Genome-wide association study revealed a promising region and candidate genes for eggshell quality in an F2 resource population

Background

Eggshell is subject to quality loss with aging process of laying hens, and damaged eggshells result in economic losses of eggs. However, the genetic architecture underlying the dynamic eggshell quality remains elusive. Here, we measured eggshell quality traits, including eggshell weight (ESW), eggshell thickness (EST) and eggshell strength (ESS) at 11 time points from onset of laying to 72 weeks of age and conducted comprehensive genome-wide association studies (GWAS) in 1534 F₂ hens derived from reciprocal crosses between White Leghorn (WL) and Dongxiang chickens (DX).

Results

ESWs at all ages exhibited moderate SNP-based heritability estimates (0.30 ~ 0.46), while the estimates for EST (0.21 ~ 0.31) and ESS (0.20 ~ 0.27) were relatively low. Eleven independent univariate genome-wide screens for each trait totally identified 1059, 1026 and 1356 significant associations with ESW, EST and ESS, respectively. Most significant loci were in a region spanning from 57.3 to 71.4 Mb of chromosome 1 (GGA1), which together account for 8.4 ~ 16.5 % of the phenotypic variance for ESW from 32 to 72 weeks of age, 4.1 ~ 6.9 % and 2.95 ~ 16.1 % for EST and ESS from 40 to 72 weeks of age. According to linkage disequilibrium (LD) and conditional analysis, the significant SNPs in this region were in extremely strong linkage disequilibrium status. Ultimately, two missense SNPs in GGA1 and one in GGA4 were considered as promising loci on three independent genes including ITPR2, PIK3C2G, and NCAPG. The homozygotes of advantageously effective alleles on PIK3C2G and ITPR2 possessed the best eggshell quality and could partly counteract the negative effect of aging process. NCAPG had certain effect on eggshell quality for young hens.

Conclusions

Identification of the promising region as well as potential candidate genes will greatly advance our understanding of the genetic basis underlying dynamic eggshell quality and has the practical significance in breeding program for the improvement of eggshell quality, especially at the later part of laying cycle.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1795-7) contains supplementary material, which is available to authorized users.     

A genome-wide SNP scan reveals novel loci for egg production and quality traits in white leghorn and brown-egg dwarf layers

Availability of the complete genome sequence as well as high-density SNP genotyping platforms allows genome-wide association studies (GWAS) in chickens. A high-density SNP array containing 57,636 markers was employed herein to identify associated variants underlying egg production and quality traits within two lines of chickens, i.e., White Leghorn and brown-egg dwarf layers. For each individual, age at first egg (AFE), first egg weight (FEW), and number of eggs (EN) from 21 to 56 weeks of age were recorded, and egg quality traits including egg weight (EW), eggshell weight (ESW), yolk weight (YW), eggshell thickness (EST), eggshell strength (ESS), albumen height(AH) and Haugh unit(HU) were measured at 40 and 60 weeks of age. A total of 385 White Leghorn females and 361 brown-egg dwarf dams were selected to be genotyped. The genome-wide scan revealed 8 SNPs showing genome-wise significant (P<1.51E-06, Bonferroni correction) association with egg production and quality traits under the Fisher's combined probability method. Some significant SNPs are located in known genes including GRB14 and GALNT1 that can impact development and function of ovary, but more are located in genes with unclear functions in layers, and need to be studied further. Many chromosome-wise significant SNPs were also detected in this study and some of them are located in previously reported QTL regions. Most of loci detected in this study are novel and the follow-up replication studies may be needed to further confirm the functional significance for these newly identified SNPs.     

Midkine is a NF-κB-inducible gene that supports prostate cancer cell survival

Background

Atherosclerotic peripheral arterial disease (PAD) affects 8–10 million people in the United States and is associated with a marked impairment in quality of life and an increased risk of cardiovascular events. Noninvasive assessment of PAD is performed by measuring the ankle-brachial index (ABI). Complex traits, such as ABI, are influenced by a large array of genetic and environmental factors and their interactions. We attempted to characterize the genetic architecture of ABI by examining the main and interactive effects of individual single nucleotide polymorphisms (SNPs) and conventional risk factors.

