Molecular Plant Breeding 2024, Vol.15, No.5, 220-232 http://genbreedpublisher.com/index.php/mpb 226 conditions. This research highlighted the potential of specific QPM lines with desirable general combining ability (GCA) effects for grain yield, which can be utilized in breeding programs to enhance maize yield (Njeri et al., 2017). Furthermore, a fine mapping study of quantitative trait loci (QTL) for plant and ear height in a maize nested-association mapping population identified 105 SNPs and 22 QTL significantly associated with these traits. The study found that variations in the promoter region of a candidate gene, Zm00001d031938, could decrease plant and ear height, which are closely related to lodging resistance and planting density, ultimately affecting yield (Yin et al., 2022). Another GWAS on tropical maize germplasm under terminal drought and combined heat and drought conditions identified several SNPs associated with grain yield and related traits. This study provided valuable insights into the genetic architecture of yield-related traits under stress conditions, which is essential for breeding climate-smart maize varieties (Osuman et al., 2022). 5.3 Impact on disease resistance traits Nucleotide polymorphisms are crucial for improving disease resistance in maize. A meta-analysis and co-expression analysis identified stable QTL and candidate genes conferring resistance to Fusarium and Gibberella ear rots, two devastating diseases that reduce maize yield and grain quality. The study identified 40 meta-QTL, with 29 associated with multiple disease-related traits, and 59 candidate genes responsive to these diseases. These findings provide a foundation for genomics-assisted breeding strategies to enhance disease resistance in maize (Table 1) (Akohoue et al., 2022). Table 1 Selected meta-QTL (MQTL) and corresponding candidate genes (CG) (Adopted from Akohoue et al., 2022) MQTLa Number ofQTL Disease and trait Number of populations PVE (%) CI 95% (cM) Physical distance (Mbp) Number of CG FER GER ZmMQTL1.2 5 KR KR, SR 4 10.60 4.72 3.04 10 ZmMQTL1.4 5 KR HC, KR, SR 5 14.00 5.85 7.00 146 ZmMQTL1.5 2 KR - 2 11.50 14.80 15.55 331 ZmMQTL1.7 2 KR DON 2 11.00 8.00 7.28 226 ZmMQTL2.1 4 SR DON, SR 3 11.75 3.02 0.63 30 ZmMQTL2.2 2 - KR, SR 2 13.00 9.74 7.28 201 ZmMQTL2.3 7 KR KR, SR 5 10.00 2.65 6.18 68 ZmMQTL3.3 3 KR,SR SR 2 10.00 3.75 3.98 77 ZmMQTL4.3 2 KR SR 2 17.00 11.51 14.50 342 ZmMQTL4.4 5 KR KR 2 13.40 8.89 6.75 155 ZmMQTL7.1 5 KR SR 2 15.20 7.75 9.85 143 ZmMQTL7.3 3 FUM SR 2 29.67 3.89 0.75 37 ZmMQTL9.2 5 KR SR 3 10.40 8.00 15.08 304 ZmMQTL9.4 2 FUM DON 2 13.50 11.71 5.94 202 Note: CL, confdeanceinteral; FER, Fusarium earot; GER, Giberel earot SR, silkresistance; KR: kerne resistance; DON: deoynivalenol acumulation; FUM: fumonisinacunulation; KD: kernel dry-down rate; HC, husk coverage; PVE, phenotypic variance explained; Meta-QTL name refered to Zea mays abbreviatedas Zm, followed by MQTL, the corresponding chromosome, and identfication number on the chromosome (Adopted from Akohoue et al., 2022) Additionally, a study on the role of a dual-subcellular localized β-glucosidase gene, ZmBGLU17, demonstrated its importance in conferring resistance to both pathogens and insect pests without a yield penalty. The research showed that structural variations and a SNP in the ZmBGLU17 gene affect its expression and function, leading to enhanced resistance against the oomycete pathogen Pythium aphanidermatum and the Asian corn borer. This gene’s overexpression lines exhibited normal growth and yield, highlighting the potential of nucleotide polymorphisms in improving disease resistance without compromising yield (Liu et al., 2023).
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