Single Nucleotide Polymorphism Chip Research Articles

Combined Genome-Wide Association Studies (GWAS) and Linkage Mapping Identifies Genomic Regions Associated with Seedling Root System Architecture (RSA) under Different Nitrogen Conditions in Wheat (Triticum aestivum L.)

The nitrogen (N) use efficiency (NUE) in the roots of seedlings is beneficial for increasing crop yield. Creating marker-assisted selection for wheat root traits can assist wheat breeders in choosing robust roots to maximize nutrient uptake. Exploring and identifying the effect of different N supply conditions on root system architecture (RSA) is of great significance for breeding N efficient wheat varieties. In this study, a total of 243 wheat varieties native to the Yellow and Huai Valley regions of China were utilized for genome-wide association studies (GWAS). Furthermore, a recombinant inbred line (RIL) population of 123 lines derived from the cross between Avocet and Chilero was utilized for linkage examination. A hydroponic seedling experiment using a 96-well tray was conducted in the lab with two treatments: normal N (NN) and low N (LN). Five RSA traits, including the relative number of root tips (RNRT), relative total root length (RTRL), relative total root surface area (RTRS), relative total root volume (RTRV), and relative average root diameter (RARD), were investigated. GWAS and linkage analysis were performed by integrating data from the wheat 660 k single nucleotide polymorphism (SNP) chip and diversity arrays technology (DArT) to identify genetic loci associated with RSA. The results showed that, based on the ratio of RSA-related traits under two N supply conditions, a total of 497 SNP markers, which are significantly associated with RSA-related traits, were detected at 148 genetic loci by GWAS. A total of 10 QTL loci related to RSA were discovered and identified by linkage mapping. Combining two gene localization methods, three colocalized intervals were found: AX-95160997/QRtrl.haust-3D, AX-109592379/QRnrt.haust-5A, and AX-110924288/QRtrl.haust-7D/QRtrs.haust-7D. According to the physical location of the colocalization of these two sites, between 39.61 and 43.74 Mb, 649.97 and 661.55 Mb, and 592.44 and 605.36 Mb are called qRtrl-3D, qRnrt-5A, and qRtrl-7D. This study has the potential to enhance the effectiveness of selecting root traits in wheat breeding programs, offering valuable insights into the genetic underpinnings of NUE in wheat. These results could help in breeding wheat varieties with higher NUE by implementing focused breeding strategies.

Development and validation of a 5K low-density SNP chip for Hainan cattle

BackgroundThis study aimed to design and develop a 5K low-density liquid chip for Hainan cattle utilizing targeted capture sequencing technology. The chip incorporates a substantial number of functional single nucleotide polymorphism (SNP) loci derived from public literature, including SNP loci significantly associated with immunity, heat stress, meat quality, reproduction, and other traits. Additionally, SNPs located in the coding regions of immune-related genes from the Bovine Genome Variation Database (BGVD) and Hainan cattle-specific SNP loci were included.ResultsA total of 5,293 SNPs were selected, resulting in 9,837 DNA probes with a coverage rate of 85.69%, thereby creating a Hainan cattle-specific 5K Genotyping by Target Sequencing (GBTS) liquid chip. Evaluation with 152 cattle samples demonstrated excellent clustering performance and a detection rate ranging from 96.60 to 99.07%, with 94.5% of SNP sites exhibiting polymorphism. The chip achieved 100% gender coverage and displayed a heterozygosity rate between 14.20% and 29.65%, with a repeatability rate of 99.65–99.85%. Analyses using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed the potential regulatory roles of exonic SNPs in immune response pathways.ConclusionThe development and validation of the 5K GBTS liquid chip for Hainan cattle represent a valuable tool for genome analysis and genetic diversity assessment. Furthermore, it facilitates breed identification, gender determination, and kinship analysis, providing a foundation for the efficient utilization and development of local cattle genetic resources.

QTL mapping for wheat ferulic acid concentration using 50 K SNP chip in a recombinant inbred line population of Zhongmai 578/Jimai 22

