A targeted genotyping approach to enhance the identification of variants for lactation persistency in dairy cows

Abstract Lactation persistency (LP), defined as the ability of a cow to maintain milk production at a high level after milk peak, is an important phenotype for the dairy industry. In this study, we used a targeted genotyping approach to scan for potentially functional single nucleotide polymorphisms (SNPs) within 57 potential candidate genes derived from our previous genome wide association study on LP and from the literature. A total of 175,490 SNPs were annotated within 10-kb flanking regions of the selected candidate genes. After applying several filtering steps, a total of 105 SNPs were retained for genotyping using target genotyping arrays. SNP association analyses were performed in 1,231 Holstein cows with 69 polymorphic SNPs using the univariate liner mixed model with polygenic effects using DMU package. Six SNPs including rs43770847, rs208794152, and rs208332214 in ADRM1; rs209443540 in C5orf34; rs378943586 in DDX11; and rs385640152 in GHR were suggestively significantly associated with LP based on additive effects and associations with 4 of them (rs43770847, rs208794152, rs208332214, and rs209443540) were based on dominance effects at P < 0.05. However, none of the associations remained significant at false discovery rate adjusted P (FDR) < 0.05. The additive variances explained by each suggestively significantly associated SNP ranged from 0.15% (rs43770847 in ADRM1) to 5.69% (rs209443540 in C5orf34), suggesting that these SNPs might be used in genetic selection for enhanced LP. The percentage of phenotypic variance explained by dominance effect ranged from 0.24% to 1.35% which suggests that genetic selection for enhanced LP might be more efficient by inclusion of dominance effects. Overall, this study identified several potentially functional variants that might be useful for selection programs for higher LP. Finally, a combination of identification of potentially functional variants followed by targeted genotyping and association analysis is a cost-effective approach for increasing the power of genetic association studies.

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Using the RTM-GWAS procedure to detect the drought tolerance QTL-allele system at the seedling stage under sand culture in a half-sib population of soybean [Glycine max(L.) Merr.]

Canadian Journal of Plant Science ◽

10.1139/cjps-2018-0309 ◽

2019 ◽

Vol 99 (6) ◽

pp. 801-814 ◽

Cited By ~ 2

Author(s):

Mueen Alam Khan ◽

Fei Tong ◽

Wubin Wang ◽

Jianbo He ◽

Tuanjie Zhao ◽

...

Keyword(s):

Drought Tolerance ◽

Genetic Architecture ◽

Genome Wide Association Study ◽

Weighted Average ◽

Dry Weight ◽

Sand Culture ◽

Phenotypic Variance ◽

Potential Candidate ◽

Nucleotide Polymorphisms ◽

Average Value

Soybean crops face drought as one of their major yield barriers. Dissecting the complete genetic architecture of drought tolerance (DT) is an ongoing challenge for soybean breeders. A half-sib population with 404 lines consisting of two recombinant inbred line (RIL) populations with M8206 as the joint parent (M8206 × TongShan and ZhengYang × M8206) was established and tested for their DT under sand culture. The population was sequenced using RAD-seq (restriction-site-associated DNA sequencing) filtered with minor allele frequency (MAF) ≥ 0.01, and 55 936 single nucleotide polymorphisms (SNPs) were obtained and organized into 6137 SNPLDBs (SNP linkage disequilibrium blocks). The innovative RTM-GWAS (restricted two stage multi-locus genome-wide association study) identified 46 novel QTLs with 107 alleles on an average of 38.67% of the phenotypic variance (PV) collectively for relative plant length (RPL) and relative plant dry weight (RPDW). The identified quantitative trait loci (QTLs) with their corresponding alleles for RPL and RPDW were structured into QTL-allele matrices, showing the DT genetic architecture of the three parents and half-sib population. From the matrices, the possible best genotype was predicted to have their weighted average value (WAV) over two indicators 1.663, while the top 10 optimal crosses among RILs with 95thpercentile WAV was 0.872–0.960, transgressive over the parents (0.469–0.675) but much less than 1.663, depicting further pyramiding potential. From the detected QTL-allele system, 63 potential candidate genes collectively for both RPL and RPDW indicators explaining on average of 26.94% PV were annotated and χ2-tested as a DT potential candidate gene system involving nine biological processes, endorsing the genetic complexity of DT.

