Genomic regions associated with herbicide tolerance in a worldwide faba bean (Vicia faba L.) collection.

Databases, Genetic Genes, Plant Genome, Plant Genome-Wide Association Study Genotype Herbicide Resistance / genetics Herbicides / pharmacology Nicotinic Acids / pharmacology Phenotype Plant Proteins / genetics Polymorphism, Single Nucleotide Quantitative Trait Loci Triazines / pharmacology Vicia faba / drug effects

Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
07 01 2022
Historique:
received: 23 06 2021
accepted: 09 12 2021
entrez: 8 1 2022
pubmed: 9 1 2022
medline: 23 2 2022
Statut: epublish

Résumé

Weeds represent one of the major constraints for faba bean crop. The identification of molecular markers associated with key genes imparting tolerance to herbicides can facilitate and fasten the efficient and effective development of herbicide tolerant cultivars. We phenotyped 140 faba bean genotypes in three open field experiments at two locations in Lebanon and Morocco against three herbicide treatments (T1 metribuzin 250 g ai/ha; T2 imazethapyr 75 g ai/ha; T3 untreated) and one in greenhouse where T1 and T3 were applied. The same set was genotyped using genotyping by sequencing (GBS) which yield 10,794 high quality single nucleotide polymorphisms (SNPs). ADMIXTURE software was used to infer the population structure which revealed two ancestral subpopulations. To identify SNPs associated with phenological and yield related traits under herbicide treatments, Single-trait (ST) and Multi-trait (MT) Genome Wide Association Studies (GWAS) were fitted using GEMMA software, showing 10 and 14 highly significant associations, respectively. Genomic sequences containing herbicide tolerance associated SNPs were aligned against the NCBI database using BLASTX tool using default parameters to annotate candidate genes underlying the causal variants. SNPs from acidic endochitinase, LRR receptor-like serine/threonine-protein kinase RCH1, probable serine/threonine-protein kinase NAK, malate dehydrogenase, photosystem I core protein PsaA and MYB-related protein P-like were significantly associated with herbicide tolerance traits.

Identifiants

DOI: 10.1038/s41598-021-03861-0 PMID: 34996977 PMC: PMC8741826
pubmed: 34996977
doi: 10.1038/s41598-021-03861-0
pii: 10.1038/s41598-021-03861-0
pmc: PMC8741826
doi:

Substances chimiques

Herbicides 0
Nicotinic Acids 0
Plant Proteins 0
Triazines 0
imazethapyr 72T2IN94I4
metribuzin QO836138OV

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

158

Informations de copyright

© 2022. The Author(s).