AbstractBackground and ObjectivesFerulic acid is a prominent bioactive compound found in wheat grains, known for its beneficial health effects, prompting significant interest from breeders and producers. The aim of this study was to identify new quantitative trait loci (QTL) to aid in the development of wheat varieties with increased ferulic acid concentration (FAC).FindingsIn this study, a recombinant inbred line population, resulting from a cross between Zhongmai 578 and Jimai 22, was evaluated in five different environments. Genotyping was performed using the wheat 50 K single‐nucleotide polymorphism (SNP) array. Three stable QTL, named QFAC.caas‐2D, QFAC.caas‐3B, and QFAC.caas‐4D, were identified. These QTL explained 4.24%–7.09%, 3.7%–4.57%, and 3.20%–5.06% of the phenotypic variances, respectively. Furthermore, three SNPs closely associated with above QTL were successfully converted into kompetitive allele‐specific polymerase chain reaction (KASP) markers.ConclusionsFAC is a complex trait governed by multiple minor‐effect QTL. The successful development of KASP markers opens up avenues for marker‐assisted selection in breeding programs.Significance and NoveltyThis study establishes a genetic foundation for understanding the genetic basis of FAC in wheat. The identified QTL and developed KASP markers offer valuable insights for quality breeding initiatives and the production of functional wheat‐based foods.

PSX-7 Heritability estimates for longevity-related traits in U.S. Katahdin ewes

Abstract Genetic selection for increased ewe longevity can directly contribute to improved flock profitability and welfare. Therefore, this study aimed to estimate heritabilities for eight longevity-related traits in 12,149 Katahdin ewes. The ewes were daughters of 1,157 sires and 6,147 dams and were born between 1989 and 2020 in 58 flocks located across the U.S. The National Sheep Improvement Program provided the data. Age at last lambing (ALL); productive life (PL; number of days between the first and last lambing), total number of litters (TLI), lambs born (TNB), and lambs weaned (TNW) over the lifetime of the ewe; total litter weight at lambing (TLB) and weaning (TLW) over the lifetime of the ewe, and TLW divided by the weight of the ewe adjusted for 120 d (TLWadj) were evaluated (Table 1). Body weights (BW) at lambing and weaning (WW) were adjusted for sex effect, while WW was also adjusted for 60 d old. Ewes with lambing interval and age at the first lambing greater than 720 d and 1,095 d, respectively, were excluded. Moreover, only flocks that reported lambing records across at least 7 consecutive years and an average of 20 or more lambing records over the yr were evaluated. Fixed effects of contemporary group (flock, year, and season of birth of the ewe), the combined effect of the birth type and rearing type of the ewe, and age class at first lambing, as well as the animal random effect, were included in the animal model fitted. Contemporary groups with less than three ewes were excluded. Moreover, we excluded records deviating ± ± 3.0 SD from the mean. Variance components were estimated by restricted maximum likelihood based on pedigree (by fitting the A matrix) and genomic information [by fitting an H matrix including pedigree and genomic relationships from 10,032 animals genotyped with a 50K single nucleotide polymorphisms (SNP) chip]. The criteria used to exclude SNP were MAF < 0.05, call rate < 0.95 (for both SNP and animals), and a maximum difference of 0.15 between the observed and expected heterozygosity (Hardy-Weinberg equilibrium). After quality control, 31,182 SNP were used for the analyses. The analyses were performed using the BLUPF90+ programs. The pedigree-based heritability estimates were: ALL (0.10 ± 0.017), PL (0.11 ± 0.023), TLI (0.10 ± 0.017), TNA (0.11 ± 0.017), TNW (0.11 ± 0.018), TLB (0.12 ± 0.020), TLW (0.10 ± 0.024), and TLWadj (0.07 ± 0.031). The genomic-based heritability estimates were: ALL (0.13 ± 0.018), PL (0.14 ± 0.024), TLI (0.13 ± 0.018), TNB (0.13 ± 0.018), TNW (0.14 ± 0.018), TLB (0.15 ± 0.021), TLW (0.11 ± 0.024), and TLWadj (0.07 ± 0.032). The relative standard error (RSE) of the estimates obtained with the A matrix ranged from 15.5% (TNB) to 44.3% (TLWadj) and from 12.9% (TNW) to 45.7% (TLWadj) when fitting the H matrix. In conclusion, longevity-related traits in U.S. Katahdin ewes are heritable, and estimates are slightly greater (with reduced RSE) when incorporating genomic information to estimate variance components.

