Biology subjects

Santamarina, C.

Publications and source records attributed to Santamarina, C..

4 recordsLinked to original sources

bioRxiv2026

Multi-omic analysis reveals the genetic architecture of water-deficit stress in Phaseolus vulgaris

Common bean (Phaseolus vulgaris L.) is one of the most important grain legumes for direct human consumption. Currently, 60% of its production is estimated to be at risk due to drought. However, the genetic basis of common beans drought resistance is poorly understood. To this end, we assessed the genetic architecture of drought-responsive changes in a whole genome-sequenced population of 218 common bean accessions. Using multi-omics-based trait evaluation, including lipidomics, photosynthetic and agronomic traits, followed by multi-omics genome-wide association studies (moGWAS), yielded in the detection of a myriad of moQTL for photosynthesis and yield, as well as the levels of various lipids. QTL associated with glycolipids, which are integral to photosynthesis, since they constitute the major membrane components of chloroplasts, were identified. In addition, we molecularly validated several lipid-related candidate genes via P. vulgaris hairy root transformation as well as transient expression in tobacco. In particular, a lipoxygenase and an allene oxide synthase were identified as explaining the variation in triacylglycerol by oxylipin production. These data provide a blueprint for multi-omics-assisted improvement of crop water stress resilience.

plant biology↗

bioRxiv2025

Genotype by Environment Interaction influenced the content of crude protein and total amino acids in lentil varieties

Lentil (Lens culinaris Medik) is a globally important grain legume valued for its high protein content and nutritional quality. However, the genetic and environmental factors influencing protein and amino acid composition, particularly the role of genotype x environment interaction (GEI), remain partially uncovered. This study evaluated 15 diverse lentil genotypes across seven agronomic trials spanning multiple years, sowing seasons, and locations to assess the effects of genotype, environment, and GEI on crude protein (CP), crude protein yield (CPY), total amino acids (TAA), and total amino acid yield (TAAY). Advanced statistical models such as AMMI, GGE, and WAASB were employed to dissect the contributions of genetic and environmental components and to identify stable, high-performing genotypes. Results revealed significant phenotypic variation for CP, Amino Acids (AA), and TAA among genotypes. Seasonal variation, especially between autumn and spring sowings, was the primary environmental driver of GEI for both CP and CPY. Notably, some landraces (PI_431710_LSP, PI_431739_LSP, PI_431753_LSP, IG_1959) demonstrated both high productivity and stability across environments, while others excelled in specific mega-environments identified through GGE analysis. Our findings emphasize the importance of integrating into lentil breeding programs, stability and adaptability, and a more comprehensive approach to measure the yield (e.g., CPY, MegaJoule, ammino acid composition and TAAY), which takes into account the quality and the effective energetic production of a crop. From this perspective, we highlight landraces as valuable sources of genetic diversity for improving yield. This work provides a foundation for targeted breeding strategies aimed at developing lentil varieties with enhanced protein content, balanced amino acid profiles, and resilience to environmental variability

genetics↗

bioRxiv2025

Newly-identified lentil genotypes adapted to Mediterraneanagro-ecosystems

Lentil cultivation and consumption promote human health and sustainable agriculture, making a significant contribution to the transition toward a plant-based diet. In Europe, lentil yields are still unstable, and the lack of breeding efforts limits the choice of farmers to few varieties. Here, we characterized 46 lentil genotypes, including local cultivars and landraces from diverse geographic origins, in Mediterranean agro-environments for flowering, architectural and production traits in seven field trials, over 3 years (2019-2021), in two localities (central and southern Italy) and during two sowing seasons (autumn and spring). We estimated the genetic merit of each genotype and identified outperforming genotypes for all traits. Indian ILL 11557AGL and Argentinian IL 4605AGL domesticated varieties resulted superior for earliness. Italian landraces and French cultivars achieved the highest values for first pod height, while landraces and breeding materials from Ethiopia, Syria and Iran were the best-yielding. Data from all seven trials were available for 16 genotypes, so we analyzed the genotype, environment and genotype x environment interaction (GEI) to identify specific genotypic adaptations. European cultivars performed well for architectural traits, whereas the best-yielding genotypes were Middle Eastern and Ethiopian landraces. Environmental effect on yield related to sowing season and locality was detected, with an overall higher yield in autumn compared to spring sowing trials and in central rather than southern Italy. By dissecting the GEI structure using additive main effect and multiplicative interaction (AMMI) analysis and Weighted Average of Absolute Scores (WAASB) index, we identified a group of Iranian landraces (PI 431633 AGL and PI 432033 LSP AGL) adapted to both autumn and spring sowing and one Ethiopian landrace (IG 1959 AGL) showing high yield stability across all environmental conditions. These findings provide a foundation to unlock the full potential of lentil cultivation in European and Mediterranean systems by identifying adapted, high-performing genotypes.

genetics↗

bioRxiv2025

Metabolite-based genome-wide association studies enable the dissection of the genetic bases of bioactive compounds in Chickpea seeds

Chickpea, is the second most consumed food legume, and significantly contributes to the human diet. Chickpea seeds are rich in a wide range of metabolites including bioactive specialized metabolites influencing nutritional qualities and human health. However, the genetic basis underlying the metabolite-based nutrient quality in chickpea remains poorly understood. Here we dissected the genetic architecture of seed metabolic diversity and explored how domestication shaped the chickpea metabolome. Through UPLC-MS we quantify over 3400 metabolic features in 509 chickpea seeds accessions from three independent multi-location field trials. The metabolite genome-wide association study (mGWAS) detected around 130,000 leading SNPs corresponding to 1890 metabolites across different environments. We further found and functionally validated a gene cluster of three CabHLH transcription factors that regulate soyasaponin biosynthesis in chickpea seeds. Our results reveal new insights on the effects of domestication process on chickpea metabolome. and provide valuable resources for the genetic improvement of the bioactive compounds in chickpea seeds.

plant biology↗