Genes controlling barley malt quality: A QTL meta-analysis

Document Type : Research Paper

Authors

1 Department of Plant Production, Faculty of Agriculture and Natural Resources, Gonbad Kavous University, Gonbad Kavous, Iran.

2 BioGenTAC lnc., Technology Incubator of Agricultural Biotechnology Research Institute of Iran, North Branch (ABRII), Rasht, Iran.

3 Olive Research Station of Tarom, Crop and Horticultural Science Research Department, , Agricultural and Natural Resources Research and Education Center, AREEO, Tarom, Iran.

10.22034/jppb.2025.69502.1390

Abstract

Objective: Malt quality in barley is a complex quantitative trait governed by multiple genes and influenced by environmental factors, making genetic improvement challenging. The present study aimed to integrate QTL data from multiple independent studies via meta-analysis to identify stable, consensus genomic regions (MQTLs) that control key malt quality traits. The ultimate goal was to provide reliable genomic targets for marker-assisted selection to accelerate breeding programs for improved barley malt quality.
Methods: A comprehensive literature search was conducted across Web of Science, Scopus, PubMed, ScienceDirect, and Google Scholar to identify all published QTL studies related to barley malt quality. A high-density consensus genetic map was constructed by integrating several well-established reference maps. The unified map incorporated multiple marker systems, including AFLP, SSR, RFLP, RAPD, SAP, DArT, EST, CAPS, STS, RGA, IFLP, and SNP markers, ensuring comprehensive genome coverage. Individual QTLs were projected onto the consensus map, and the optimal number of MQTLs per chromosome was determined using the Akaike Information Criterion, Bayesian Information Criterion (BIC), and empirical Bayesian procedures. To validate the biological relevance of the identified MQTLs, genes located within 2 Mb intervals flanking each MQTL peak position were retrieved from major genomic databases, including EnsemblPlants, GrainGenes, NCBI Gene, and BarleyMap.
Results: Through meta-analysis, the 184 individual QTLs were consolidated into 35 MQTLs distributed across all seven barley chromosomes. The most significant MQTL, designated MQTL7.2, harbored 25 overlapping QTLs and explained 68% of the phenotypic variance. MQTL6.4 contained 12 QTLs controlling alpha amylase, diastatic power, viscosity, beta glucan, Wort beta glucan, and grain protein content, explaining 38% of phenotypic variance. Gene mining within MQTL intervals identified 54 unique candidate genes. Gene ontology enrichment analysis revealed significant involvement in monoatomic anion transport, tetracycline transmembrane transport, mRNA pseudouridine synthesis, and transmembrane transporter activity. MicroRNA prediction revealed 33 unique miRNAs regulating the identified genes, with hvu miR6192, hvu miR6184, hvu miR6182, hvu miR6176, hvu miR6189, and hvu miR6214 targeting multiple genes. 
Conclusion: The identified MQTLs exhibited substantially narrowed confidence intervals compared to individual QTLs, providing more precise genomic targets for breeding applications. Eleven major MQTLs with R² values exceeding 20% represented high-priority genomic regions for marker-assisted selection. The Mega MQTL7.2, explaining 68% of phenotypic variance and harboring QTLs for multiple malt quality parameters, represents a particularly valuable breeding target. These findings will facilitate marker-assisted selection strategies to accelerate genetic improvement of barley for the malting and brewing industries, ultimately contributing to the development of superior malting barley cultivars with enhanced quality characteristics.
 