Methods

We applied linear regression analysis to investigate the association of 435 SNPs in 112 positional and biological candidate genes with ABI and related physiological and biochemical traits in 1046 non-Hispanic white, hypertensive participants from the Genetic Epidemiology Network of Arteriopathy (GENOA) study. The main effects of each SNP, as well as SNP-covariate and SNP-SNP interactions, were assessed to investigate how they contribute to the inter-individual variation in ABI. Multivariable linear regression models were then used to assess the joint contributions of the top SNP associations and interactions to ABI after adjustment for covariates. We reduced the chance of false positives by 1) correcting for multiple testing using the false discovery rate, 2) internal replication, and 3) four-fold cross-validation.

Results

When the results from these three procedures were combined, only two SNP main effects in NOS3, three SNP-covariate interactions (ADRB2 Gly 16 – lipoprotein(a) and SLC4A5 – diabetes interactions), and 25 SNP-SNP interactions (involving SNPs from 29 different genes) were significant, replicated, and cross-validated. Combining the top SNPs, risk factors, and their interactions into a model explained nearly 18% of variation in ABI in the sample. SNPs in six genes (ADD2, ATP6V1B1, PRKAR2B, SLC17A2, SLC22A3, and TGFB3) were also influencing triglycerides, C-reactive protein, homocysteine, and lipoprotein(a) levels.

Conclusion

We found that candidate gene SNP main effects, SNP-covariate and SNP-SNP interactions contribute to the inter-individual variation in ABI, a marker of PAD. Our findings underscore the importance of conducting systematic investigations that consider context-dependent frameworks for developing a deeper understanding of the multidimensional genetic and environmental factors that contribute to complex diseases.     

Whole-genome sequencing identifies potential candidate genes for reproductive traits in pigs

Reproductive performance is a complex quantitative trait, that is determined by multiple genes, regulatory pathways and environmental factors. A list of major genes with large effect have been detected, although multiple QTLs are identified. To identify candidate genes for pig prolificacy, whole genome variants from five high- and five low-prolificacy Yorkshire sows were collected using whole-genome resequencing. A total of 13,955,609 SNPs and 2,666,366 indels were detected across the genome. Common differential SNPs and indels were identified between the two groups of sows. Genes encoding components of the TGF-beta signaling pathway were enriched with the variations, including BMP5, BMP6, BMP7, ACVR1, INHBA, ZFYVE9, TGFBR2, DCN, ID4, BAMBI, and ACVR2A. Several differential variants within these genes related to reproductive traits were identified to be associated with litter size. A comparison of selective regions and published QTL data suggests that NEDD9, SLC39A11, SNCA, and UNC5D are candidate genes for reproduction traits.     

Genomewide association study for economic traits in the large yellow croaker with different numbers of extreme phenotypes

A traditional genomewide association study (GWAS) detects genotype–phenotype associations by the vast number of genotyped individuals. This method requires large-scale samples and considerable sequencing costs. Extreme phenotypic sampling proposes make GWAS more cost-efficient and are applied more widely. With extreme phenotypic sampling, we performed a GWAS for n-3 highly unsaturated fatty acids (HUFA) and eviscerated weight (EW) traits in the large yellow croaker population. Of the 32,249 and 29,748 detected SNPs for the two traits, three candidate regions were found in each trait. Three candidate regions associated with HUFA were known near genes on chromosomes 4 and 11, and three candidate regions were on chromosome 6, and 15 for the EW trait. By combing through our GWAS results and the biological functional analysis of the genes, we suggest that the FABP, DGAT, ATP8B1, FAF2 and CERS2 genes,  as well as the IGF2, BORA, CYP1A1, GRTP1 and HOX genes are promising candidate genes for n-3 HUFA and EW, respectively, in the large yellow croaker. Moreover, compared with the different numbers of the extreme phenotypic sampling, we conclude that 60% of the extreme phenotypic subsample can obtain a similar result as GWAS with whole phenotypes. Thus, extreme phenotypic sampling could save 40% of the cost for genotyping and DNA extraction without loss of the candidate regions and functional genes. Our study may provide a basis for further genomic breeding and a reference for others who want to perform GWAS with extreme phenotypes.     

