» Articles » PMID: 33903955

Genetic Dissection of Flowering Time in Flax (Linum Usitatissimum L.) Through Single- and Multi-locus Genome-wide Association Studies

Overview
Specialty Genetics
Date 2021 Apr 27
PMID 33903955
Citations 11
Authors
Affiliations
Soon will be listed here.
Abstract

In a rapidly changing climate, flowering time (FL) adaptation is important to maximize seed yield in flax (Linum usitatissimum L.). However, our understanding of the genetic mechanism underlying FL in this multipurpose crop remains limited. With the aim of dissecting the genetic architecture of FL in flax, a genome-wide association study (GWAS) was performed on 200 accessions of the flax core collection evaluated in four environments. Two single-locus and six multi-locus models were applied using 70,935 curated single nucleotide polymorphism (SNP) markers. A total of 40 quantitative trait nucleotides (QTNs) associated with 27 quantitative trait loci (QTL) were identified in at least two environments. The number of QTL with positive-effect alleles in accessions was significantly correlated with FL (r = 0.77 to 0.82), indicating principally additive gene actions. Nine QTL were significant in at least three of the four environments accounting for 3.06-14.71% of FL variation. These stable QTL spanned regions that harbored 27 Arabidopsis thaliana and Oryza sativa FL-related orthologous genes including FLOWERING LOCUS T (Lus10013532), FLOWERING LOCUS D (Lus10028817), transcriptional regulator SUPERMAN (Lus10021215), and gibberellin 2-beta-dioxygenase 2 (Lus10037816). In silico gene expression analysis of the 27 FL candidate gene orthologous suggested that they might play roles in the transition from vegetative to reproductive phase, flower development and fertilization. Our results provide new insights into the QTL architecture of flowering time in flax, identify potential candidate genes for further studies, and demonstrate the effectiveness of combining different GWAS models for the genetic dissection of complex traits.

Citing Articles

History and prospects of flax genetic markers.

Zhernova D, Pushkova E, Rozhmina T, Borkhert E, Arkhipov A, Sigova E Front Plant Sci. 2025; 15:1495069.

PMID: 39881731 PMC: 11774856. DOI: 10.3389/fpls.2024.1495069.


Identification of novel candidate genes for Ascochyta blight resistance in chickpea.

Dariva F, Arman A, Morales M, Navasca H, Shah R, Atanda S Sci Rep. 2024; 14(1):31415.

PMID: 39733039 PMC: 11682179. DOI: 10.1038/s41598-024-83007-0.


The Genetic Dissection of Nitrogen Use-Related Traits in Flax ( L.) at the Seedling Stage through the Integration of Multi-Locus GWAS, RNA-seq and Genomic Selection.

Soto-Cerda B, Larama G, Cloutier S, Fofana B, Inostroza-Blancheteau C, Aravena G Int J Mol Sci. 2023; 24(24).

PMID: 38139451 PMC: 10743809. DOI: 10.3390/ijms242417624.


Genome-wide association study reveals loci and candidate genes of flowering time in jute ( L.).

Yao J, Jiang S, Li H, Li Q, Qiu Z, Tao A Mol Breed. 2023; 43(12):85.

PMID: 38009098 PMC: 10667207. DOI: 10.1007/s11032-023-01435-8.


Genome-wide association studies using multi-models and multi-SNP datasets provide new insights into pasmo resistance in flax.

He L, Sui Y, Che Y, Wang H, Rashid K, Cloutier S Front Plant Sci. 2023; 14:1229457.

PMID: 37954993 PMC: 10634603. DOI: 10.3389/fpls.2023.1229457.


References
1.
Ambreen H, Kumar S, Kumar A, Agarwal M, Jagannath A, Goel S . Association Mapping for Important Agronomic Traits in Safflower ( L.) Core Collection Using Microsatellite Markers. Front Plant Sci. 2018; 9:402. PMC: 5885069. DOI: 10.3389/fpls.2018.00402. View

2.
Andres F, Coupland G . The genetic basis of flowering responses to seasonal cues. Nat Rev Genet. 2012; 13(9):627-39. DOI: 10.1038/nrg3291. View

3.
Bonnafous F, Fievet G, Blanchet N, Boniface M, Carrere S, Gouzy J . Comparison of GWAS models to identify non-additive genetic control of flowering time in sunflower hybrids. Theor Appl Genet. 2017; 131(2):319-332. PMC: 5787229. DOI: 10.1007/s00122-017-3003-4. View

4.
Bradbury P, Zhang Z, Kroon D, Casstevens T, Ramdoss Y, Buckler E . TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics. 2007; 23(19):2633-5. DOI: 10.1093/bioinformatics/btm308. View

5.
Craufurd P, Wheeler T . Climate change and the flowering time of annual crops. J Exp Bot. 2009; 60(9):2529-39. DOI: 10.1093/jxb/erp196. View