Significant Single Nucleotide Polymorphisms Research Articles

Disentangling the causal effects of education and participation bias on Alzheimer’s disease using Mendelian Randomization

AbstractBackgroundHigher education has been associated with reduced risk of Alzheimer’s Disease (AD) based on previous epidemiological research. However, the relationship between education and AD could be influenced by participation bias whereby people with higher education may be more likely to be enrolled in studies. In this study, we use two‐sample Mendelian randomization (MR) to investigate the potential effects of education and participation bias on AD and further investigate their relationship.MethodGenome‐wide association summary (GWAS) statistics were obtained from GWAS’s of educational attainment (n = 1,100,000), participation in an optional mental health questionnaire (MHQ) of the UK Biobank (n = 451,036) and AD (n = 94,437). Independent genome‐wide significant (r2 = 0.001, 10Mb window, p<5×10−8) single nucleotide polymorphisms (SNPs) were extracted from the exposure summary statistics and harmonized with the outcome SNPs. Inverse variance weighted (IVW) meta‐analysis was the primary MR method and sensitivity analyses included MR Egger, Weighted Median and Weighted mode. Cochran’s Q statistic was used to test for heterogeneity, MR Egger intercept for pleiotropy, and radial MR to identify outliers.ResultGenetically predicted higher educational attainment was causally associated with a reduced risk of AD (IVW OR [95% CI]: 0.691 [0.548, 0.832], p = 3.29e‐07). Similarly, participation in the MHQ was also associated with a reduction in AD risk (IVW OR [95% CI]: 0.987 [0.975, 0.998], p = 0.031]. Our analysis showed no evidence of heterogeneity or pleiotropy and radial MR analysis did not identify any significant outliers, indicating that our univariate MR analyses were robust.ConclusionUnivariant MR analyses indicated that education and participation were both associated with a reduced risk of AD. However, further investigation using multivariable MR is necessary to fully evaluate their independent effects on AD through multiple clumping and proxy variant identification steps. This will allow us to see if the protective effect of education on AD is mediated by participation bias.

Kernel Bioassay Evaluation of Maize Ear Rot and Genome-Wide Association Analysis for Identifying Genetic Loci Associated with Resistance to Fusarium graminearum Infection.

Gibberella ear rot (GER) caused by Fusarium graminearum (teleomorph Gibberella zeae) is one of the most destructive diseases in maize, which severely reduces yield and contaminates several potential mycotoxins in the grain. However, few efforts had been devoted to dissecting the genetic basis of maize GER resistance. In the present study, a genome-wide association study (GWAS) was conducted in a maize association panel consisting of 303 diverse inbred lines. The phenotypes of GER severity were evaluated using kernel bioassay across multiple time points in the laboratory. Then, three models, including the fixed and random model circulating probability unification model (FarmCPU), general linear model (GLM), and mixed linear model (MLM), were conducted simultaneously in GWAS to identify single-nucleotide polymorphisms (SNPs) significantly associated with GER resistance. A total of four individual significant association SNPs with the phenotypic variation explained (PVE) ranging from 3.51 to 6.42% were obtained. Interestingly, the peak SNP (PUT-163a-71443302-3341) with the greatest PVE value, was co-localized in all models. Subsequently, 12 putative genes were captured from the peak SNP, and several of these genes were directly or indirectly involved in disease resistance. Overall, these findings contribute to understanding the complex plant-pathogen interactions in maize GER resistance. The regions and genes identified herein provide a list of candidate targets for further investigation, in addition to the kernel bioassay that can be used for evaluating and selecting elite germplasm resources with GER resistance in maize.

Genome-Wide Association Analysis of Freezing Tolerance and Winter Hardiness in Winter Wheat of Nordic Origin

Climate change and global food security efforts are driving the need for adaptable crops in higher latitude temperate regions. To achieve this, traits linked with winter hardiness must be introduced in winter-type crops. Here, we evaluated the freezing tolerance (FT) of a panel of 160 winter wheat genotypes of Nordic origin under controlled conditions and compared the data with the winter hardiness of 74 of these genotypes from a total of five field trials at two locations in Norway. Germplasm with high FT was identified, and significant differences in FT were detected based on country of origin, release years, and culton type. FT measurements under controlled conditions significantly correlated with overwintering survival scores in the field (r ≤ 0.61) and were shown to be a reliable complementary high-throughput method for FT evaluation. Genome-wide association studies (GWAS) revealed five single nucleotide polymorphism (SNP) markers associated with FT under controlled conditions mapped to chromosomes 2A, 2B, 5A, 5B, and 7A. Field trials yielded 11 significant SNP markers located within or near genes, mapped to chromosomes 2B, 3B, 4A, 5B, 6B, and 7D. Candidate genes identified in this study can be introduced into the breeding programs of winter wheat in the Nordic region.

