Integrated Meta-QTL analysis and transcriptomic profiling reveal genomic regions for fruit quality, abiotic and biotic stress resilience in cucumber (Cucumis sativus L.).
This study conducted a comprehensive Meta-QTL analysis by integrating 647 initial QTLs from 40 independent studies published between 2003 and 2024, identifying 38 robust mQTLs associated with fruit quality, biotic and abiotic stress tolerance and key drivers of fruit quality.
Abstract
Cucumber is a globally significant vegetable crop whose production and market value are affected by fruit quality and resilience to diverse environmental stressors. Despite the identification of numerous Quantitative Trait Loci (QTL) over the last two decades, their direct application in breeding has been hindered by inconsistent genomic positions and broad confidence intervals. In this study, we conducted a comprehensive Meta-QTL (mQTL) analysis by integrating 647 initial QTLs from 40 independent studies published between 2003 and 2024. Using a high-density consensus map containing 9,299 markers, we projected 531 QTLs, identifying 38 robust mQTLs associated with fruit quality, biotic and abiotic stress tolerance. The identified mQTLs exhibited a significant reduction in the average confidence interval (CI) by 5.3-fold, compared to the average CI of the original QTLs and phenotypic variance explained values reaching up to 49.81% (mQTL 6.8). Our results identifying specific genomic hotspots on chromosomes 1, 3, 5, and 6 that harbor high-confidence candidate genes responsible for stress tolerance and fruit quality. Comparative analysis with seven independent genome-wide association studies validated 16 mQTL regions, confirming their stability across diverse genetic backgrounds. Biotic stress resilience was linked to immune regulators such as LRK10L2 and MLO-like protein 12, while abiotic stress tolerance was anchored by genes like NCED5 (cold), ClpB1 (heat), and MYB44-like (waterlogging). Furthermore, we identified key drivers of fruit quality, including Expansin-A4 and CNR2 for dimensions, CsWOX9 for epidermal spine initiation, and Hd3a for flowering phenology. Transcriptomic profiling provided robust expression support for these prioritized candidate genes within the target mQTL intervals. The markers linked to these genes serve as robust tools for marker-assisted selection and fine mapping, offering precise targets for the development of climate-resilient, high-quality cucumber cultivars.
Water deficit is a major constraint on pepper (Capsicum annuum) yield, yet the genetic architecture of reproductive-stage drought tolerance remains poorly resolved. We phenotyped a Balkan C. annuum diversity panel (n = 133) and an interspecific backcross inbred line (BIL) population (n = 76) under well-watered (WW) and water-stress (WS) conditions. WS was applied from anthesis of the second truss as a stepwise reduction in irrigation volume relative to WW (30% for 7 days, then 60% thereafter), maintained for 90 days across the reproductive period. We assessed yield components, soluble solids, and stress-tolerance (STI) and stress-susceptibility (SSI) indices. Genome-wide association study (GWAS) identified 104 SNP-trait associations (P < 1×10-5), and QTL mapping detected 38 significant QTLs (1,000 permutations, α = 0.01), with the QTL intervals defined at LOD ≥ 8. Integrating GWAS and QTL mapping under WS revealed overlapping loci on chromosomes 5 and 6, harboring two consensus intergenic SNPs associated with yield components and soluble solids. Haplotype analysis linked chromosome 5 alleles to higher fruit number and soluble solids. At chromosome 6, the G allele at SNP 6_28348737 was enriched in tolerant lines for fruit number. These regions harbor candidate genes for reproductive development and stress response, including GREEN RIPE-LIKE1 (GRL1), CYP77A19, Endoglucanase-like, and FLOWERING PROMOTING FACTOR 1 (FPF1), possibly through cis-regulatory variation. Together, these results advance understanding of the genetic basis of pepper yield under drought and identify candidate breeding markers.
Avanish Rai, Emil Vatov, Alicja Wieteska Georgieva et al.· Journal of Experimental Bota...· 0 citations
The cultivated strawberry (
Fragaria
×
ananassa
Duch.) is an economically important fruit crop. Improvement of fruit quality is a major breeding objective. Although numerous quantitative trait loci (QTLs) have been identified for fruit‐related traits, less information is available on quality attributes such as fruit mass, total soluble solids (TSS) and susceptibility to water soaking (WS). The objective of our study is to identify and validate genetic regions associated with fruit mass, TSS and WS susceptibility using a model population derived from an interspecific cross between
F
. ×
ananassa
and
Fragaria chiloensis
. Phenotyping was conducted in three seasons, and QTL analysis was performed using an already existing linkage map consisting of 2990 SNP markers. The introgression of the wild‐type
F. chiloensis
resulted in a decrease in fruit mass and an increase in fruit TSS. Annual broad‐sense heritabilities
H
2
indicated that the expression of all three traits is affected by genetic but also by environmental factors (
H
2
ranging from 0.27 to 0.68). Multiple QTLs for each trait were identified, with significant QTLs explaining up to 27% of the phenotypic variation. For TSS content, QTLs on linkage group 1C, 3A and 4A; and for WS susceptibility, QTLs on linkage group 1B, 1C, 4A and 6D were stable in at least two seasons. None of the QTLs was stable for fruit mass. This study confirmed the polygenic and complex nature of fruit mass, TSS and WS susceptibility. Some regions involved in these traits could be validated in our study, thus providing useful insights for breeding of cultivars with improved fruit mass, TSS content and tolerance against WS.
