Work

Consensus genomic regions and key genes for biotic, abiotic and key nutritional traits identified using meta- QTL analysis in peanut

Year: 2025

Type: article

Study designs: Systematic Review, Meta-Analysis

Abstract: . Despite many large-effect QTLs identified for yield and key traits, their use in breeding is limited by unfavorable genetic interactions. To overcome this, we aimed to identify consensus genomic regions and candidate genes linked to key traits by analyzing QTL data from 30 independent studies conducted over the past 12 years, focusing on biotic, abiotic, aflatoxin, morphological, nutritional, phenological, and yield-associated traits. Using genetic map information, we constructed consensus maps and performed a meta-analysis on 891 QTLs, leading to the identification of 70 Meta-QTLs (MQTLs) with confidence intervals ranging from 0.07 to 9.63 cM and an average of 2.33 cM. This reduction in confidence intervals enhances the precision of trait mapping, making the identified MQTLs more applicable for breeding purposes. Furthermore, we identified key genes associated with aflatoxin resistance in MQTL5.2 (serine/threonine-protein kinase, BOI-related E3 ubiquitin-protein ligase), MQTL5.3, MQTL7.3, and MQTL13.1. Similarly, for yield-related traits in MQTL3.1-MQTL3.4 (mitogen-activated protein kinase, auxin response factor), MQTL11.2 (MADS-box protein, squamosa promoter-binding protein), and MQTL14.1. Genes related to oil composition within MQTL5.2 (fatty-acid desaturase FAD2, linoleate 9S-lipoxygenase), MQTL9.3, MQTL19.1 (acyl-CoA-binding protein, fatty acyl-CoA reductase FAR1), MQTL19.4, and MQTL19.5. Nutritional traits like iron and zinc content are linked to MQTL1.1 (probable methyltransferase, ferredoxin C), MQTL10.1, and MQTL12.1. These regions and genes serve as precise targets for marker-assisted breeding to enhance peanut yield, resilience, and quality.

Source: Frontiers in Plant Science

DOI: 10.3389/fpls.2025.1539641