Genome-wide association analysis of eggshell color of an F2 generation population reveals candidate genes in chickens

Eggshell color is an important visual characteristic that affects consumer preferences for eggs. Eggshell color, which has moderate to high heritability, can be effectively enhanced through molecular marker selection. Various studies have been conducted on eggshell color at specific time points. However, few longitudinal data are available on eggshell color. Therefore, the objective of this study was to investigate eggshell color using the Commission International de L'Eclairage L*a*b* system with multiple measurements at different ages (age at the first egg and at 32, 36, 40, 44, 48, 52, 56, 60, 66, and 72 weeks) within the same individuals from an F2 resource population produced by crossing White Leghorn and Dongxiang Blue chicken. Using an Affymetrix 600 single nucleotide polymorphism (SNP) array, we estimated the genetic parameters of the eggshell color trait, performed genome-wide association studies (GWASs), and screened for the potential candidate genes. The results showed that pink-shelled eggs displayed a significant negative correlation between L* values and both a* and b* values. Genetic heritability based on SNPs showed that the heritability of L*, a*, and b* values ranged from 0.32 to 0.82 for pink-shelled eggs, indicating a moderate to high level of genetic control. The genetic correlations at each time point were mostly above 0.5. The major-effect regions affecting the pink eggshell color were identified in the 10.3-13.0 Mb interval on Gallus gallus chromosome 20, and candidate genes were selected, including SLC35C2, PCIF1, and SLC12A5. Minor effect polygenic regions were identified on chromosomes 1, 6, 9, 12, and 15, revealing 11 candidate genes, including MTMR3 and SLC35E4. Members of the solute carrier family play an important role in influencing eggshell color. Overall, our findings provide valuable insights into the phenotypic and genetic aspects underlying the variation in eggshell color. Using GWAS analysis, we identified multiple quantitative trait loci (QTLs) for pink eggshell color, including a major QTL on chromosome 20. Genetic variants associated with eggshell color may be used in genomic breeding programs.

A comprehensive lettuce variation map reveals the impact of structural variations in agronomic traits

BACKGROUND

As an important vegetable crop, cultivated lettuce is grown worldwide and a great variety of agronomic traits have been preserved within germplasm collections. The mechanisms underlying these phenotypic variations remain to be elucidated in association with sequence variations. Compared with single nucleotide polymorphisms, structural variations (SVs) that have more impacts on gene functions remain largely uncharacterized in the lettuce genome.

RESULTS

Here, we produced a comprehensive SV set for 333 wild and cultivated lettuce accessions. Comparison of SV frequencies showed that the SVs prevalent in L. sativa affected the genes enriched in carbohydrate derivative catabolic and secondary metabolic processes. Genome-wide association analysis of seven agronomic traits uncovered potentially causal SVs associated with seed coat color and leaf anthocyanin content.

CONCLUSION

Our work characterized a great abundance of SVs in the lettuce genome, and provides a valuable genomic resource for future lettuce breeding.

Auditory oddball hypoactivation in schizophrenia

Individuals with schizophrenia (SZ) show aberrant activations, assessed via functional magnetic resonance imaging (fMRI), during auditory oddball tasks. However, associations with cognitive performance and genetic contributions remain unknown. This study compares individuals with SZ to healthy volunteers (HVs) using two cross-sectional data sets from multi-center brain imaging studies. It examines brain activation to auditory oddball targets, and their associations with cognitive domain performance, schizophrenia polygenic risk scores (PRS), and genetic variation (loci). Both sample 1 (137 SZ vs. 147 HV) and sample 2 (91 SZ vs. 98 HV), showed hypoactivation in SZ in the left-frontal pole, and right frontal orbital, frontal pole, paracingulate, intracalcarine, precuneus, supramarginal and hippocampal cortices, and right thalamus. In SZ, precuneus activity was positively related to cognitive performance. Schizophrenia PRS showed a negative correlation with brain activity in the right-supramarginal cortex. GWA analyses revealed significant single-nucleotide polymorphisms associated with right-supramarginal gyrus activity. RPL36 also predicted right-supramarginal gyrus activity. In addition to replicating hypoactivation for oddball targets in SZ, this study identifies novel relationships between regional activity, cognitive performance, and genetic loci that warrant replication, emphasizing the need for continued data sharing and collaborative efforts.

Genetic associations vary across the spectrum of fasting serum insulin: results from the European IDEFICS/I.Family children's cohort

AIMS/HYPOTHESIS

There is increasing evidence for the existence of shared genetic predictors of metabolic traits and neurodegenerative disease. We previously observed a U-shaped association between fasting insulin in middle-aged women and dementia up to 34 years later. In the present study, we performed genome-wide association (GWA) analyses for fasting serum insulin in European children with a focus on variants associated with the tails of the insulin distribution.

METHODS

Genotyping was successful in 2825 children aged 2-14 years at the time of insulin measurement. Because insulin levels vary during childhood, GWA analyses were based on age- and sex-specific z scores. Five percentile ranks of z-insulin were selected and modelled using logistic regression, i.e. the 15th, 25th, 50th, 75th and 85th percentile ranks (P15-P85). Additive genetic models were adjusted for age, sex, BMI, survey year, survey country and principal components derived from genetic data to account for ethnic heterogeneity. Quantile regression was used to determine whether associations with variants identified by GWA analyses differed across quantiles of log-insulin.

RESULTS

A variant in the SLC28A1 gene (rs2122859) was associated with the 85th percentile rank of the insulin z score (P85, p value=3×10-8). Two variants associated with low z-insulin (P15, p value <5×10-6) were located on the RBFOX1 and SH3RF3 genes. These genes have previously been associated with both metabolic traits and dementia phenotypes. While variants associated with P50 showed stable associations across the insulin spectrum, we found that associations with variants identified through GWA analyses of P15 and P85 varied across quantiles of log-insulin.

CONCLUSIONS/INTERPRETATION

The above results support the notion of a shared genetic architecture for dementia and metabolic traits. Our approach identified genetic variants that were associated with the tails of the insulin spectrum only. Because traditional heritability estimates assume that genetic effects are constant throughout the phenotype distribution, the new findings may have implications for understanding the discrepancy in heritability estimates from GWA and family studies and for the study of U-shaped biomarker-disease associations.

Quantitative trait loci and candidate genes for yield-related traits of upland cotton revealed by genome-wide association analysis under drought conditions

BACKGROUND

Due to the influence of extreme weather, the environment in China's main cotton-producing areas is prone to drought stress conditions, which affect the growth and development of cotton and lead to a decrease in cotton yield.