Keywords

Main Subjects

References

Ajandouz EH, Abe JI, Svensson B, Marchis-Mouren G. 1992. Barley malt-α-amylase. Purification, action pattern, and subsite mapping of isozyme 1 and two members of the isozyme 2 subfamily using p-nitrophenylated maltooligosaccharide substrates. Biochim Biophys Acta. 1159(2): 193-202. https://doi.org/10.1016/0167-4838(92)90050-D
Akbari M, Sabouri H, Sajadi SJ, Yarahmadi S, Ahangar L, Abedi A, Katouzi M. 2022. Mega MQTLs: a strategy for the production of golden barley (Hordeum vulgare L.) tolerant to abiotic stresses. Genes. 13(11): 2087. https://doi.org/10.3390/genes13112087
Almaguer C, Kollmannsberger H, Gastl M, Becker T. 2024. Influence of the malting conditions on the modification and variation in the physicochemical properties and volatile composition of barley (Hordeum vulgare L.), rye (Secale cereale L.), and quinoa (Chenopodium quinoa Willd.) malts. Food Res Int. 2024: 114965. https://doi.org/10.1016/j.foodres.2024.114965
American Malting Barley Association. 2014. Malting barley breeding guidelines: Ideal commercial malt criteria. Milwaukee, Wisconsin, USA: American Malting Barley Association, Inc.
Amo J, Jiménez‐Estévez E, Martínez‐Martínez A, Yáñez A, Martínez V, Nieves‐Cordones M, Rubio F. 2024. Mutation of the K+ transporter SlHAK5 of tomato alters pistil morphology, ionome, metabolome and transcriptome in flowers. Physiol Plant. 176(6): e14585. https://doi.org/10.1111/ppl.14585
Anilkumar C, Sah RP, Muhammed Azharudheen TP, Behera S, Singh N, Prakash NR, Sunitha NC, Devanna BN, Marndi BC, Patra BC, Nair SK. 2022. Understanding complex genetic architecture of rice grain weight through QTL-meta analysis and candidate gene identification. Sci Rep. 12(1): 13832. https://doi.org/10.1038/s41598-022-18169-w
Arcade A, Labourdette A, Falque M, Mangin B, Chardon F, Charcosset A, Joets J. 2004. BioMercator: integrating genetic maps and QTL towards discovery of candidate genes. J Bioinformatics. 20(14): 2324-2326. https://doi.org/10.1093/bioinformatics/bth232
Arends AM, Fox GP, Henry R.J, Marschke RJ, Symons MH. 1995. Genetic and environmental variation in the diastatic power of Australian barley. J Cereal Sci. 21(1): 63-70. https://doi.org/10.1016/S0733-5210(95)80016-6
Arifuzzaman M, Sayed MA, Muzammil S, Pillen K, Schumann H, Naz AA, Léon J. 2014. Detection and validation of novel QTL for shoot and root traits in barley (Hordeum vulgare L.). Mol Breed. 34: 1373-1387. https://doi.org/10.1007/s11032-014-0121-4
Back W, Gastl M, Krottenthaler M, Narziß L, Zarnkow M. 2020. Brewing techniques in practice: An in-depth review of beer production with problem solving strategies. Nuremberg, Germany: Fachverlag Hans Carl.
Bahmani M, Juhász A, Bose U, Nye-Wood MG, Blundell M, Howitt CA, Colgrave ML. 2024. From grain to malt: tracking changes of ultra-low-gluten barley storage proteins after malting. Food Chem. 432: 137189. https://doi.org/10.1016/j.foodchem.2023.137189
Bamforth CW, Barclay AHP. 1993. Malting technology and the uses of malt. In: MacGregor AW, Bhatty RS (eds). Barley: Chemistry and technology. St. Paul, Minnesota, USA: American Association of Cereal Chemists, Inc., pp. 297-354.
Basu D, Shoots JM, Haswell, ES. 2020. Interactions between the N-and C-termini of the mechanosensitive ion channel At MSL10 are consistent with a three-step mechanism for activation. J Exp Bot.71(14):  4020-4032. https://doi.org/10.1093/jxb/eraa177
Bettenhausen HM, Barr L, Broeckling CD, Chaparro JM, Holbrook C, Sedin D, Heuberger AL. 2018. Influence of malt source on beer chemistry, flavor, and flavor stability. Food Res Int. 113: 487-504. https://doi.org/10.1016/j.foodres.2018.07.027
Bolser D, Staines DM, Pritchard E, Kersey P. 2016. Ensembl plants: integrating tools for visualizing, mining, and analyzing plant genomics data. In: Edwards D. (ed.) Plant bioinformatics. Methods in Molecular Biology, Vol. 1374. New York: Humana Press. https://doi.org/10.1007/978-1-4939-3167-5_6
Broughton S, Zhou G, Teakle NL, Matsuda R, Zhou M, O’Leary RA, Colmer TD, Li C. 2015. Waterlogging tolerance is associated with root porosity in barley (Hordeum vulgare L.). Mol Breed. 35: 1-15. https://doi.org/10.1007/s11032-015-0243-3
Bugoni M, Takiya CS, Grigoletto NS, Nunes AT, Júnior PCV, Chesini RG, da Silva GG, de Alcantara LB, Rennó LN, Rennó FP. 2022. Dry malt extract from barley partially replacing ground corn in diets of dairy cows: Nutrient digestibility, ruminal fermentation, and milk composition. J Dairy Sci. 105(7): 5714-5722. https://doi.org/10.3168/jds.2021-21345
Carvalho GR, Monteiro RL, Laurindo JB, Augusto PED. 2021. Microwave and microwave-vacuum drying as alternatives to convective drying in barley malt processing. Innov Food Sci Emerg Technol. 73: 102770. https://doi.org/10.1016/j.ifset.2021.102770
Charmier LM, McLoughlin C, McCleary BV. 2021. Diastatic power and maltose value: a method for the measurement of amylolytic enzymes in malt. J Inst Brew. 127(4): 327-344. https://doi.org/10.1002/jib.673
Chen C, Wu Y, Li J, Wang X, Zeng Z, Xu J, Liu Y, Feng J, Chen H, He Y, Xia R. 2023. TBtools-II: A “one for all, all for one” bioinformatics platform for biological big-data mining. Mol Plant. 16(11): 1733-1742. https://doi.org/10.1016/j.molp.2023.09.010