Références

Cubero, J. I. On the evolution of Vicia faba L. Theor. Appl. Genet. 45, 47–51 (1974).
pubmed: 24419274 doi: 10.1007/BF00283475
Tanno, K. I. & Willcox, G. The origins of cultivation of Cicer arietinum L. and Vicia faba L.: early finds from Tell el-Kerkh, north-west Syria, late 10th millennium BP. Veg. Hist. Archaeobot. 15, 197–204 (2006).
doi: 10.1007/s00334-005-0027-5
Caracuta, V. et al. 14,000-year-old seeds indicate the Levantine origin of the lost progenitor of faba bean. Sci. Rep. 6, 1–6 (2016).
doi: 10.1038/srep37399
FAOSTAT. Food and Agriculture Organization of the United Nations. www.faostat.fao.org . Accessed 25 April 2021 (2020).
Crépon, K. et al. Nutritional value of faba bean (Vicia faba L.) seeds for feed and food. Field Crops Res. 115, 329–339 (2010).
doi: 10.1016/j.fcr.2009.09.016
Hauggaard-Nielsen, H., Mundus, S. & Jensen, E. S. Nitrogen dynamics following grain legumes and subsequent catch crops and the effects on succeeding cereal crops. Nutr. Cycl. Agroecosyst. 84, 281–291 (2009).
doi: 10.1007/s10705-008-9242-7
Stagnari, F., Maggio, A., Galieni, A. & Pisante, M. Multiple benefits of legumes for agriculture sustainability: An overview. Chem. Biol. Technol. Agric. 4, 1–13 (2017).
doi: 10.1186/s40538-016-0085-1
Zhou, R. et al. Phenotyping of faba beans (Vicia faba L.) under cold and heat stresses using chlorophyll fluorescence. Euphytica 214, 1–13 (2017).
Anjum, N. A. Book review: Legumes under environmental stress: Yield, improvement and adaptations. Front. Plant Sci. 7, 798 (2016).
pmcid: 4891354 doi: 10.3389/fpls.2016.00798
Stoddard, F. L. et al. Screening techniques and sources of resistance to abiotic stresses in cool-season food legumes. Euphytica 147, 167–186 (2006).
doi: 10.1007/s10681-006-4723-8
Sillero, J. C. et al. Faba bean breeding for disease resistance. Field Crops Res. 115, 297–307 (2010).
doi: 10.1016/j.fcr.2009.09.012
Stoddard, F. L., Nicholas, A. H., Rubiales, D., Thomas, J. & Villegas-Fernández, A. M. Integrated pest management in faba bean. Field Crops Res. 115, 308–318 (2010).
doi: 10.1016/j.fcr.2009.07.002
Khamassi, K. et al. A baseline study of vicine–convicine levels in faba bean (Vicia faba L.) germplasm. Plant Genet. Resour. 11, 250–257 (2013).
doi: 10.1017/S1479262113000105
Cooper, J. W. et al. Enhancing faba bean (Vicia faba L.) genome resources. J. Exp. Bot. 68, 1941–1953 (2017).
pubmed: 28419381 pmcid: 5429004 doi: 10.1093/jxb/erx117
Carrillo-Perdomo, E. et al. Development of new genetic resources for faba bean (Vicia faba L.) breeding through the discovery of gene-based SNP markers and the construction of a high-density consensus map. Sci. Rep. 10, 1–14 (2020).
doi: 10.1038/s41598-020-63664-7
Mardis, E. R. The impact of next-generation sequencing technology on genetics. Trends Genet. 24, 133–141 (2008).
pubmed: 18262675 doi: 10.1016/j.tig.2007.12.007
Morozova, O. & Marra, M. A. Applications of next-generation sequencing technologies in functional genomics. Genomics 92, 255–264 (2008).
pubmed: 18703132 doi: 10.1016/j.ygeno.2008.07.001
Gnanasambandam, A. et al. Impact of molecular technologies on faba bean (Vicia faba L.) breeding strategies. Agron. 2, 132–166 (2012).
doi: 10.3390/agronomy2030132
Flint-Garcia, S. A., Thornsberry, J. M. & Buckler, E. S. IV. Structure of linkage disequilibrium in plants. Annu. Rev. Plant Biol. 54, 357–374 (2003).
pubmed: 14502995 doi: 10.1146/annurev.arplant.54.031902.134907
Korte, A. & Farlow, A. The advantages and limitations of trait analysis with GWAS: A review. Plant Methods 9, 1–9 (2013).
doi: 10.1186/1746-4811-9-29
Zhou, X. & Stephens, M. Efficient multivariate linear mixed model algorithms for genome-wide association studies. Nat. Methods 11, 407–409 (2014).
pubmed: 24531419 pmcid: 4211878 doi: 10.1038/nmeth.2848