RESULTS

In this study, 188 upland cotton germplasm resources were phenotyped for data of 8 traits (including 3 major yield traits) under drought conditions in three environments for two consecutive years. Correlation analysis revealed significant positive correlations between the three yield traits. Genetic analysis showed that the estimated heritability of the seed cotton index (SC) under drought conditions was the highest (80.81%), followed by that of boll weight (BW) (80.64%) and the lint cotton index (LC) (70.49%) With genome-wide association study (GWAS) analysis, a total of 75 quantitative trait loci (QTLs) were identified, including two highly credible new QTL hotspots. Three candidate genes (Gh_D09G064400, Gh_D10G261000 and Gh_D10G254000) located in the two new QTL hotspots, QTL51 and QTL55, were highly expressed in the early stage of fiber development and showed significant correlations with SC, LC and BW. The expression of three candidate genes in two extreme materials after drought stress was analyzed by qRT-PCR, and the expression of these two materials in fibers at 15, 20 and 25 DPA. The expression of these three candidate genes was significantly upregulated after drought stress and was significantly higher in drought-tolerant materials than in drought-sensitive materials. In addition, the expression levels of the three candidate genes were higher in the early stage of fiber development (15 DPA), and the expression levels in drought-tolerant germplasm were higher than those in drought-sensitive germplasm. These three candidate genes may play an important role in determining cotton yield under drought conditions.

CONCLUSIONS

This study is helpful for understanding the regulatory genes affecting cotton yield under drought conditions and provides germplasm and candidate gene resources for breeding high-yield cotton varieties under these conditions.

The genetic architecture of the corpus callosum and its genetic overlap with common neuropsychiatric diseases

BACKGROUND

The corpus callosum (CC) is the main structure transferring information between the cerebral hemispheres. Although previous large-scale genome-wide association study (GWAS) has illustrated the genetic architecture of white matter integrity of CC, CC volume is less stressed.

METHODS

Using MRI data from 33,861 individuals in UK Biobank, we conducted univariate and multivariate GWAS for CC fractional anisotropy (FA) and volume with PLINK 2.0 and MOSTest. All discovered SNPs in the multivariate framework were functionally annotated in FUMA v1.3.8. In the meanwhile, a series of gene property analyses was conducted simultaneously. In addition, we estimated genetic relationship between CC metrics and other neuropsychiatric traits and diseases.

RESULTS

We identified a total of 36 and 82 significant genomic loci for CC FA and volume (P < 5 × 10^-8). And 53 and 27 genes were respectively mapped by four mapping strategies. For CC volume, gene-set analysis revealed pathways mainly relating to cell migration; cell-type analysis found the top enrichment in neuroglia while for CC FA in GABAergic neurons. Furthermore, we found a lot of genetic overlap and shared loci between CC FA and volume and common neuropsychiatric diseases.

DISCUSSION

Collectively, this study helps to better understand the genetic architecture of whole CC and CC subregions. However, the way to divide CC FA and volume in our study restricts the interpretations of our results. Future work will be needed to pay attention to the genetic structure of white matter volume, and an appropriate division of CC may help to better understand CC structure.

Exploratory factor analysis of shared and specific genetic associations in depression and anxiety

BACKGROUND

Previous genetic studies of anxiety and depression were mostly based on independent phenotypes. This study aims to investigate the shared and specific genetic structure between anxiety and depression.

METHOD

To identify the underlying factors of Generalized Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-9 (PHQ-9), and their combined scale (joint scale), we employed exploratory factor analysis (EFA) using the eigenvalue of parallel analysis. Subsequently, we conducted a genome-wide association study (GWAS) for these factors. In addition, we utilized LD Score Regression (LDSC) to determine the genetic correlations between the identified factors and four common mental disorders, three sleep phenotypes, and other traits that have been previously linked to anxiety and depression.

RESULTS

The EFA uncovered two factors for the GAD-7 scale, namely nervousness and disturbance, two factors for the PHQ-9 scale, namely negative affect and sleep/appetite disturbance, and four factors for the joint scale, specifically nervousness, anhedonia, sleep/appetite disturbance, and fidget. We identified two genome-wide significant genomic loci, with overlap across GAD-7 factor 1 and joint scale factor 1: rs148579586 (P_GAD-7 = 1.365 × 10^-09, P_{Joint scale} = 1.434 × 1^0-09) and rs201074060 (P_GAD-7 = 3.672 × 10^-09, P_{Joint scale} = 3.824 × 10^-09). Genetic correlations in factors ranged from 0.722 to 1.000 (all p < 1.786 × 10^-3) with 27 of 28 correlations being significantly smaller than one. The genetic correlations with external phenotypes showed small variation across the eight factors.

CONCLUSION

Unidimensional structures can provide more precise scores, which can aid in identifying the shared and specific genetic associations between anxiety and depression. This is a crucial step in characterizing the genetic structure of these conditions and their co-occurrence.

Genome-wide association analysis of kernel nutritional quality in two natural maize populations

As one of the three staple crops, nutritional traits in maize are important for human and animal nutrition. Grain quality-related traits are closely related to grain commercial value. Understanding the genetic basis of quality-related traits in maize would be helpful for breeding high-quality maize varieties. In this study, two association panels (AM122 and AM180) were subjected to genome-wide association analysis of grain quality-related traits, including protein content, oil content, starch content, and fiber content. In total, 98 SNPs (P < 1 × 10-4) were identified to be significantly associated with these four grain quality-related traits. By integrating two sets of public transcriptome data, 31 genes located in 200 kb regions flanking the associated SNP showed high expression during kernel development and were differentially expressed in two maize inbred lines, KA225 and KB035, with significantly different quality. These genes might regulate maize grain quality by participating in plant hormone processes, autophagy processes, and others. All these results could provide important reference information for breeding high‑quality maize varieties.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01360-w.

Whole-genome resequencing reveals genetic differences and the genetic basis of parapodium number in Russian and Chinese Apostichopus japonicus

BACKGROUND

Apostichopus japonicus is an economically important species in the global aquaculture industry. Russian A. japonicus, mainly harvested in the Vladivostok region, exhibits significant phenotypic differentiation, including in many economically important traits, compared with Chinese A. japonicus owing to differences in their habitat. However, both the genetic basis for the phenotypic divergence and the population genetic structure of Russian and Chinese A. japonicus are unknown.

RESULT

In this study, 210 individuals from seven Russian and Chinese A. japonicus populations were sampled for whole-genome resequencing. The genetic structure analysis differentiated the Russian and Chinese A. japonicus into two groups. Population genetic analyses indicated that the Russian population showed a high degree of allelic linkage and had undergone stronger positive selection compared with the Chinese populations. Gene ontology terms enriched among candidate genes with group selection analysis were mainly involved in immunity, such as inflammatory response, antimicrobial peptides, humoral immunity, and apoptosis. Genome-wide association analysis yielded eight single-nucleotide polymorphism loci significantly associated with parapodium number, and these loci are located in regions with a high degree of genomic differentiation between the Chinese and Russia populations. These SNPs were associated with five genes. Gene expression validation revealed that three of these genes were significantly differentially expressed in individuals differing in parapodium number. AJAP08772 and AJAP08773 may directly affect parapodium production by promoting endothelial cell proliferation and metabolism, whereas AJAP07248 indirectly affects parapodium production by participating in immune responses.

CONCLUSIONS

This study, we performed population genetic structure and GWAS analysis on Chinese and Russian A. japonicus, and found three candidate genes related to the number of parapodium. The results provide an in-depth understanding of the differences in the genetic structure of A. japonicus populations in China and Russia, and provide important information for subsequent genetic analysis and breeding of this species.