Multiple loci associated with canine hip dysplasia (CHD) in German shepherd dogs

Canine hip dysplasia (CHD) is the most common hereditary skeletal disorder in dogs. To identify common alleles associated with CHD, we developed 37 informative single nucleotide polymorphisms (SNPs) within 13 quantitative trait loci (QTL) previously identified for German shepherd dogs. These SNPs were genotyped in 95 German shepherd dogs affected by CHD and 95 breed, sex, and birth year-matched controls. A total of ten SNPs significant at a nominal P value of 0.05 were validated in 843 German shepherd dogs including 277 unaffected dogs and 566 CHD-affected dogs. Cases and controls were sampled from the whole German shepherd dog population in Germany in such a way that mean coancestry coefficients were below 0.1 % within cases and controls as well as among cases and controls. We identified nine SNPs significantly associated with CHD within five QTL on dog chromosomes (CFA) 3, 9, 26, 33, and 34. Genotype effects of these nine SNPs explained between 22 and 34 % of the phenotypic variance of hip dysplasia in German shepherd dogs. The strongest associated SNPs were located on CFA33 and 34 within the candidate genes PNCP, TRIO, and SLC6A3. Thus, the present study validated positional candidate genes within five QTL for CHD.     

Genome-Wide Association Study Identifies Loci and Candidate Genes for Body Composition and Meat Quality Traits in Beijing-You Chickens

Body composition and meat quality traits are important economic traits of chickens. The development of high-throughput genotyping platforms and relevant statistical methods have enabled genome-wide association studies in chickens. In order to identify molecular markers and candidate genes associated with body composition and meat quality traits, genome-wide association studies were conducted using the Illumina 60 K SNP Beadchip to genotype 724 Beijing-You chickens. For each bird, a total of 16 traits were measured, including carcass weight (CW), eviscerated weight (EW), dressing percentage, breast muscle weight (BrW) and percentage (BrP), thigh muscle weight and percentage, abdominal fat weight and percentage, dry matter and intramuscular fat contents of breast and thigh muscle, ultimate pH, and shear force of the pectoralis major muscle at 100 d of age. The SNPs that were significantly associated with the phenotypic traits were identified using both simple (GLM) and compressed mixed linear (MLM) models. For nine of ten body composition traits studied, SNPs showing genome wide significance (P<2.59E−6) have been identified. A consistent region on chicken (Gallus gallus) chromosome 4 (GGA4), including seven significant SNPs and four candidate genes (LCORL, LAP3, LDB2, TAPT1), were found to be associated with CW and EW. Another 0.65 Mb region on GGA3 for BrW and BrP was identified. After measuring the mRNA content in beast muscle for five genes located in this region, the changes in GJA1 expression were found to be consistent with that of breast muscle weight across development. It is highly possible that GJA1 is a functional gene for breast muscle development in chickens. For meat quality traits, several SNPs reaching suggestive association were identified and possible candidate genes with their functions were discussed.     

Genetic variants in the JAK1 gene confer higher risk of Behcet’s disease with ocular involvement in Han Chinese