Maalouf, F. et al. Breeding and genomics status in faba bean (Vicia faba). Plant Breed. 138, 465–473 (2019).
doi: 10.1111/pbr.12644
Webb, A. et al. A SNP-based consensus genetic map for synteny-based trait targeting in faba bean (Vicia faba L.). Plant Biotechnol. J. 14, 177–185 (2016).
pubmed: 25865502 doi: 10.1111/pbi.12371
Satovic, Z. et al. A reference consensus genetic map for molecular markers and economically important traits in faba bean (Vicia faba L.). BMC Genom. 14, 1–15 (2019).
Ellwood, S. R. et al. Construction of a comparative genetic map in faba bean (Vicia faba L.); conservation of genome structure with Lens culinaris. BMC Genom. 9, 1–1 (2008).
doi: 10.1186/1471-2164-9-380
Kaur, S. et al. SNP discovery and high-density genetic mapping in faba bean (Vicia faba L.) permits identification of QTLs for ascochyta blight resistance. Plant Sci. 217, 47–55 (2014).
pubmed: 24467895 doi: 10.1016/j.plantsci.2013.11.014
Ocaña-Moral, S., Gutiérrez, N., Torres, A. M. & Madrid, E. Saturation mapping of regions determining resistance to Ascochyta blight and broomrape in faba bean using transcriptome-based SNP genotyping. Theor. Appl. Genet. 130, 2271–2282 (2017).
pubmed: 28791437 doi: 10.1007/s00122-017-2958-5
Khazaei, H. et al. Flanking SNP markers for vicine–convicine concentration in faba bean (Vicia faba L.). Mol. Breed. 35, 1–6 (2015).
doi: 10.1007/s11032-015-0214-8
Song, M. Preventing favism by selecting faba bean mutants using molecular markers. SFJ. 3, 2–6 (2017).
Maalouf, F. et al. Breeding for post-emergence herbicide tolerance in cool-season food legumes. In Proceedings of the International Conference on Pulses, 65 (Marrakesh, 18–20 April 2016).
Babiker, A. G. T. & Khalid, M. E. Chemical weed control in faba bean at Wad Hamid. In Annual Report, Hudieba Research Station 183–185 (Agric. Res. Corp (ARC), 1990).
Rubiales, D. & Fernández-Aparicio, M. Innovations in parasitic weeds management in legume crops. A review. Agron. Sustain. Dev. 32, 433–449 (2012).
doi: 10.1007/s13593-011-0045-x
Pérez-de-Luque, A. et al. Broomrape management in faba bean. Field Crops Res. 115, 319–328 (2010).
doi: 10.1016/j.fcr.2009.02.013
Singh, N. P. & Yadav, I. S. Herbicide tolerant food legume crops: possibilities and prospects. In Herbicides-properties, synthesis and control of weeds (ed. Hasaneen M. N.) 435–452. (InTech, 2012).‏‏
Minotti, P. L. & Sweet, R. D. Role of crop competition in limiting losses from weeds. In Handbook of Pest Management in Agriculture (ed. Pimental, D.) 351–367 (CRC Handbook of Pest Management in Agriculture, 1981).
Berkowitz, A. R. Competition for resources in weed-crop mixtures. In Weed Management in Agrosystems: Ecological Approaches (eds Altiera, M. A. & Liebman, M.) 89–119 (CRC Press, 1981).
Gaudet, C. L. & Keddy, P. A. A comparative approach to predicting competitive ability from plant traits. Nature 334, 242–243 (1988).
doi: 10.1038/334242a0
Rubiales, D. Can we breed for durable resistance to broomrapes?. Phytopath. Mediterranea 57, 170–185 (2018).
Rispail, N. et al. Plant resistance to parasitic plants: Molecular approaches to an old foe. New Phytol. 173, 703–712 (2007).
pubmed: 17286819 doi: 10.1111/j.1469-8137.2007.01980.x
Beckie, H. J. et al. A decade of herbicide-resistant crops in Canada. Can. J. Plant Sci. 86, 1243–1264 (2006).
doi: 10.4141/P05-193
Mao, D. et al. Developing Improved Herbicide Tolerance in Pulse Crops. (Grain Research and Development Corporation, 2016). https://grdc.com.au/resources-and-publications/grdc-update-papers/tab-content/grdc-update-papers/2016/02/developing-improved-herbicide-tolerance-in-pulse-crops (accessed on 24 April 2021).
Abou-Khater, L. et al. Identification of tolerance to metribuzin and imazethapyr herbicides in faba bean (Vicia faba L.). Crop Sci. 1–19 (2021).
GRDC. Grownotes Faba Bean Section 17 Environmental Issues. https://grdc.com.au/ (accessed on 5 April 2021). (2017).
