Mega Meta-QTLs: A Strategy for the Production of Golden Barley ( L.) Tolerant to Abiotic Stresses

Overview

Journal Genes (Basel)

Publisher MDPI

Date 2022 Nov 11

PMID 36360327

Authors

Mahjoubeh Akbari

Hossein Sabouri

Sayed Javad Sajadi

Saeed Yarahmadi

Leila Ahangar

Amin Abedi

Mahnaz Katouzi

Affiliations

Soon will be listed here.

Abstract

Abiotic stresses cause a significant decrease in productivity and growth in agricultural products, especially barley. Breeding has been considered to create resistance against abiotic stresses. Pyramiding genes for tolerance to abiotic stresses through selection based on molecular markers connected to Mega MQTLs of abiotic tolerance can be one of the ways to reach Golden Barley. In this study, 1162 original QTLs controlling 116 traits tolerant to abiotic stresses were gathered from previous research and mapped from various populations. A consensus genetic map was made, including AFLP, SSR, RFLP, RAPD, SAP, DArT, EST, CAPS, STS, RGA, IFLP, and SNP markers based on two genetic linkage maps and 26 individual linkage maps. Individual genetic maps were created by integrating individual QTL studies into the pre-consensus map. The consensus map covered a total length of 2124.43 cM with an average distance of 0.25 cM between markers. In this study, 585 QTLs and 191 effective genes related to tolerance to abiotic stresses were identified in MQTLs. The most overlapping QTLs related to tolerance to abiotic stresses were observed in MQTL6.3. Furthermore, three MegaMQTL were identified, which explained more than 30% of the phenotypic variation. MQTLs, candidate genes, and linked molecular markers identified are essential in barley breeding and breeding programs to develop produce cultivars resistant to abiotic stresses.

Citing Articles

Unravelling drought and salinity stress responses in barley genotypes: physiological, biochemical, and molecular insights.

Alsamadany H, Abdulbaki A, Alzahrani Y Front Plant Sci. 2024; 15:1417021.

PMID: 39049857 PMC: 11266107. DOI: 10.3389/fpls.2024.1417021.

Genome-wide screening of meta-QTL and candidate genes controlling yield and yield-related traits in barley (Hordeum vulgare L.).

Du B, Wu J, Wang Q, Sun C, Sun G, Zhou J PLoS One. 2024; 19(5):e0303751.

PMID: 38768114 PMC: 11104655. DOI: 10.1371/journal.pone.0303751.

Detection of consensus genomic regions and candidate genes for quality traits in barley using QTL meta-analysis.

Du B, Wu J, Wang M, Wu J, Sun C, Zhang X Front Plant Sci. 2024; 14:1319889.

PMID: 38283973 PMC: 10811794. DOI: 10.3389/fpls.2023.1319889.

Unravelling the genetic framework associated with grain quality and yield-related traits in maize ( L.).

Sethi M, Saini D, Devi V, Kaur C, Singh M, Singh J Front Genet. 2023; 14:1248697.

PMID: 37609038 PMC: 10440565. DOI: 10.3389/fgene.2023.1248697.

References

Sbei H, Sato K, Shehzad T, Harrabi M, Okuno K . Detection of QTLs for salt tolerance in Asian barley (Hordeum vulgare L.) by association analysis with SNP markers. Breed Sci. 2015; 64(4):378-88. PMC: 4267313. DOI: 10.1270/jsbbs.64.378. View

Ramsay L, MacAulay M, Degli Ivanissevich S, MacLean K, Cardle L, Fuller J . A simple sequence repeat-based linkage map of barley. Genetics. 2000; 156(4):1997-2005. PMC: 1461369. DOI: 10.1093/genetics/156.4.1997. View

Varshney R, Marcel T, Ramsay L, Russell J, Roder M, Stein N . A high density barley microsatellite consensus map with 775 SSR loci. Theor Appl Genet. 2007; 114(6):1091-103. DOI: 10.1007/s00122-007-0503-7. View

Sosnowski O, Charcosset A, Joets J . BioMercator V3: an upgrade of genetic map compilation and quantitative trait loci meta-analysis algorithms. Bioinformatics. 2012; 28(15):2082-3. PMC: 3400960. DOI: 10.1093/bioinformatics/bts313. View

Sato K, Nankaku N, Takeda K . A high-density transcript linkage map of barley derived from a single population. Heredity (Edinb). 2009; 103(2):110-7. DOI: 10.1038/hdy.2009.57. View