Recent surveys have identified SLC22A4, SLC22A5, RUNX1, JAK1 as susceptibility genes for various immune-related diseases. An association study was performed in 738 Behcet’s patients with ocular involvement and 1,873 controls using the iPLEX system method. The first-stage study for 30 SNPs showed that SNPs rs2780815, rs310241, rs3790532 in JAK1 were associated with Behcet’s disease in Han Chinese (Pc_{(Bonferroni correction)} = 0.022–7.7 × 10^?3). The G allele and AA genotype of SNP rs2834643 in RUNX1 (Pc = 0.041–1.75 × 10^?3), but none of the other SNPs, were associated with Behcet’s disease. Haplotype analysis for the SLC22A4, SLC22A5 genes showed an increased tendency for AGTCTGCCGC frequency in patients compared with controls; however, the significance was lost after Bonferroni correction (P = 0.004, Pc > 0.05). Subsequently, we further replicated the significantly associated SNPs using another independent cohort. Replication and combining studies showed that three SNPs rs2780815, rs310241, rs3790532 in JAK1, but not SNP rs2834643 in RUNX1, were consistently associated with Behcet’s disease (replication: Pc = 0.012–9.60 × 10^?4; combining: Pc = 0.030–1.90 × 10^?4). SNPs rs2780815, rs310241, rs3790532 were estimated to confer a population attributable risk of 35.0, 28.0, 27.0 %, respectively. We found a strong association between HLA-B51 with Behcet’s disease in Chinese Han population (P = 1.35 × 10^?73; OR = 5.15; 95 % CI 4.28–6.19). GMDR analysis showed that no gene–gene interaction was detectable between JAK1 and HLA-B51. Logistic analysis indicated that the JAK1 gene was an independent risk factor for Behcet’s disease (P > 0.05). Real-time PCR analysis showed that no difference on the expression of JAK1 in PBMCs or LPS-stimulated PBMCs between individuals with the different rs1762780815 genotypes studied (P > 0.05). In conclusion, this study suggests that JAK1, but not SLC22A4, SLC22A5 and RUNX1, contributes to the genetic susceptibility to Behcet’s disease with ocular involvement.     

Genetic analysis and characterization of a new maize association mapping panel for quantitative trait loci dissection

Association mapping based on the linkage disequilibrium provides a promising tool to identify genes responsible for quantitative variations underlying complex traits. Presented here is a maize association mapping panel consisting of 155 inbred lines with mainly temperate germplasm, which was phenotyped for 34 traits and genotyped using 82 SSRs and 1,536 SNPs. Abundant phenotypic and genetic diversities were observed within the panel based on the phenotypic and genotypic analysis. A model-based analysis using 82 SSRs assigned all inbred lines to two groups with eight subgroups. The relative kinship matrix was calculated using 884 SNPs with minor allele frequency ≥20% indicating that no or weak relationships were identified for most individual pairs. Three traits (total tocopherol content in maize kernel, plant height and kernel length) and 1,414 SNPs with missing data <20% were used to evaluate the performance of four models for association mapping analysis. For all traits, the model controlling relative kinship (K) performed better than the model controlling population structure (Q), and similarly to the model controlling both population structure and relative kinship (Q + K) in this panel. Our results suggest this maize panel can be used for association mapping analysis targeting multiple agronomic and quality traits with optimal association model.     

Variants from GIPR, TCF7L2, DGKB, MADD, CRY2, GLIS3, PROX1, SLC30A8 and IGF1 are associated with glucose metabolism in the Chinese

Background

Recent meta-analysis of genome-wide association studies in European descent samples identified novel loci influencing glucose and insulin related traits. In the current study, we aimed to evaluate the association between these loci and traits related to glucose metabolism in the Chinese.

Methods/Principal Findings

We genotyped seventeen single nucleotide polymorphisms (SNPs) from fifteen loci including GIPR, ADCY5, TCF7L2, VPS13C, DGKB, MADD, ADRA2A, FADS1, CRY2, SLC2A2, GLIS3, PROX1, C2CD4B, SLC30A8 and IGF1 in 6,822 Shanghai Chinese Hans comprising 3,410 type 2 diabetic patients and 3,412 normal glucose regulation subjects. MADD rs7944584 showed strong association to type 2 diabetes (p = 3.5×10⁻⁶, empirical p = 0.0002) which was not observed in the European descent populations. SNPs from GIPR, TCF7L2, CRY2, GLIS3 and SLC30A8 were also associated with type 2 diabetes (p = 0.0487∼2.0×10⁻⁸). Further adjusting age, gender and BMI as confounders found PROX1 rs340874 was associated with type 2 diabetes (p = 0.0391). SNPs from DGKB, MADD and SLC30A8 were associated with fasting glucose while PROX1 rs340874 was significantly associated with OGTT 2-h glucose (p = 0.0392∼0.0014, adjusted for age, gender and BMI), the glucose-raising allele also showed association to lower insulin secretion. IGF1 rs35767 showed significant association to both fasting and 2-h insulin levels as well as insulin secretion and sensitivity indices (p = 0.0160∼0.0035, adjusted for age, gender and BMI).