Genome-Wide Association Mapping and Genomic Prediction of Fusarium Wilt Race 2 Resistance in the USDA Citrullus amarus Collection.

Fusarium wilt caused by Fusarium oxysporum f. sp. niveum (Fon) race 2 is a serious disease in watermelon and can reduce yields by 80%. Genome-wide association studies (GWAS) are a valuable tool in dissecting the genetic basis of traits. Citrullus amarus accessions (n = 120) from the USDA germplasm collection were genotyped with whole-genome resequencing, resulting in 2,126,759 single nucleotide polymorphic (SNP) markers that were utilized for GWAS. Three models were used for GWAS with the R package GAPIT. Mixed linear model (MLM) analysis did not identify any significant marker associations. FarmCPU identified four quantitative trait nucleotides (QTN) on three different chromosomes (i.e., chromosomes 1, 5, and 9), and Bayesian-information and linkage-disequilibrium iteratively nested keyway (BLINK) identified one QTN on chromosome 10 as significantly associated with Fon race 2 resistance. FarmCPU identified four QTN that explained 60% of Fon race 2 resistance, and the single QTN from BLINK explained 27%. Relevant candidate genes were found within the linkage disequilibrium (LD) blocks of these significant SNPs, including genes encoding aquaporins, expansins, 2S albumins, and glutathione S-transferases which have been shown to be involved in imparting resistance to Fusarium spp. Genomic predictions (GP) for Fon race 2 resistance using all 2,126,759 SNPs resulted in a mean prediction accuracy of 0.08 with five-fold cross-validation employing genomic best linear unbiased prediction (gBLUP) or ridge-regression best linear unbiased prediction (rrBLUP). Mean prediction accuracy with gBLUP leave-one-out cross-validation was 0.48. Thus, along with identifying genomic regions associated with Fon race 2 resistance among the accessions, this study observed prediction accuracies that were strongly influenced by population size.

Genome-Wide Association Studies and Runs of Homozygosity to Identify Reproduction-Related Genes in Yorkshire Pig Population.

Reproductive traits hold considerable economic importance in pig breeding and production. However, candidate genes underpinning the reproductive traits are still poorly identified. In the present study, we executed a genome-wide association study (GWAS) and runs of homozygosity (ROH) analysis using the PorcineSNP50 BeadChip array for 585 Yorkshire pigs. Results from the GWAS identified two genome-wide significant and eighteen suggestive significant single nucleotide polymorphisms (SNPs) associated with seven reproductive traits. Furthermore, we identified candidate genes, including ELMO1, AOAH, INSIG2, NUP205, LYPLAL1, RPL34, LIPH, RNF7, GRK7, ETV5, FYN, and SLC30A5, which were chosen due to adjoining significant SNPs and their functions in immunity, fertilization, embryonic development, and sperm quality. Several genes were found in ROH islands associated with spermatozoa, development of the fetus, mature eggs, and litter size, including INSL6, TAF4B, E2F7, RTL1, CDKN1C, and GDF9. This study will provide insight into the genetic basis for pig reproductive traits, facilitating reproduction improvement using the marker-based selection methods.

Joint analysis of multiple phenotypes for extremely unbalanced case-control association studies using multi-layer network.

