Meta-QTLs and candidate genes mining for starch and climate resilience to improve bioethanol production in maize

Maize ( Zea mays L.) is a globally important crop used for food, feed, and biofuels production. High kernel starch content is a key breeding target for yield, bioethanol production and other industrial uses. However, drought and waterlogging stresses in maize severely limit maize production and starch content and quality. A critical gap exists in identifying common genomic regions relevant to high starch, drought and water logging stresses tolerance in maize. Present study addresses this gap by presenting a novel integration of starch and abiotic stress-related quantitative trait loci (QTLs) to identify stable genomic regions for them in maize. We performed a meta-QTL (MQTL) analysis, a method that enhances mapping resolution and identifies stable multi-trait loci to facilitate marker-assisted selection (MAS). This approach aims to enhance breeding efficiency for drought, waterlogging and starch content, thus improving bioethanol production under challenging environmental conditions. Integrating 254 QTLs from 21 studies, MQTL analysis identified 21 stable MQTLs for targeted traits with an average confidence interval (CI) of 6.2 cM, achieving a 73.4 % (3.76-fold) reduction from the initial QTL average CI of 23.3 cM. The phenotypic variance explained (PVE %) for the identified MQTLs ranged from 3.0 % (MQTLST2.1) to 30 % (MQTLST5.3), with an average of 9.2 %. Within the MQTL regions, 680 candidate genes were identified, which includes 414 for starch content, 164 for waterlogging, and 102 drought tolerance. Four MQTL hotspots (overlapping MQTL regions) on chromosomes 1, 3, 4, and 5 harboured key genes associated together with stress tolerance and starch metabolism, making them promising targets for improving bioethanol production under adverse conditions. RNA-seq-based expression profiling using public datasets confirmed the tissue-specific expression of candidate genes. These findings will be useful for the development of maize hybrids with enhanced starch/ethanol yields and stress resilience through MAS, genomic selection, and genetic engineering. • Meta-analysis identified 21 stable MQTLs with high resolution for abiotic stress tolerance and starch content. • In meta-QTL analysis, CI decreased by 73 % over the initial QTLs. • 15 vital CGs identified enhance stress tolerance and bioethanol production. • Identified MQTL hotspots harbour CGs key to starch/ethanol production and stress resilience.