Costa JM, Corey A, Hayes PM, Jobet C, Kleinhofs A, Kopisch-Obusch A, Kramer SF, Kudrna D, Li M, Riera-Lizarazu O, Sato K. 2001. Molecular mapping of the Oregon Wolfe Barleys: a phenotypically polymorphic doubled-haploid population. Theor Appl Genet. 103: 415-424. https://doi.org/10.1007/s001220100622
Cu ST, March TJ, Stewart S, Degner S, Coventry S, Box A, Stewart D, Skadhauge B, Burton RA, Fincher GB, Eglinton J. 2016. Genetic analysis of grain and malt quality in an elite barley population. Mol Breed. 36: 1-16. https://doi.org/10.1007/s11032-016-0453-3
Dahleen LS, Agrama, HA, Horsley RD, Steffenson BJ, Schwarz PB, Mesfin A, Franckowiak JD. 2003. Identification of QTLs associated with Fusarium head blight resistance in Zhedar 2 barley. Theor Appl Genet. 108: 95-104. https://doi.org/10.1007/s00122-003-1419-5
Darvasi A, Soller M.1997. A simple method to calculate resolving power and confidence interval of QTL map location. Behav Genet. 27: 125-132. https://doi.org/10.1023/A:1025685324830
De Angeli A, Thomine S, Frachisse JM, Ephritikhine G, Gambale F, Barbier-Brygoo H. 2007. Anion channels and transporters in plant cell membranes. FEBS Lett. 581(12): 2367-2374. https://doi.org/10.1016/j.febslet.2007.04.003
Diab AA, Teulat-Merah B, This D, Ozturk NZ, Benscher D, Sorrells ME. 2004. Identification of drought-inducible genes and differentially expressed sequence tags in barley. Theor Appl Genet. 109: 1417-1425. https://doi.org/10.1007/s00122-004-1755-0
Dracatos PM, Haghdoust R, Singh RP, Huerta-Espino J, Barnes CW, Forrest K, Hayden M, Niks RE, Park RF, Singh D. 2019. High-density mapping of triple rust resistance in barley using DArT-seq markers. Front Plant Sci. 10: 467. https://doi.org/10.3389/fpls.2019.00467
 Du B, Wu J, Wang M, Wu J, Sun C, Zhang X, Ren X, Wang Q. 2024. Detection of consensus genomic regions and candidate genes for quality traits in barley using QTL meta-analysis. Front Plant Sci. 14: 1319889. https://doi.org/10.3389/fpls.2023.1319889
Ellis RP, Forster BP, Gordon DC, Handley LL, Keith RP, Lawrence P, Meyer R, Powell W, Robinson D, Scrimgeour CM, Young, G. 2002. Phenotype/genotype associations for yield and salt tolerance in a barley mapping population segregating for two dwarfing genes. J Exp Bot. 53(371): 1163-1176. https://doi.org/10.1093/jexbot/53.371.1163
Emebiri LC, Moody DB, Panozzo JF, Chalmers KJ, Kretschmer JM, Ablett GA. 2003. Identification of QTLs associated with variations in grain protein concentration in two-row barley. Aust J Agric Res. 54(12): 1211-1221. https://doi.org/10.1071/AR02237
Emebiri LC, Moody DB, Panozzo JF, Read BJ. 2004. Mapping of QTL for malting quality attributes in barley based on a cross of parents with low grain protein concentration. Field Crops Res. 87(2): 195-205. https://doi.org/10.1016/j.fcr.2003.11.002
Evans DE, Sheehan MC. 2002. Don't be fobbed off: The substance of beer foam—A review. J Am Soc Brew Chem. 60(2): 47-57. https://doi.org/10.1094/ASBCJ-60-0047
Evans DE, Li C, Harasymow S, Roumeliotis S, Eglinton JK. 2009. Improved prediction of malt fermentability by measurement of the diastatic power enzymes β-amylase, α-amylase, and limit dextrinase: II. Impact of barley genetics, growing environment, and gibberellin on levels of α-amylase and limit dextrinase in malt. J Am Soc Brew Chem. 67(1): 14-22. https://doi.org/10.1094/ASBCJ-2009-0113-01
Fan Y, Shabala S, Ma Y, Xu R, Zhou M. 2015. Using QTL mapping to investigate the relationships between abiotic stress tolerance (drought and salinity) and agronomic and physiological traits. BMC Genomics. 16: 1-11. https://doi.org/10.1186/s12864-015-1243-8
Fan C, Zhai H, Wang H, Yue Y, Zhang M, Li J, Wen S, Guo G, Zeng Y, Ni Z, You M. 2017. Identification of QTLs controlling grain protein concentration using a high-density SNP and SSR linkage map in barley (Hordeum vulgare L.). BMC Plant Biol. 17: 1-14. https://doi.org/10.1186/s12870-017-1056-9
Fang Y, Zhang X, Xue D. 2019. Genetic analysis and molecular breeding applications of malting quality QTLs in barley. Front Genet. 10: 352. https://doi.org/10.3389/fgene.2019.00352
Farag MA, Xiao J, Abdallah HM. 2022. Nutritional value of barley cereal and better opportunities for its processing as a value-added food: a comprehensive review. Crit Rev Food Sci Nutr. 62(4): 1092-1104. https://doi.org/10.1080/10408398.2020.1835817
Feng X, Zhu G, Meng Q, Zeng J, He X, Liu W. 2024. Comprehensive analysis of PLATZ family genes and their responses to abiotic stresses in Barley. BMC Plant Biol. 24(1): 982. https://doi.org/10.1186/s12870-024-05215-0
Fincher GB. 1993. Physiology and biochemistry of germination in barley. In: MacGregor AW, Bhatty RS (eds) Barley: Chemistry and technology. St. Paul, Minnesota, USA: American Association of Cereal Chemists, Inc., pp. 247-295.
Francia E, Rizza F, Cattivelli L, Stanca AM, Galiba G, Toth B, Hayes PM, Skinner JS, Pecchioni N.2004. Two loci on chromosome 5H determine low-temperature tolerance in a ‘Nure’(winter)בTremois’(spring) barley map. Theor Appl Genet. 108: 670-680. https://doi.org/10.1007/s00122-003-1469-8
Ghaffari-Moghadam S, Sabouri H, Gholizadeh A, Ali H. 2019. Identification of QTLs associated with some (Hordeum vulgare L.) traits in a germination stage under salt stress conditions. Iran J Plant Biol. 11(3): 79-94.