Pulse Australia. Managing Pulses to Minimize Frost Damage. http://www.pulseaus.com.au/ (accessed on 5 April 2021).
García-Torres, L. & López-Granados, F. Control of broomrape (Orobanche crenata Forsk.) in broad bean (Vicia faba L.) with imidazolinones and other herbicides. Weed Res. 31, 227–235 (1991).
doi: 10.1111/j.1365-3180.1991.tb01762.x
Sharma, S. R. et al. Effect of post-emergence herbicide metribuzin application on morpho-physiological traits,yield and yield components in Lentil (Lens culinaris Medik.). In Proceedings of the International Conference on Pulses for Health, Nutrition, and Sustainable Agriculture in Drylands, 100 (Marrakesh, Morocco,18–20 April 2016).
Sharma, S. R. et al. Genetic variation for tolerance to post-emergence herbicide, imazethapyr in lentil (Lens culinaris Medik). Arch. Agron. Soil Sci. 64, 1818–1830 (2018).
doi: 10.1080/03650340.2018.1463519
Taran, B., Warkentin, T. D., Vandenberg, A. & Holm, F. A. Variation in chickpea germplasm for tolerance to imazethapyr and imazamox herbicides. Can. J. Plant Sci. 90, 139–142 (2010).
doi: 10.4141/CJPS09061
Wall, D. A. Lentil (Lens culinaris) and faba bean (Vicia faba) tolerance to post-emergence applications of imazethapyr. Can. J. Plant Sci. 76, 525–529 (1996).
doi: 10.4141/cjps96-096
Sajja, S. et al. Effect of post-emergence herbicide imazethapyr on phenological and agronomic traits in chickpea breeding lines. In Proceedings of the International Plant Breeding Congress (IPBC) and Eucarpia—Oil and Protein Crops Section Conference (Antalya, Turkey, 1–5 November 2015).
Senseman, S. A. Herbicide Handbook. 9th ed.; Weed Science Society of America. (Lawrence, US, 2007) ISBN 1891276565, 9781891276569.
Trebst, A. & Wietoska, H. Mode of action and structure-activity-relationships of the aminotriazinone herbicide Metribuzin. Inhibition of photosynthetic electron transport in chloroplasts by Metribuzin (author's transl). Zeitschrift fur Naturforschung, Section C, Biosciences 30, 499–504 (1975).
Shaner, D. L., Anderson, P. C. & Stidham, M. A. Imidazolinones: potent inhibitors of acetohydroxyacid synthase. Plant Physiol. 76, 545–546 (1984).
pubmed: 16663878 pmcid: 1064324 doi: 10.1104/pp.76.2.545
Saari, L. L. & Mauvais, C. J. Sulfonylurea herbicide-resistant crops. In Herbicide-Resistant crops (ed. Duke, S. O.) 127–142 (CRC Press, 1996).
Tecle, B., Da Cunha, A. & Shaner, D. L. Differential routes of metabolism of imidazolinones, basis for soybean (Glycine max) selectivity. Pestic. Biochem. Phys. 46, 120–130 (1993).
doi: 10.1006/pest.1993.1043
Manickavelu, A. et al. Genome wide association mapping of stripe rust resistance in Afghan wheat landraces. Plant Sci. 252, 222–229 (2016).
pubmed: 27717458 doi: 10.1016/j.plantsci.2016.07.018
Oladzad, A. et al. Single and multi-trait GWAS identify genetic factors associated with production traits in common bean under abiotic stress environments. G3 9, 1881–1892 (2019).
pubmed: 31167806 pmcid: 6553540
Sallam, A. & Martsch, R. Association mapping for frost tolerance using multi-parent advanced generation inter-cross (MAGIC) population in faba bean (Vicia faba L.). Genetica 143, 501–514 (2015).
pubmed: 26041397 doi: 10.1007/s10709-015-9848-z
Ali, M. B. et al. Association analyses to genetically improve drought and freezing tolerance of faba bean (Vicia faba L.). Crop Sci. 56, 1036–1048 (2016).
doi: 10.2135/cropsci2015.08.0503
Mulugeta, B., Tesfaye, K., Keneni, G. & Ahmed, S. Genetic diversity in spring faba bean (Vicia faba L.) genotypes as revealed by high-throughput KASP SNP markers. Genet Resour. Crop Evol. 68, 1971–1986 (2021).
doi: 10.1007/s10722-021-01110-x
Yu, X., Yang, A. & James, A. T. Selecting soybeans for sulfonylurea herbicide tolerance: A comparative proteomic study of seed germinations. Crop Pasture Sci. 68, 27–32 (2017).