Association of the ABCG2 rs2231142 variant with the Framingham Cardiovascular Disease Risk score in the Taiwanese population

BackgroundSerum uric acid (SUA) is an important predictor of cardiovascular events and mortality. The ABCG2 rs2231142 variant (TT genotype) is associated with hyperuricemia (HUA), but the relationship between ABCG2 gene polymorphisms and coronary artery disease (CAD) risk is poorly elucidated. We investigated the association between ABCG2 rs2231142 genetic variants and the Framingham Risk Score for Cardiovascular Disease (FRS-CVD) in a Taiwanese population. MethodsThis cross-sectional study enrolled 139,508 Taiwanese participants aged 30–70 years based on data from the Taiwan Biobank (TWB) database that was obtained from questionnaires, laboratory investigations, anthropometry, and Affymetrix TWB genome-wide single-nucleotide polymorphism (SNP) chip data analysis. The association between ABCG2 rs2231142 and FRS-CVD risk was evaluated using logistic regression analysis. ResultsCompared to those with the GG genotype, participants with the ABCG2 rs2231142 TT genotype had a significantly lower systolic blood pressure, smoking rate, body mass index, triglyceride level, waist circumference, waist–hip ratio, and body fat percentage, but had higher high-density lipoprotein cholesterol level. Despite the same FRS-CVD score, participants with TT genotypes had higher SUA. Even with the same SUA, TT carriers had a lower FRS-CVD than GT and GG carriers. Participants with the TT genotype had significantly lower CVD risk, particularly female participants with HUA and BMI <27 (OR: 0.760, 95 % CI: 0.587–0.985; p = 0.0381) group. ConclusionThe ABCG2 rs2231142 TT genotype is associated with a lower FRS-CVD, particularly in non-obese hyperuricemic female individuals. The complicated interplay among genetic variations, metabolic profile, and CVD risk provides insights for precision health.

Integration of ssGWAS and ROH analyses for uncovering genetic variants associated with reproduction traits in Large White pigs.

The low heritability of reproduction traits such as total number born (TNB), number born alive (NBA) and adjusted litter weight until 21 days at weaning (ALW) poses a challenge for genetic improvement. In this study, we aimed to identify genetic variants that influence these traits and evaluate the accuracy of genomic selection (GS) using these variants as genomic features. We performed single-step genome-wide association studies (ssGWAS) on 17 823 Large White (LW) pigs, of which 2770 were genotyped by 50K single nucleotide polymorphism (SNP) chips. Additionally, we analyzed runs of homozygosity (ROH) in the population and tested their effects on the traits. The genomic feature best linear unbiased prediction (GFBLUP) was then carried out in an independent population of 350 LW pigs using identified trait-related SNP subsets as genomic features. As a result, our findings identified five, one and four SNP windows that explaining more than 1% of genetic variance for ALW, TNB, and NBA, respectively and discovered 358 hotspots and nine ROH islands. The ROH SSC1:21814570-27186456 and SSC11:7220366-14276394 were found to be significantly associated with ALW and NBA, respectively. We assessed the genomic estimated breeding value accuracy through 20 replicates of five-fold cross-validation. Our findings demonstrate that GFBLUP, incorporating SNPs located in effective ROH (p-value < 0.05) as genomic features, might enhance GS accuracy for ALW compared with GBLUP. Additionally, using SNPs explaining more than 0.1% of the genetic variance in ssGWAS for NBA as genomic features might improve the GS accuracy, too. However, it is important to note that the incorporation of inappropriate genomic features can significantly reduce GS accuracy. In conclusion, our findings provide valuable insights into the genetic mechanisms of reproductive traits in pigs and suggest that the ssGWAS and ROH have the potential to enhance the accuracy of GS for reproductive traits in LW pigs.

Genotypic and phenotypic characterisation of three local chicken ecotypes of Ghana based on principal component analysis and body measurements.

This study aimed to characterise three Ghanaian local chicken ecotypes, namely, Interior Savannah, Forest, and Coastal Savannah, based on morphological data and single nucleotide polymorphism (SNP) genotypes. Morphological data including body weight, shank length, body girth, back length, thigh length, beak length, comb length, and wattle length were collected from 250 local chickens. DNA isolated from blood of 1,440 local chickens was used for SNP genotyping with the Affymetrix chicken 600k SNP chip. Principal component analysis showed that Forest and Coastal Savannah birds were closely related. Generally, all three ecotypes exhibited high genetic diversity, especially birds from the Interior Savannah zone. Morphological characterisation showed that ecotype (p = 0.016) and sex (p = 0.000) had significant effects on body weight. Birds of the Interior Savannah ecotype were the heaviest (p = 0.004), with mean weights of 1.23 kg for females and 1.40 kg for males. Sex also had a strong significant effect on most of the morphological measurements, but the sex * ecotype interaction effect was not significant. Very few of the feather phenotypes previously reported to be associated with heat resistance-frizzle (2%) and naked neck (1.6%)-were found in the studied populations. It is concluded that the three local ecotypes are genetically diverse but with similar morphological features and the information provided would be useful for future selection decisions.