Genome-wide association studies is an essential tool for analyzing associations between phenotypes and single nucleotide polymorphisms (SNPs). Most of binary phenotypes in large biobanks are extremely unbalanced, which leads to inflated type I error rates for many widely used association tests for joint analysis of multiple phenotypes. In this article, we first propose a novel method to construct a Multi-Layer Network (MLN) using individuals with at least one case status among all phenotypes. Then, we introduce a computationally efficient community detection method to group phenotypes into disjoint clusters based on the MLN. Finally, we propose a novel approach, MLN with Omnibus (MLN-O), to jointly analyse the association between phenotypes and a SNP. MLN-O uses the score test to test the association of each merged phenotype in a cluster and a SNP, then uses the Omnibus test to obtain an overall test statistic to test the association between all phenotypes and a SNP. We conduct extensive simulation studies to reveal that the proposed approach can control type I error rates and is more powerful than some existing methods. Meanwhile, we apply the proposed method to a real data set in the UK Biobank. Using phenotypes in Chapter XIII (Diseases of the musculoskeletal system and connective tissue) in the UK Biobank, we find that MLN-O identifies more significant SNPs than other methods we compare with. https://github.com/Hongjing-Xie/Multi-Layer-Network-with-Omnibus-MLN-O.

Elucidation of the genetic determination of clutch traits in Chinese local chickens of the Laiwu Black breed

BackgroundEgg laying rate (LR) is associated with a clutch, which is defined as consecutive days of oviposition. The clutch trait can be used as a selection indicator to improve egg production in poultry breeding. However, little is known about the genetic basis of clutch traits. In this study, our aim was to estimate genetic parameters and identify quantitative trait single nucleotide polymorphisms for clutch traits in 399 purebred Laiwu Black chickens (a native Chinese breed) using a genome-wide association study (GWAS).MethodsIn this work, after estimating the genetic parameters of age at first egg, body weight at first egg, LR, longest clutch until 52 week of age, first week when the longest clutch starts, last week when the longest clutch ends, number of clutches, and longest number of days without egg-laying until 52 week of age, we identified single nucleotide polymorphisms (SNPs) and potential candidate genes associated with clutch traits in Laiwu Black chickens. The restricted maximum likelihood method was used to estimate genetic parameters of clutch pattern in 399 Laiwu Black hens, using the GCTA software.ResultsThe results showed that SNP-based heritability estimates of clutch traits ranged from 0.06 to 0.59. Genotyping data were obtained from whole genome re-sequencing data. After quality control, a total of 10,810,544 SNPs remained to be analyzed. The GWAS revealed that 421 significant SNPs responsible for clutch traits were scattered on chicken chromosomes 1–14, 17–19, 21–25, 28 and Z. Among the annotated genes, NELL2, SMYD9, SPTLC2, SMYD3 and PLCL1 were the most promising candidates for clutch traits in Laiwu Black chickens.ConclusionThe findings of this research provide critical insight into the genetic basis of clutch traits. These results contribute to the identification of candidate genes and variants. Genes and SNPs potentially provide new avenues for further research and would help to establish a framework for new methods of genomic prediction, and increase the accuracy of estimated genetic merit for egg production and clutch traits.

Genetic diversity and breed-informative SNPs identification in domestic pig populations using coding SNPs.

Background: The use of breed-informative genetic markers, specifically coding Single Nucleotide Polymorphisms (SNPs), is crucial for breed traceability, authentication of meat and dairy products, and the preservation and improvement of pig breeds. By identifying breed informative markers, we aimed to gain insights into the genetic mechanisms that influence production traits, enabling informed decisions in animal management and promoting sustainable pig production to meet the growing demand for animal products. Methods: Our dataset consists of 300 coding SNPs genotyped from three Italian commercial pig populations: Landrace, Yorkshire, and Duroc. Firstly, we analyzed the genetic diversity among the populations. Then, we applied a discriminant analysis of principal components to identify the most informative SNPs for discriminating between these populations. Lastly, we conducted a functional enrichment analysis to identify the most enriched pathways related to the genetic variation observed in the pig populations. Results: The alpha diversity indexes revealed a high genetic diversity within the three breeds. The higher proportion of observed heterozygosity than expected revealed an excess of heterozygotes in the populations that was supported by negative values of the fixation index (FIS) and deviations from the Hardy-Weinberg equilibrium. The Euclidean distance, the pairwise FST, and the pairwise Nei's GST genetic distances revealed that Yorkshire and Landrace breeds are genetically the closest, with distance values of 2.242, 0.029, and 0.033, respectively. Conversely, Landrace and Duroc breeds showed the highest genetic divergence, with distance values of 2.815, 0.048, and 0.052, respectively. We identified 28 significant SNPs that are related to phenotypic traits and these SNPs were able to differentiate between the pig breeds with high accuracy. The Functional Enrichment Analysis of the informative SNPs highlighted biological functions related to DNA packaging, chromatin integrity, and the preparation of DNA into higher-order structures. Conclusion: Our study sheds light on the genetic underpinnings of phenotypic variation among three Italian pig breeds, offering potential insights into the mechanisms driving breed differentiation. By prioritizing breed-specific coding SNPs, our approach enables a more focused analysis of specific genomic regions relevant to the research question compared to analyzing the entire genome.