Genome-wide Association Study Shows That Executive Functioning Is Influenced by GABAergic Processes and Is a Neurocognitive Genetic Correlate of Psychiatric Disorders

BACKGROUND

Deficits in executive functions (EFs), cognitive processes that control goal-directed behaviors, are associated with psychopathology and neurologic disorders. Little is known about the molecular bases of individual differences in EFs. Prior candidate gene studies have been underpowered in their search for dopaminergic processes involved in cognitive functioning, and existing genome-wide association studies of EFs used small sample sizes and/or focused on individual tasks that are imprecise measures of EFs.

METHODS

We conducted a genome-wide association study of a common EF (cEF) factor score based on multiple tasks in the UK Biobank (n = 427,037 individuals of European descent).

RESULTS

We found 129 independent genome-wide significant lead variants in 112 distinct loci. cEF was associated with fast synaptic transmission processes (synaptic, potassium channel, and GABA [gamma-aminobutyric acid] pathways) in gene-based analyses. cEF was genetically correlated with measures of intelligence (IQ) and cognitive processing speed, but cEF and IQ showed differential genetic associations with psychiatric disorders and educational attainment.

CONCLUSIONS

Results suggest that cEF is a genetically distinct cognitive construct that is particularly relevant to understanding the genetic variance in psychiatric disorders.

Combing Genome-Wide Association Studies and Single-Cell Analysis to Elucidate the Mechanisms of Kidney Disease: Proceedings of the Henry Shavelle Professorship

Background

Kidney diseases pose a significant global health burden; there is an urgent need to deepen our understanding of their underlying mechanisms.

Summary

This review focuses on new innovative approaches that merge genome-wide association studies (GWAS) and single-cell omics (including transcriptomics) in kidney disease research. We begin by detailing how GWAS has identified numerous genetic risk factors, offering valuable insight into disease susceptibility. Then, we explore the application of scRNA-seq, highlighting its ability to unravel how genetic variants influence cellular phenotypes. Through a synthesis of recent studies, we illuminate the synergy between these two powerful methodologies, demonstrating their potential in elucidating the complex etiology of kidney diseases. Moreover, we discuss how this integrative approach could pave the way for precise diagnostics and personalized treatments.

Key Message

This review underscores the transformative potential of combining GWAS and scRNA-seq in the journey toward a deeper understanding of kidney diseases.

Sex-related differences in single nucleotide polymorphisms associated with dyslipidemia in a Korean population

BACKGROUND

The prevalence of dyslipidemia has increased steadily in Korea, and the incidence of dyslipidemia differs by sex. In this study, we identified single nucleotide polymorphisms (SNPs) related to dyslipidemia in Korean cohorts through genome-wide association study (GWAS) analysis.

METHODS

Genotyping was conducted to determine the genotypes of 72,298 participants and investigate genotypes for 7,079,946 SNPs. Sex, age, and BMI were set as covariates for GWAS, and significant SNPs were identified in the discovery and replication stages using logistic regression.

RESULTS

GWAS of the entire cohort revealed a total of five significant SNPs: rs117026536 (LPL), rs651821 (APOA5), rs9804646 (APOA5), rs9926440 (CETP), and rs429358 (APOE). GWAS of the male subjects revealed a total of four significant SNPs. While rs9804646 (APOA5) and rs429358 (APOE) were significant for all the subjects, rs662799 (APOA5) and rs56156922 (CETP) were significant only for the male subjects. GWAS of the female subjects revealed two significant SNPs, rs651821 (APOA5) and rs9804646 (APOA5), both of which were significant in all the subjects.

CONCLUSION

This is the first study to identify sex-related differences in genetic polymorphisms in Korean populations with dyslipidemia. Further studies considering environmental variables will be needed to elucidate these sex-related genetic differences in dyslipidemia.

Polygenic risk and causal inference of psychiatric comorbidity in inflammatory bowel disease among patients with European ancestry

BACKGROUND

Approximately 40% of persons with inflammatory bowel disease (IBD) experience psychiatric comorbidities (PC). Previous studies demonstrated the polygenetic effect on both IBD and PC. In this study, we evaluated the contribution of genetic variants to PC among the IBD population. Additionally, we evaluated whether this effect is mediated by the expression level of the RBPMS gene, which was identified in our previous studies as a potential risk factor of PC in persons with IBD.

MATERIALS AND METHODS

The polygenic risk score (PRS) was estimated among persons with IBD of European ancestry (n = 240) from the Manitoba IBD Cohort Study by using external genome-wide association studies (GWAS). The association and prediction performance were examined between the estimated PRS and PC status among persons with IBD. Finally, regression-based models were applied to explore whether the imputed expression level of the RBPMS gene is a mediator between estimated PRS and PC status in IBD.

RESULTS

The estimated PRS had a significantly positive association with PC status (for the highest effect: P-value threshold = 5 × 10^-3, odds ratio = 2.0, P-value = 1.5 × 10^-5). Around 13% of the causal effect between the PRS and PC status in IBD was mediated by the expression level of the RBPMS gene. The area under the curve of the PRS-based PC prediction model is around 0.7 at the threshold of 5 × 10^-4.

CONCLUSION

PC status in IBD depends on genetic influences among persons with European ancestry. The PRS could potentially be applied to PC risk screening to identify persons with IBD at a high risk of PC. Around 13% of this genetic influence could be explained by the expression level of the RBPMS gene.

The genome of oil-Camellia and population genomics analysis provide insights into seed oil domestication

BACKGROUND

As a perennial crop, oil-Camellia possesses a long domestication history and produces high-quality seed oil that is beneficial to human health. Camellia oleifera Abel. is a sister species to the tea plant, which is extensively cultivated for edible oil production. However, the molecular mechanism of the domestication of oil-Camellia is still limited due to the lack of sufficient genomic information.

RESULTS

To elucidate the genetic and genomic basis of evolution and domestication, here we report a chromosome-scale reference genome of wild oil-Camellia (2.95 Gb), together with transcriptome sequencing data of 221 cultivars. The oil-Camellia genome, assembled by an integrative approach of multiple sequencing technologies, consists of a large proportion of repetitive elements (76.1%) and high heterozygosity (2.52%). We construct a genetic map of high-density corrected markers by sequencing the controlled-pollination hybrids. Genome-wide association studies reveal a subset of artificially selected genes that are involved in the oil biosynthesis and phytohormone pathways. Particularly, we identify the elite alleles of genes encoding sugar-dependent triacylglycerol lipase 1, β-ketoacyl-acyl carrier protein synthase III, and stearoyl-acyl carrier protein desaturases; these alleles play important roles in enhancing the yield and quality of seed oil during oil-Camellia domestication.

CONCLUSIONS

We generate a chromosome-scale reference genome for oil-Camellia plants and demonstrate that the artificial selection of elite alleles of genes involved in oil biosynthesis contributes to oil-Camellia domestication.

Genome-Wide Association Analysis to Search for New Loci Associated with Lifelong Premature Ejaculation Risk in Chinese Male Han Population

PURPOSE

Genetic factors play an indispensable role in the pathogenesis of lifelong premature ejaculation (LPE). The susceptibility genes/SNPs that have been discovered are very limited and can only explain part of the genetic effects of LPE. Therefore, discovering more genetic polymorphisms associated with the occurrence and development of LPE will help reveal the pathogenesis of LPE.