Genome-wide association study for polledness, horn shape, and wool traits in Original Valachian sheep

Abstract. The Original Valachian sheep is an endangered Slovak national breed that is well adapted to high-altitude pastures. The sheep can be horned with various shapes and can have multi-coloured or completely white or black wool. Breeders are interested in learning about the genetic basis of these traits. We conducted a genome-wide association study based on the genomic information of 96 sheep genotyped by the GeneSeek GGP Ovine 50K SNP (single-nucleotide polymorphism) chip and on the following traits: polledness (presence or absence of horns), horn shape, and wool colour (completely white and completely black). The univariate linear mixed model was used to discover genetic variants significantly associated with tested traits. The Bonferroni correction and the false-discovery rate were used as significance thresholds. The RXFP2 gene (chromosome 10, 29.5 Mb) was identified as a strong candidate for polledness. In addition, when compared to animals with sideways-turned horns vs. polled, the region around the ADAMTS3 gene (chromosome 6, 88.47 Mb) was significant. A total of nine significant genomic regions were found when comparing the sideways-turned spiral horns with the backwards-curled horns, the two most frequent horn types in Original Valachian sheep. The RXFP2 may also contribute to the genetic control of horn shape. Genes identified in other regions were involved to osteogenic differentiation and osteoblast proliferation (PCP4, chromosome 1, 260.7 Mb), bone mineral density and mineral content (NKX1-2, chromosome 22, 43.75 Mb). The significant genetic variants close to the region of MC1R (chromosome 14, at 14.2 Mb) were associated with the wool colour of sheep that were fully white or fully black animals. The results of this study will contribute to a better understanding of the phenotypic variability of the Original Valachian sheep, especially regarding traits that are very important for breeders of this endangered breed.

Genetic characterization of Tibetan pigs adapted to high altitude under natural selection based on a large whole-genome dataset

The Qinghai-Tibet Plateau is a valuable genetic resource pool, and the high-altitude adaptation of Tibetan pigs is a classic example of the adaptive evolution of domestic animals. Here, we report the presence of Darwinian positive selection signatures in Tibetan pigs (TBPs) using 348 genome-wide datasets (127 whole-genome sequence datasets (WGSs) and 221 whole-genome single-nucleotide polymorphism (SNP) chip datasets). We characterized a high-confidence list of genetic signatures related response to high-altitude adaptation in Tibetan pigs, including 4,598 candidate SNPs and 131 candidate genes. Functional annotation and enrichment analysis revealed that 131 candidate genes are related to multiple systems and organs in Tibetan pigs. Notably, eight of the top ten novel genes, RALB, NBEA, LIFR, CLEC17A, PRIM2, CDH7, GK5 and FAM83B, were highlighted and associated with improved adaptive heart functions in Tibetan pigs high-altitude adaptation. Moreover, genome-wide association analysis revealed that 29 SNPs were involved in 13 candidate genes associated with at least one adaptive trait. In particular, among the top ten candidate genes, CLEC17A is related to a reduction in hemoglobin (HGB) in Tibetan pigs. Overall, our study provides a robust SNP/gene list involving genetic adaptation for Tibetan pig high-altitude adaptation, and it will be a valuable resource for future Tibetan pig studies.

Genetic diversity and population structure of wheat landraces in Southern Winter Wheat Region of China

BackgroundWheat landraces are considered a valuable source of genetic diversity for breeding programs. It is useful to evaluate the genetic diversity in breeding studies such as marker-assisted selection (MAS), genome-wide association studies (GWAS), and genomic selection. In addition, constructing a core germplasm set that represents the genetic diversity of the entire variety set is of great significance for the efficient conservation and utilization of wheat landrace germplasms.ResultsTo understand the genetic diversity in wheat landrace, 2,023 accessions in the Jiangsu Provincial Crop Germplasm Resource Bank were used to explore the molecular diversity and population structure using the Illumina 15 K single nucleotide polymorphism (SNP) chip. These accessions were divided into five subpopulations based on population structure, principal coordinate and kinship analysis. A significant variation was found within and among the subpopulations based on the molecular variance analysis (AMOVA). Subpopulation 3 showed more genetic variability based on the different allelic patterns (Na, Ne and I). The M strategy as implemented in MStratv 4.1 software was used to construct the representative core collection. A core collection with a total of 311 accessions (15.37%) was selected from the entire landrace germplasm based on genotype and 12 different phenotypic traits. Compared to the initial landrace collections, the core collection displayed higher gene diversity (0.31) and polymorphism information content (PIC) (0.25), and represented almost all phenotypic variation.ConclusionsA core collection comprising 311 accessions containing 100% of the genetic variation in the initial population was developed. This collection provides a germplasm base for effective management, conservation, and utilization of the variation in the original set.