Elucidating the causal association between gut microbiota and intrahepatic cholangiocarcinoma through Mendelian randomization analysis.

Intrahepatic cholangiocarcinoma (ICC) is an aggressive liver cancer with poor prognosis. The gut microbiota has been linked to ICC, but evidence for causality is lacking. Elucidating causal gut microbiota-ICC links could inform prevention and treatment strategies. We performed a bidirectional two-sample Mendelian randomization (MR) study to investigate causal associations between gut microbiota and ICC risk. Genome-wide significant single nucleotide polymorphisms (SNPs) associated with gut microbiota abundances were utilized as instrumental variables (IVs). Multiple methods assessed causality and sensitivity analyses evaluated result robustness. Bioinformatics analysis of genetic loci linked to gut microbiota and ICC examined potential mechanisms. Genetically predicted increases in Veillonellaceae, Alistipes, Enterobacteriales, and Firmicutes were suggestively associated with higher ICC risk, while increases in Anaerostipes, Paraprevotella, Parasutterella, and Verrucomicrobia appeared protective. Bioinformatics analysis revealed differentially expressed genes near gut microbiota-associated loci may influence ICC through regulating pathways and tumor immune microenvironment. Our findings provide suggestive evidence for causal links between specific gut microbiota and ICC risk.

GWAS and Meta-QTL Analysis of Yield-Related Ear Traits in Maize.

Maize ear traits are an important component of yield, and the genetic basis of ear traits facilitates further yield improvement. In this study, a panel of 580 maize inbred lines were used as the study material, eight ear-related traits were measured through three years of planting, and whole genome sequencing was performed using the maize 40 K breeding chip based on genotyping by targeted sequencing (GBTS) technology. Five models were used to conduct a genome-wide association study (GWAS) on best linear unbiased estimate (BLUE) of ear traits to find the best model. The FarmCPU (Fixed and random model Circulating Probability Unification) model was the best model for this study; a total of 104 significant single nucleotide polymorphisms (SNPs) were detected, and 10 co-location SNPs were detected simultaneously in more than two environments. Through gene function annotation and prediction, a total of nine genes were identified as potentially associated with ear traits. Moreover, a total of 760 quantitative trait loci (QTL) associated with yield-related traits reported in 37 different articles were collected. Using the collected 760 QTL for meta-QTL analysis, a total of 41 MQTL (meta-QTL) associated with yield-related traits were identified, and 19 MQTL detected yield-related ear trait functional genes and candidate genes that have been reported in maize. Five significant SNPs detected by GWAS were located within these MQTL intervals, and another three significant SNPs were close to MQTL (less than 1 Mb). The results provide a theoretical reference for the analysis of the genetic basis of ear-related traits and the improvement of maize yield.

PSVII-8 Genome-Wide Association Studies for Feed Efficiency and Growth Traits in American Mink

Abstract Feed efficiency (FE) traits contribute to the economic output of mink production systems as feed costs comprise the largest proportion of their variable expenses. However, the genetic architecture underlying FE-related traits is largely unknown in American mink. The objective of this study was to identify potential genetic variants and candidate genes associated with feed efficiency and growth traits, including body weight (BW), average daily gain (ADG), daily feed intake (DFI), feed conversion ratio (FCR), residual feed intake (RFI), residual gain (RG), residual intake and gain (RIG), and Kleiber ratio (KR). Genome-wide association studies (GWAS) were performed using deregressed estimated breeding values (DEBVs) of 1,255 to 2,160 individuals (as pseudophenotypes), genotyped with the Affymetrix Mink 70K single nucleotide polymorphisms (SNP) array. Association analyses were performed using the mixed linear model in GCTA software. A total of 36 SNPs located on 11 different chromosomes were significantly (FDR < 0.01) associated with eight feed efficiency and growth traits, among which nine SNPs had pleiotropic effects on at least two analyzed traits. The phenotypic variance (of DEBVs) explained by all significant SNPs for BW, ADG, DFI, FCR, RFI, RG, RIG, and KR, were 0.54%, 2.35%, 0.51%, 2.45%, 0.03%, 3.67%, 0.21%, and 2.60%, respectively. Furthermore, 191 genes were identified within 1-Mb windows around these significant SNPs. These regions included candidate genes such as FABP6, ADAMTS18, ADGRB3, GRM8, DSCAM, COL9A1, and CSRP2, previously associated with feed efficiency and growth traits in other livestock species. Gene ontology analyses revealed that these genes were involved in molecular functions such as ATPase activity and ATP binding, which provide the direct energy source for the body. To our knowledge, this is the first GWAS to identify genetic variants and biological mechanisms associated with FE and growth traits in American mink. These findings provide a biological foundation for improving these traits using genomic selection programs to select more efficient mink.