Ghaffari-Moghadam S, Sabouri H, Gholizadeh A, Fallahi H. 2019. Genetic structure of some agronomic traits of barley under normal and salinity conditions. Mod Genet J. 13: 489–502. 
Goddard R, de Vos S, Steed A, Muhammed A, Thomas K, Griggs D, Ridout C, Nicholson P. 2019. Mapping of agronomic traits, disease resistance and malting quality in a wide cross of two-row barley cultivars. PLoS One. 14(7): e0219042. https://doi.org/10.1371/journal.pone.0219042
Ghomi K, Rabiei B, Sabouri H. Gholamalipour Alamdar, E. 2021. Association analysis, genetic diversity and population structure of barley (Hordeum vulgare L.) under heat stress conditions using SSR and ISSR markers linked to primary and secondary metabolites. Mol Biol Rep. 48: 6673–6694. https://doi.org/10.1007/s11033-021-06652-y
Glass GV. 1976. Primary, secondary, and meta-analysis of research. Educ Res. 5: 3-8.
https://doi.org/10.3102/0013189X005010003
Graner A, Jahoor A, Schondelmaier J, Siedler H, Pillen K, Fischbeck G, Wenzel G, Herrmann RG. 1991. Construction of an RFLP map of barley. Theor Appl Genet. 83: 250-256. https://doi.org/10.1007/BF00226259
Gubatz S, Shewry PR. 2011. The development, structure, and composition of the barley grain. In: Ullrich SE (ed.) Barley: Production, improvement, and uses. Chichester, West Sussex, UK: John Wiley & Sons Ltd, pp. 391-448. https://doi.org10.1002/9780470958636.ch13.
Gudys K, Guzy-Wrobelska J, Janiak A, Dziurka MA, Ostrowska A, Hura K, Jurczyk B, Żmuda K, Grzybkowska D, Śróbka J, Urban W. 2018. Prioritization of candidate genes in QTL regions for physiological and biochemical traits underlying drought response in barley (Hordeum vulgare L.). Front Plant Sci. 9: 769. https://doi.org/10.3389/fpls.2018.00769
Guo, B., Sleper DA, Lu P, Shannon JG, Nguyen HT, Arelli PR. 2006. QTLs associated with resistance to soybean cyst nematode in soybean: Meta‐analysis of QTL locations. Crop Sci. 46(2): 595-602. https://doi.org/10.2135/cropsci2005.04-0036
Gupta M, Choudhary M, Singh A, Sheoran S, Singla D, Rakshit S.2023. MQTL analysis for mining of candidate genes and constitutive gene network development for fungal disease resistance in maize (Zea mays L). Crop J. 11(2): 511-522. https://doi.org/10.1016/j.cj.2022.07.014
Habschied K, Lalić A, Horvat D, Mastanjević K, Lukinac J, Jukić M, Krstanović V. 2020. β-glucan degradation during malting of different purpose barley varieties. Fermentation. 6(1): 21. https://doi.org/10.3390/fermentation6010021
Han F, Clancy JA, Jones BL, Wesenberg DM, Kleinhofs A, Ullrich SE.2004. Dissection of a malting quality QTL region on chromosome 1 (7H) of barley. Mol Breed. 14: 339-347. https://doi.org/10.1023/B:MOLB.0000049215.09961.06
Han M, Wong J, Su T, Beatty PH, Good AG. 2016. Identification of nitrogen use efficiency genes in barley: searching for QTLs controlling complex physiological traits. Front Plant Sci. 7: 1587. https://doi.org/10.3389/fpls.2016.01587
Hardie DG. 1975. Control of carbohydrase formation by gibberellic acid in barley endosperm. Phytochemistry. 14(8): 1719-1722. https://doi.org/10.1016/0031-9422(75)85303-8
Henson CA, Duke SH. 2007. Osmolyte concentration as an indicator of malt quality. J Am Soc Brew Chem. 65(1):  59-62. https://doi.org/10.1094/ASBCJ-2007-0110-01
Horsley RD, Schmierer D, Maier C, Kudrna D, Urrea CA, Steffenson BJ, Schwarz PB, Franckowiak JD, Green MJ, Zhang B, Kleinhofs A. 2006. Identification of QTLs associated with Fusarium head blight resistance in barley accession CIho 4196. Crop Sci. 46(1): 145-156. https://doi.org/10.2135/cropsci2005.0206
Huang X, Fan Y, Shabala L, Rengel Z, Shabala S, Zhou MX.2018. A major QTL controlling the tolerance to manganese toxicity in barley (Hordeum vulgare L.). Mol Breed. 38: 1-9. https://doi.org/10.1007/s11032-018-0772-7
Huang Y, Cao H, Yang L, Chen C, Shabala L, Xiong M, Niu M, Liu J, Zheng Z, Zhou L, et al. 2019. Tissue-specific respiratory burst oxidase homolog-dependent H2O2 signaling to the plasma membrane H+-ATPase confers potassium uptake and salinity tolerance in Cucurbitaceae. J Exp Bot. 70(20): 5879-5893. https://doi.org/10.1093/jxb/erz328
Jarošová J, Singh K, Chrpová J, Kundu JK. 2020. Analysis of small RNAs of barley genotypes associated with resistance to barley yellow dwarf virus. J Plants. 9(1): 60. https://doi.org/10.3390/plants9010060
Jiang SY, Ramamoorthy R, Ramachandran S. 2008. Comparative transcriptional profiling and evolutionary analysis of the GRAM domain family in eukaryotes. Dev Biol. 314(2): 418-432. https://doi.org/10.1016/j.ydbio.2007.11.027
Jones BL. 2005. Endoproteases of barley and malt. J Cereal Sci. 42(2): 139-156. https://doi.org/10.1016/j.jcs.2005.03.007
Karakousis A, Barr AR, Kretschmer JM, Manning S, Jefferies SP, Chalmers KJ, Islam AKM, Langridge P. 2003. Mapping and QTL analysis of the barley population Clipper× Sahara. Aust J Agric Res. 54(12): 1137-1140. https://doi.org/10.1071/AR02238
Karnatam KS, Chhabra G, Saini DK, Singh R, Kaur G, Praba UP, Kumar P, Goyal S, Sharma P, Ranjan R, Sandhu SK.2023. Genome-wide meta-analysis of QTLs associated with root traits and implications for maize breeding. Int J Mol Sci. 24(7): 6135. https://doi.org/10.3390/ijms24076135