MATERIALS AND METHODS

We conducted a genome-wide association study of LPE in 486 Chinese male Han people (cases and controls). We used Gene Titan multi-channel instrument and Axiom Analysis Suite 6.0 software for genotyping. Imputation was performed by IMPUTE2 software and the 1000 Genomes Project (Phase3) was used as reference for haplotype. Finally, logistic regression analysis was performed on all loci that passed the quality control. The odds ratio and 95% confidence interval were calculated to determine the association between each SNPs and Chinese male Han population LPE risk.

RESULTS

The results showed that a total of 33 genetic variants in 13 genes (LACTBL1, SSBP3, ACOT11, LINC02486, TMEM154, LINC01098, NONE, HCG27, HLA-C, TNFSF8, TNC, FAM53B, SULF2) have a suggestively significant genome-wide association with LPE risk (p<5×10^-6).

CONCLUSIONS

This study is the first to conduct a GWAS on LPE in Chinese male Han population 33 genetic polymorphisms have a suggestive genome-wide association with LPE risk. This study have provided data supplement for the genetic loci of LPE risk, and laid a scientific foundation for the pathogenesis and the targeted therapy of LPE.

Identification of yield-related genes through genome-wide association: case study of weeping forsythia, an emerging medicinal crop

KEY MESSAGE

This study identified candidate genes related to fruit yield for an emerging medicinal crop, weeping forsythia.

BACKGROUND

The genetic basis of crop yield is an agricultural research hotspot. Identifying the genes related to yield traits is the key to increase the yield. Weeping forsythia is an emerging medicinal crop that currently lacks excellent varieties. The genes related to fruit yield in weeping forsythia have not been identified.

OBJECTIVE

Thus, we aimed to screen the candidate genes related to fruit yield of weeping forsythia by using genome-wide association analysis.

METHODS

Here, 60 samples from the same field and source of weeping forsythia were collected to identify its yield-related candidate genes. Association analysis was performed on the variant loci and the traits related to yield, i.e., fruit length, width, thickness, and weight.

RESULTS

Results from admixture, neighbor-joining, and kinship matrix analyses supported the non-significant genetic differentiation of these samples. Significant association was found between 2 variant loci and fruit length, 8 loci and fruit width, 24 loci and fruit thickness, and 13 loci and fruit weight. Further search on the 20 kb up/downstream of these variant loci revealed 1 gene related to fruit length, 16 genes related to fruit width, 12 genes related to fruit thickness, and 13 genes related to fruit weight. Among which, 4 genes, namely, WRKY transcription factor 35, salicylic acid-binding protein, auxin response factor 6, and alpha-mannosidase were highly related to the fruit development of weeping forsythia.

CONCLUSION

This study identify four candidate genes related to fruit development, which will provide useful information for the subsequent molecular-assisted and genetic breeding of weeping forsythia.

Integrative analysis of GWAS and transcriptome to reveal novel loci regulation flowering time in semi-winter rapeseed

Flowering is an important turning point from vegetative growth to reproductive growth, and vernalization is an essential condition for the flowering of annual winter plants. To investigate the genetic architecture of flowering time in rapeseed, we used the 60 K Brassica Infinium SNP array to perform a genome-wide analysis of haplotype blocks associated with flowering time in 203 Chinese semi-winter rapeseed inbred lines. Twenty-one haplotype regions carrying one or more candidate genes showed a significant association with flowering time. Interestingly, we detected a SNP (Bn-scaff_22728_1-p285715) located in exon 3 of the BnVIN3-C03 gene that showed a significant association with flowering time on chromosome C03. Based on the SNP alleles A and G, two groups of accessions with early and late flowering time phenotypes were selected, respectively, and PCR amplification and gene expression analysis were combined to reveal the structural variation of the BnVIN3-C03 gene that affected flowering time. Moreover, we found that BnVIN3-C03 inhibited the expression of BnFLC-A02, BnFLC-A03.1, BnFLC-A10 and BnFLC-C03.1, thus modulating the flowering time of Brassica napus. This result provides insight into the genetic improvement of flowering time in B. napus.

A validated generally applicable approach using the systematic assessment of disease modules by GWAS reveals a multi-omic module strongly associated with risk factors in multiple sclerosis

BACKGROUND

There exist few, if any, practical guidelines for predictive and falsifiable multi-omic data integration that systematically integrate existing knowledge. Disease modules are popular concepts for interpreting genome-wide studies in medicine but have so far not been systematically evaluated and may lead to corroborating multi-omic modules.

RESULT

We assessed eight module identification methods in 57 previously published expression and methylation studies of 19 diseases using GWAS enrichment analysis. Next, we applied the same strategy for multi-omic integration of 20 datasets of multiple sclerosis (MS), and further validated the resulting module using both GWAS and risk-factor-associated genes from several independent cohorts. Our benchmark of modules showed that in immune-associated diseases modules inferred from clique-based methods were the most enriched for GWAS genes. The multi-omic case study using MS data revealed the robust identification of a module of 220 genes. Strikingly, most genes of the module were differentially methylated upon the action of one or several environmental risk factors in MS (n = 217, P = 10- 47) and were also independently validated for association with five different risk factors of MS, which further stressed the high genetic and epigenetic relevance of the module for MS.

CONCLUSIONS

We believe our analysis provides a workflow for selecting modules and our benchmark study may help further improvement of disease module methods. Moreover, we also stress that our methodology is generally applicable for combining and assessing the performance of multi-omic approaches for complex diseases.

Deep-gated recurrent unit and diet network-based genome-wide association analysis for detecting the biomarkers of Alzheimer's disease

Genome-wide association analysis (GWAS) is a commonly used method to detect the potential biomarkers of Alzheimer's disease (AD). Most existing GWAS methods entail a high computational cost, disregard correlations among imaging data and correlations among genetic data, and ignore various associations between longitudinal imaging and genetic data. A novel GWAS method was proposed to identify potential AD biomarkers and address these problems. A network based on a gated recurrent unit was applied without imputing incomplete longitudinal imaging data to integrate the longitudinal data of variable lengths and extract an image representation. In this study, a modified diet network that can considerably reduce the number of parameters in the genetic network was proposed to perform GWAS between image representation and genetic data. Genetic representation can be extracted in this way. A link between genetic representation and AD was established to detect potential AD biomarkers. The proposed method was tested on a set of simulated data and a real AD dataset. Results of the simulated data showed that the proposed method can accurately detect relevant biomarkers. Moreover, the results of real AD dataset showed that the proposed method can detect some new risk-related genes of AD. Based on previous reports, no research has incorporated a deep-learning model into a GWAS framework to investigate the potential information on super-high-dimensional genetic data and longitudinal imaging data and create a link between imaging genetics and AD for detecting potential AD biomarkers. Therefore, the proposed method may provide new insights into the underlying pathological mechanism of AD.