Estimation of genetic correlations and genomic prediction accuracy for reproductive and carcass traits in Hanwoo cows.

This study estimated the heritabilities (h2) and genetic and phenotypic correlations between reproductive traits, including calving interval (CI), age at first calving (AFC), gestation length (GL), number of artificial inseminations per conception (NAIPC), and carcass traits, including carcass weight (CWT), eye muscle area (EMA), backfat thickness (BF), and marbling score (MS) in Korean Hanwoo cows. In addition, the accuracy of genomic predictions of breeding values was evaluated by applying the genomic best linear unbiased prediction (GBLUP) and the weighted GBLUP (WGBLUP) method. The phenotypic data for reproductive and carcass traits were collected from 1,544 Hanwoo cows, and all animals were genotyped using Illumina Bovine 50K single nucleotide polymorphism (SNP) chip. The genetic parameters were estimated using a multi-trait animal model using the MTG2 program. The estimated h2 for CI, AFC, GL, NAIPC, CWT, EMA, BF, and MS were 0.10, 0.13, 0.17, 0.11, 0.37, 0.35, 0.27, and 0.45, respectively, according to the GBLUP model. The GBLUP accuracy estimates ranged from 0.51 to 0.74, while the WGBLUP accuracy estimates for the traits under study ranged from 0.51 to 0.79. Strong and favorable genetic correlations were observed between GL and NAIPC (0.61), CWT and EMA (0.60), NAIPC and CWT (0.49), AFC and CWT (0.48), CI and GL (0.36), BF and MS (0.35), NAIPC and EMA (0.35), CI and BF (0.30), EMA and MS (0.28), CI and AFC (0.26), AFC and EMA (0.24), and AFC and BF (0.21). The present study identified low to moderate positive genetic correlations between reproductive and CWT traits, suggesting that a heavier body weight may lead to a longer CI, AFC, GL, and NAIPC. The moderately positive genetic correlation between CWT and AFC, and NAIPC, with a phenotypic correlation of nearly zero, suggesting that the genotype-environment interactions are more likely to be responsible for the phenotypic manifestation of these traits. As a result, the inclusion of these traits by breeders as selection criteria may present a good opportunity for developing a selection index to increase the response to the selection and identification of candidate animals, which can result in significantly increased profitability of production systems.

Tag SNP selection for prediction of adaptation traits in Braford and Hereford cattle using Bayesian methods

AbstractThis study utilized Bayesian inference in a genome‐wide association study (GWAS) to identify genetic markers associated with traits relevant to the adaptation of Hereford and Braford cattle breeds. We focused on eye pigmentation (EP), weaning hair coat (WHC), yearling hair coat (YHC), and breeding standard (BS). Our dataset comprised 126,290 animals in the pedigree. Out of these, 233 sires were genotyped using high‐density (HD) chips, and 3750 animals with medium‐density (50 K) single‐nucleotide polymorphism (SNP) chips. Employing the Bayes B method with a prior probability of π = 0.99, we identified and tagged single nucleotide polymorphisms (Tag SNPs), ranging from 18 to 117 SNPs depending on the trait. These Tag SNPs facilitated the construction of reduced SNP panels. We then evaluated the predictive accuracy of these panels in comparison to traditional medium‐density SNP chips. The accuracy of genomic predictions using these reduced panels varied significantly depending on the clustering method, ranging from 0.13 to 0.65. Additionally, we conducted functional enrichment analysis that found genes associated with the most informative SNP markers in the current study, thereby providing biological insights into the genomic basis of these traits.

Analysis of genetic diversity and structure of endangered Dengchuan cattle population using a single-nucleotide polymorphism chip

This study aimed to evaluate the genetic diversity and structure within the Dengchuan cattle population and effectively protect and utilize their germplasm resources. Herein, the single-nucleotide polymorphisms (SNPs) of 100 Dengchuan cattle (46 bulls and 54 cows) were determined using the GGP Bovine 100K SNP Beadchip. The results showed that among the Dengchuan cattle, a total of 101,220 SNPs were detected, and there were 83,534 SNPs that passed quality control, of which 85.7% were polymorphic. The average genetic distance based on identity-by-state (IBS) within the conservation population of Dengchuan cattle was 0.26 ± 0.02. A total of 3,999 genome-length runs of homozygosity (ROHs) were detected in the Dengchuan cattle, with ROH lengths primarily concentrated in the range of 1–5 Mb, accounting for 87.02% of the total. The average inbreeding coefficient based on ROHs was 4.6%, within the conservation population of Dengchuan cattle, whereas it was 4.9% for bulls, and the Wright inbreeding coefficient (FIS) value was 2.4%, demonstrating a low level of inbreeding within the Dengchuan cattle population. Based on neighbor-joining tree analysis, the Dengchuan cattle could be divided into 16 families. In summary, the conservation population of Dengchuan cattle displays relatively abundant diversity and a moderate genetic relationship. Inbreeding was observed among a few individuals, but the overall inbreeding level of the population remained low. It is important to maintain this low level of inbreeding when introducing purebred bloodlines to expand the core group. This approach will ensure the long-term conservation of Dengchuan cattle germplasm resources and prevent loss of genetic diversity.