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Candidate genes for productivity identified by genome-wide association study with indicators of class in the Russian meat merino sheep breed

Vavilov Journal of Genetics and Breeding ◽

10.18699/vj20.681 ◽

2020 ◽

Vol 24 (8) ◽

pp. 836-843

Author(s):

A. Y. Krivoruchko ◽

O. A. Yatsyk ◽

E. Y. Safaryan

Keyword(s):

Candidate Genes ◽

Genome Wide Association Study ◽

Association Studies ◽

Genome Wide Association ◽

Phenotypic Traits ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

High Association ◽

Genome Wide ◽

Individual Snps

Genome-wide association studies allow identification of loci and polymorphisms associated with the formation of relevant phenotypes. When conducting a full genome analysis of sheep, particularly promising is the study of individuals with outstanding productivity indicators – exhibition animals, representatives of the super-elite class. The aim of this study was to identify new candidate genes for economically valuable traits based on the search for single nucleotide polymorphisms (SNPs) associated with belonging to different evaluation classes in rams of the Russian meat merino breed. Animal genotyping was performed using Ovine Infinium HD BeadChip 600K DNA, association search was performed using PLINK v. 1.07 software. Highly reliable associations were found between animals belonging to different evaluation classes and the frequency of occurrence of individual SNPs on chromosomes 2, 6, 10, 13, and 20. Most of the substitutions with high association reliability are concentrated on chromosome 10 in the region 10: 30859297–31873769. To search for candidate genes, 15 polymorphisms with the highest association reliability were selected (–log10(р) > 9). Determining the location of the analyzed SNPs relative to the latest annotation Oar_rambouillet_v1.0 allowed to identify 11 candidate genes presumably associated with the formation of a complex of phenotypic traits of animals in the exhibition group: RXFP2, ALOX5AP, MEDAG, OPN5, PRDM5, PTPRT, TRNAS-GGA, EEF1A1, FRY, ZBTB21-like, and B3GLCT-like. The listed genes encode proteins involved in the control of the cell cycle and DNA replication, regulation of cell proliferation and apoptosis, lipid and carbohydrate metabolism, the development of the inflammatory process and the work of circadian rhythms. Thus, the candidate genes under consideration can influence the formation of exterior features and productive qualities of sheep. However, further research is needed to confirm the influence of genes and determine the exact mechanisms for implementing this influence on the phenotype.

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Genome-Wide Association Analysis of Growth Curve Parameters in Chinese Simmental Beef Cattle

Animals ◽

10.3390/ani11010192 ◽

2021 ◽

Vol 11 (1) ◽

pp. 192

Author(s):

Xinghai Duan ◽

Bingxing An ◽

Lili Du ◽

Tianpeng Chang ◽

Mang Liang ◽

...

Keyword(s):

Beef Cattle ◽

Candidate Genes ◽

Growth Curve ◽

Growth And Development ◽

Genome Wide Association Study ◽

Genome Wide Association ◽

Coefficient Of Determination ◽

Nucleotide Polymorphisms ◽

Genome Wide ◽

A Genome

The objective of the present study was to perform a genome-wide association study (GWAS) for growth curve parameters using nonlinear models that fit original weight–age records. In this study, data from 808 Chinese Simmental beef cattle that were weighed at 0, 6, 12, and 18 months of age were used to fit the growth curve. The Gompertz model showed the highest coefficient of determination (R2 = 0.954). The parameters’ mature body weight (A), time-scale parameter (b), and maturity rate (K) were treated as phenotypes for single-trait GWAS and multi-trait GWAS. In total, 9, 49, and 7 significant SNPs associated with A, b, and K were identified by single-trait GWAS; 22 significant single nucleotide polymorphisms (SNPs) were identified by multi-trait GWAS. Among them, we observed several candidate genes, including PLIN3, KCNS3, TMCO1, PRKAG3, ANGPTL2, IGF-1, SHISA9, and STK3, which were previously reported to associate with growth and development. Further research for these candidate genes may be useful for exploring the full genetic architecture underlying growth and development traits in livestock.