Conclusions/Significance

Our results indicated that SNPs from GIPR, TCF7L2, DGKB, MADD, CRY2, GLIS3, PROX1, SLC30A8 and IGF1 were associated with traits related to glucose metabolism in the Chinese population.     

Common Polymorphisms Influencing Serum Uric Acid Levels Contribute to Susceptibility to Gout,but Not to Coronary Artery Disease

Background

Recently, a large meta-analysis including over 28,000 participants identified nine different loci with association to serum uric acid (UA) levels. Since elevated serum UA levels potentially cause gout and are a possible risk factor for coronary artery disease (CAD) and myocardial infarction (MI), we performed two large case-control association analyses with participants from the German MI Family Study. In the first study, we assessed the association of the qualitative trait gout and ten single nucleotide polymorphisms (SNP) markers that showed association to UA serum levels. In the second study, the same genetic polymorphisms were analyzed for association with CAD.

Methods and Findings

A total of 683 patients suffering from gout and 1,563 healthy controls from the German MI Family Study were genotyped. Nine SNPs were identified from a recently performed genome-wide meta-analysis on serum UA levels (rs12129861, rs780094, rs734553, rs2231142, rs742132, rs1183201, rs12356193, rs17300741 and rs505802). Additionally, the marker rs6855911 was included which has been associated with gout in our cohort in a previous study. SNPs rs734553 and rs6855911, located in SLC2A9, and SNP rs2231142, known to be a missense polymorphism in ABCG2, were associated with gout (p = 5.6*10⁻⁷, p = 1.1*10⁻⁷, and p = 1.3*10⁻³, respectively). Other SNPs in the genes PDZK1, GCKR, LRRC16A, SLC17A1-SLC17A3, SLC16A9, SLC22A11 and SLC22A12 failed the significance level. None of the ten markers were associated with risk to CAD in our study sample of 1,473 CAD cases and 1,241 CAD-free controls.

Conclusion

SNP markers in SLC2A9 and ABCG2 genes were found to be strongly associated with the phenotype gout. However, not all SNP markers influencing serum UA levels were also directly associated with the clinical manifestation of gout in our study sample. In addition, none of these SNPs showed association with the risk to CAD in the German MI Family Study.     

A Family with Atypical Hailey Hailey Disease- Is There More to the Underlying Genetics than ATP2C1?

The autosomal dominant Hailey Hailey disease (HHD) is caused by mutations in the ATP2C1 gene encoding for human secretory pathway Ca2+/Mn2+ ATPase protein (hSPCA1) in the Golgi apparatus. Clinically, HHD presents with erosions and hyperkeratosis predominantly in the intertrigines. Here we report an exome next generation sequencing (NGS) based analysis of ATPase genes in a Greek family with 3 HHD patients presenting with clinically atypical lesions mainly localized on the neck and shoulders. By NGS of one HHD-patient and in silico SNP calling and SNP filtering we identified a SNP in the expected ATP2C1 gene and SNPs in further ATPase genes. Verification in all 3 affected family members revealed a heterozygous frameshift deletion at position 2355_2358 in exon 24 of ATP2C1 in all three patients. 7 additional SNPs in 4 ATPase genes (ATP9B, ATP11A, ATP2B3 and ATP13A5) were identified. The SNPs rs138177421 in the ATP9B gene and rs2280268 in the ATP13A5 gene were detected in all 3 affected, but not in 2 non affected family members. The SNPs in the ATP2B3 and ATP11A gene as well as further SNPs in the ATP13A5 gene could not be confirmed in all affected family members. One may speculate that besides the level of functional hSPCA1 protein, levels of other ATPase proteins may influence expressivity of the disease and might also contribute, as in this case, to atypical presentations.     

