Crop production globally, faces major challenges due to increasing global population and changing climates. The production and productivity are challenged by several biotic and abiotic stresses. There is also a pressing demand to enhance grain yield and quality/nutrition to ensure global food and nutritional security. QTL studies have also enriched our knowledge of the inheritance mechanism of complex quantitative traits. However, the usage and stability of these QTLs in breeding programs are severely constrained by the fact that QTL results are highly influenced by the type of mapping population, density of molecular markers, environment and statistical models used. Identifying reliable and stable QTLs that have a significant impact on the desired trait is thus crucial. To address these multifaceted concerns, researchers have conducted numerous meta-QTL (MQTL) studies, resulting in the identification of candidate genes that govern these complex quantitative traits.

MQTL analysis is a relatively recent concept that helps in the identification of robust and consistent QTLs/MQTL regions often linked to trait variations across different mapping studies and narrows down their CI, hence facilitate the identification of candidate genes for MAS. The free software BioMercator, used for MQTL analysis, allows the compilation of a vast number of genetic maps from various sources and can project QTL to a consensus or reference map. Thus, MQTL analysis could identify the consensus QTL associated with the trait in multiple environments and genetic backgrounds3.

A genome-wide meta-QTL analysis on 768 QTLs from 35 rice populations published from 2001 to 2022 was conducted to identify consensus regions and the candidate genes underlying those regions responsible for the salinity tolerance, a total of 65 MQTLs were extracted with an average CI reduced from 17.35 to 1.66 cM including the smallest of 0.03 cM2. Similarly, 393 leaf rust resistance QTL were collected from 50 QTL mapping studies and meta-QTL (MQTL) analysis was performed. A total of 75MQTLs were discovered and refined to 15 high confidence MQTL (hcmQTL) and also candidate genes discovered within the hcmQTL interval1.

Meta-QTL analysis is an effective approach to synthesize QTL information, reduced the confidence intervals and allowed the identification of candidate genes. The primary use of MQTL for breeding purposes is the development of improved cultivars with enhanced yield that are resistant to diseases via MAS. MQTL analysis will remain a critical tool in the toolbox of modern agriculture, contributing to crop improvement and food production in an ever-evolving world.

References: 1AMO, A. AND SORIANO, J.M., 2022, Unravelling consensus genomic regions conferring leaf rust resistance in wheat via meta‐QTL analysis. Plant Genome, 15(1): 20185. 2SATASIYA, P., PATEL, S., PATEL, R., RAIGAR, O.P., MODHA, K., PAREKH, V., JOSHI, H., PATEL, V., CHAUDHARY, A., SHARMA, D. AND PRAJAPATI, M., 2024, Meta-analysis of identified genomic regions and candidate genes underlying salinity tolerance in rice (Oryza sativa L.). Sci. Rep., 14(1): 5730. 3SHARMA, D., KUMARI, A., SHARMA, P., SINGH, A., SHARMA, A., MIR, Z.A., KUMAR, U., JAN, S., PARTHIBAN, M., MIR, R.R. AND BHATI, P., 2023, Meta-QTL analysis in wheat: progress, challenges and opportunities. Theor. Appl. Genet., 136(12): 247.