Sakurai T, Kataoka K . Basic and applied features of multicopper oxidases, CueO, bilirubin oxidase, and laccase. Chem Rec. 2007; 7(4):220-9. DOI: 10.1002/tcr.20125. View

Li H, Vaillancourt R, Mendham N, Zhou M . Comparative mapping of quantitative trait loci associated with waterlogging tolerance in barley (Hordeum vulgare L.). BMC Genomics. 2008; 9:401. PMC: 2533678. DOI: 10.1186/1471-2164-9-401. View

Gurel F, Ozturk Z, Ucarli C, Rosellini D . Barley Genes as Tools to Confer Abiotic Stress Tolerance in Crops. Front Plant Sci. 2016; 7:1137. PMC: 4971604. DOI: 10.3389/fpls.2016.01137. View

Kidwai M, Ahmad I, Chakrabarty D . Class III peroxidase: an indispensable enzyme for biotic/abiotic stress tolerance and a potent candidate for crop improvement. Plant Cell Rep. 2020; 39(11):1381-1393. DOI: 10.1007/s00299-020-02588-y. View

10.

Lopes-Caitar V, de Carvalho M, Darben L, Kuwahara M, Nepomuceno A, Dias W . Genome-wide analysis of the Hsp20 gene family in soybean: comprehensive sequence, genomic organization and expression profile analysis under abiotic and biotic stresses. BMC Genomics. 2013; 14:577. PMC: 3852298. DOI: 10.1186/1471-2164-14-577. View

11.

Diab A, Teulat-Merah B, This D, Ozturk N, Benscher D, Sorrells M . Identification of drought-inducible genes and differentially expressed sequence tags in barley. Theor Appl Genet. 2004; 109(7):1417-25. DOI: 10.1007/s00122-004-1755-0. View

12.

Francia E, Rizza F, Cattivelli L, Stanca A, Galiba G, Toth B . Two loci on chromosome 5H determine low-temperature tolerance in a 'Nure' (winter) x 'Tremois' (spring) barley map. Theor Appl Genet. 2003; 108(4):670-80. DOI: 10.1007/s00122-003-1468-9. View

13.

Han M, Wong J, Su T, Beatty P, Good A . Identification of Nitrogen Use Efficiency Genes in Barley: Searching for QTLs Controlling Complex Physiological Traits. Front Plant Sci. 2016; 7:1587. PMC: 5073129. DOI: 10.3389/fpls.2016.01587. View

14.

Wang M, Yuan J, Qin L, Shi W, Xia G, Liu S . TaCYP81D5, one member in a wheat cytochrome P450 gene cluster, confers salinity tolerance via reactive oxygen species scavenging. Plant Biotechnol J. 2019; 18(3):791-804. PMC: 7004906. DOI: 10.1111/pbi.13247. View

15.

Dracatos P, Haghdoust R, Singh R, Espino J, Barnes C, Forrest K . High-Density Mapping of Triple Rust Resistance in Barley Using DArT-Seq Markers. Front Plant Sci. 2019; 10:467. PMC: 6498947. DOI: 10.3389/fpls.2019.00467. View

16.

Bian M, Jin X, Broughton S, Zhang X, Zhou G, Zhou M . A new allele of acid soil tolerance gene from a malting barley variety. BMC Genet. 2015; 16:92. PMC: 4518660. DOI: 10.1186/s12863-015-0254-4. View

17.

Tripathi R, Aguirre J, Singh J . Genome-wide analysis of wall associated kinase (WAK) gene family in barley. Genomics. 2020; 113(1 Pt 2):523-530. DOI: 10.1016/j.ygeno.2020.09.045. View

18.

Tong C, Hill C, Zhou G, Zhang X, Jia Y, Li C . Opportunities for Improving Waterlogging Tolerance in Cereal Crops-Physiological Traits and Genetic Mechanisms. Plants (Basel). 2021; 10(8). PMC: 8401455. DOI: 10.3390/plants10081560. View

19.

Shavrukov Y, Gupta N, Miyazaki J, Baho M, Chalmers K, Tester M . HvNax3--a locus controlling shoot sodium exclusion derived from wild barley (Hordeum vulgare ssp. spontaneum). Funct Integr Genomics. 2010; 10(2):277-91. DOI: 10.1007/s10142-009-0153-8. View

20.

Etesami H, Jeong B . Silicon (Si): Review and future prospects on the action mechanisms in alleviating biotic and abiotic stresses in plants. Ecotoxicol Environ Saf. 2017; 147:881-896. DOI: 10.1016/j.ecoenv.2017.09.063. View