Additional file 2 of Genome‑wide association study and genomic prediction for growth traits in yellow-plumage chicken using genotyping-by-sequencing Article Swipe

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Ruifei Yang , Zhenqiang Xu , Qi Wang , Di Zhu , Cheng Bian , Jiangli Ren , Zhuolin Huang , Xiaoning Zhu , Zhixin Tian , Yuzhe Wang , Zi-Qin Jiang , Yiqiang Zhao , Dexiang Zhang , Ning Li , Xiaoxiang Hu ·

YOU? · · 2021 · Open Access · · DOI: https://doi.org/10.6084/m9.figshare.16893115

Additional file 2: Table S1. Information on the significant SNPs associated with 42 DW in the QTL region on chromosome 4. The data present the genomic location, effect, heritability, P value, and functional annotation of each GWAS significant SNP associated with 42 DW on chromosome 4. Table S2. Information on the significant SNPs associated with 84 DW in the QTL region on chromosome 4. The data present the genomic location, effect, heritability, P value, and functional annotation of each GWAS significant SNP associated with 84 DW on chromosome 4. Table S3. Information on the significant SNPs associated with ADG in the QTL region on chromosome 4. The data present the genomic location, effect, heritability, P value, and functional annotation of each GWAS significant SNP associated with ADG on chromosome 4. Table S4. Information on the significant SNPs associated with FCR in the QTL region on chromosome 4. The data present the genomic location, effect, heritability, P value, and functional annotation of each GWAS significant SNP associated with FCR on chromosome 4. Table S5. Average prediction inflation based on tenfold cross-validation. The data provide the average prediction inflation using ABLUP, GBLUP or GFBLUP models. Table S6. QTL contributions to the theoretical prediction accuracy (%). Description: The contributions were estimated by setting GWAS significant SNPs in each QTL as fixed factors. Table S7. Average prediction inflation addition after setting GWAS significant SNPs as fixed factors. The average prediction inflation changes after setting GWAS significant SNPs as fixed factors, where values approaching 0 represent lower inflations. Table S8. QTL contributions to heritability and observed prediction accuracy (%) using the GFBLUP model. The contributions were evaluated by estimating the contribution of two GRM using the GFBLUP model. Table S9. Average theoretical prediction accuracy using two GRM in the GFBLUP model. The data provide the average theoretical accuracy of prediction based on the GRM of GWAS significant sites and the remaining sites, respectively. Table S10. Average prediction inflation addition in the GFBLUP model. The changes in average prediction inflation evaluated by using the GRM without GWAS significant SNPs compared to that using both GRM, where values approaching 0 represent lower inflations.

Related Topics

Biology

Genome-Wide Association Study

Computational Biology

Zoology

Concepts

Plumage Genotyping Biology Genome-wide association study Genetics Computational biology Genome Gene Genotype Single-nucleotide polymorphism Zoology

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Type: dataset
Language: en
Landing Page: https://doi.org/10.6084/m9.figshare.16893115
OA Status: gold
References: 72
Related Works: 10
OpenAlex ID: https://openalex.org/W4394169230

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Title: Additional file 2 of Genome‑wide association study and genomic prediction for growth traits in yellow-plumage chicken using genotyping-by-sequencing

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Publication year: 2021

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Authors: Ruifei Yang, Zhenqiang Xu, Qi Wang, Di Zhu, Cheng Bian, Jiangli Ren, Zhuolin Huang, Xiaoning Zhu, Zhixin Tian, Yuzhe Wang, Zi-Qin Jiang, Yiqiang Zhao, Dexiang Zhang, Ning Li, Xiaoxiang Hu

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Concepts: Plumage, Genotyping, Biology, Genome-wide association study, Genetics, Computational biology, Genome, Gene, Genotype, Single-nucleotide polymorphism, Zoology

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abstract_inverted_index.effect,	27, 70, 112, 153
abstract_inverted_index.genomic	25, 68, 110, 151
abstract_inverted_index.models.	192
abstract_inverted_index.present	23, 66, 108, 149
abstract_inverted_index.provide	182, 298
abstract_inverted_index.setting	209, 226, 239
abstract_inverted_index.tenfold	178
abstract_inverted_index.without	339
abstract_inverted_index.accuracy	201, 262, 288, 302
abstract_inverted_index.addition	224, 323
abstract_inverted_index.compared	343
abstract_inverted_index.factors,	245
abstract_inverted_index.factors.	218, 232
abstract_inverted_index.observed	260
abstract_inverted_index.estimated	207
abstract_inverted_index.evaluated	271, 334
abstract_inverted_index.inflation	175, 186, 223, 236, 322, 333
abstract_inverted_index.location,	26, 69, 111, 152
abstract_inverted_index.remaining	315
abstract_inverted_index.represent	250, 353
abstract_inverted_index.Additional	0
abstract_inverted_index.annotation	33, 76, 118, 159
abstract_inverted_index.associated	10, 39, 53, 82, 96, 124, 137, 165
abstract_inverted_index.chromosome	19, 44, 62, 87, 104, 128, 145, 169
abstract_inverted_index.estimating	273
abstract_inverted_index.functional	32, 75, 117, 158
abstract_inverted_index.prediction	174, 185, 200, 222, 235, 261, 287, 304, 321, 332
abstract_inverted_index.Information	5, 48, 91, 132
abstract_inverted_index.approaching	248, 351
abstract_inverted_index.inflations.	252, 355
abstract_inverted_index.significant	8, 37, 51, 80, 94, 122, 135, 163, 211, 228, 241, 311, 341
abstract_inverted_index.theoretical	199, 286, 301
abstract_inverted_index.Description:	203
abstract_inverted_index.contribution	275
abstract_inverted_index.heritability	258
abstract_inverted_index.contributions	196, 205, 256, 269
abstract_inverted_index.heritability,	28, 71, 113, 154
abstract_inverted_index.respectively.	317
abstract_inverted_index.cross-validation.	179
cited_by_percentile_year
countries_distinct_count	0
institutions_distinct_count	15
citation_normalized_percentile