Genome-wide association study reveals novel loci associated with feeding behavior in Pekin ducks

Background

Feeding behavior traits are an essential part of livestock production. However, the genetic base of feeding behavior traits remains unclear in Pekin ducks. This study aimed to determine novel loci related to feeding behavior in Pekin ducks.

Results

In this study, the feeding information of 540 Pekin ducks was recorded, and individual genotype was evaluated using genotyping-by-sequencing methods. Genome-wide association analysis (GWAS) was conducted for feeding behavior traits. Overall, thirty significant (P-value < 4.74E-06) SNPs for feeding behavior traits were discovered, and four of them reached the genome-wide significance level (P-value < 2.37E-07). One genome-wide significance locus associated with daily meal times was located in a 122.25 Mb region on chromosome 2, which was within the intron of gene ubiquitin-conjugating enzyme E2 E2 (UBE2E2), and could explain 2.64% of the phenotypic variation. This locus was also significantly associated with meal feed intake, and explained 2.72% of this phenotypic variation.

Conclusions

This study is the first GWAS for feeding behavior traits in ducks. Our results provide a list of candidate genes associated with feeding behavior, and also help to better understand the genetic mechanisms of feeding behavior patterns in ducks.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07668-1.

A multilayered post-GWAS assessment on genetic susceptibility to pancreatic cancer

BACKGROUND

Pancreatic cancer (PC) is a complex disease in which both non-genetic and genetic factors interplay. To date, 40 GWAS hits have been associated with PC risk in individuals of European descent, explaining 4.1% of the phenotypic variance.

METHODS

We complemented a new conventional PC GWAS (1D) with genome spatial autocorrelation analysis (2D) permitting to prioritize low frequency variants not detected by GWAS. These were further expanded via Hi-C map (3D) interactions to gain additional insight into the inherited basis of PC. In silico functional analysis of public genomic information allowed prioritization of potentially relevant candidate variants.

RESULTS

We identified several new variants located in genes for which there is experimental evidence of their implication in the biology and function of pancreatic acinar cells. Among them is a novel independent variant in NR5A2 (rs3790840) with a meta-analysis p value = 5.91E-06 in 1D approach and a Local Moran's Index (LMI) = 7.76 in 2D approach. We also identified a multi-hit region in CASC8-a lncRNA associated with pancreatic carcinogenesis-with a lowest p value = 6.91E-05. Importantly, two new PC loci were identified both by 2D and 3D approaches: SIAH3 (LMI = 18.24), CTRB2/BCAR1 (LMI = 6.03), in addition to a chromatin interacting region in XBP1-a major regulator of the ER stress and unfolded protein responses in acinar cells-identified by 3D; all of them with a strong in silico functional support.

CONCLUSIONS

This multi-step strategy, combined with an in-depth in silico functional analysis, offers a comprehensive approach to advance the study of PC genetic susceptibility and could be applied to other diseases.

Genome-wide association analysis of opioid use disorder: A novel approach using clinical data

BACKGROUND

Opioid use disorder (OUD) represents a large and pervasive global public health challenge. Previous genetic studies have demonstrated the significant heritability of OUD and identified several single-nucleotide polymorphisms (SNPs) associated with its prevalence.

METHODS

In this paper, we conducted a genome-wide association analysis on opioid use disorder that leveraged genetic and clinical data contained in a biobank of 21,310 patients of European ancestry. We identified 1039 cases of opioid use disorder based on diagnostic codes from nearly 16 million encounters in electronic health records (EHRs).

RESULTS

We discovered one novel OUD-associated locus on chromosome 4 that was significant at a genome-wide threshold (p = 2.40 × 10^-8). Heritability analysis suggested that common SNPs explained 0.06 (se 0.02, p = 0.0065) of the phenotypic variation in OUD. When we restricted controls to those with previous opioid prescriptions, we were able to further strengthen the original signal and discovered another significant locus on chromosome 16. Pair-wise genetic correlation analysis yielded strong positive correlations between OUD and two other major substance use disorders, alcohol and nicotine, with the strongest correlation between nicotine and opioid use disorder (genetic correlation 0.65, se = 0.19, p = 0.00048), suggesting a significant shared genetic component across different substance disorders.

CONCLUSIONS

This pragmatic, clinically-focused approach may supplement more traditional methods to facilitate identification of new genetic underpinnings of OUD and related disorders.

Genetics of Equine Endocrine and Metabolic Disease

A role for a genetic contribution to equine metabolic syndrome (EMS) and pars pituitary intermedia dysfunction (PPID) has been hypothesized. Heritability estimates of EMS biochemical measurements were consistent with moderately to highly heritable traits. Further, genome-wide association analyses have identified hundreds of regions of the genome contributing to EMS and candidate variants have been identified. The genetics of PPID has not yet been proven. Continued research for the specific genetic risk factors for both EMS and PPID is crucial for gaining a better understanding of the pathophysiology of both conditions and allowing development of genetic tests.

Genome-wide association analysis reveals the genetic locus for high reproduction trait in Chinese Arbas Cashmere goat

BACKGROUND

Litter size is the most important reproductive trait which plays a crucial role in goat production. Therefore, improvement of litter size trait has been of increasing interest in goat industry as small improvement in litter size may lead to large profit. The recent Cashmere goat breeding program produced a high-reproductive genetic line of Arbas Cashmere goat. But the genetic mechanism of high reproduction rate remains largely unknown in this Chinese native goat breed. To address this question, we performed a genome-wide association studies (GWAS) using two groups of goats varying in fecundity.

OBJECTIVES

Our study was aimed to investigate the significant SNPs and genes associated with high reproduction trait in Inner Mongolia Arbas Cashmere Goat.

METHODS

We used logistic model association to perform GWAS using 47 goats from high fecundity group (~ 190%) and 314 goats from low fecundity group (~ 130%) of the Arbas Cashmere goat breed.

RESULTS

We identified 66 genomic regions associated with genome wide significant level wherein six loci were found to be associated with reproduction traits. Further analysis showed that five key candidate genes including KISS1, KHDRBS2, WNT10B, SETDB2 and PPP3CA genes are involved in goat fecundity trait. Gene ontology enrichment analysis revealed that several biological pathways could be involved in the variation of fecundity in female goats.

CONCLUSIONS

The identified significant SNPs or genes provide useful information about the underlying genetic control of fecundity trait which will be helpful to use them in goat breeding programs for improving the reproductive efficiency of goats.

A trans-ethnic two-stage polygenetic scoring analysis detects genetic correlation between osteoporosis and schizophrenia

BACKGROUNDS

To explore the genetic correlation between schizophrenia (SCZ) and osteoporosis (OP).

DESIGN, SETTING, PARTICIPANTS, MEASUREMENTS

We conducted a trans-ethnic two-stage genetic correlation analysis of OP and SCZ, totally invoking 2286 Caucasia subjects in discovery stage and 4124 Chinese subjects in replication stage. The bone mineral density (BMD) and bone area values of ulna & radius, hip and spine were measured using Hologic 4500W dual energy X-ray absorptiometry machine. SCZ was diagnosed according to DSM-IV criteria. For the genome-wide association study (GWAS) of Caucasian OP, Chinese OP and Chinese SCZ, SNP genotyping was performed using Affymetrix SNP 6.0 array. For the GWAS of Caucasian SCZ, SNP genotyping was conducted using the Affymetrix 5.0 array, Affymetrix 6.0 array and Illumina 550 K array. Polygenetic risk scoring (PRS) analysis was conducted by PRSice software. Also, Linkage disequilibrium score regression (LD Score regression) analysis was performed to evaluate the genetic correlation between OP and SCZ. Multi-trait analysis of GWAS (MTAG) was performed to detect novel candidate genes for osteoporosis and SCZ.