Kaur A, Taneja M, Tyagi S, Sharma A, Singh K, Upadhyay SK. 2020. Genome-wide characterization and expression analysis suggested diverse functions of the mechanosensitive channel of small conductance-like (MSL) genes in cereal crops. Sci Rep. 10(1): 16583. https://doi.org/10.1038/s41598-020-73641-9
Kaur S, Rakshit S, Choudhary M, Das AK, Kumar RR. 2021. Meta-analysis of QTLs associated with popping traits in maize (Zea mays L). PLoS One. 16(8): e0256389. https://doi.org/10.1371/journal.pone.0256389
Kaur S, Das A, Sheoran S, Rakshit S.2023. QTL Meta-analysis: an Approach to detect robust and precise QTL. Trop Plant Biol. 16(4): 225-243. https://doi.org/10.1007/s12042-023-09338-w
Khahani B, Tavakol E, Shariati JV. 2019. Genome-wide meta-analysis on yield and yield-related QTLs in barley (Hordeum vulgare L.). Mol Breed. 39: 1-16. https://doi.org/10.1007/s11032-019-1027-y
Kindu GA, Tang J, Yin X, Struik PC. 2014. Quantitative trait locus analysis of nitrogen use efficiency in barley (Hordeum vulgare L.). Euphytica. 199: 207-221. https://doi.org/10.1007/s10681-014-1134-0
Kleinhofs A, Kilian A, Saghai Maroof MA, Biyashev RM, Hayes P, Chen FQ, Lapitan N, Fenwick A, Blake TK, Kanazin V, Ananiev E. 1993. A molecular, isozyme and morphological map of the barley (Hordeum vulgare) genome. Theor Appl Genet. 86: 705-712. https://doi.org/10.1007/BF00222660
Kochevenko A, Jiang Y, Seiler C, Surdonja K, Kollers S, Reif JC, Korzun V, Graner A. 2018. Identification of QTL hot spots for malting quality in two elite breeding lines with distinct tolerance to abiotic stress. BMC Plant Biol. 18: 1-17. https://doi.org/10.1186/s12870-018-1265-x
Krebs G, Becker T, Gastl M. 2020 Influence of malt modification and the corresponding macromolecular profile on palate fullness in cereal-based beverages. Eur Food Res Technol. 246(6): 1219-1229. https://doi.org/10.1007/s00217-020-03477-0
Kumar S, Singh VP, Saini DK, Sharma H, Saripalli G, Kumar S, Balyan HS, Gupta PK. 2021. MQTLs, ortho-MQTLs, and candidate genes for thermotolerance in wheat (Triticum aestivum L.). Mol Breed. 41: 1-22. https://doi.org/10.1007/s11032-021-01225-0
Kumar D, Verma R.PS, Khippal AK, Kharub AS, Singh C, Singh GP. 2022. BK 306: A two-row barley (Hordeum vulgare L) as potential source of higher diastatic power and FAN content for malt barley improvement. J Cereal Res. 14(2): 175-182.
Kumar S, Saini DK, Jan F, Jan S, Tahir M, Djalovic I, Latkovic D, Khan MA, Kumar S, Vikas VK, Kumar, U. 2023. Comprehensive MQTL analysis for dissecting the genetic architecture of stripe rust resistance in bread wheat. BMC Genomics. 24(1): 259. https://doi.org/10.1186/s12864-023-09352-y.
Kumari A, Sharma D, Sharma P, Sahil Wang C, Verma V, Patil A, Imran M, Singh MP, Kumar K, Paritosh K. 2023. MQTL and haplo-pheno analysis reveal superior haplotype combinations associated with low grain chalkiness under high temperature in rice. Front Plant Sci. 14: 1133115. https://doi.org/10.3389/fpls.2023.1133115
Kumari A, Sharma D, Sahil Kumar K, Sevanthi AM, Agarwal M. 2024. Meta-analysis of mapping studies: Integrating QTLs towards candidate gene discovery. In: Anjoy P, Kumar K, Chandra G, Gaikwad K (eds.) Genomics data analysis for crop improvement. Singapore: Springer Protocols Handbooks, Springer, pp. 191-216. https://doi.org/10.1007/978-981-99-6913-5_7 
Kunze W. 2004. Technology brewing and malting. Berlin: VIB.
Laidò G, Barabaschi D, Tondelli A, Gianinetti A, Stanca AM, Li-Destri-Nicosia O, Di-Fonzo N, Francia E, Pecchioni N. 2009. QTL alleles from a winter feed type can improve malting quality in barley. Plant Breed. 128(6): 598-605. https://doi.org/10.1111/j.1439-0523.2009.01616.x
Lehnhardt F, Nobis A, Skornia A, Becker T, Gastl M. 2021. A Comprehensive Evaluation of Flavor Instability of Beer (Part 1): Influence of Release of Bound State Aldehydes. Foods. 10(10): 2432. https://doi.org/10.3390/foods10102432
Li JZ, Sjakste TG, Röder MS, Ganal MW. 2003. Development and genetic mapping of 127 new microsatellite markers in barley. Theor Appl Genet. 107: 1021-1027. https://doi.org/10.1007/s00122-003-1343-8
Li JZ, Huang XQ, Heinrichs F, Ganal MW, Röder MS. 2005. Analysis of QTLs for yield, yield components, and malting quality in a BC 3-DH population of spring barley. Theor Appl Genet. 110: 356-363. https://doi.org/10.1007/s00122-004-1833-3
Li Y, Schwarz PB, Barr JM, Horsley RD. 2008. Factors predicting malt extract within a single barley cultivar. J Cereal Sci. 48(2): 531-538. https://doi.org/10.1016/j.jcs.2008.02.002
Li HB, Zhou MX, Liu CJ. 2009. A major QTL conferring crown rot resistance in barley and its association with plant height. Theor Appl Genet. 118: 903-910. https://doi.org/10.1007/s00122-008-0950-9
Li WT, Liu C, Liu YX, Pu ZE, Dai SF, Wang JR, Lan XJ, Zheng YL, Wei YM. 2013. Meta-analysis of QTL associated with tolerance to abiotic stresses in barley.  Euphytica. 189: 31-49. https://doi.org/10.1007/s10681-012-0753-6
Li L, Guo N, Zhang Y, Yuan Z, Lu A, Li S, Wang Z. 2022. Reprogramming of fundamental miRNA and gene expression during the barley-Piriformospora indica interaction. J Fungi. 9(1): 24. https://doi.org/10.3390/jof9010024