Genome-Wide Testing of Putative Functional Exonic Variants in Relationship with Breast and Prostate Cancer Risk in a Multiethnic Population

Rare variation in protein coding sequence is poorly captured by GWAS arrays and has been hypothesized to contribute to disease heritability. Using the Illumina HumanExome SNP array, we successfully genotyped 191,032 common and rare non-synonymous, splice site, or nonsense variants in a multiethnic sample of 2,984 breast cancer cases, 4,376 prostate cancer cases, and 7,545 controls. In breast cancer, the strongest associations included either SNPs in or gene burden scores for genes LDLRAD1, SLC19A1, FGFBP3, CASP5, MMAB, SLC16A6, and INS-IGF2. In prostate cancer, one of the most associated SNPs was in the gene GPRC6A (rs2274911, Pro91Ser, OR = 0.88, P = 1.3×10⁻⁵) near to a known risk locus for prostate cancer; other suggestive associations were noted in genes such as F13A1, ANXA4, MANSC1, and GP6. For both breast and prostate cancer, several of the most significant associations involving SNPs or gene burden scores (sum of minor alleles) were noted in genes previously reported to be associated with a cancer-related phenotype. However, only one of the associations (rs145889899 in LDLRAD1, p = 2.5×10⁻⁷ only seen in African Americans) for overall breast or prostate cancer risk was statistically significant after correcting for multiple comparisons. In addition to breast and prostate cancer, other cancer-related traits were examined (body mass index, PSA level, and alcohol drinking) with a number of known and potentially novel associations described. In general, these findings do not support there being many protein coding variants of moderate to high risk for breast and prostate cancer with odds ratios over a range that is probably required for protein coding variation to play a truly outstanding role in risk heritability. Very large sample sizes will be required to better define the role of rare and less penetrant coding variation in prostate and breast cancer disease genetics.     

Comprehensive evaluation of one-carbon metabolism pathway gene variants and renal cell cancer risk

Introduction

Folate and one-carbon metabolism are linked to cancer risk through their integral role in DNA synthesis and methylation. Variation in one-carbon metabolism genes, particularly MTHFR, has been associated with risk of a number of cancers in epidemiologic studies, but little is known regarding renal cancer.

Methods

Tag single nucleotide polymorphisms (SNPs) selected to produce high genomic coverage of 13 gene regions of one-carbon metabolism (ALDH1L1, BHMT, CBS, FOLR1, MTHFR, MTR, MTRR, SHMT1, SLC19A1, TYMS) and the closely associated glutathione synthesis pathway (CTH, GGH, GSS) were genotyped for 777 renal cell carcinoma (RCC) cases and 1,035 controls in the Central and Eastern European Renal Cancer case-control study. Associations of individual SNPs (n = 163) with RCC risk were calculated using unconditional logistic regression adjusted for age, sex and study center. Minimum p-value permutation (Min-P) tests were used to identify gene regions associated with risk, and haplotypes were evaluated within these genes.

Results

The strongest associations with RCC risk were observed for SLC19A1 (P_min-P = 0.03) and MTHFR (P_min-P = 0.13). A haplotype consisting of four SNPs in SLC19A1 (rs12483553, rs2838950, rs2838951, and rs17004785) was associated with a 37% increased risk (p = 0.02), and exploratory stratified analysis suggested the association was only significant among those in the lowest tertile of vegetable intake.

Conclusions

To our knowledge, this is the first study to comprehensively examine variation in one-carbon metabolism genes in relation to RCC risk. We identified a novel association with SLC19A1, which is important for transport of folate into cells. Replication in other populations is required to confirm these findings.     