PSXIII-26 Investigating the Genetic Background of Juniper Consumption in Goats

Abstract Junipers (Juniperus spp.) are woody invasive plants that have caused encroachment problems in the U.S. western rangeland, decreasing forage productivity and biodiversity. A potential solution to this issue is the use of goats in target grazing programs. Selecting goats for juniper consumption is of great interest to rangeland farmers. Therefore, our main objectives were to 1) estimate genetic parameters, including heritability and repeatability, for juniper consumption in Angora (ANG) and Boer x Spanish (BxS) composite population of goats grazing on West Texas rangelands (USA); and, 2) perform a genome-wide association study (GWAS) to identify candidate genes associated with juniper consumption. Fecal samples were collected multiple times between 2008 and 2017 and analyzed using near-infrared reflectance spectroscopy (NIRS) to estimate the percentage of juniper in the diet of goats, using calibration equations previously developed in controlled studies. We analyzed a dataset comprising 2,327 records from 459 ANG and 8,714 records from 1,996 BxS. The pedigree file included 1,601 and 2,426 ANG and BxS goats, respectively. Genomic information for 50,957 single nucleotide polymorphisms (SNP) from 93 ANG and 238 BxS goats was included in the analyses. Sampling date and sex were fitted as categorical fixed effects and age as a linear covariate in the statistical models. Animal direct additive genetic and permanent environment were considered as random effects. Genetic parameters were calculated based on the Restricted Maximum Likelihood method under the single-step genomic BLUP procedure implemented in the BLUPf90+ family of programs. We used de-regressed estimated breeding values and whole-genome sequence data for the GWAS analyses with 8 million SNP for the ANG and 5.3 million SNP for the BxS. The software GCTA was employed for these analyses. Juniper percentage in their diets varied across the years and ranged from 2.14% (± 7.51%) to 14.6% (± 11.0%) for ANG and from 10.5% (± 14.7) to 33.8% (± 18.1) for the BxS population. The heritability estimate for juniper consumption was 0.19 (± 0.038) for ANG and 0.28 (± 0.022) for BxS, indicating that juniper consumption can be increased through selection. The repeatability values were 0.21 for ANG and 0.37 for BxS. The GWAS revealed 1,257 significant SNP located within or close to 220 genes in ANG, and 878 SNP related to 159 genes in BxS, suggesting their association with juniper consumption. These findings suggest that juniper consumption is under genetic control and has a polygenic inheritance pattern influenced by multiple genes of small effect. The heritability and repeatability estimates indicate that genetic improvement of juniper consumption is feasible in both goat populations.

CYP450 and drug efflux transporters polymorphism influence clinical outcomes of Thai osimertinib-treated non-small cell lung cancer patients.

