scholarly journals Effect of using different number and type of records from different generations as reference population on the accuracy of genomic evaluation

2013 ◽  
Vol 56 (1) ◽  
pp. 684-690
Author(s):  
A. Boustan ◽  
A. Nejati-Javaremi ◽  
M. M. Shahrbabak ◽  
M. Saatchi
Keyword(s):  
Finite Population ◽  
Random Mating ◽  
Reference Population ◽  
Breeding Value ◽  
Nucleotide Polymorphisms ◽  
Genomic Evaluation ◽  
Single Nucleotide ◽  
A Genome ◽  
Estimated Breeding Values ◽  
Marker Distance

Abstract. One important question about genomic evaluation is how distance between generations of individuals in reference population and selection candidates, would affect the accuracy of genomic estimated breeding value of selection candidates. There were two schemes in the present study. In first scheme, for each individual a genome consisting 30 chromosomes each with 100 equally spaced single nucleotide polymorphisms (SNPs) and in second scheme a genome consisting 3 chromosomes each with 1000 equally spaced SNPs was simulated. To generate enough linkage disequilibrium between loci, random mating for 50 generations was done in a finite population. In generation 51, population size was expanded to 250 individuals. This structure was continued until generation 55. Individuals in generation 55 were juvenile and did not have phenotypic records and were selection candidates. Heritability was assumed to be 0.3. Our results showed using information from more distant generations would decrease accuracy of genomic estimated breeding values of selection candidates but in scheme in which marker distance was 1 centimorgan, increasing generation number between reference population and selection candidates would decrease accuracy more than scheme in which marker distance was 0.1 centimorgan. According to our results using EBVs of reference population instead of phenotypic records would increase accuracy extremely.

scholarly journals Genomic selection in French dairy cattle

2012 ◽  
Vol 52 (3) ◽  
pp. 115 ◽  
Author(s):  
D. Boichard ◽  
F. Guillaume ◽  
A. Baur ◽  
P. Croiseau ◽  
M. N. Rossignol ◽  
...  
Keyword(s):  
Linkage Disequilibrium ◽  
Genomic Selection ◽  
Reference Population ◽  
Specific Reference ◽  
Nucleotide Polymorphisms ◽  
Genomic Evaluation ◽  
Linear Unbiased Prediction ◽  
Best Linear Unbiased ◽  
Estimated Breeding Values ◽  
Restricted Use

Genomic selection is implemented in French Holstein, Montbéliarde, and Normande breeds (70%, 16% and 12% of French dairy cows). A characteristic of the model for genomic evaluation is the use of haplotypes instead of single-nucleotide polymorphisms (SNPs), so as to maximise linkage disequilibrium between markers and quantitative trait loci (QTLs). For each trait, a QTL-BLUP model (i.e. a best linear unbiased prediction model including QTL random effects) includes 300–700 trait-dependent chromosomal regions selected either by linkage disequilibrium and linkage analysis or by elastic net. This model requires an important effort to phase genotypes, detect QTLs, select SNPs, but was found to be the most efficient one among all tested ones. QTLs are defined within breed and many of them were found to be breed specific. Reference populations include 1800 and 1400 bulls in Montbéliarde and Normande breeds. In Holstein, the very large reference population of 18 300 bulls originates from the EuroGenomics consortium. Since 2008, ~65 000 animals have been genotyped for selection by Labogena with the 50k chip. Bulls genomic estimated breeding values (GEBVs) were made official in June 2009. In 2010, the market share of the young bulls reached 30% and is expected to increase rapidly. Advertising actions have been undertaken to recommend a time-restricted use of young bulls with a limited number of doses. In January 2011, genomic selection was opened to all farmers for females. Current developments focus on the extension of the method to a multi-breed context, to use all reference populations simultaneously in genomic evaluation.

