Using Genome-Wide Association Studies to Reveal DArTseq and SNP Loci Associated with Agronomic Traits and Yield in Maize

cris.virtual.author-orcid0000-0001-9516-8911
cris.virtual.author-orcid0000-0002-0102-0084
cris.virtual.author-orcid0000-0001-8208-2801
cris.virtual.author-orcid0000-0002-2214-406X
cris.virtual.author-orcid0000-0003-2480-855X
cris.virtual.author-orcid0000-0001-9250-4393
cris.virtual.author-orcid0000-0002-1041-4341
cris.virtual.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtual.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtualsource.author-orcid2faa4bbb-a129-4bec-8137-bd8eeedf40e0
cris.virtualsource.author-orcid51a5a68b-106b-4e9d-bd9b-79d15d3ec0c1
cris.virtualsource.author-orcida9b12673-f948-47a8-868e-383feced1281
cris.virtualsource.author-orcidf05e8789-119d-453f-9d8c-5ae717b7917e
cris.virtualsource.author-orcid07a12041-d6ed-46a8-8dc3-df09345a7119
cris.virtualsource.author-orcidb449fb52-7ef2-4cac-9b3b-ec94daac3768
cris.virtualsource.author-orcid94714645-6b07-4d4d-bd16-1baacaa7ba63
cris.virtualsource.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtualsource.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
dc.abstract.enNext-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.
dc.affiliationWydział Rolnictwa, Ogrodnictwa i Biotechnologii
dc.affiliation.instituteKatedra Genetyki i Hodowli Roślin
dc.affiliation.instituteKatedra Metod Matematycznych i Statystycznych
dc.affiliation.instituteKatedra Fitopatologii i Nasiennictwa
dc.contributor.authorLenort, Maciej
dc.contributor.authorTomkowiak, Agnieszka
dc.contributor.authorBocianowski, Jan
dc.contributor.authorBobrowska, Roksana
dc.contributor.authorKurasiak-Popowska, Danuta
dc.contributor.authorMikołajczyk, Sylwia
dc.contributor.authorKosiada, Tomasz
dc.contributor.authorWeigt, Dorota
dc.contributor.authorGawrysiak, Przemysław
dc.date.access2025-12-29
dc.date.accessioned2025-12-29T06:41:05Z
dc.date.available2025-12-29T06:41:05Z
dc.date.copyright2025-11-30
dc.date.issued2025
dc.description.abstract<jats:p>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.</jats:p>
dc.description.accesstimeat_publication
dc.description.bibliographyil., bibliogr.
dc.description.financepublication_research
dc.description.financecost12000,00
dc.description.if3,0
dc.description.number12
dc.description.points70
dc.description.versionfinal_published
dc.description.volume47
dc.identifier.doi10.3390/cimb47121008
dc.identifier.eissn1467-3045
dc.identifier.issn1467-3037
dc.identifier.urihttps://sciencerep.up.poznan.pl/handle/item/6519
dc.identifier.weblinkhttps://www.mdpi.com/1467-3045/47/12/1008
dc.languageen
dc.relation.ispartofCurrent Issues in Molecular Biology
dc.relation.pagesart. 1008
dc.rightsCC-BY
dc.sciencecloudsend
dc.share.typeOPEN_JOURNAL
dc.subject.enZea mays
dc.subject.enyield
dc.subject.enassociation mapping
dc.subject.ennext-generation sequencing (NGS)
dc.subject.encandidate genes
dc.titleUsing Genome-Wide Association Studies to Reveal DArTseq and SNP Loci Associated with Agronomic Traits and Yield in Maize
dc.title.volumeSpecial Issue Featured Papers in Bioinformatics and Systems Biology
dc.typeJournalArticle
dspace.entity.typePublication
oaire.citation.issue12
oaire.citation.volume47