Development and verification of a 10K liquid chip for Hainan black goat based on genotyping by pinpoint sequencing of liquid captured targets

BackgroundChina has thousands years of goat breeding and abundant goat genetic resources. Additionally, the Hainan black goat is one of the high-quality local goat breeds in China. In order to conserve the germplasm resources of the Hainan black goat, facilitate its genetic improvement and further protect the genetic diversity of goats, it is urgent to develop a single nucleotide polymorphism (SNP) chip for Hainan black goat.ResultsIn this study, we aimed to design a 10K liquid chip for Hainan black goat based on genotyping by pinpoint sequencing of liquid captured targets (cGPS). A total of 45,588 candidate SNP sites were obtained, 10,677 of which representative SNP sites were selected to design probes, which finally covered 9,993 intervals and formed a 10K cGPS liquid chip for Hainan black goat. To verify the 10K cGPS liquid chip, some southern Chinese goat breeds and a sheep breed with similar phenotype to the Hainan black goat were selected. A total of 104 samples were used to verify the clustering ability of the 10K cGPS liquid chip for Hainan black goat. The results showed that the detection rate of sites was 97.34% -99.93%. 84.5% of SNP sites were polymorphic. The heterozygosity rate was 3.08%-36.80%. The depth of more than 99.4% sites was above 10X. The repetition rate was 99.66%-99.82%. The average consistency between cGPS liquid chip results and resequencing results was 85.58%. In addition, the phylogenetic tree clustering analysis verified that the SNP sites on the chip had better clustering ability.ConclusionThese results indicate that we have successfully realized the development and verification of the 10K cGPS liquid chip for Hainan black goat, which provides a useful tool for the genome analysis of Hainan black goat. Moreover, the 10K cGPS liquid chip is conducive to the research and protection of Hainan black goat germplasm resources and lays a solid foundation for its subsequent breeding work.

Runs of homozygosity analysis for selection signatures in the Yellow Korean native chicken.

Yellow Korean native chicken (KNC-Y) is one of the five pure Korean indigenous chicken breeds that were restored through a government project in 1992. KNC-Y is recognized for its superior egg production performance compared to other KNC lines. In this study, we performed runs of homozygosity (ROH) analysis to discover selection signatures associated with egg production traits in the KNC-Y population. A total of 675 DNA samples from KNC-Y were genotyped to generate single nucleotide polymorphism (SNP) data using custom 60K Affymetrix SNP chips. ROH analysis was performed using PLINK software, with predefined parameters set for the analysis. The threshold of ROH island was defined as the top 1% frequency of SNPs withing the ROH among the population. In the KNC-Y population, a total of 29,958 runs of homozygosity (ROH) fragments were identified. The average total length of ROH was 120.84 Mb, with each ROH fragment having an average length of 2.71 Mb. The calculated ROH-based inbreeding coefficient (FROH) was 0.13. Furthermore, we revealed the presence of ROH islands on chromosomes 1, 2, 4, 5, 7, 8, and 11. Within the identified regions, a total of 111 genes were annotated, and among them were genes related to economic traits, including PRMT3, ANO5, HDAC4, LSS, PLA2G4A, and PTGS2. Most of the overlapping quantitative trait locus regions with ROH islands were found to be associated with production traits. This study conducted a comprehensive analysis of ROH in the KNC-Y population. Notably, among the findings, the PTGS2 gene is believed to play a crucial role in influencing the laying performance of KNC-Y.