Liu X, Fan Y, Mak M, Babla M, Holford P, Wang F, Chen G, Scott G, Wang G, Shabala S, Zhou M. 2017. QTLs for stomatal and photosynthetic traits related to salinity tolerance in barley. BMC Genomics.18: 1-13. https://doi.org/10.1186/s12864-017-3950-9
Makhtoum S, Sabouri H, Gholizadeh A, Ahangar L, Katouzi M, Gholamalipour-Alamdari E. 2021a. Mapping of genes controlling secondary metabolites in barley (Hordeum vulgare L.) under salinity stress. Environ Stresses Crop Sci. 14(3): 771-781. https://doi.org/10.22077/escs.2020.3163.1808
Makhtoum S, Sabouri H, Gholizadeh A, Ahangar L, Taliei F, Katouzi M. 2021b. Important chromosomal regions for genetic control of powdery mildew resistance under control, drought, and saline conditions in barley (Hordeum vulgare L.). Trop Plant Pathol. 46: 622-642. https://doi.org/10.1007/s40858-021-00443-3
Makhtoum S, Sabouri H, Gholizadeh A, Ahangar L, Katouzi M. 2022a. QTLs controlling physiological and morphological traits of barley (Hordeum vulgare L.) seedlings under salinity, drought, and normal conditions. BioTech. 11(3): 26. https://doi.org/10.3390/biotech11030026
Makhtoum S, Sabouri H, Gholizadeh A, Ahangar L, Katouzi M, Mastinu A. 2022b. Mapping of QTLs controlling barley agronomic traits (Hordeum vulgare L.) under normal conditions and drought and salinity stress at reproductive stage. Plant Gene. 31: 100375. https://doi.org/10.1016/j.plgene.2022.100375
Mano Y, Takeda K. 1997. Mapping quantitative trait loci for salt tolerance at germination and the seedling stage in barley (Hordeum vulgare L.). Euphytica. 94: 263-272. https://doi.org/10.1023/A:1002968207362
Marcel TC, Varshney RK, Barbieri M, Jafary H, De-Kock MJD, Graner A, Niks R. 2007. A high-density consensus map of barley to compare the distribution of QTLs for partial resistance to Puccinia hordei and of defence gene homologues. Theor Appl Genet. 114: 487-500. https://doi.org/10.1007/s00122-006-0447-3
Marconi O, Tomasi I, Dionisio L, Perretti G, Fantozzi P. 2014. Effects of malting on molecular weight distribution and content of water-extractable β-glucans in barley. Food Res Int. 64: 677-682. https://doi.org/10.1016/j.foodres.2014.07.037.
Marquez-Cedillo LA, Hayes PM, Jones BL, Kleinhofs A, Legge WG, Rossnagel BG, Sato K, Ullrich SE, Wesenberg DM. 2000. QTL analysis of malting quality in barley based on the doubled-haploid progeny of two elite North American varieties representing different germplasm groups. Theor Appl Genet. 101: 173-184. https://doi.org/10.1007/s001220051468
Meints B, Hayes P.M. 2019. Breeding naked barley for food, feed, and malt. Plant Breed Rev. 43: 95-119. https://doi.org/10.1002/9781119521358.ch3
Mesfin A, Smith KP, Dill‐Macky R, Evans CK, Waugh R, Gustus CD, Muehlbauer GJ. 2003. Quantitative trait loci for Fusarium head blight resistance in barley detected in a two‐rowed by six‐rowed population. Crop Sci. 43(1): 307-318. https://doi.org/10.2135/cropsci2003.0307
Morrissy CP, Halstead MA, Féchir M, Carrijo D, Fisk SP, Johnson V, Bettenhausen HM, Shellhammer TH, Hayes PM. 2023. Barley variety and growing location provide nuanced contributions to beer flavor using elite germplasm in commercial-type malts and beers. J Am Soc Brew Chem. 81(3): 404-415. https://doi.org/10.1080/03610470.2022.2159917.
Navakode S, Weidner A, Varshney R, Lohwasser U, Scholz U, Börner A. 2009. A QTL analysis of aluminium tolerance in barley, using gene-based markers. Cereal Res Commun. 37(4): 531-540. https://doi.org/10.1556/CRC.37.2009.4.7.
Oliveira PM, Mauch A, Jacob F, Waters DM, Arendt EK. 2012. Fundamental study on the influence of Fusarium infection on quality and ultrastructure of barley malt. Int J Food Microbiol. 156(1): 32-43. https://doi.org/10.1016/j.ijfoodmicro.2012.02.018.
Park SC, Yoon AM, Kim YM, Lee MY, Lee JR. 2023. Antifungal action of Arabidopsis thaliana TCP21 via induction of oxidative stress and apoptosis. J Antioxidants. 12(9): 1767. https://doi.org/10.3390/antiox12091767.
Ramsay L, Macaulay M, Ivanissevich SD, MacLean K, Cardle L, Fuller J, Edwards KJ, Tuvesson S, Morgante M, Massari A, Maestri E. 2000. A simple sequence repeat-based linkage map of barley. J Genetics. 156(4): 1997-2005. https://doi.org/10.1093/genetics/156.4.1997.
Rani H, Bhardwaj RD. 2021. Quality attributes for barley malt:“The backbone of beer”. J Food Sci. 86(8): 3322-3340. https://doi.org/10.1111/1750-3841.15836.
Ren X, Wang J, Liu L, Sun G, Li C, Luo H, Sun D. 2016. SNP-based high density genetic map and mapping of btwd1 dwarfing gene in barley. Sci Rep. 6(1): 31741. https://doi.org/10.1038/srep31741.
Roy-Choudhury D, Maurya A, Singh NK, Singh GP, Singh R. 2024. Discovering New QTNs and Candidate Genes Associated with Rice-Grain-Related Traits within a Collection of Northeast Core Set and Rice Landraces. Plants. 13(12): 1707. https://doi.org/10.3390/plants13121707.
Saal B, von-Korff M, Léon J, Pillen K. 2011. Advanced-backcross QTL analysis in spring barley: IV. Localization of QTL× nitrogen interaction effects for yield-related traits. Euphytica. 177: 223-239. https://doi.org/10.1007/s10681-010-0263-3.
Sabouri H, Pezeshkian Z, Taliei F, Akbari M, Kazerani B. 2024. Detection of closely linked QTLs and candidate genes controlling germination indices in response to drought and salinity stresses in barley. Sci Rep. (1): 15656. https://doi.org/10.1038/s41598-024-66394-2.