Targeting 160 Candidate Genes for Blood Pressure Regulation with a Genome-Wide Genotyping Array

The outcome of Genome-Wide Association Studies (GWAS) has challenged the field of blood pressure (BP) genetics as previous candidate genes have not been among the top loci in these scans. We used Affymetrix 500K genotyping data of KORA S3 cohort (n = 1,644; Southern-Germany) to address (i) SNP coverage in 160 BP candidate genes; (ii) the evidence for associations with BP traits in genome-wide and replication data, and haplotype analysis. In total, 160 gene regions (genic region±10 kb) covered 2,411 SNPs across 11.4 Mb. Marker densities in genes varied from 0 (n = 11) to 0.6 SNPs/kb. On average 52.5% of the HAPMAP SNPs per gene were captured. No evidence for association with BP was obtained for 1,449 tested SNPs. Considerable associations (P<10⁻³) were detected for the genes, where >50% of HAPMAP SNPs were tagged. In general, genes with higher marker density (>0.2 SNPs/kb) revealed a better chance to reach close to significance associations. Although, none of the detected P-values remained significant after Bonferroni correction (P<0.05/2319, P<2.15×10⁻⁵), the strength of some detected associations was close to this level: rs10889553 (LEPR) and systolic BP (SBP) (P = 4.5×10⁻⁵) as well as rs10954174 (LEP) and diastolic BP (DBP) (P = 5.20×10⁻⁵). In total, 12 markers in 7 genes (ADRA2A, LEP, LEPR, PTGER3, SLC2A1, SLC4A2, SLC8A1) revealed considerable association (P<10⁻³) either with SBP, DBP, and/or hypertension (HYP). None of these were confirmed in replication samples (KORA S4, HYPEST, BRIGHT). However, supportive evidence for the association of rs10889553 (LEPR) and rs11195419 (ADRA2A) with BP was obtained in meta-analysis across samples stratified either by body mass index, smoking or alcohol consumption. Haplotype analysis highlighted LEPR and PTGER3. In conclusion, the lack of associations in BP candidate genes may be attributed to inadequate marker coverage on the genome-wide arrays, small phenotypic effects of the loci and/or complex interaction with life-style and metabolic parameters.     

Genome Wide Association Study Identifies 20 Novel Promising Genes Associated with Milk Fatty Acid Traits in Chinese Holstein

Detecting genes associated with milk fat composition could provide valuable insights into the complex genetic networks of genes underling variation in fatty acids synthesis and point towards opportunities for changing milk fat composition via selective breeding. In this study, we conducted a genome-wide association study (GWAS) for 22 milk fatty acids in 784 Chinese Holstein cows with the PLINK software. Genotypes were obtained with the Illumina BovineSNP50 Bead chip and a total of 40,604 informative, high-quality single nucleotide polymorphisms (SNPs) were used. Totally, 83 genome-wide significant SNPs and 314 suggestive significant SNPs associated with 18 milk fatty acid traits were detected. Chromosome regions that affect milk fatty acid traits were mainly observed on BTA1, 2, 5, 6, 7, 9, 13, 14, 18, 19, 20, 21, 23, 26 and 27. Of these, 146 SNPs were associated with more than one milk fatty acid trait; most of studied fatty acid traits were significant associated with multiple SNPs, especially C18:0 (105 SNPs), C18 index (93 SNPs), and C14 index (84 SNPs); Several SNPs are close to or within the DGAT1, SCD1 and FASN genes which are well-known to affect milk composition traits of dairy cattle. Combined with the previously reported QTL regions and the biological functions of the genes, 20 novel promising candidates for C10:0, C12:0, C14:0, C14:1, C14 index, C18:0, C18:1n9c, C18 index, SFA, UFA and SFA/UFA were found, which composed of HTR1B, CPM, PRKG1, MINPP1, LIPJ, LIPK, EHHADH, MOGAT1, ECHS1, STAT1, SORBS1, NFKB2, AGPAT3, CHUK, OSBPL8, PRLR, IGF1R, ACSL3, GHR and OXCT1. Our findings provide a groundwork for unraveling the key genes and causal mutations affecting milk fatty acid traits in dairy cattle.     