RESULTS

In the Caucasia discovery samples, significant genetic correlations were observed for ulna & radius BMD vs. SCZ (P value = 0.010), ulna & radius area vs. SCZ (P value = 0.031). In the Chinese replication samples, we observed significant correlation for ulna & radius area vs. SCZ (P value = 0.019). In addition, LD Score regression also identified significant genetic correlations between SCZ and bone phenotypes in Caucasian and Chinese sample respectively. MTAG analysis identified several novel candidate genes, such as CTNNA2 (MTAG P value = 2.24 × 10-6) for SCZ and FADS2 (MTAG P value = 2.66 × 10-7) for osteoporosis.

CONCLUSIONS

Our study results support the overlapped genetic basis for osteoporosis and SCZ, and provide novel clues for elucidating the biological mechanism of increased osteoporosis risk in SCZ patients.

Comparative genomics and association analysis identifies virulence genes of Cercospora sojina in soybean

BACKGROUND

Recently, a new strain of Cercospora sojina (Race15) has been identified, which has caused the breakdown of resistance in most soybean cultivars in China. Despite this serious yield reduction, little is known about why this strain is more virulent than others. Therefore, we sequenced the Race15 genome and compared it to the Race1 genome sequence, as its virulence is significantly lower. We then re-sequenced 30 isolates of C. sojina from different regions to identifying differential virulence genes using genome-wide association analysis (GWAS).

RESULTS

The 40.12-Mb Race15 genome encodes 12,607 predicated genes and contains large numbers of gene clusters that have annotations in 11 different common databases. Comparative genomics revealed that although these two genomes had a large number of homologous genes, their genome structures have evolved to introduce 245 specific genes. The most important 5 candidate virulence genes were located on Contig 3 and Contig 1 and were mainly related to the regulation of metabolic mechanisms and the biosynthesis of bioactive metabolites, thereby putatively affecting fungi self-toxicity and reducing host resistance. Our study provides insight into the genomic basis of C. sojina pathogenicity and its infection mechanism, enabling future studies of this disease.

CONCLUSIONS

Via GWAS, we identified five candidate genes using three different methods, and these candidate genes are speculated to be related to metabolic mechanisms and the biosynthesis of bioactive metabolites. Meanwhile, Race15 specific genes may be linked with high virulence. The genes highly prevalent in virulent isolates should also be proposed as candidates, even though they were not found in our SNP analysis. Future work should focus on using a larger sample size to confirm and refine candidate gene identifications and should study the functional roles of these candidates, in order to investigate their potential roles in C. sojina pathogenicity.

Evaluation of genetic diversity, agronomic traits, and anthracnose resistance in the NPGS Sudan Sorghum Core collection

Background

The United States Department of Agriculture (USDA) National Plant Germplasm System (NPGS) sorghum core collection contains 3011 accessions randomly selected from 77 countries. Genomic and phenotypic characterization of this core collection is necessary to encourage and facilitate its utilization in breeding programs and to improve conservation efforts. In this study, we examined the genome sequences of 318 accessions belonging to the NPGS Sudan sorghum core set, and characterized their agronomic traits and anthracnose resistance response.

Results

We identified 183,144 single nucleotide polymorphisms (SNPs) located within or in proximity of 25,124 annotated genes using the genotyping-by-sequencing (GBS) approach. The core collection was genetically highly diverse, with an average pairwise genetic distance of 0.76 among accessions. Population structure and cluster analysis revealed five ancestral populations within the Sudan core set, with moderate to high level of genetic differentiation. In total, 171 accessions (54%) were assigned to one of these populations, which covered 96% of the total genomic variation. Genome scan based on Tajima’s D values revealed two populations under balancing selection. Phenotypic analysis showed differences in agronomic traits among the populations, suggesting that these populations belong to different ecogeographical regions. A total of 55 accessions were resistant to anthracnose; these accessions could represent multiple resistance sources. Genome-wide association study based on fixed and random model Circulating Probability (farmCPU) identified genomic regions associated with plant height, flowering time, panicle length and diameter, and anthracnose resistance response. Integrated analysis of the Sudan core set and sorghum association panel indicated that a large portion of the genetic variation in the Sudan core set might be present in breeding programs but remains unexploited within some clusters of accessions.

Conclusions

The NPGS Sudan core collection comprises genetically and phenotypically diverse germplasm with multiple anthracnose resistance sources. Population genomic analysis could be used to improve screening efforts and identify the most valuable germplasm for breeding programs. The new GBS data set generated in this study represents a novel genomic resource for plant breeders interested in mining the genetic diversity of the NPGS sorghum collection.

Identification of loci associated with conception rate in primiparous Holstein cows

Background

Subfertility is a major issue facing the dairy industry as the average US Holstein cow conception rate (CCR) is approximately 35%. The genetics underlying the physiological processes responsible for CCR, the proportion of cows able to conceive and maintain a pregnancy at each breeding, are not well characterized. The objectives of this study were to identify loci, positional candidate genes, and transcription factor binding sites (TFBS) associated with CCR and determine if there was a genetic correlation between CCR and milk production in primiparous Holstein cows. Cows were bred via artificial insemination (AI) at either observed estrus or timed AI and pregnancy status was determined at day 35 post-insemination. Additive, dominant, and recessive efficient mixed model association expedited (EMMAX) models were used in two genome-wide association analyses (GWAA). One GWAA focused on CCR at first service (CCR1) comparing cows that conceived and maintained pregnancy to day 35 after the first AI (n = 494) to those that were open after the first AI (n = 538). The second GWAA investigated loci associated with the number of times bred (TBRD) required for conception in cows that either conceived after the first AI (n = 494) or repeated services (n = 472).

Results

The CCR1 GWAA identified 123, 198, and 76 loci associated (P < 5 × 10^− 08) in additive, dominant, and recessive models, respectively. The TBRD GWAA identified 66, 95, and 33 loci associated (P < 5 × 10^− 08) in additive, dominant, and recessive models, respectively. Four of the top five loci were shared in CCR1 and TBRD for each GWAA model. Many of the associated loci harbored positional candidate genes and TFBS with putative functional relevance to fertility. Thirty-six of the loci were validated in previous GWAA studies across multiple breeds. None of the CCR1 or TBRD associated loci were associated with milk production, nor was their significance with phenotypic and genetic correlations to 305-day milk production.

Conclusions

The identification and validation of loci, positional candidate genes, and TFBS associated with CCR1 and TBRD can be utilized to improve, and further characterize the processes involved in cattle fertility.