Genomic prediction of blood biomarkers of metabolic disorders in Holstein cattle using parametric and nonparametric models

BackgroundMetabolic disturbances adversely impact productive and reproductive performance of dairy cattle due to changes in endocrine status and immune function, which increase the risk of disease. This may occur in the post-partum phase, but also throughout lactation, with sub-clinical symptoms. Recently, increased attention has been directed towards improved health and resilience in dairy cattle, and genomic selection (GS) could be a helpful tool for selecting animals that are more resilient to metabolic disturbances throughout lactation. Hence, we evaluated the genomic prediction of serum biomarkers levels for metabolic distress in 1353 Holsteins genotyped with the 100K single nucleotide polymorphism (SNP) chip assay. The GS was evaluated using parametric models best linear unbiased prediction (GBLUP), Bayesian B (BayesB), elastic net (ENET), and nonparametric models, gradient boosting machine (GBM) and stacking ensemble (Stack), which combines ENET and GBM approaches.ResultsThe results show that the Stack approach outperformed other methods with a relative difference (RD), calculated as an increment in prediction accuracy, of approximately 18.0% compared to GBLUP, 12.6% compared to BayesB, 8.7% compared to ENET, and 4.4% compared to GBM. The highest RD in prediction accuracy between other models with respect to GBLUP was observed for haptoglobin (hapto) from 17.7% for BayesB to 41.2% for Stack; for Zn from 9.8% (BayesB) to 29.3% (Stack); for ceruloplasmin (CuCp) from 9.3% (BayesB) to 27.9% (Stack); for ferric reducing antioxidant power (FRAP) from 8.0% (BayesB) to 40.0% (Stack); and for total protein (PROTt) from 5.7% (BayesB) to 22.9% (Stack). Using a subset of top SNPs (1.5k) selected from the GBM approach improved the accuracy for GBLUP from 1.8 to 76.5%. However, for the other models reductions in prediction accuracy of 4.8% for ENET (average of 10 traits), 5.9% for GBM (average of 21 traits), and 6.6% for Stack (average of 16 traits) were observed.ConclusionsOur results indicate that the Stack approach was more accurate in predicting metabolic disturbances than GBLUP, BayesB, ENET, and GBM and seemed to be competitive for predicting complex phenotypes with various degrees of mode of inheritance, i.e. additive and non-additive effects. Selecting markers based on GBM improved accuracy of GBLUP.

Genetic architecture of white striping in turkeys (Meleagris gallopavo).

White striping (WS) is a myopathy of growing concern to the turkey industry. It is rising in prevalence and has negative consequences for consumer acceptance and the functional properties of turkey meat. The objective of this studywas to conduct a genome-wide association study (GWAS) and functional analysis on WS severity. Phenotypic data consisted of white striping scored on turkey breast fillets (N = 8422) by trained observers on a 0-3 scale (none to severe). Of the phenotyped birds, 4667 genotypic records were available using a proprietary 65K single nucleotide polymorphism (SNP) chip. The SNP effects were estimated using a linear mixed model with a 30-SNP sliding window approach used to express the percentage genetic variance explained. Positional candidate genes were those located within 50kb of the top 1% of SNP windows explaining the most genetic variance. Of the 95 positional candidate genes, seven were further classified as functional candidate genes because of their association with both a significant gene ontology and molecular function term. The results of the GWAS emphasize the polygenic nature of the trait with no specific genomic region contributing a large portion to the overall genetic variance. Significant pathways relating to growth, muscle development, collagen formation, circulatory system development, cell response to stimulus, and cytokine production were identified. These results help to support published biological associations between WS and hypoxia and oxidative stress and provide information that may be useful for future-omics studies in understanding the biological associations with WS development in turkeys.

Evaluation of non-additive genetic effects on carcass and meat quality traits in Korean Hanwoo cattle using genomic models

The traditional genetic evaluation methods generally consider additive genetic effects only and often ignore non-additive (dominance and epistasis) effects that may have contributed to genetic variation of complex traits of livestock species. The available dense single nucleotide polymorphisms (SNPs) panels offer to investigate the potential benefits of including non-additive genetic effects in the genomic evaluation models. Data from 16 971 genotyped (Illumina Bovine 50 K SNP chip) Korean Hanwoo cattle were used to estimate genetic variance components and prediction accuracy of genomic breeding values (GEBVs) for four carcass and meat quality traits: carcass weight (CWT), eye muscle area (EMA), back fat thickness (BFT) and marbling score (MS). Five different genetic models were evaluated through including additive, dominance and epistatic interactions (additive by additive, A × A; additive by dominance, A × D and dominance by dominance, D × D) successively in the models. The estimates of additive genetic variances and narrow sense heritabilities (ha2) were found similar across the evaluated models and traits except when additive interaction (A × A) was included. The dominance variance estimates relative to phenotypic variance ranged from 1.7–3.4% for CWT and MS traits, whereas, they were close to zero for EMA and BFT traits. The magnitude of A × A epistatic heritability (haa2) ranged between 14.8 and 27.7% in all traits. However, heritability estimates for A × D and D × D epistatic interactions (had2 and hdd2) were quite low compared to haa2 and were contributed only 0.0–9.7% of the total phenotypic variation. In general, broad sense heritability (hG2) estimates were almost twice (ranging between 0.54 and 0.68) the ha2 for all of the investigated traits. The inclusion of dominance effects did not improve the prediction accuracy of GEBV but improved 2.0–3.0% when epistatic effects were included in the model. More importantly, rank correlation revealed that partitioning of variance components considering dominance and epistatic effects in the model would enable to re-rank of top animals with better prediction of GEBV. The present result suggests that dominance and epistatic effects could be included in the genomic evaluation model for better estimates of variance components and more accurate prediction of GEBV for carcass and meat quality traits in Korean Hanwoo cattle.

