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For: Yoshida GM, Yáñez JM. Multi-trait GWAS using imputed high-density genotypes from whole-genome sequencing identifies genes associated with body traits in Nile tilapia. BMC Genomics 2021;22:57. [PMID: 33451291 DOI: 10.1186/s12864-020-07341-z] [Cited by in Crossref: 22] [Cited by in F6Publishing: 24] [Article Influence: 11.0] [Reference Citation Analysis]
Number Citing Articles
1 Nosková A, Mehrotra A, Kadri NK, Lloret-villas A, Neuenschwander S, Hofer A, Pausch H. Comparison of two multi-trait association testing methods and sequence-based fine mapping of six QTL in Swiss Large White pigs.. [DOI: 10.21203/rs.3.rs-2377700/v1] [Reference Citation Analysis]
2 Lu Y, Yu Y, Fu Y, Yu Y, Tang M, Sun Y, Wang Y, Zhang K, Li H, Guo H, Wang B, Wang N. Investigating the shared genetic architecture between schizophrenia and obesity.. [DOI: 10.21203/rs.3.rs-2452107/v1] [Reference Citation Analysis]
3 Valette T, Leitwein M, Lascaux JM, Desmarais E, Berrebi P, Guinand B. Redundancy analysis, genome-wide association studies and the pigmentation of brown trout (Salmo trutta L.). J Fish Biol 2023;102:96-118. [PMID: 36218076 DOI: 10.1111/jfb.15243] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
4 Sánchez-Roncancio C, García B, Gallardo-Hidalgo J, Yáñez JM. GWAS on Imputed Whole-Genome Sequence Variants Reveal Genes Associated with Resistance to Piscirickettsia salmonis in Rainbow Trout (Oncorhynchus mykiss). Genes (Basel) 2022;14. [PMID: 36672855 DOI: 10.3390/genes14010114] [Reference Citation Analysis]
5 Cappa EP, Chen C, Klutsch JG, Sebastian-azcona J, Ratcliffe B, Wei X, Da Ros L, Ullah A, Liu Y, Benowicz A, Sadoway S, Mansfield SD, Erbilgin N, Thomas BR, El-kassaby YA. Multiple-trait analyses improved the accuracy of genomic prediction and the power of genome-wide association of productivity and climate change-adaptive traits in lodgepole pine. BMC Genomics 2022;23. [DOI: 10.1186/s12864-022-08747-7] [Reference Citation Analysis]
6 Rocha LF, Benatti TR, de Siqueira L, de Souza ICG, Bianchin I, de Souza AJ, Fernandes ACM, Oda S, Stape JL, Yassue RM, Carvalho HF, Müller NA, Fladung M, Acosta JJ, Fritsche-neto R, Tambarussi EV. Quantitative trait loci related to growth and wood quality traits in Eucalyptus grandis W. Hill identified through single- and multi-trait genome-wide association studies. Tree Genetics & Genomes 2022;18. [DOI: 10.1007/s11295-022-01570-x] [Reference Citation Analysis]
7 Prchal M, D'ambrosio J, Lagarde H, Lallias D, Patrice P, François Y, Poncet C, Desgranges A, Haffray P, Dupont-nivet M, Phocas F. Genome-wide association study and genomic prediction of tolerance to acute hypoxia in rainbow trout. Aquaculture 2022. [DOI: 10.1016/j.aquaculture.2022.739068] [Reference Citation Analysis]
8 Selionova M, Aibazov M, Mamontova T, Malorodov V, Sermyagin A, Zinovyeva N, Easa AA. Genome-wide association study of live body weight and body conformation traits in young Karachai goats. Small Ruminant Research 2022;216:106836. [DOI: 10.1016/j.smallrumres.2022.106836] [Reference Citation Analysis]
9 Gao Y, Jiang G, Yang W, Jin W, Gong J, Xu X, Niu X. Animal-SNPAtlas: a comprehensive SNP database for multiple animals. Nucleic Acids Res 2023;51:D816-26. [PMID: 36300636 DOI: 10.1093/nar/gkac954] [Reference Citation Analysis]
10 Ros-freixedes R, Johnsson M, Whalen A, Chen C, Valente BD, Herring WO, Gorjanc G, Hickey JM. Genomic prediction with whole-genome sequence data in intensely selected pig lines. Genet Sel Evol 2022;54. [DOI: 10.1186/s12711-022-00756-0] [Reference Citation Analysis]
11 Marina H, Pelayo R, Gutiérrez-Gil B, Suárez-Vega A, Esteban-Blanco C, Reverter A, Arranz JJ. Low-density SNP panel for efficient imputation and genomic selection of milk production and technological traits in dairy sheep. J Dairy Sci 2022:S0022-0302(22)00472-6. [PMID: 36028350 DOI: 10.3168/jds.2021-21601] [Reference Citation Analysis]
12 Zhu X, Ni P, Sturrock M, Wang Y, Ding J, Chang Y, Hu J, Bao Z. Fine-mapping and association analysis of candidate genes for papilla number in sea cucumber, Apostichopus japonicus. Mar Life Sci Technol 2022;4:343-55. [DOI: 10.1007/s42995-022-00139-w] [Reference Citation Analysis]
13 Fraslin C, Koskinen H, Nousianen A, Houston RD, Kause A. Genome-wide association and genomic prediction of resistance to Flavobacterium columnare in a farmed rainbow trout population. Aquaculture 2022;557:738332. [DOI: 10.1016/j.aquaculture.2022.738332] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
14 Chen B, Xiao W, Zou Z, Zhu J, Li D, Yu J, Yang H. Comparing Transcriptomes Reveals Key Metabolic Mechanisms in Superior Growth Performance Nile Tilapia (Oreochromis niloticus). Front Genet 2022;13:879570. [DOI: 10.3389/fgene.2022.879570] [Reference Citation Analysis]