Background: Osimertinib has shown greater efficacy than standard epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) and fewer grade 3 or higher adverse drug reactions (ADRs) in patients with advanced non-small cell lung cancer (NSCLC) harboring epidermal growth factor receptor (EGFR) mutations. However, the clinical outcomes of osimertinib treatment vary depending on the patient's ethnicity. Therefore, further research is necessary to evaluate the impact of single nucleotide polymorphisms (SNPs) in cytochrome P450 (CYP450) and drug transporters on the therapeutic outcomes and ADRs to osimertinib in Thai patients, to provide improved pharmacological treatments for cancer patients. Methods: This retrospective and prospective cohort study enrolled 63 Thai patients with NSCLC treated with 80mg of osimertinib once daily as monotherapy. Seventeen SNPs in candidate genes related to drug metabolism and transport pathways were analyzed in each patient. Chi-square or Fisher's exact tests were used to evaluate the associations between SNPs and clinical outcomes, including ADR incidence and objective response rate (ORR). In addition, the correlation between the genotype and median time to treatment failure (TTF) or progression-free survival (PFS) was assessed using Kaplan-Meier analysis and a log-rank test. Results: We identified six SNPs (rs2231142 and rs2622604 in ABCG2, rs762551 in CYP1A2, rs1057910 in CYP2C9, rs28371759 in CYP3A4, and CYP2A6 deletion polymorphism (CYP2A6*4)) that significantly increased the incidence of ADRs. In addition, we found two SNPs (rs2069514 in CYP1A2 and rs1057910 in CYP2C9) that significantly decreased the median TTF, and two SNPs (rs28399433 in CYP2A6 and rs1057910 in CYP2C9) that significantly decreased the median progression-free survival (PFS). Specifically, we found that one of these SNPs (rs1057910 in CYP2C9) influenced ADRs, TTF, and PFS. Additionally, SNPs in the CYP2A6 heterozygous variant (non4/*4) significantly increased ADR incidence, leading to a high frequency of dose reduction (27.0%). Conclusion: Our study demonstrated significant SNPs associated with increased ADR incidence, decreased PFS, and decreased TTF in Thai patients with NSCLC treated with osimertinib. The CYP2C9 (*3) and CYP2A6 (*4) allele frequencies differed between ethnicities and were associated with an increased incidence of ADRs. These findings highlight the importance of considering genetic factors in NSCLC treatment and may facilitate personalized medicine approaches. Moreover, our study showed a higher incidence of ADRs than the previous trials, including FLAURA and AURA2, and a higher frequency of dose reduction than reported in the AURA 3 trial, possibly due to genetic differences among the study populations.

Across-country genetic and genomic analyses of foot score traits in American and Australian Angus cattle

BackgroundHoof structure and health are essential for the welfare and productivity of beef cattle. Therefore, we assessed the genetic and genomic background of foot score traits in American (US) and Australian (AU) Angus cattle and investigated the feasibility of performing genomic evaluations combining data for foot score traits recorded in US and AU Angus cattle. The traits evaluated were foot angle (FA) and claw set (CS). In total, 109,294 and ~ 1.12 million animals had phenotypic and genomic information, respectively. Four sets of analyses were performed: (1) genomic connectedness between US and AU Angus cattle populations and population structure, (2) estimation of genetic parameters, (3) single-step genomic prediction of breeding values, and (4) single-step genome-wide association studies for FA and CS.ResultsThere was no clear genetic differentiation between US and AU Angus populations. Similar heritability estimates (FA: 0.22–0.24 and CS: 0.22–0.27) and moderate-to-high genetic correlations between US and AU foot scores (FA: 0.61 and CS: 0.76) were obtained. A joint-genomic prediction using data from both populations outperformed within-country genomic evaluations. A genomic prediction model considering US and AU datasets as a single population performed similarly to the scenario accounting for genotype-by-environment interactions (i.e., multiple-trait model considering US and AU records as different traits), even though the genetic correlations between countries were lower than 0.80. Common significant genomic regions were observed between US and AU for FA and CS. Significant single nucleotide polymorphisms were identified on the Bos taurus (BTA) chromosomes BTA1, BTA5, BTA11, BTA13, BTA19, BTA20, and BTA23. The candidate genes identified were primarily from growth factor gene families, including FGF12 and GDF5, which were previously associated with bone structure and repair.ConclusionsThis study presents comprehensive population structure and genetic and genomic analyses of foot scores in US and AU Angus cattle populations, which are essential for optimizing the implementation of genomic selection for improved foot scores in Angus cattle breeding programs. We have also identified candidate genes associated with foot scores in the largest Angus cattle populations in the world and made recommendations for genomic evaluations for improved foot score traits in the US and AU.