Large-scale genome-wide SNP analysis reveals the rugged (and ragged) landscape of global ancestry, phylogeny, and demographic history in chicken breeds.

The worldwide chicken gene pool encompasses a remarkable, but shrinking, number of divergently selected breeds of diverse origin. This study was a large-scale genome-wide analysis of the landscape of the complex molecular architecture, genetic variability, and detailed structure among 49 populations. These populations represent a significant sample of the world's chicken breeds from Europe (Russia, Czech Republic, France, Spain, UK, etc.), Asia (China), North America (USA), and Oceania (Australia). Based on the results of breed genotyping using the Illumina 60K single nucleotide polymorphism (SNP) chip, a bioinformatic analysis was carried out. This included the calculation of heterozygosity/homozygosity statistics, inbreeding coefficients, and effective population size. It also included assessment of linkage disequilibrium and construction of phylogenetic trees. Using multidimensional scaling, principal component analysis, and ADMIXTURE-assisted global ancestry analysis, we explored the genetic structure of populations and subpopulations in each breed. An overall 49-population phylogeny analysis was also performed, and a refined evolutionary model of chicken breed formation was proposed, which included egg, meat, dual-purpose types, and ambiguous breeds. Such a large-scale survey of genetic resources in poultry farming using modern genomic methods is of great interest both from the viewpoint of a general understanding of the genetics of the domestic chicken and for the further development of genomic technologies and approaches in poultry breeding. In general, whole genome SNP genotyping of promising chicken breeds from the worldwide gene pool will promote the further development of modern genomic science as applied to poultry.

A genotyping array for the globally invasive vector mosquito, Aedes albopictus

BackgroundAlthough whole-genome sequencing (WGS) is the preferred genotyping method for most genomic analyses, limitations are often experienced when studying genomes characterized by a high percentage of repetitive elements, high linkage, and recombination deserts. The Asian tiger mosquito (Aedes albopictus), for example, has a genome comprising up to 72% repetitive elements, and therefore we set out to develop a single-nucleotide polymorphism (SNP) chip to be more cost-effective. Aedes albopictus is an invasive species originating from Southeast Asia that has recently spread around the world and is a vector for many human diseases. Developing an accessible genotyping platform is essential in advancing biological control methods and understanding the population dynamics of this pest species, with significant implications for public health.MethodsWe designed a SNP chip for Ae. albopictus (Aealbo chip) based on approximately 2.7 million SNPs identified using WGS data from 819 worldwide samples. We validated the chip using laboratory single-pair crosses, comparing technical replicates, and comparing genotypes of samples genotyped by WGS and the SNP chip. We then used the chip for a population genomic analysis of 237 samples from 28 sites in the native range to evaluate its usefulness in describing patterns of genomic variation and tracing the origins of invasions.ResultsProbes on the Aealbo chip targeted 175,396 SNPs in coding and non-coding regions across all three chromosomes, with a density of 102 SNPs per 1 Mb window, and at least one SNP in each of the 17,461 protein-coding genes. Overall, 70% of the probes captured the genetic variation. Segregation analysis found that 98% of the SNPs followed expectations of single-copy Mendelian genes. Comparisons with WGS indicated that sites with genotype disagreements were mostly heterozygotes at loci with WGS read depth < 20, while there was near complete agreement with WGS read depths > 20, indicating that the chip more accurately detects heterozygotes than low-coverage WGS. Sample sizes did not affect the accuracy of the SNP chip genotype calls. Ancestry analyses identified four to five genetic clusters in the native range with various levels of admixture.ConclusionsThe Aealbo chip is highly accurate, is concordant with genotypes from WGS with high sequence coverage, and may be more accurate than low-coverage WGS.Graphical