Diana Seidler, Grecia Hurtado, Moritz Knoche et al.· Plant Breeding· 0 citations
Seed oil content (SOC) is a key determinant of oil yield in rapeseed, but translating high-resolution QTL and functional gene information into effective breeding selection remains challenging. Here, we integrated high-quality genome assembly, QTL fine mapping, gene function validation, and QTL-informed genomic prediction to improve the SOC in rapeseed. The improved, chromosome-scale genome of the semi-winter cultivar NY7 served as a reliable reference for fine mapping via its bidirectional introgression populations. Seven major QTLs were rapidly fine-mapped into 117 kb ~ 358 kb intervals; each increased the SOC by 2% ~ 6%. Integrated transcriptomic and haplotype analyses revealed eight candidate genes, highlighting BnaDIR1.C2 as the hub gene underlying qOC.C2–1. Functional validation confirmed the positive regulation of BnaDIR1.C2 in SOC. Moreover, genomic prediction models incorporating QTL-weighted markers substantially improved the prediction performance by an average of 20.34% across different populations. This study bridges the gap between high-resolution genetic dissection and predictive breeding, providing a practical framework to accelerate oil yield improvement in rapeseed.
Hao Wang, Zunxu Zhang, Meng Wang et al.· Horticulture Research· 0 citations
Soil salinity is a major constraint limiting rice productivity, particularly at the reproductive stage. To elucidate the genetic basis of reproductive stage salinity tolerance, this study validated and fine-mapped quantitative trait loci (QTL) for yield-related traits using a salinity-tolerant line SL506, identified through screening of Nona Bokra–CSSLs in a Koshihikari background. In 2016, the F2 population derived from SL506/Koshihikari was evaluated under long-term salt stress; three QTLs associated with plant dry weight, panicle number, and grain weight were detected on chromosome 2. In 2023, validation analysis using F3 individuals confirmed the presence of these QTLs. Subsequent fine-mapping using F4 near-isogenic lines (NILs) delimited the QTL to a 1.7 Mb interval and high-resolution mapping using an F5 recombinant population progressively refined it to a 473 kb genomic region containing 69 annotated genes. Variant Effect Predictor analysis identified 15 deleterious nonsynonymous variants (SIFT < 0.05) in six candidate genes. Based on annotated gene functions, predicted variant effects, and their membership in stress-related gene families, OsPP2C24, OsFbox102, and OsWAK14 were suggested as the most promising candidate genes underlying qPDW2. These findings provide insights into the genetic basis of reproductive-stage salinity tolerance from valuable resources for the future improvement of salt tolerance and yield stability in rice.
Farjana Rauf, H. Trần, T. Nguyen et al.· Agronomy· 0 citations
Cowpea (Vigna unguiculata [L.] Walp.) is a resilient grain legume and an important global source of dietary protein, yet the genetic and environmental basis of phenological and canopy development, as well as grain composition, remains incompletely characterized across production environments. In this study, we evaluated a cowpea multi-parent advanced generation intercross (MAGIC) population along an environmental gradient in California (with contrasting daylengths, temperatures, and soil types) using agronomic, grain compositional, and uncrewed aerial vehicle (UAV) and rover-enabled phenotyping. Near-infrared spectroscopy (NIRS) enabled assessment of grain compositional traits, while sensing-enabled time-series imaging captured canopy and reproductive dynamics. Quantitative trait locus (QTL) mapping identified 267 QTL, and genome-wide association studies (GWAS) detected 1,973 marker-trait associations. Integrating QTL mapping and GWAS results identified two major genomic hotspots affecting multiple traits. A chromosome 9 hotspot (5.8–6.0 Mb) was associated with flowering time and co-localized with sensing-enabled measures of flower and pod counts, plant height, and vegetation fraction, indicating broad effects on phenological and canopy development. A chromosome 8 hotspot (37.3–37.9 Mb) contained co-localized signals for seed weight, protein, starch, phytate, and moisture. A total of 22 prioritized candidate genes were identified within these and other loci with multi-environment QTL and GWAS support. Genomic predictive abilities were moderate to high for most traits and scenarios, with multi-trait MegaLMM outperforming RR-BLUP. Together, these results define major genomic regions controlling cowpea phenology, canopy development, and grain composition, and provide targets and strategies for breeding cowpea cultivars with favorable and environmentally resilient productivity and grain composition. Significance Statement To dissect the genetic basis of cowpea productivity, adaptation, and grain composition, and how performance for these traits varies and can be predicted across environments, we combined multi-environment phenotyping, including sensing of canopy and reproductive traits, with quantitative genetic analyses in a multi-parental population. We identified genomic hotspots for seed size/composition and reproductive phenology and an across-environment predictive advantage for multi-trait vs. single-trait genomic prediction. Overall, these findings support the comprehensive improvement of cowpea.
Jonathan M. Berlingeri, Sassoum Lo, Margaret Riggs et al.· bioRxiv· 0 citations