Bisphosphonate-related osteonecrosis of the jaw is associated with polymorphisms of the cytochrome P450 CYP2C8 in multiple myeloma: a genome-wide single nucleotide polymorphism analysis

Blood ◽  
2008 ◽  
Vol 112 (7) ◽  
pp. 2709-2712 ◽  
Author(s):  
Maria E. Sarasquete ◽  
Ramon García-Sanz ◽  
Luis Marín ◽  
Miguel Alcoceba ◽  
Maria C. Chillón ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Cytochrome P450 ◽  
Genome Wide Association Study ◽  
Osteonecrosis Of The Jaw ◽  
Bisphosphonate Therapy ◽  
Polymorphism Analysis ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Genome Wide ◽  
A Genome

Abstract We have explored the potential role of genetics in the development of osteonecrosis of the jaw (ONJ) in multiple myeloma (MM) patients under bisphosphonate therapy. A genome-wide association study was performed using 500 568 single nucleotide polymorphisms (SNPs) in 2 series of homogeneously treated MM patients, one with ONJ (22 MM cases) and another without ONJ (65 matched MM controls). Four SNPs (rs1934951, rs1934980, rs1341162, and rs17110453) mapped within the cytochrome P450-2C gene (CYP2C8) showed a different distribution between cases and controls with statistically significant differences (P = 1.07 × 10−6, P = 4.231 × 10−6, P = 6.22 × 10−6, and P = 2.15 × 10−6, respectively). SNP rs1934951 was significantly associated with a higher risk of ONJ development even after Bonferroni correction (P corrected value = .02). Genotyping results displayed an overrepresentation of the T allele in cases compared with controls (48% vs 12%). Thus, individuals homozygous for the T allele had an increased likelihood of developing ONJ (odds ratio 12.75, 95% confidence interval 3.7-43.5).

scholarly journals Haplotypes within tandemly duplicated candidate genes at BnaA9.MRP5 modulate phytate concentration in canola (Brassica napus L.)

2021 ◽  
Author(s):  
Haijiang Liu ◽  
xiaojuan Li ◽  
Qianwen Zhang ◽  
pan yuan ◽  
Lei Liu ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Oilseed Rape ◽  
Genome Wide Association Study ◽  
Mineral Elements ◽  
Nucleotide Polymorphisms ◽  
Brassica Napus L ◽  
Single Nucleotide ◽  
Genome Wide ◽  
A Genome ◽  
Phytate Content

Phytate is the storage form of phosphorus in angiosperm seeds and plays vitally important roles during seed development. However, in crop plants phytate decreases bioavailability of seed-sourced mineral elements for humans, livestock and poultry, and contributes to phosphate-related water pollution. However, there is little knowledge about this trait in oilseed rape B. napus (oilseed rape). Here, a panel of 505 diverse B. napus accessions was screened in a genome-wide association study (GWAS) using 3.28 x 106 single nucleotide polymorphisms (SNPs). This identified 119 SNPs significantly associated with phytate concentration (PA_Conc) and phytate content (PA_Cont) and six candidate genes were identified. Of these, BnaA9.MRP5 represented the candidate gene for the significant SNP chrA09_5198034 (27kb) for both PA_Cont and PA_Conc. Transcription of BnaA9.MRP5 in a low -phytate variety (LPA20) was significantly elevated compared with a high -phytate variety (HPA972). Association and haplotype analysis indicated that inbred lines carrying specific SNP haplotypes within BnaA9.MRP5 were associated with high- and low-phytate phenotypes. No significant differences in seed germination and seed yield were detected between low and high phytate cultivars examined. Candidate genes, favorable haplotypes and the low phytate varieties identified in this study will be useful for low-phytate breeding of B. napus.

Lifestyle factors and genetic variants on two biological age measures: evidence from 94,443 Taiwan Biobank participants

2021 ◽  
Author(s):  
Wan-Yu Lin
Keyword(s):  
Genetic Variants ◽  
Genome Wide Association Study ◽  
Lifestyle Factors ◽  
Biological Age ◽  
Biological Aging ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Genome Wide ◽  
A Genome ◽  
The Uk