doi: 10.1071/CP16272
Brown, H. M. Mode of action, crop selectivity, and soil relations of the sulfonylurea herbicides. Pestic. Sci. 29, 263–281 (1990).
doi: 10.1002/ps.2780290304
Lehti-Shiu, M. D., Zou, C., Hanada, K. & Shiu, S. H. Evolutionary history and stress regulation of plant receptor-like kinase/pelle genes. Plant Physiol. 150, 12–26 (2009).
pubmed: 19321712 pmcid: 2675737 doi: 10.1104/pp.108.134353
Boller, T. & Felix, G. A renaissance of elicitors: perception of microbe-associated molecular patterns and danger signals by pattern-recognition receptors. Annu. Rev. Plant Biol. 60, 379–406 (2009).
pubmed: 19400727 doi: 10.1146/annurev.arplant.57.032905.105346
Chae, L., Pandey, G. K., Luan, S., Cheong, Y. H. & Kim, K. N. Protein kinases and phosphatases for stress signal transduction in plants. In Abiotic Stress Adaptation in Plants (eds Pareek, A. et al.) 123–163 (Springer, 2009).
doi: 10.1007/978-90-481-3112-9_7
Shehzad, M. et al. Genome-wide mining and identification of protein Kinase Gene Family impacts salinity stress tolerance in highly dense genetic map developed from interspecific cross between G. hirsutum L. and G. darwinii G Watt. Agronomy 9, 560 (2019).
doi: 10.3390/agronomy9090560
Burns, E. E., Keith, B. K., Refai, M. Y., Bothner, B. & Dyer, W. E. Constitutive redox and phosphoproteome changes in multiple herbicide resistant Avena fatua L. are similar to those of systemic acquired resistance and systemic acquired acclimation. J. Plant Physiol. 220, 105–114 (2018).
pubmed: 29169105 doi: 10.1016/j.jplph.2017.11.004
Roy, S. Function of MYB domain transcription factors in abiotic stress and epigenetic control of stress response in plant genome. Plant Signal. Behav. 11, e1117723 (2016).
pubmed: 26636625 doi: 10.1080/15592324.2015.1117723
Katiyar, A. et al. Genome-wide classification and expression analysis of MYB transcription factor families in rice and Arabidopsis. BMC Genom. 13, 1–19 (2012).
doi: 10.1186/1471-2164-13-544
Bhoite, R., Si, P., Siddique, K. H. & Yan, G. Comparative transcriptome analyses for metribuzin tolerance provide insights into key genes and mechanisms restoring photosynthetic efficiency in bread wheat (Triticum aestivum L.). Genomics 113, 910–918 (2021).
pubmed: 33600945 doi: 10.1016/j.ygeno.2021.02.004
Rachna, C. Difference Between Photosystem I and Photosystem II. Bio Differences. https://biodifferences.com/difference-between-photosystem-i-and-photosystem-ii.html (accessed on 10 May 2021) (2019).
Lancashire, P. D. et al. A uniform decimal code for growth stages of crops and weeds. Ann. App. Biol. 119, 561–601 (1991).
doi: 10.1111/j.1744-7348.1991.tb04895.x
Poland, J. A., Brown, P. J., Sorrells, M. E. & Jannink, J. L. Development of high-density genetic maps for barley and wheat using a novel two-enzyme genotyping-by-sequencing approach. PLoS ONE 7, e32253 (2012).
pubmed: 22389690 pmcid: 3289635 doi: 10.1371/journal.pone.0032253
Glaubitz, J. C. et al. TASSEL-GBS: A high capacity genotyping by sequencing analysis pipeline. PLoS ONE 9, e90346 (2014).
pubmed: 24587335 pmcid: 3938676 doi: 10.1371/journal.pone.0090346
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357 (2012).
pubmed: 22388286 pmcid: 3322381 doi: 10.1038/nmeth.1923
Goedhart, P. W. & Thissen, J. T. N. M. Biometris Genstat procedure library manual 19th edn. (Biometris, Wageningen, 2018).
Alexander, D. H., Novembre, J. & Lange, K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 19, 1655–1664 (2009).
pubmed: 19648217 pmcid: 2752134 doi: 10.1101/gr.094052.109
VanRaden, P. M. Efficient methods to compute genomic predictions. J. Dairy Sci. 91, 4414–4423 (2008).
pubmed: 18946147 doi: 10.3168/jds.2007-0980
Weir, B. S. Genetic Data Analysis. Methods for Discrete Population Genetic Data (Sinauer Associates Inc Publishers, Sunderland, 1990).

