Soorni J, Loni F, Daryani P, Amirbakhtiar N, Pourhang L, Pouralibaba H
Plant Genome. 2025; 18(1):e70004.
PMID: 40050693
PMC: 11885688.
DOI: 10.1002/tpg2.70004.
Vieira R, Nogueira A, Fritsche-Neto R
Front Plant Sci. 2025; 16:1495662.
PMID: 39996117
PMC: 11847808.
DOI: 10.3389/fpls.2025.1495662.
Viviani A, Haile J, Fernando W, Ceoloni C, Kuzmanovic L, Lhamo D
Plant Genome. 2025; 18(1):e20539.
PMID: 39757924
PMC: 11701714.
DOI: 10.1002/tpg2.20539.
Tan C, Guo X, Dong H, Li M, Chen Q, Cheng M
Front Plant Sci. 2024; 15:1499055.
PMID: 39737382
PMC: 11682887.
DOI: 10.3389/fpls.2024.1499055.
Fang Z, Peltz G
Lab Anim (NY). 2024; 54(1):9-15.
PMID: 39592878
PMC: 11695262.
DOI: 10.1038/s41684-024-01491-3.
GWAS and Meta-QTL Analysis of Kernel Quality-Related Traits in Maize.
Tang R, Zhuang Z, Bian J, Ren Z, Ta W, Peng Y
Plants (Basel). 2024; 13(19).
PMID: 39409600
PMC: 11479128.
DOI: 10.3390/plants13192730.
Independent genetic factors control floret number and spikelet number in ssp.
A Y K, E M, R B, E M, M D, L C
Front Plant Sci. 2024; 15:1390401.
PMID: 39253571
PMC: 11381284.
DOI: 10.3389/fpls.2024.1390401.
Refinement of rice blast disease resistance QTLs and gene networks through meta-QTL analysis.
Devanna B, Sucharita S, Sunitha N, Anilkumar C, Singh P, Pramesh D
Sci Rep. 2024; 14(1):16458.
PMID: 39013915
PMC: 11252161.
DOI: 10.1038/s41598-024-64142-0.
Unraveling the genetic basis of quantitative resistance to diseases in tomato: a meta-QTL analysis and mining of transcript profiles.
Khojasteh M, Darzi Ramandi H, Taghavi S, Taheri A, Rahmanzadeh A, Chen G
Plant Cell Rep. 2024; 43(7):184.
PMID: 38951262
DOI: 10.1007/s00299-024-03268-x.
QTL Analysis of β-Glucan Content and Other Grain Traits in a Recombinant Population of Spring Barley.
Gianinetti A, Ghizzoni R, Desiderio F, Morcia C, Terzi V, Baronchelli M
Int J Mol Sci. 2024; 25(12).
PMID: 38928003
PMC: 11204098.
DOI: 10.3390/ijms25126296.
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.
Meta QTL analysis for dissecting abiotic stress tolerance in chickpea.
Panigrahi S, Kumar U, Swami S, Singh Y, Balyan P, Singh K
BMC Genomics. 2024; 25(1):439.
PMID: 38698307
PMC: 11067088.
DOI: 10.1186/s12864-024-10336-9.
Meta-Quantitative Trait Loci Analysis and Candidate Gene Mining for Drought Tolerance-Associated Traits in Maize ( L.).
Li R, Wang Y, Li D, Guo Y, Zhou Z, Zhang M
Int J Mol Sci. 2024; 25(8).
PMID: 38673880
PMC: 11049847.
DOI: 10.3390/ijms25084295.
Integrated meta-analysis and transcriptomics pinpoint genomic loci and novel candidate genes associated with submergence tolerance in rice.
Aloryi K, Okpala N, Guo H, Karikari B, Amo A, Bello S
BMC Genomics. 2024; 25(1):338.
PMID: 38575927
PMC: 10993490.
DOI: 10.1186/s12864-024-10219-z.
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.
Uncovering the Genomic Regions Associated with Yield Maintenance in Rice Under Drought Stress Using an Integrated Meta-Analysis Approach.
Daryani P, Amirbakhtiar N, Soorni J, Loni F, Darzi Ramandi H, Shobbar Z
Rice (N Y). 2024; 17(1):7.
PMID: 38227151
PMC: 10792158.
DOI: 10.1186/s12284-024-00684-1.
High confidence QTLs and key genes identified using Meta-QTL analysis for enhancing heat tolerance in chickpea ( L.).
Kumar R, Sharma V, Rangari S, Jha U, Sahu A, Paul P
Front Plant Sci. 2023; 14:1274759.
PMID: 37929162
PMC: 10623133.
DOI: 10.3389/fpls.2023.1274759.
Mapping of QTLs and meta-QTLs for Heterodera avenae Woll. resistance in common wheat (Triticum aestivum L.).
Pundir S, Singh R, Singh V, Sharma S, Balyan H, Gupta P
BMC Plant Biol. 2023; 23(1):529.
PMID: 37904124
PMC: 10617160.
DOI: 10.1186/s12870-023-04526-y.
QTL mapping for kernel-related traits in a durum wheat x . segregating population.
Valladares Garcia A, Desiderio F, Simeone R, Ravaglia S, Ciorba R, Fricano A
Front Plant Sci. 2023; 14:1253385.
PMID: 37849841
PMC: 10577384.
DOI: 10.3389/fpls.2023.1253385.
A meta-QTL analysis highlights genomic hotspots associated with phosphorus use efficiency in rice ( L.).
Navea I, Maung P, Yang S, Han J, Jing W, Shin N
Front Plant Sci. 2023; 14:1226297.
PMID: 37662146
PMC: 10471825.
DOI: 10.3389/fpls.2023.1226297.