Abstract Background Biological age (BA) can be estimated by phenotypes and is useful for predicting lifespan and healthspan. Levine et al. proposed a PhenoAge and a BioAge to measure BA. Although there have been studies investigating the genetic predisposition to BA acceleration in Europeans, little has been known regarding this topic in Asians. Methods I here estimated PhenoAgeAccel (age-adjusted PhenoAge) and BioAgeAccel (age-adjusted BioAge) of 94,443 Taiwan Biobank (TWB) participants, wherein 25,460 TWB1 subjects formed a discovery cohort and 68,983 TWB2 individuals constructed a replication cohort. Lifestyle factors and genetic variants associated with PhenoAgeAccel and BioAgeAccel were investigated through regression analysis and a genome-wide association study (GWAS). Results A unit (kg/m 2) increase of BMI was associated with a 0.177-year PhenoAgeAccel (95% C.I. = 0.163~0.191, p = 6.0×) and 0.171-year BioAgeAccel (95% C.I. = 0.165~0.177, p = 0). Smokers on average had a 1.134-year PhenoAgeAccel (95% C.I. = 0.966~1.303, p = 1.3×) compared with non-smokers. Drinkers on average had a 0.640-year PhenoAgeAccel (95% C.I. = 0.433~0.847, p = 1.3×) and 0.193-year BioAgeAccel (95% C.I. = 0.107~0.279, p = 1.1×) relative to non-drinkers. A total of 11 and 4 single-nucleotide polymorphisms (SNPs) were associated with PhenoAgeAccel and BioAgeAccel (p<5× in both TWB1 and TWB2), respectively. Conclusions A PhenoAgeAccel-associated SNP (rs1260326 in GCKR) and two BioAgeAccel-associated SNPs (rs7412 in APOE; rs16998073 near FGF5) were consistent with the finding from the UK Biobank. The lifestyle analysis shows that prevention from obesity, cigarette smoking, and alcohol consumption is associated with a slower rate of biological aging.

scholarly journals Progressive effects of single-nucleotide polymorphisms on 16 phenotypic traits based on longitudinal data

2020 ◽  
Vol 42 (4) ◽  
pp. 393-403
Author(s):  
Donghe Li ◽  
Hahn Kang ◽  
Sanghun Lee ◽  
Sungho Won
Keyword(s):  
Single Nucleotide Polymorphisms ◽  
Longitudinal Data ◽  
Density Lipoprotein ◽  
Phenotypic Traits ◽  
Chromosome 2 ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Longitudinal Changes ◽  
Genome Wide ◽  
A Genome

Abstract Background There are many research studies have estimated the heritability of phenotypic traits, but few have considered longitudinal changes in several phenotypic traits together. Objective To evaluate the progressive effect of single nucleotide polymorphisms (SNPs) on prominent health-related phenotypic traits by determining SNP-based heritability ($$h_{snp}^{2}$$hsnp2) using longitudinal data. Methods Sixteen phenotypic traits associated with major health indices were observed biennially for 6843 individuals with 10-year follow-up in a Korean community-based cohort. Average SNP heritability and longitudinal changes in the total period were estimated using a two-stage model. Average and periodic differences for each subject were considered responses to estimate SNP heritability. Furthermore, a genome-wide association study (GWAS) was performed for significant SNPs. Results Each SNP heritability for the phenotypic mean of all sixteen traits through 6 periods (baseline and five follow-ups) were significant. Gradually, the forced vital capacity in one second (FEV1) reflected the only significant SNP heritability among longitudinal changes at a false discovery rate (FDR)-adjusted 0.05 significance level ($$h_{snp}^{2} = 0.171$$hsnp2=0.171, FDR = 0.0012). On estimating chromosomal heritability, chromosome 2 displayed the highest heritability upon periodic changes in FEV1. SNPs including rs2272402 and rs7209788 displayed a genome-wide significant association with longitudinal changes in FEV1 (P = 1.22 × 10−8 for rs2272402 and P = 3.36 × 10−7 for rs7209788). De novo variants including rs4922117 (near LPL, P = 2.13 × 10−15) of log-transformed high-density lipoprotein (HDL) ratios and rs2335418 (near HMGCR, P = 3.2 $$\times$$× 10−9) of low-density lipoprotein were detected on GWAS. Conclusion Significant genetic effects on longitudinal changes in FEV1 among the middle-aged general population and chromosome 2 account for most of the genetic variance.

scholarly journals Genome-wide identification, phylogenetic and expression pattern analysis of GATA family genes in Brassica napus

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Weizhuo Zhu ◽  
Yiyi Guo ◽  
Yeke Chen ◽  
Dezhi Wu ◽  
Lixi Jiang
Keyword(s):  
Brassica Napus ◽  
Stress Condition ◽  
Expression Patterns ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Good Opportunity ◽  
Domain Structures ◽  
Genome Wide ◽  
A Genome

