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For: Lam S, Miglior F, Fonseca PAS, Gómez-Redondo I, Zeidan J, Suárez-Vega A, Schenkel F, Guan LL, Waters S, Stothard P, Cánovas A. Identification of functional candidate variants and genes for feed efficiency in Holstein and Jersey cattle breeds using RNA-sequencing. J Dairy Sci 2021;104:1928-50. [PMID: 33358171 DOI: 10.3168/jds.2020-18241] [Cited by in Crossref: 10] [Cited by in F6Publishing: 11] [Article Influence: 5.0] [Reference Citation Analysis]
Number Citing Articles
1 Esmaeili M, Carter CG, Wilson R, Walker SP, Miller MR, Bridle AR, Young T, Alfaro AC, Laroche O, Symonds JE. An integrated proteomics and metabolomics investigation of feed efficiency in seawater reared Chinook salmon (Oncorhynchus tshawytscha). Aquaculture 2023;562:738845. [DOI: 10.1016/j.aquaculture.2022.738845] [Reference Citation Analysis]
2 Olasege BS, Porto-Neto LR, Tahir MS, Gouveia GC, Cánovas A, Hayes BJ, Fortes MRS. Correlation scan: identifying genomic regions that affect genetic correlations applied to fertility traits. BMC Genomics 2022;23:684. [PMID: 36195838 DOI: 10.1186/s12864-022-08898-7] [Reference Citation Analysis]
3 Lindholm-Perry AK, Meyer AM, Kern-Lunbery RJ, Cunningham-Hollinger HC, Funk TH, Keel BN. Genes Involved in Feed Efficiency Identified in a Meta-Analysis of Rumen Tissue from Two Populations of Beef Steers. Animals (Basel) 2022;12:1514. [PMID: 35739852 DOI: 10.3390/ani12121514] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
4 Pezeshkian Z, Mirhoseini SZ, Ghovvati S, Ebrahimie E. Transcriptome Analysis of Breast Muscle Reveals Pathways Related to Protein Deposition in High Feed Efficiency of Native Turkeys. Animals 2022;12:1240. [DOI: 10.3390/ani12101240] [Reference Citation Analysis]
5 Asselstine V, Medrano JF, Cánovas A. Identification of novel alternative splicing associated with mastitis disease in Holstein dairy cows using large gap read mapping. BMC Genomics 2022;23. [DOI: 10.1186/s12864-022-08430-x] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
6 Yang C, Zhu Y, Ding Y, Huang Z, Dan X, Shi Y, Kang X. Identifying the key genes and functional enrichment pathways associated with feed efficiency in cattle. Gene 2022;807:145934. [PMID: 34478820 DOI: 10.1016/j.gene.2021.145934] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
7 Fonseca PAS, Caldwell T, Mandell I, Wood K, Cánovas A. Genome-wide association study for meat tenderness in beef cattle identifies patterns of the genetic contribution in different post-mortem stages. Meat Sci 2022;186:108733. [PMID: 35007800 DOI: 10.1016/j.meatsci.2022.108733] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
8 Fonseca PAS, Schenkel FS, Cánovas A. Genome-wide association study using haplotype libraries and repeated measures model to identify candidate genomic regions for stillbirth in Holstein cattle. J Dairy Sci 2022:S0022-0302(21)01117-6. [PMID: 34998559 DOI: 10.3168/jds.2021-20936] [Reference Citation Analysis]
9 Olasege BS, Porto-neto LR, Tahir MS, Gouveia GC, Cánovas A, Hayes BJ, Fortes MRS. Correlation scan: identifying genomic regions that affect genetic correlations applied to fertility traits.. [DOI: 10.1101/2021.11.05.467409] [Reference Citation Analysis]
10 Asselstine V, Lam S, Miglior F, Brito LF, Sweett H, Guan L, Waters SM, Plastow G, Cánovas A. The potential for mitigation of methane emissions in ruminants through the application of metagenomics, metabolomics, and other -OMICS technologies. J Anim Sci 2021;99:skab193. [PMID: 34586400 DOI: 10.1093/jas/skab193] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]