15 Patton AH, Richards EJ, Gould KJ, Buie LK, Martin CH. Hybridization alters the shape of the genotypic fitness landscape, increasing access to novel fitness peaks during adaptive radiation. Elife 2022;11:e72905. [PMID: 35616528 DOI: 10.7554/eLife.72905] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
16 Omeka W, Liyanage D, Lee S, Lim C, Yang H, Sandamalika WG, Udayantha H, Kim G, Ganeshalingam S, Jeong T, Oh S, Won S, Koh H, Kim M, Jones DB, Massault C, Jerry DR, Lee J. Genome-wide association study (GWAS) of growth traits in olive flounder (Paralichthys olivaceus). Aquaculture 2022. [DOI: 10.1016/j.aquaculture.2022.738257] [Reference Citation Analysis]
17 Nousias O, Oikonomou S, Manousaki T, Papadogiannis V, Angelova N, Tsaparis D, Tsakogiannis A, Duncan N, Estevez A, Tzokas K, Pavlidis M, Chatziplis D, Tsigenopoulos CS. Linkage mapping, comparative genome analysis, and QTL detection for growth in a non-model teleost, the meagre Argyrosomus regius, using ddRAD sequencing. Sci Rep 2022;12:5301. [PMID: 35351938 DOI: 10.1038/s41598-022-09289-4] [Cited by in Crossref: 2] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
18 Fraslin C, Koskinen H, Nousianen A, Houston RD, Kause A. Genome-wide association and genomic prediction of resistance to Flavobacterium columnare in a farmed rainbow trout population.. [DOI: 10.1101/2022.02.28.482244] [Reference Citation Analysis]
19 Sukhavachana S, Senanan W, Tunkijjanukij S, Poompuang S. Improving genomic prediction accuracy for harvest traits in Asian seabass (Lates calcarifer, Bloch 1790) via marker selection. Aquaculture 2022;550:737851. [DOI: 10.1016/j.aquaculture.2021.737851] [Cited by in Crossref: 1] [Cited by in F6Publishing: 4] [Article Influence: 1.0] [Reference Citation Analysis]
20 Garcia BF, Yoshida GM, Carvalheiro R, Yáñez JM. Accuracy of genotype imputation to whole genome sequencing level using different populations of Nile tilapia. Aquaculture 2022;551:737947. [DOI: 10.1016/j.aquaculture.2022.737947] [Reference Citation Analysis]
21 Gu B, Sun R, Fang X, Zhang J, Zhao Z, Huang D, Zhao Y, Zhao Y. Genome-Wide Association Study of Body Conformation Traits by Whole Genome Sequencing in Dazu Black Goats. Animals (Basel) 2022;12:548. [PMID: 35268118 DOI: 10.3390/ani12050548] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
22 Ros-freixedes R, Johnsson M, Whalen A, Chen C, Valente BD, Herring WO, Gorjanc G, Hickey JM. Genomic prediction with whole-genome sequence data in intensely selected pig lines.. [DOI: 10.1101/2022.02.02.478838] [Reference Citation Analysis]
23 Gui J, Zhou L, Li X. Rethinking fish biology and biotechnologies in the challenge era for burgeoning genome resources and strengthening food security. Water Biology and Security 2022;1:100002. [DOI: 10.1016/j.watbs.2021.11.001] [Cited by in Crossref: 19] [Cited by in F6Publishing: 22] [Article Influence: 19.0] [Reference Citation Analysis]
24 Oikonomou S, Samaras A, Tekeoglou M, Loukovitis D, Dimitroglou A, Kottaras L, Papanna K, Papaharisis L, Tsigenopoulos CS, Pavlidis M, Chatziplis D. Genomic Selection and Genome-Wide Association Analysis for Stress Response, Disease Resistance and Body Weight in European Seabass. Animals 2022;12:277. [DOI: 10.3390/ani12030277] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 5.0] [Reference Citation Analysis]
25 Li C, Duan D, Xue Y, Han X, Wang K, Qiao R, Li XL, Li XJ. An association study on imputed whole-genome resequencing from high-throughput sequencing data for body traits in crossbred pigs. Anim Genet 2022. [PMID: 35026054 DOI: 10.1111/age.13170] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
26 Barría A, Benzie JAH, Houston RD, De Koning DJ, de Verdal H. Genomic Selection and Genome-wide Association Study for Feed-Efficiency Traits in a Farmed Nile Tilapia (Oreochromis niloticus) Population. Front Genet 2021;12:737906. [PMID: 34616434 DOI: 10.3389/fgene.2021.737906] [Cited by in Crossref: 9] [Cited by in F6Publishing: 10] [Article Influence: 4.5] [Reference Citation Analysis]
27 Takahashi T, Nagano AJ, Sota T. Mapping of quantitative trait loci underlying a magic trait in ongoing ecological speciation. BMC Genomics 2021;22:615. [PMID: 34384356 DOI: 10.1186/s12864-021-07908-4] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
28 Palaiokostas C, Anjum A, Jeuthe H, Kurta K, Lopes Pinto F, Koning DJ. A genomic‐based vision on the genetic diversity and key performance traits in selectively bred Arctic charr ( Salvelinus alpinus ). Evol Appl. [DOI: 10.1111/eva.13261] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]