Common Genetic Variation In Cellular Transport Genes and Epithelial Ovarian Cancer (EOC) Risk

Background

Defective cellular transport processes can lead to aberrant accumulation of trace elements, iron, small molecules and hormones in the cell, which in turn may promote the formation of reactive oxygen species, promoting DNA damage and aberrant expression of key regulatory cancer genes. As DNA damage and uncontrolled proliferation are hallmarks of cancer, including epithelial ovarian cancer (EOC), we hypothesized that inherited variation in the cellular transport genes contributes to EOC risk.

Methods

In total, DNA samples were obtained from 14,525 case subjects with invasive EOC and from 23,447 controls from 43 sites in the Ovarian Cancer Association Consortium (OCAC). Two hundred seventy nine SNPs, representing 131 genes, were genotyped using an Illumina Infinium iSelect BeadChip as part of the Collaborative Oncological Gene-environment Study (COGS). SNP analyses were conducted using unconditional logistic regression under a log-additive model, and the FDR q<0.2 was applied to adjust for multiple comparisons.

Results

The most significant evidence of an association for all invasive cancers combined and for the serous subtype was observed for SNP rs17216603 in the iron transporter gene HEPH (invasive: OR = 0.85, P = 0.00026; serous: OR = 0.81, P = 0.00020); this SNP was also associated with the borderline/low malignant potential (LMP) tumors (P = 0.021). Other genes significantly associated with EOC histological subtypes (p<0.05) included the UGT1A (endometrioid), SLC25A45 (mucinous), SLC39A11 (low malignant potential), and SERPINA7 (clear cell carcinoma). In addition, 1785 SNPs in six genes (HEPH, MGST1, SERPINA, SLC25A45, SLC39A11 and UGT1A) were imputed from the 1000 Genomes Project and examined for association with INV EOC in white-European subjects. The most significant imputed SNP was rs117729793 in SLC39A11 (per allele, OR = 2.55, 95% CI = 1.5-4.35, p = 5.66x10^-4).

Conclusion

These results, generated on a large cohort of women, revealed associations between inherited cellular transport gene variants and risk of EOC histologic subtypes.     

Genome-wide association study reveals the genetic determinism of growth traits in a Gushi-Anka F2 chicken population

Chicken growth traits are economically important, but the relevant genetic mechanisms have not yet been elucidated. Herein, we performed a genome-wide association study to identify the variants associated with growth traits. In total, 860 chickens from a Gushi-Anka F₂ resource population were phenotyped for 68 growth and carcass traits, and 768 samples were genotyped based on the genotyping-by-sequencing (GBS) method. Finally, 734 chickens and 321,314 SNPs remained after quality control and removal of the sex chromosomes, and these data were used to carry out a GWAS analysis. A total of 470 significant single-nucleotide polymorphisms (SNPs) for 43 of the 68 traits were detected and mapped on chromosomes (Chr) 1–6, -9, -10, -16, -18, -23, and -27. Of these, the significant SNPs in Chr1, -4, and -27 were found to be associated with more than 10 traits. Multiple traits shared significant SNPs, indicating that the same mutation in the region might have a large effect on multiple growth or carcass traits. Haplotype analysis revealed that SNPs within the candidate region of Chr1 presented a mosaic pattern. The significant SNPs and pathway enrichment analysis revealed that the MLNR, MED4, CAB39L, LDB2, and IGF2BP1 genes could be putative candidate genes for growth and carcass traits. The findings of this study improve our understanding of the genetic mechanisms regulating chicken growth and carcass traits and provide a theoretical basis for chicken breeding programs.Subject terms: Genome-wide association studies, Genetic linkage study, Development, DNA sequencing, Animal breeding