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Identification of a Cis-Acting Regulatory Polymorphism in a Eucalypt COBRA-Like Gene Affecting Cellulose Content

Genetics ◽

10.1534/genetics.109.106591 ◽

2009 ◽

Vol 183 (3) ◽

pp. 1153-1164 ◽

Cited By ~ 68

Author(s):

Bala R. Thumma ◽

Bronwyn A. Matheson ◽

Deqiang Zhang ◽

Christian Meeske ◽

Roger Meder ◽

...

Keyword(s):

Quantitative Traits ◽

Association Studies ◽

Allelic Expression ◽

Cellulose Content ◽

Nucleotide Polymorphisms ◽

Cis Acting ◽

Functional Polymorphisms ◽

Functional Variants ◽

Regulatory Polymorphism ◽

Trait Locus

Populations with low linkage disequilibrium (LD) offer unique opportunities to study functional variants influencing quantitative traits. We exploited the low LD in forest trees to identify functional polymorphisms in a Eucalyptus nitens COBRA-like gene (EniCOBL4A), whose Arabidopsis homolog has been implicated in cellulose deposition. Linkage analysis in a full-sib family revealed that EniCOBL4A is the most strongly associated marker in a quantitative trait locus (QTL) region for cellulose content. Analysis of LD by genotyping 11 common single-nucleotide polymorphisms (SNPs) and a simple sequence repeat (SSR) in an association population revealed that LD declines within the length of the gene. Using association studies we fine mapped the effect of the gene to SNP7, a synonymous SNP in exon 5, which occurs between two small haplotype blocks. We observed patterns of allelic expression imbalance (AEI) and differential binding of nuclear proteins to the SNP7 region that indicate that SNP7 is a cis-acting regulatory polymorphism affecting allelic expression. We also observed AEI in SNP7 heterozygotes in a full-sib family that is linked to heritable allele-specific methylation near SNP7. This study demonstrates the potential to reveal functional polymorphisms underlying quantitative traits in low LD populations.

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297 GWAS for complex models accounting for populations structure with GBLUP and ssGBLUP

Journal of Animal Science ◽

10.1093/jas/skaa278.057 ◽

2020 ◽

Vol 98 (Supplement_4) ◽

pp. 32-32

Author(s):

Juan P Steibel ◽

Ignacio Aguilar

Keyword(s):

Hypothesis Testing ◽

Large Scale ◽

Mixed Model ◽

Prediction Models ◽

Association Studies ◽

Least Square ◽

Type I ◽

Phenotypic Variance ◽

Genome Wide Association Studies ◽

Formal Hypothesis Testing

Abstract Genomic Best Linear Unbiased Prediction (GBLUP) is the method of choice for incorporating genomic information into the genetic evaluation of livestock species. Furthermore, single step GBLUP (ssGBLUP) is adopted by many breeders’ associations and private entities managing large scale breeding programs. While prediction of breeding values remains the primary use of genomic markers in animal breeding, a secondary interest focuses on performing genome-wide association studies (GWAS). The goal of GWAS is to uncover genomic regions that harbor variants that explain a large proportion of the phenotypic variance, and thus become candidates for discovering and studying causative variants. Several methods have been proposed and successfully applied for embedding GWAS into genomic prediction models. Most methods commonly avoid formal hypothesis testing and resort to estimation of SNP effects, relying on visual inspection of graphical outputs to determine candidate regions. However, with the advent of high throughput phenomics and transcriptomics, a more formal testing approach with automatic discovery thresholds is more appealing. In this work we present the methodological details of a method for performing formal hypothesis testing for GWAS in GBLUP models. First, we present the method and its equivalencies and differences with other GWAS methods. Moreover, we demonstrate through simulation analyses that the proposed method controls type I error rate at the nominal level. Second, we demonstrate two possible computational implementations based on mixed model equations for ssGBLUP and based on the generalized least square equations (GLS). We show that ssGBLUP can deal with datasets with extremely large number of animals and markers and with multiple traits. GLS implementations are well suited for dealing with smaller number of animals with tens of thousands of phenotypes. Third, we show several useful extensions, such as: testing multiple markers at once, testing pleiotropic effects and testing association of social genetic effects.

