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A genome-wide association and prediction study in grapevine deciphers the genetic architecture of multiple traits and identifies genes under many new QTLs.

ABSTRACT: To cope with the challenges facing agriculture, speeding-up breeding programs is a worthy endeavor, especially for perennial species such as grapevine, but requires understanding the genetic architecture of target traits. To go beyond the mapping of quantitative trait loci in bi-parental crosses, we exploited a diversity panel of 279 Vitis vinifera L. cultivars planted in 5 blocks in the vineyard. This panel was phenotyped over several years for 127 traits including yield components, organic acids, aroma precursors, polyphenols, and a water stress indicator. The panel was genotyped for 63k single nucleotide polymorphisms by combining an 18K microarray and genotyping-by-sequencing. The experimental design allowed to reliably assess the genotypic values for most traits. Marker densification via genotyping-by-sequencing markedly increased the proportion of genetic variance explained by single nucleotide polymorphisms, and 2 multi-single nucleotide polymorphism models identified quantitative trait loci not found by a single nucleotide polymorphism-by-single nucleotide polymorphism model. Overall, 489 reliable quantitative trait loci were detected for 41% more response variables than by a single nucleotide polymorphism-by-single nucleotide polymorphism model with microarray-only single nucleotide polymorphisms, many new ones compared with the results from bi-parental crosses. A prediction accuracy higher than 0.42 was obtained for 50% of the response variables. Our overall approach as well as quantitative trait locus and prediction results provide insights into the genetic architecture of target traits. New candidate genes and the application into breeding are discussed.

SUBMITTER: Flutre T

PROVIDER: S-EPMC9258538 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundIn grapevine, as in other fruit crops, fruit size and seed content are key components of yield and quality; however, very few Quantitative Trait Loci (QTLs) for berry weight and seed content (number, weight, and dry matter percentage) have been discovered so far. To identify new stable QTLs for marker-assisted selection and candidate gene identification, we performed simultaneous QTL detection in four mapping populations (seeded or seedless) with various genetic backgrounds.ResultsFor berry weight, we identified five new QTLs, on linkage groups (LGs) 1, 8, 11, 17 and 18, in addition to the known major QTL on LG 18. The QTL with the largest effect explained up to 31% of total variance and was found in two genetically distant populations on LG 17, where it colocalized with a published putative domestication locus. For seed traits, besides the major QTLs on LG 18 previously reported, we found four new QTLs explaining up to 51% of total variance, on LGs 4, 5, 12 and 14. The previously published QTL for seed number on LG 2 was found related in fact to sex. We found colocalizations between seed and berry weight QTLs only for the major QTL on LG 18 in a seedless background, and on LGs 1 and 13 in a seeded background. Candidate genes belonging to the cell number regulator CNR or cytochrome P450 families were found under the berry weight QTLs on LGs 1, 8, and 17. The involvement of these gene families in fruit weight was first described in tomato using a QTL-cloning approach. Several other interesting candidate genes related to cell wall modifications, water import, auxin and ethylene signalling, transcription control, or organ identity were also found under berry weight QTLs.ConclusionWe discovered a total of nine new QTLs for berry weight or seed traits in grapevine, thereby increasing more than twofold the number of reliable QTLs for these traits available for marker assisted selection or candidate gene studies. The lack of colocalization between berry and seed QTLs suggests that these traits may be partly dissociated.

Project description:A Genome-wide association (GWAS) study was conducted for phosphorous (P)-use responsive physiological traits in bread wheat at the seedling stage under contrasting P regimes. A panel of 158 diverse advanced breeding lines and released varieties, and a set of 10,800 filtered single nucleotide polymorphism (SNP) markers were used to study marker-trait associations over the eight shoot traits. Principle component analysis separated the two environments (P regimes) because of the differential response of the traits indicating the essentiality of the separate breeding programmes for each environment. Significant variations for genotypic, environmental, and genotype × environment (GEI) effects were observed for all the traits in the combined analysis of variance with moderately high broad sense heritability traits (0.50–0.73). With the different algorithms of association mapping viz., BLINK, FarmCPU, and MLM, 38 unique QTLs under non-limiting P (NLP) and 45 QTLs for limiting P (LP) conditions for various shoot traits were identified. Some of these QTLs were captured by all three algorithms. Interestingly, a Q.iari.dt.sdw.1 on chromosome 1D was found to explain the significant variations in three important physiological traits under non-limiting phosphorus (NLP) conditions. We identified the putative candidate genes for QTLs namely Q.iari.dt.chl.1, Q.iari.dt.sdw.16, Q.iari.dt.sdw.9 and Q.iari.dt.tpc.1 which are potentially involved in the mechanism regulating phosphorus use efficiency through improved P absorption due to improved root architectural traits and better mobilization such as sulfotransferase involved in postembryonic root development, WALLS ARE THIN1 (WAT1), a plant-specific protein that facilitates auxin export; lectin receptor-like kinase essentially involved in plant development, stress response during germination and lateral root development and F-box component of the SKP-Cullin-F box E3 ubiquitin ligase complex and strigolactone signal perception. Expression profiling of putative genes located in identified genomic regions against the wheat expression atlas revealed their significance based on the expression of these genes for stress response and growth development processes in wheat. Our results thus provide an important insight into understanding the genetic basis for improving PUE under phosphorus stress conditions and can shape the future breeding programme by developing and integrating molecular markers for these difficult-to-score important traits.

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A genome-wide association and prediction study in grapevine deciphers the genetic architecture of multiple traits and identifies genes under many new QTLs.

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