Abstract Background Transcription factors GATAs are involved in plant developmental processes and respond to environmental stresses through binding DNA regulatory regions to regulate their downstream genes. However, little information on the GATA genes in Brassica napus is available. The release of the reference genome of B. napus provides a good opportunity to perform a genome-wide characterization of GATA family genes in rapeseed. Results In this study, 96 GATA genes randomly distributing on 19 chromosomes were identified in B. napus, which were classified into four subfamilies based on phylogenetic analysis and their domain structures. The amino acids of BnGATAs were obvious divergence among four subfamilies in terms of their GATA domains, structures and motif compositions. Gene duplication and synteny between the genomes of B. napus and A. thaliana were also analyzed to provide insights into evolutionary characteristics. Moreover, BnGATAs showed different expression patterns in various tissues and under diverse abiotic stresses. Single nucleotide polymorphisms (SNPs) distributions of BnGATAs in a core collection germplasm are probably associated with functional disparity under environmental stress condition in different genotypes of B. napus. Conclusion The present study was investigated genomic structures, evolution features, expression patterns and SNP distributions of 96 BnGATAs. The results enrich our understanding of the GATA genes in rapeseed.

scholarly journals Indirect predictions with a large number of genotyped animals using the algorithm for proven and young

2020 ◽  
Vol 98 (6) ◽  
Author(s):  
Andre L S Garcia ◽  
Yutaka Masuda ◽  
Shogo Tsuruta ◽  
Stephen Miller ◽  
Ignacy Misztal ◽  
...  
Keyword(s):  
Random Sample ◽  
Best Linear Unbiased Prediction ◽  
Single Step ◽  
Nucleotide Polymorphisms ◽  
Linear Unbiased Prediction ◽  
Single Nucleotide ◽  
Large Numbers ◽  
Minimum Number ◽  
Best Linear Unbiased ◽  
Estimated Breeding Values

Abstract Reliable single-nucleotide polymorphisms (SNP) effects from genomic best linear unbiased prediction BLUP (GBLUP) and single-step GBLUP (ssGBLUP) are needed to calculate indirect predictions (IP) for young genotyped animals and animals not included in official evaluations. Obtaining reliable SNP effects and IP requires a minimum number of animals and when a large number of genotyped animals are available, the algorithm for proven and young (APY) may be needed. Thus, the objectives of this study were to evaluate IP with an increasingly larger number of genotyped animals and to determine the minimum number of animals needed to compute reliable SNP effects and IP. Genotypes and phenotypes for birth weight, weaning weight, and postweaning gain were provided by the American Angus Association. The number of animals with phenotypes was more than 3.8 million. Genotyped animals were assigned to three cumulative year-classes: born until 2013 (N = 114,937), born until 2014 (N = 183,847), and born until 2015 (N = 280,506). A three-trait model was fitted using the APY algorithm with 19,021 core animals under two scenarios: 1) core 2013 (random sample of animals born until 2013) used for all year-classes and 2) core 2014 (random sample of animals born until 2014) used for year-class 2014 and core 2015 (random sample of animals born until 2015) used for year-class 2015. GBLUP used phenotypes from genotyped animals only, whereas ssGBLUP used all available phenotypes. SNP effects were predicted using genomic estimated breeding values (GEBV) from either all genotyped animals or only core animals. The correlations between GEBV from GBLUP and IP obtained using SNP effects from core 2013 were ≥0.99 for animals born in 2013 but as low as 0.07 for animals born in 2014 and 2015. Conversely, the correlations between GEBV from ssGBLUP and IP were ≥0.99 for animals born in all years. IP predictive abilities computed with GEBV from ssGBLUP and SNP predictions based on only core animals were as high as those based on all genotyped animals. The correlations between GEBV and IP from ssGBLUP were ≥0.76, ≥0.90, and ≥0.98 when SNP effects were computed using 2k, 5k, and 15k core animals. Suitable IP based on GEBV from GBLUP can be obtained when SNP predictions are based on an appropriate number of core animals, but a considerable decline in IP accuracy can occur in subsequent years. Conversely, IP from ssGBLUP based on large numbers of phenotypes from non-genotyped animals have persistent accuracy over time.

Sign in / Sign up

Export Citation Format

Share Document