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Genome-wide association study reveals candidate genes for flowering time in cowpea (Vigna unguiculata [L.] Walp)

10.1101/2021.04.01.438123 ◽

2021 ◽

Author(s):

Dev Paudel ◽

Rocheteau Dareus ◽

Julia Rosenwald ◽

Maria Munoz-Amatriain ◽

Esteban Rios

Keyword(s):

Flowering Time ◽

Candidate Genes ◽

Vigna Unguiculata ◽

Association Studies ◽

Snp Markers ◽

Genome Wide Association ◽

Human Consumption ◽

Phenotypic Variance ◽

Genome Wide Association Studies ◽

Genome Wide

Cowpea (Vigna unguiculata [L.] Walp., diploid, 2n = 22) is a major crop used as a protein source for human consumption as well as a quality feed for livestock. It is drought and heat tolerant and has been bred to develop varieties that are resilient to changing climates. Plant adaptation to new climates and their yield are strongly affected by flowering time. Therefore, understanding the genetic basis of flowering time is critical to advance cowpea breeding. The aim of this study was to perform genome-wide association studies (GWAS) to identify marker trait associations for flowering time in cowpea using single nucleotide polymorphism (SNP) markers. A total of 367 accessions from a cowpea mini-core collection were evaluated in Ft. Collins, CO in 2019 and 2020, and 292 accessions were evaluated in Citra, FL in 2018. These accessions were genotyped using the Cowpea iSelect Consortium Array that contained 51,128 SNPs. GWAS revealed seven reliable SNPs for flowering time that explained 8-12% of the phenotypic variance. Candidate genes including FT, GI, CRY2, LSH3, UGT87A2, LIF2, and HTA9 that are associated with flowering time were identified for the significant SNP markers. Further efforts to validate these loci will help to understand their role in flowering time in cowpea, and it could facilitate the transfer of some of this knowledge to other closely related legume species.

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Genome-Wide Association Mapping for Heat and Drought Adaptive Traits in Pea

Genes ◽

10.3390/genes12121897 ◽

2021 ◽

Vol 12 (12) ◽

pp. 1897

Author(s):

Endale G. Tafesse ◽

Krishna K. Gali ◽

V. B. Reddy Lachagari ◽

Rosalind Bueckert ◽

Thomas D. Warkentin

Keyword(s):

Association Mapping ◽

Candidate Genes ◽

Vegetation Index ◽

Genome Wide Association Study ◽

Genome Wide Association ◽

Nucleotide Polymorphisms ◽

Adaptive Traits ◽

Flowering Duration ◽

Genome Wide ◽

A Genome

Heat and drought, individually or in combination, limit pea productivity. Fortunately, substantial genetic diversity exists in pea germplasm for traits related to abiotic stress resistance. Understanding the genetic basis of resistance could accelerate the development of stress-adaptive cultivars. We conducted a genome-wide association study (GWAS) in pea on six stress-adaptive traits with the aim to detect the genetic regions controlling these traits. One hundred and thirty-five genetically diverse pea accessions were phenotyped in field studies across three or five environments under stress and control conditions. To determine marker trait associations (MTAs), a total of 16,877 valuable single nucleotide polymorphisms (SNPs) were used in association analysis. Association mapping detected 15 MTAs that were significantly (p ≤ 0.0005) associated with the six stress-adaptive traits averaged across all environments and consistent in multiple individual environments. The identified MTAs were four for lamina wax, three for petiole wax, three for stem thickness, two for the flowering duration, one for the normalized difference vegetation index (NDVI), and two for the normalized pigment and chlorophyll index (NPCI). Sixteen candidate genes were identified within a 15 kb distance from either side of the markers. The detected MTAs and candidate genes have prospective use towards selecting stress-hardy pea cultivars in marker-assisted selection.

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

10.22541/au.161165160.08519096/v1 ◽

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.

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Association of GWAS-Based Candidate Genes with HDL-Cholesterol Levels before and after Bariatric Surgery in the Swedish Obese Subjects Study

The Journal of Clinical Endocrinology & Metabolism ◽

10.1210/jc.2010-2227 ◽

2011 ◽

Vol 96 (6) ◽

pp. E953-E957 ◽

Cited By ~ 21

Author(s):

Mark A. Sarzynski ◽

Peter Jacobson ◽

Tuomo Rankinen ◽

Björn Carlsson ◽

Lars Sjöström ◽

...