Auteurs

Lynn Abou-Khater (L)

International Center for Agricultural Research in the Dry Areas (ICARDA), Terbol, Lebanon. lynnaboukhater@hotmail.com.

Fouad Maalouf (F)

International Center for Agricultural Research in the Dry Areas (ICARDA), Terbol, Lebanon. f.maalouf@cgiar.org.

Abdulqader Jighly (A)

Agriculture Victoria, Victoria, Australia.

Alsamman M Alsamman (AM)

Molecular Genetics and Genome Mapping, Agricultural Genetic Engineering Research Institute, Giza, Egypt.
African Genome Center, Mohammed VI Polytechnic University, Ben Guerir, Morocco.

Diego Rubiales (D)

Institute for Sustainable Agriculture, CSIC, 14004, Córdoba, Spain.

Nicolas Rispail (N)

Institute for Sustainable Agriculture, CSIC, 14004, Córdoba, Spain.

Jinguo Hu (J)

USDA-ARS Plant Germplasm Introduction & Testing Research Unit, Pullman, USA.

Yu Ma (Y)

Department of Horticulture, Washington State University, Pullman, USA.

Rind Balech (R)

International Center for Agricultural Research in the Dry Areas (ICARDA), Terbol, Lebanon.

Aladdin Hamwieh (A)

ICARDA, Rabat, Morocco.

Michael Baum (M)

ICARDA, Cairo, Egypt.

Shiv Kumar (S)

ICARDA, Cairo, Egypt.

Articles similaires

Planting density effect on poplar growth traits and soil nutrient availability, and response of microbial community, assembly and function.

Rongye Qiao, Zhen Song, Yinglong Chen et al.
1.00
Populus Soil Microbiology Soil Microbiota Fungi

Multiple NADPH-cytochrome P450 reductases from Lycoris radiata involved in Amaryllidaceae alkaloids biosynthesis.

Yuqing Wu, Yifeng Zhang, Haitong Fan et al.
1.00
Amaryllidaceae Alkaloids Lycoris NADPH-Ferrihemoprotein Reductase Gene Expression Regulation, Plant Plant Proteins

Fasciola hepatica and Fasciola hybrid form co-existence in yak from Tibet of China: application of rDNA internal transcribed spacer.

Wenqiang Tang, Yule Zhou, Leyi Li et al.
1.00
Animals Cattle Tibet Fasciola Fascioliasis

Systematical characterization of Rab7 gene family in Gossypium and potential functions of GhRab7B3-A gene in drought tolerance.

Mengyuan Yan, Zhiwei Dong, Tian Pan et al.
1.00
Drought Resistance Gene Expression Profiling Gene Expression Regulation, Plant Gossypium Multigene Family

Classifications MeSH

questionsmedicales.fr › Sciences de l'information › Mémorisation et recherche des informations › Bases de données comme sujet › Bases de données factuelles › Bases de données génétiques › Genomic regions associated with herbicide...
questionsmedicales.fr › Phénomènes génétiques › Structures génétiques › Génome › Génome végétal › Gènes de plante › Genomic regions associated with herbicide...
questionsmedicales.fr › Phénomènes génétiques › Structures génétiques › Génome › Génome végétal › Genomic regions associated with herbicide...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Épidémiologie moléculaire › Étude d'association pangénomique › Genomic regions associated with herbicide...
questionsmedicales.fr › Phénomènes génétiques › Génotype › Genomic regions associated with herbicide...
questionsmedicales.fr › Phénomènes physiologiques › Phénomènes pharmacologiques et toxicologiques › Phénomènes pharmacologiques › Résistance aux substances › Résistance aux herbicides › Genomic regions associated with herbicide...
questionsmedicales.fr › Actions chimiques et utilisations › Actions toxiques › Pesticides › Herbicides › Genomic regions associated with herbicide...
questionsmedicales.fr › Composés hétérocycliques › Composés hétéromonocycliques › Pyridines › Acides nicotiniques › Genomic regions associated with herbicide...
questionsmedicales.fr › Phénomènes génétiques › Phénotype › Genomic regions associated with herbicide...
questionsmedicales.fr › Acides aminés, peptides et protéines › Protéines › Protéines végétales › Genomic regions associated with herbicide...
questionsmedicales.fr › Phénomènes génétiques › Variation génétique › Polymorphisme génétique › Polymorphisme de nucléotide simple › Genomic regions associated with herbicide...
questionsmedicales.fr › Phénomènes génétiques › Structures génétiques › Génome › Composants de génome › Locus génétiques › Locus de caractère quantitatif › Genomic regions associated with herbicide...
questionsmedicales.fr › Composés hétérocycliques › Composés hétéromonocycliques › Triazines › Genomic regions associated with herbicide...
questionsmedicales.fr › Eucaryotes › Viridiplantae › Streptophyta › Embryophyta › Tracheobionta › Magnoliopsida › Fabaceae › Vicia › Vicia faba › Genomic regions associated with herbicide...