Complete mitochondrial genome sequence of historical olive (Olea europaea Linnaeus 1753 subsp. europaea) cultivar Mehras in Jordan

The complete mitochondrial genome of the olive cultivar Mehras was determined using high-throughput sequencing technology. It consisted of 710,808 base pairs and comprised 70 genes, including 44 protein-coding genes, 23 tRNA genes, and three rRNA genes, with a GC content of 44.7%. Significant single nucleotide polymorphisms (SNPs) and insertions/deletions (InDels) were detected throughout the mitogenome. Phylogenetic analysis was conducted using other genotypes, including five olive cultivars, three related species, and Olea exasperata as an out-group. The analysis revealed that the olive cultivar Mehras shares an ancient common ancestor with the Frantoio cultivar from Italy and the Manzanilla cultivar from Spain, which confirms previous findings based on plastome sequencing.

Ethnic-specific associations between body mass index and gastric cancer: a Mendelian randomization study in European and Korean populations.

Given the uncertainties surrounding the associations in previous epidemiological studies, we conducted linear and nonlinear Mendelian randomization (MR) studies to evaluate whether body mass index (BMI) associated with gastric cancer (GC) risk in European and Korean. Genome-wide association study-summary statistics were used from the Pan-UK Biobank, the Genetic Investigation of Anthropometric Traits consortium, the K-CHIP consortium, and BioBank Japan. BMI-associated single nucleotide polymorphisms (SNPs) were used as instrumental variables (IVs) in MR to identify the association between BMI and GC. Both linear and nonlinear MR analyses were performed. Sensitivity analyses were also conducted for individuals below or above a BMI of 24kg/m2. The study used 22 and 55 SNPs as IVs for BMI in European and Korean populations, respectively. Genetically predicted BMI was positively associated with GC risk in the European population (Odds ratio per 1kg/m2 increase; 95% CI = 1.17; 1.01-1.36 using simple median method), but no significant association was observed in the Korean population. However, the nonlinear MR identified a U-shaped association between BMI and GC in the Korean population, with both low and high BMIs associated with increased GC risk. A BMI of 24kg/m2 presented the lowest risk. Sensitivity analyses did not yield any genome-wide significant SNPs. While MR analysis suggests a linear association between BMI and GC in those of European ancestry, nonlinear MR hints at a U-shaped association in Koreans. This suggests the association between BMI and GC risk may vary according to ethnic ancestry.

Novel genetic resources associated with sucrose and stachyose content through genome-wide association study in soybean (Glycine max (L.) Merr.).

The nutritional value of soybean [Glycine max (L.) Merr.] for animals is influenced by soluble carbohydrates, such as sucrose and stachyose. Although sucrose is nutritionally desirable, stachyose is an antinutrient causing diarrhea and flatulence in non-ruminant animals. We conducted a genome-wide association study of 220 soybean accessions using 21,317 single nucleotide polymorphisms (SNPs) from the SoySNP50K iSelect Beadchip data to identify significant SNPs associated with sucrose and stachyose content. Seven significant SNPs were identified for sucrose content across chromosomes (Chrs.) 2, 8, 12, 17, and 20, while thirteen significant SNPs were identified for stachyose content across Chrs. 2, 5, 8, 9, 10, 13, 14, and 15. Among those significant SNPs, three sucrose-related SNPs on Chrs. 8 and 17 were novel, while twelve stachyose-related SNPs on Chrs. 2, 5, 8, 9, 10, 13, 14, and 15 were novel. Based on Phytozome, STRING, and GO annotation, 17 and 24 candidate genes for sucrose and stachyose content, respectively, were highly associated with the carbohydrate metabolic pathway. Among these, the publicly available RNA-seq Atlas database highlighted four candidate genes associated with sucrose (Glyma.08g361200 and Glyma.17g258100) and stachyose (Glyma.05g025300 and Glyma.13g077900) content, which had higher gene expression levels in developing seed and multiple parts of the soybean plant. The results of this study will extend knowledge of the molecular mechanism and genetic basis underlying sucrose and stachyose content in soybean seed. Furthermore, the novel candidate genes and SNPs can be valuable genetic resources that soybean breeders may utilize to modify carbohydrate profiles for animal and human usage.