Keyword(s):

Bariatric Surgery ◽

Weight Loss ◽

Candidate Genes ◽

Association Studies ◽

Statistical Significance ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Cross Sectional ◽

Time Points ◽

Obese Subjects

Context and Objective: The magnitude of weight loss-induced high-density lipoprotein cholesterol (HDL-C) changes may depend on genetic factors. We examined the associations of eight candidate genes, identified by genome-wide association studies, with HDL-C at baseline and 10 yr after bariatric surgery in the Swedish Obese Subjects study. Methods: Single-nucleotide polymorphisms (SNP) (n = 60) in the following gene loci were genotyped: ABCA1, APOA5, CETP, GALNT2, LIPC, LIPG, LPL, and MMAB/MVK. Cross-sectional associations were tested before (n = 1771) and 2 yr (n = 1583) and 10 yr (n = 1196) after surgery. Changes in HDL-C were tested between baseline and yr 2 (n = 1518) and yr 2 and 10 (n = 1149). A multiple testing corrected threshold of P = 0.00125 was used for statistical significance. Results: In adjusted multivariate models, CETP SNP rs3764261 explained from 3.2–4.2% (P < 10−14) of the variation in HDL-C at all three time points, whereas CETP SNP rs9939224 contributed an additional 0.6 and 0.9% at baseline and yr 2, respectively. LIPC SNP rs1077834 showed consistent associations across all time points (R2 = 0.4–1.1%; 3.8 × 10−6 < P < 3 × 10−3), whereas LPL SNP rs6993414 contributed approximately 0.5% (5 × 10−4 < P < 0.0012) at yr 2 and 10. In aggregate, four SNP in three genes explained 4.2, 6.8, and 5.6% of the HDL-C variance at baseline, yr 2, and yr 10, respectively. None of the SNP was significantly associated with weight loss-related changes in HDL-C. Conclusions: SNP in the CETP, LIPC, and LPL loci contribute significantly to plasma HDL-C levels in obese individuals, and the associations persist even after considerable weight loss due to bariatric surgery. However, they are not associated with surgery-induced changes in HDL-C levels.

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Longitudinal Phenotypes Improve Genotype Association for Hyperketonemia in Dairy Cattle

Animals ◽

10.3390/ani9121059 ◽

2019 ◽

Vol 9 (12) ◽

pp. 1059 ◽

Cited By ~ 1

Author(s):

Francisco A. Leal Yepes ◽

Daryl V. Nydam ◽

Sabine Mann ◽

Luciano Caixeta ◽

Jessica A. A. McArt ◽

...

Keyword(s):

Linear Models ◽

Association Studies ◽

Genetic Selection ◽

Area Under The Curve ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Mixed Linear Models ◽

Biological Insight ◽

Group 2 ◽

Genomic Regions

The objective of our study was to identify genomic regions associated with varying concentrations of non-esterified fatty acid (NEFA), β-hydroxybutyrate (BHB), and the development of hyperketonemia (HYK) in longitudinally sampled Holstein dairy cows. Our study population consisted of 147 multiparous cows intensively characterized by serial NEFA and BHB concentrations. To identify individuals with contrasting combinations in longitudinal BHB and NEFA concentrations, phenotypes were established using incremental area under the curve (AUC) and categorized as follows: Group (1) high NEFA and high BHB, group (2) low NEFA and high BHB), group (3) low NEFA and low BHB, and group (4) high NEFA and low BHB. Cows were genotyped on the Illumina Bovine High-density (777 K) beadchip. Genome-wide association studies using mixed linear models with the least-related animals were performed to establish a genetic association with HYK, BHB-AUC, NEFA-AUC, and the comparisons of the 4 AUC phenotypic groups using Golden Helix software. Nine single-nucleotide polymorphisms were associated with high longitudinal concentrations of BHB and further investigated. Five candidate genes related to energy metabolism and homeostasis were identified. These results provide biological insight and help identify susceptible animals thus improving genetic selection criteria thereby decreasing the incidence of HYK.

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