Combined genome-wide association analysis and transcriptome sequencing to identify candidate genes for flax seed fatty acid metabolism

Flax seeds have a high oil content and are rich in unsaturated fatty acids, which have advantageous effects in preventing chronic diseases, such as cardiovascular diseases. At present, flax seeds are mainly developed for oil. Therefore, it is of practical significance to identify the candidate genes of fatty acid metabolism in flax seeds for breeding flax seeds with high oil content. In the present study, a natural population of flax containing 224 samples planted in 3 different environments was studied. The genome-wide association analysis (GWAS) of seed fatty acid content was conducted based on specific length amplified fragment sequencing (SLAF-seq) data. Transcriptome sequencing (RNA-seq) of samples from 3 different periods (14 d, 21 d and 28 d after anthesis) during seed development of the low oil variety Shuangya 4 and the high oil variety NEW was performed. The candidate genes for seed fatty acid metabolism were identified by combined analysis of these 2 methods. GWAS detected 16 SNP loci significantly associated with seed fatty acid content, and RNA-seq analysis identified 11,802 differentially expressed genes between high and low oil samples. Pathway enrichment analysis revealed that some differentially expressed genes were classified into fatty acid-related pathways. After comparison of these differentially expressed genes with the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, 20 genes homologous to other species were obtained. After analysis, 10 candidate genes were screened by GWAS and RNA-seq screening. Of these 10 genes, qRT-PCR assays using flax seeds in 5 different developmental stages showed that the expression levels of 6 candidate genes were significantly correlated with 5 fatty acid contents in seeds of the high oil variety NEW. Through metabolic pathway analysis found that 6 genes were involved in important fatty acid metabolic pathways, and some of them also have upstream and downstream regulation relations. The present study combined GWAS and RNA-seq methods to identify candidate genes for fatty acid metabolism in flax seeds, which provided reference for screening of candidate genes with complex traits.

Genome wide association mapping and candidate gene analysis for hundred seed weight in soybean [Glycine max (L.) Merrill]

BACKGROUND

The hundred seed weight (HSW) is one of the yield components of soybean [Glycine max (L.) Merrill] and is especially critical for various soybean food types. In this study, a representative sample consisting of 185 accessions was selected from Northeast China and analysed in three tested environments to determine the quantitative trait nucleotide (QTN) of HSW through a genome-wide association study (GWAS).

RESULT

A total of 24,180 single nucleotide polymorphisms (SNPs) with minor allele frequencies greater than 0.2 and missing data less than 3% were utilized to estimate linkage disequilibrium (LD) levels in the tested association panel. Thirty-four association signals were identified as associated with HSW via GWAS. Among them, nineteen QTNs were novel, and another fifteen QTNs were overlapped or located near the genomic regions of known HSW QTL. A total of 237 genes, derived from 31 QTNs and located near peak SNPs from the three tested environments in 2015 and 2016, were considered candidate genes, were related to plant growth regulation, hormone metabolism, cell, RNA, protein metabolism, development, starch accumulation, secondary metabolism, signalling, and the TCA cycle, some of which have been found to participate in the regulation of HSW. A total of 106 SNPs from 16 candidate genes were significantly associated with HSW in soybean.

CONCLUSIONS

The identified loci with beneficial alleles and candidate genes might be valuable for the molecular network and MAS of HSW.

Genome-wide association study of inflorescence length of cultivated soybean based on the high-throughout single-nucleotide markers

As an important and complex trait, inflorescence length (IL) of soybean [Glycine max (L.) Merr.] significantly affected seed yields. Therefore, elucidating molecular basis of inflorescence architecture, especially for IL, was important for improving soybean yield potentials. Longer IL meaned to have more pod and seed in soybean. Hence, increasing IL and improving yield are targets for soybean breeding. In this study, a association panel, comprising 283 diverse samples, was used to dissect the genetic basis of IL based on genome-wide association analysis (GWAS) and haplotype analysis. GWAS and haplotype analysis were conducted through high-throughout single-nucleotide polymorphisms (SNP) developed by SLAF-seq methodology. A total of 39, 057 SNPs (minor allele frequency ≥ 0.2 and missing data ≤ 10%) were utilized to evaluate linkage disequilibrium (LD) level in the tested association panel. A total of 30 association signals were identified to be associated with IL via GWAS. Among them, 13 SNPs were novel, and another 17 SNPs were overlapped or located near the linked regions of known quantitative trait nucleotide (QTN) with soybean seed yield or yield component. The functional genes, located in the 200-kb genomic region of each peak SNP, were considered as candidate genes, such as the cell division/ elongation, specific enzymes, and signaling or transport of specific proteins. These genes have been reported to participant in the regulation of IL. Ten typical long-IL lines and ten typical short-IL lines were re-sequencing, and then, six SNPs from five genes were obtained based on candidate gene-based association. In addition, 42 haplotypes were defined based on haplotype analysis. Of them, 11 haplotypes were found to regulate long IL (> 14 mm) in soybean. The identified 30 QTN with beneficial alleles and their candidate genes might be valuable for dissecting the molecular mechanisms of IL and further improving the yield potential of soybean.

SNP genotype calling and quality control for multi-batch-based studies

BACKGROUND

In genetic analyses, the term 'batch effect' refers to systematic differences caused by batch heterogeneity. Controlling this unintended effect is the most important step in quality control (QC) processes that precede analyses. Currently, batch effects are not appropriately controlled by statistics, and newer approaches are required.

METHODS

In this report, we propose a new method to detect the heterogeneity of probe intensities among different batches and a procedure for calling genotypes and QC in the presence of a batch effect. First, we conducted a multivariate analysis of variance (MANOVA) to test the differences in probe intensities among batches. If heterogeneity is detected, subjects should be clustered using a K-medoid algorithm using the averages of the probe intensity measurements for each batch and the genotypes of subjects in different clusters should be called separately.

RESULTS

The proposed method was used to assess genotyping data of 3619 subjects consisting of 1074 patients with Alzheimer's disease, 296 with mild cognitive impairment (MCI), and 1153 controls. The proposed method improves the accuracy of called genotypes without the need to filter a lot of subjects and SNPs, and therefore is a reasonable approach for controlling batch effects.

CONCLUSIONS

We proposed a new strategy that detects batch effects with probe intensity measurement and calls genotypes in the presence of batch effects. The application of the proposed method to real data shows that it produces a balanced approach. Furthermore, the proposed method can be extended to various scenarios with a simple modification.

Comparing the mRNA expression profile and the genetic determinism of intramuscular fat traits in the porcine gluteus medius and longissimus dorsi muscles

Background

Intramuscular fat (IMF) content and composition have a strong impact on the nutritional and organoleptic properties of porcine meat. The goal of the current work was to compare the patterns of gene expression and the genetic determinism of IMF traits in the porcine gluteus medius (GM) and longissimus dorsi (LD) muscles.