Genome-wide association study of feed conversion ratio in turbot (Scophthalmus maximus) based on genome resequencing

The feed conversion rate (FCR) is a crucial economic trait in aquaculture fish, as feed costs account for the vast majority of aquaculture costs. Given the importance of this trait, there have little efforts to unravel the genomic architecture of FCR and identify key genes or genomic regions useful as selection makers. This situation may stem from the inherent swimming behavior of fish, which presents challenges in obtaining individual FCRs. In this work, we developed a specialized small cage culture system. Through this system, the Feed Conversion Ratio (FCR) of 300 individuals was successfully determined, marking the first successful determination of individual FCRs for turbot. The results revealed a range of FCR values from 35.3% to 192.6%, with an average of 126.5% ± 23.5%. On this basis, a genome-wide association study (GWAS) was conducted to identify single nucleotide polymorphisms (SNP) associated with FCR. A total of 2613,115 SNPs on 22 chromosomes were selected for GWAS analysis by Efficient Mixed-Model Association eXpedited (EMMAX) software. A linear mixed model was employed to test the association between each SNP and FCR, considering population structure and genetic relatedness among individuals. Two significant SNPs on Chr6 were identified to be correlated with FCR. According to their localization in genome, four candidate genes were identified on Chr6, including uncharacterized protein KIAA1755, Kinesin Family Member 21B (KIF21B), Discs large homolog-associated protein 4B (DLGAP4B), and Copine 5B (CPNE5B), all of which are closely located in the genome and exhibit significant functional similarities. Our results will facilitate the implementation of marker-assisted selection in breeding programs and serve as a foundation for future research in this area.

Identification of genetic variants associated with anterior cruciate ligament rupture and AKC standard coat color in the Labrador Retriever

Canine anterior cruciate ligament (ACL) rupture is a common complex disease. Prevalence of ACL rupture is breed dependent. In an epidemiological study, yellow coat color was associated with increased risk of ACL rupture in the Labrador Retriever. ACL rupture risk variants may be linked to coat color through genetic selection or through linkage with coat color genes. To investigate these associations, Labrador Retrievers were phenotyped as ACL rupture case or controls and for coat color and were single nucleotide polymorphism (SNP) genotyped. After filtering, ~ 697 K SNPs were analyzed using GEMMA and mvBIMBAM for multivariate association. Functional annotation clustering analysis with DAVID was performed on candidate genes. A large 8 Mb region on chromosome 5 that included ACSF3, as well as 32 additional SNPs, met genome-wide significance at P < 6.07E-7 or Log10(BF) = 3.0 for GEMMA and mvBIMBAM, respectively. On chromosome 23, SNPs were located within or near PCCB and MSL2. On chromosome 30, a SNP was located within IGDCC3. SNPs associated with coat color were also located within ADAM9, FAM109B, SULT1C4, RTDR1, BCR, and RGS7. DZIP1L was associated with ACL rupture. Several significant SNPs on chromosomes 2, 3, 7, 24, and 26 were located within uncharacterized regions or long non-coding RNA sequences. This study validates associations with the previous ACL rupture candidate genes ACSF3 and DZIP1L and identifies novel candidate genes. These variants could act as targets for treatment or as factors in disease prediction modeling. The study highlighted the importance of regulatory SNPs in the disease, as several significant SNPs were located within non-coding regions.

Identification of Candidate Genes for Economically Important Carcass Cutting in Commercial Pigs through GWAS.

During the process of pork production, the carcasses of pigs are divided and sold, which provides better economic benefits and market competitiveness for pork production than selling the carcass as a whole. Due to the significant cost of post-slaughter phenotypic measurement, the genetic architecture of tenderloin weight (TLNW) and rib weight (RIBW)-important components of pig carcass economic value-remain unknown. In this study, we conducted genome-wide association studies (GWAS) for TLNW and RIBW traits in a population of 431 Duroc × Landrace × Yorkshire (DLY) pigs. In our study, the most significant single nucleotide polymorphism (SNP) associated with TLNW was identified as ASGA0085853 (3.28 Mb) on Sus scrofa chromosome 12 (SSC12), while for RIBW, it was Affx-1115046258 (172.45 Mb) on SSC13. Through haplotype block analysis, we discovered a novel quantitative trait locus (QTL) associated with TLNW, spanning a 5 kb region on SSC12, and a novel RIBW-associated QTL spanning 1.42 Mb on SSC13. Furthermore, we hypothesized that three candidate genes, TIMP2 and EML1, and SMN1, are associated with TLNW and RIBW, respectively. Our research not only addresses the knowledge gap regarding TLNW, but also serves as a valuable reference for studying RIBW. The identified SNP loci strongly associated with TLNW and RIBW may prove useful for marker-assisted selection in pig breeding programs.