number of days from sowing to anthesis, number of days from sowing to silk emergence, tassel: angle between the axis and lateral branches and plant height. Sequences with a length of 71 bp were used for physical mapping. The BLAST and EnsemblPlants databases were searched against the maize genome to identify the positions of both markers. Marker 4578734 was localized on chromosome 7, the closest gene was Zm00001d022467, approximately 55 Kb apart, encoding anthocyanidin 3-O-glucosyltransferase. Marker 4778900 was located on chromosome 7, at a distance of 45 Kb from the gene Zm00001d045261 encoding starch synthase I. The latter observation indicated that these flanking SilicoDArT and SNP markers were not in a state of linkage disequilibrium.
Highlights
A stronger emphasis on increased and more balanced nutritional production has been noticeable for a long time
Modern genotyping methods based on next-generation sequencing (NGS) include, among others, genotyping by sequencing (GBS) [30] and DArTseq technology [31,32,33]
The current study found that 11 markers were significantly associated with plant height (SilicoDArT and single-nucleotide polymorphisms (SNPs) jointly), and 19 markers were significantly associated with the height of the first cob
Summary
A stronger emphasis on increased and more balanced nutritional production has been noticeable for a long time. The currently used selection methods have been complemented with molecular biology findings and statistical models enabling both the identification of markers of individual traits, resulting from the action of individual genes, and those conditioned by many QTLs that explain the phenotypic variability of a trait to a varying degree [2,3]. The relationship between phenotypic and genetic variability can be analyzed using association mapping, called linkage disequilibrium [4,5,6]. As regards candidate gene association, the following hypothesis is tested: “Is there a correlation between a DNA polymorphism in a specific gene and a trait?” GWAS approach is justified in the absence of detailed biochemical knowledge related to the sought trait. GWAS searches for a genome-wide trait-marker association and assumes that there are markers exhibiting linkage disequilibrium in the genome conditioning trait expression [7]. Next-generation sequencing (NGS) is applied to identify SNP and SilicoDArT markers
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