Safonova EA, Borodulin DM, Ivanets VN, Komarov SS, Sidorin KM. 2018. Innovative technologies in production of malt extract. Adv Eng Res. 151: 610–614.
Saini DK, Chopra Y, Pal N, Chahal A, Srivastava P, Gupta P.K. 2021. MQTLs, ortho-MQTLs and candidate genes for nitrogen use efficiency and root system architecture in bread wheat (Triticum aestivum L). Physiol Mol Biol Plants. 27(10): 2245–2267. https://doi.org/10.1007/s12298-021-01078-z
Saini DK, Srivastava P, Pal N, Gupta PK. 2022. MQTLs, ortho-MQTLs and candidate genes for grain yield and associated traits in wheat (Triticum aestivum L). Theor Appl Genet. 135: 1049-1081. https://doi.org/10.1007/s00122-021-04018-3
Salvo-Garrido H, Laurie DA, Jaffe B, Snape JW. 2001. An RFLP map of diploid Hordeum bulbosum L. and comparison with maps of barley (H. vulgare L.) and wheat (Triticum aestivum L.). Theor Appl Genet. 103: 869-880. https://doi.org/10.1007/s001220100642
Sandhu N, Pruthi G, Prakash-Raigar O, Singh MP, Phagna K, Kumar A, Sethi M, Singh J, Ade PA, Saini DK. 2021. MQTL analysis in rice and cross-genome talk of the genomic regions controlling nitrogen use efficiency in cereal crops revealing phylogenetic relationship. Front Genet. 12: 807210. https://doi.org/10.3389/fgene.2021.807210
Sato K, Nankaku N, Takeda K. 2009. A high-density transcript linkage map of barley derived from a single population. Heredity. 103(2): 110-117. https://doi.org/10.1038/hdy.2009.57
Sayed MA. 2011. QTL analysis for drought tolerance related to root and shoot traits in barley (Hordeum vulgare L.). Doctoral dissertation, Universitäts-und Landesbibliothek, Bonn, Germany.
Sayed MA, Schumann H, Pillen K, Naz AA. Léon J. 2012. AB-QTL analysis reveals new alleles associated to proline accumulation and leaf wilting under drought stress conditions in barley (Hordeum vulgare L.). BMC Genet. 13: 1-12. https://doi.org/10.1186/1471-2156-13-61
Sayre-Chavez B, Bettenhausen H, Windes S, Aron P, Cistué L, Fisk S, Helgerson L, Heuberger AL, Tynan S, Hayes P, Muñoz-Amatriaín M. 2022. Genetic basis of barley contributions to beer flavor. J Cereal Sci. 104: 103430. https://doi.org/10.1016/j.jcs.2022.103430
Sethi M, Saini DK, Devi V, Kaur C, Singh MP, Singh J, Pruthi G, Kaur A, Singh A, Chaudhary DP. 2023. Unravelling the genetic framework associated with grain quality and yield-related traits in maize (Zea mays L.). Front Genet. 14: 1248697. https://doi.org/10.3389/fgene.2023.1248697
Shavrukov Y, Gupta NK, Miyazaki J, Baho MN, Chalmers KJ, Tester M, Langridge P, Collins NC. 2010. HvNax3—a locus controlling shoot sodium exclusion derived from wild barley (Hordeum vulgare ssp. spontaneum). Funct Integr Genomics. 10: 277-291. https://doi.org/10.1007/s10142-009-0153-8
Sheoran S, Gupta M, Kumari S, Kumar S, Rakshit S. 2022. MQTL analysis and candidate genes identification for various abiotic stresses in maize (Zea mays L) and their implications in breeding programs. Mol Breed. 42(5): 26. https://doi.org/10.1007/s11032-022-01293-w
Skinner JS, Szűcs P, von-Zitzewitz J, Marquez-Cedillo L, Filichkin T, Stockinger EJ, Thomashow MF, Chen TH, Hayes PM. 2006. Mapping of barley homologs to genes that regulate low temperature tolerance in Arabidopsis. Theor Appl Genet. 112: 832-842. https://doi.org/10.1007/s00122-005-0185-y
Sopanen T, Laurière C. 1989. Release and activity of bound β-amylase in a germinating barley grain. Plant Physiol. 89(1): 244-249. https://doi.org/10.1104/pp.89.1.244
Sosnowski O, Charcosset A, Joets J. 2012. BioMercator V3: an upgrade of genetic map compilation and quantitative trait loci meta-analysis algorithms. Bioinformatics. 28(15): 2082-2083. https://doi.org/10.1093/bioinformatics/bts313
Stavert JR, Bailey C, Kirkland L, Rader R. 2020. Pollen tube growth from multiple pollinator visits more accurately quantifies pollinator performance and plant reproduction. Sci Rep. 10(1): 16958. https://doi.org/10.1038/s41598-020-73883-7
Stewart S, Sanders R, Ivanova N, Wilkinson KL, Stewart DC, Dong J, Hu S, Evans DE, Able JA. 2023. The influence of malt variety and origin on Wort  flavor. J Am Soc Brew Chem. 81(2): 282-298. https://doi.org/10.1080/03610470.2022.2159916
Szűcs P, Blake VC, Bhat PR, Chao S, Close TJ, Cuesta‐Marcos A, Muehlbauer GJ, Ramsay L, Waugh R, Hayes PM. 2009. An integrated resource for barley linkage map and malting quality QTL alignment. Plant Genome. 2(2). https://doi.org/10.3835/plantgenome2008.01.0005
Tanin MJ, Saini DK, Sandhu KS, Pal N, Gudi S, Chaudhary J, Sharma A. 2022. Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding. Sci Rep. 12(1): 13680. https://doi.org/10.1038/s41598-022-18149-0
Tosh SM, Bordenave N. 2020. Emerging science on benefits of whole grain oat and barley and their soluble dietary fibers for heart health, glycemic response, and gut microbiota. Nutrition reviews. Nutr Rev. 78(Suppl_1): 13-20. https://doi.org/10.1093/nutrit/nuz085
Tura AG, Abera S, Olika BD, Chalcisa T. 2020. Effects of Germination Temperature and Time on Malt Quality of Temash Barley (Hordeum vulgare L.). J Food Nutr Sci. 8(3): 63-73
Varshney RK, Marcel TC, Ramsay L, Russell J, Röder MS, Stein N, Waugh R. Langridge P., Niks RE, Graner A. 2007. A high density barley microsatellite consensus map with 775 SSR loci. Theor Appl Genet. 114: 1091-1103. https://doi.org/10.1007/s00122-007-0503-7
Veyrieras JB, Goffinet B, Charcosset A.2007. MetaQTL: a package of new computational methods for the meta-analysis of QTL mapping experiments. BMC Bioinformatics. 8: 1-16. https://doi.org/10.1186/1471-2105-8-49
von Korff M, Wang H, Léon J, Pillen K. 2008. AB-QTL analysis in spring barley: III. Identification of exotic alleles for the improvement of malting quality in spring barley (H. vulgare ssp. spontaneum). Mol Breed. 21: 81-93. https://doi.org/10.1007/s11032-007-9112-z
Walker CK, Ford R, Muñoz-Amatriaín M, Panozzo JF. 2013. The detection of QTLs in barley associated with endosperm hardness, grain density, grain size and malting quality using rapid phenotyping tools. Theor Appl Genet. 126: 2533-2551. https://doi.org/10.1007/s00122-013-2154-1
Wang J, Yang J, Hua W, Wu X, Zhu J, Shang Y, Zhou M. 2018. QTL mapping reveals the relationship between pasting properties and malt extract in barley. Int J Mol Sci. 19(11): 3559. https://doi.org/10.3390/ijms19113559
Wang W, Ren Z, Li L, Du Y, Zhou Y, Zhang M, Li Z, Yi F, Duan L. 2022. MQTL analysis explores the key genes, especially hormone related genes, involved in the regulation of grain water content and grain dehydration rate in maize. BMC Plant Biol. 22: 346. https://doi.org/10.1186/s12870-022-03727-1
Wenzl P, Li H, Carling J, Zhou M, Raman H, Paul E, Hearnden P, Maier C, Xia L, Caig V, Ovesná J. 2006. A high-density consensus map of barley linking DArT markers to SSR, RFLP and STS loci and agricultural traits. BMC Genomics. 7: 1-22. https://doi.org/10.1186/1471-2164-7-206
Xu R, Wang J, Li C, Johnson P, Lu C, Zhou M. 2012. A single locus is responsible for salinity tolerance in a Chinese landrace barley (Hordeum vulgare L.). PLoS One. 7(8): e43079. https://doi.org/10.1371/journal.pone.0043079
Xue D., Huang Y, Zhang X, Wei K, Westcott S, Li C, Chen M, Zhang G, Lance R. 2009. Identification of QTLs associated with salinity tolerance at late growth stage in barley. Euphytica. 169 : 187-196. https://doi.org/10.1007/s10681-009-9919-2
Xue DW, Zhou MX, Zhang XQ, Chen S, Wei K, Zeng FR, Mao Y, Wu FB, Zhang GP. 2010. Identification of QTLs for yield and yield components of barley under different growth conditions. J Zhejiang Univ Sci B. 11(3): 169-176. https://doi.org/10.1631/jzus.B0900334
Xue W, Yan J, Zhao G, Jiang Y, Cheng J, Cattivelli L, Tondelli A. 2017. A major QTL on chromosome 7HS controls the response of barley seedling to salt stress in the Nure× Tremois population. BMC Genet. 18: 1-15. https://doi.org/10.1186/s12863-017-0496-4
Yang L, Mickelson S, See D, Blake TK, Fischer AM. 2004. Genetic analysis of the function of major leaf proteases in barley (Hordeum vulgare L.) nitrogen remobilization. J Exp Bot. 55(408): 2607-2616. https://doi.org/10.1093/jxb/erh261
Yin C, Zhang GP, Wang JM, Chen JX. 2002. Variation of beta-amylase activity in barley as affected by cultivar and environment and its relation to protein content and grain weight. J Cereal Sci. 36(3): 307-312. https://doi.org/10.1006/jcrs.2002.0467
Yousif AM, Evans DE. 2020. Changes in malt quality during production in two commercial malt houses. J Inst Brew. 126(3): 233-252. https://doi.org/10.1002/jib.607
Zhang X, Shabala S, Koutoulis A, Shabala L, Zhou M. 2017. Meta-analysis of major QTL for abiotic stress tolerance in barley and implications for barley breeding.  Planta. 245: 283-295. https://doi.org/10.1007/s00425-016-2603-6
Zhou MX. 2009. Barley production and consumption. In: Zhang G, Li C (eds.) Genetics and improvement of barley malt quality. Advanced Topics in Science and Technology in China. Berlin, Heidelberg: Springer, pp. 1-17. https://doi.org/10.1007/978-3-642-01279-2_1
Zhou G, Johnson P, Ryan PR, Delhaize E, Zhou M. 2012a. Quantitative trait loci for salinity tolerance in barley (Hordeum vulgare L.). Mol Breed. 29: 427-436. https://doi.org/10.1007/s11032-011-9559-9
Zhou M, Johnson P, Zhou G, Li C, Lance R. 2012b. Quantitative trait loci for waterlogging tolerance in a barley cross of Franklin× YuYaoXiangTian Erleng and the relationship between waterlogging and salinity tolerance. Crop Sci. 52(5): 2082-2088. https://doi.org/10.2135/cropsci2011.12.0636
 Zhou TS, Takashi I, Ryouichi K, Naohiko H, Makoto K, Takehiro H, Kazuhiro S. 2012c. Malting quality quantitative trait loci on a high-density map of Mikamo golden× Harrington cross in barley (Hordeum vulgare L.). Mol Breed. 30: 103-112. https://doi.org/10.1007/s11032-011-9604-8
Zhou G, Zhang Q, Tan C, Zhang XQ, Li C. 2015. Development of genome-wide InDel markers and their integration with SSR, DArT and SNP markers in single barley map. BMC Genomics.16: 1-8. https://doi.org/10.1186/s12864-015-1497-1
 Zhou G, Panozzo J, Zhang XQ, Cakir M, Harasymow S, Li C. 2016. QTL mapping reveals genetic architectures of malting quality between Australian and Canadian malting barley (Hordeum vulgare L.). Mol Breed. 36: 1-12. https://doi.org/10.1007/s11032-016-0460-4
 
 
Journal of Plant Physiology and Breeding
Volume 15, Issue 2
December 2025
Pages 373-410

Files

Share

How to cite

Statistics