Results

A comparative analysis of the mRNA expression profiles of the pig GM and LD muscles in 16 Duroc pigs with available microarray mRNA expression measurements revealed the existence of 106 differentially expressed probes (fold-change > 1.5 and q-value < 0.05). Amongst the genes displaying the most significant differential expression, several loci belonging to the Hox transcription factor family were either upregulated (HOXA9, HOXA10, HOXB6, HOXB7 and TBX1) or downregulated (ARX) in the GM muscle. Differences in the expression of genes with key roles in carbohydrate and lipid metabolism (e.g. FABP3, ORMDL1 and SLC37A1) were also detected. By performing a GWAS for IMF content and composition traits recorded in the LD and GM muscles of 350 Duroc pigs, we identified the existence of one region on SSC14 (110–114 Mb) displaying significant associations with C18:0, C18:1(n-7), saturated and unsaturated fatty acid contents in both GM and LD muscles. Moreover, we detected several genome-wide significant associations that were not consistently found in both muscles. Further studies should be performed to confirm whether these associations are muscle-specific. Finally, the performance of an eQTL scan for 74 genes, located within GM QTL regions and with available microarray measurements of gene expression, made possible to identify 14 cis-eQTL regulating the expression of 14 loci, and six of them were confirmed by RNA-Seq.

Conclusions

We have detected significant differences in the mRNA expression patterns of the porcine LD and GM muscles, evidencing that the transcriptomic profile of the skeletal muscle tissue is affected by anatomical, metabolic and functional factors. A highly significant association with IMF composition on SSC14 was replicated in both muscles, highlighting the existence of a common genetic determinism, but we also observed the existence of a few associations whose magnitude and significance varied between LD and GM muscles.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5557-9) contains supplementary material, which is available to authorized users.

Genome-wide meta-analysis identifies novel loci associated with parathyroid hormone level

Background

Parathyroid hormone (PTH) is one of the principal regulators of calcium homeostasis. Although serum PTH level is mostly accounted by genetic factors, genetic background underlying PTH level is insufficiently known. Therefore, the aim of this study was to identify novel genetic variants associated with PTH levels.

Methods

We performed GWAS meta-analysis within two genetically isolated Croatian populations followed by replication analysis in a Croatian mainland population and we also combined results across all three analyzed populations. The analyses included 2596 individuals. A total of 7,411,206 variants, imputed using the 1000 Genomes reference panel, were analysed for the association. In addition, a sex-specific GWAS meta-analyses were performed.

Results

Polymorphisms with the lowest P-values were located on chromosome 4 approximately 84 kb of the 5′ of RASGEF1B gene. The most significant SNP was rs11099476 (P = 1.15 × 10⁻⁸). Sex-specific analysis identified genome-wide significant association of the variant rs77178854, located within DPP10 gene in females only (P = 2.21 × 10^− 9). There were no genome-wide significant findings in the meta-analysis of males.

Conclusions

We identified two biologically plausible novel loci associated with PTH levels, providing us with further insights into the genetics of this complex trait.

Electronic supplementary material

The online version of this article (10.1186/s10020-018-0018-5) contains supplementary material, which is available to authorized users.

Including gene networks to predict calving difficulty in Holstein, Brown Swiss and Jersey cattle

Background

Calving difficulty or dystocia has a great economic impact in the US dairy industry. Reported risk factors associated with calving difficulty are feto-pelvic disproportion, gestation length and conformation. Different dairy cattle breeds have different incidence of calving difficulty, with Holstein having the highest dystocia rates and Jersey the lowest. Genomic selection becomes important especially for complex traits with low heritability, where the accuracy of conventional selection is lower. However, for complex traits where a large number of genes influence the phenotype, genome-wide association studies showed limitations. Biological networks could overcome some of these limitations and better capture the genetic architecture of complex traits. In this paper, we characterize Holstein, Brown Swiss and Jersey breed-specific dystocia networks and employ them in genomic predictions.

Results

Marker association analysis identified single nucleotide polymorphisms explaining the largest average proportion of genetic variance on BTA18 in Holstein, BTA25 in Brown Swiss, and BTA15 in Jersey. Gene networks derived from the genome-wide association included 1272 genes in Holstein, 1454 genes in Brown Swiss, and 1455 genes in Jersey. Furthermore, 256 genes in Holstein network, 275 genes in the Brown Swiss network, and 253 genes in the Jersey network were within previously reported dystocia quantitative trait loci. The across-breed network included 80 genes, with 9 genes being within previously reported dystocia quantitative trait loci. The gene-gene interactions in this network differed in the different breeds. Gene ontology enrichment analysis of genes in the networks showed Regulation of ARF GTPase was very significant (FDR ≤ 0.0098) on Holstein. Neuron morphogenesis and differentiation was the term most enriched (FDR ≤ 0.0539) on the across-breed network. Genomic prediction models enriched with network-derived relationship matrices did not outperform regular GBLUP models.

Conclusions

Regions identified in the genome were in the proximity of previously described quantitative trait loci that would most likely affect calving difficulty by altering the feto-pelvic proportion. Inclusion of identified networks did not increase prediction accuracy. The approach used in this paper could be extended to any instance with asymmetric distribution of phenotypes, for example, resistance to disease data.

Electronic supplementary material

The online version of this article (10.1186/s12863-018-0606-y) contains supplementary material, which is available to authorized users.

Identification of novel loci associated with maturity and yield traits in early maturity soybean plant introduction lines

BACKGROUND

To continue to meet the increasing demands of soybean worldwide, it is crucial to identify key genes regulating flowering and maturity to expand the cultivated regions into short season areas. Although four soybean genes have been successfully utilized in early maturity breeding programs, new genes governing maturity are continuously being identified suggesting that there remains as yet undiscovered loci governing agronomic traits of interest. The objective of this study was to identify novel loci and genes involved in a diverse set of early soybean maturity using genome-wide association (GWA) analyses to identify loci governing days to maturity (DTM), flowering (DTF) and pod filling (DTPF), as well as yield and 100 seed weight in Canadian environments. To do so, soybean plant introduction lines varying significantly for maturity, but classified as early varieties, were used. Plants were phenotyped for the five agronomic traits for five site-years and GWA approaches used to identify candidate loci and genes affecting each trait.

RESULTS

Genotyping using genotyping-by-sequencing and microarray methods identified 67,594 single nucleotide polymorphisms, of which 31,283 had a linkage disequilibrium < 1 and minor allele frequency > 0.05 and were used for GWA analyses. A total of 9, 6, 4, 5 and 2 loci were detected for GWA analyses for DTM, DTF, DTPF, 100 seed weight and yield, respectively. Regions of interest, including a region surrounding the E1 gene for flowering and maturity, and several novel loci, were identified, with several loci having pleiotropic effects. Novel loci affecting maturity were identified on chromosomes five and 13 and reduced maturity by 7.2 and 3.3 days, respectively. Novel loci for maturity and flowering contained genes orthologous to known Arabidopsis flowering genes, while loci affecting yield and 100 seed weight contained genes known to cause dwarfism.

CONCLUSIONS

This study demonstrated substantial variation in soybean agronomic traits of interest, including maturity and flowering dates as well as yield, and the utility of GWA analyses in identifying novel genetic factors underlying important agronomic traits. The loci and candidate genes identified serve as promising targets for future studies examining the mechanisms underlying the related soybean traits.

Population-based analysis of ocular Chlamydia trachomatis in trachoma-endemic West African communities identifies genomic markers of disease severity

BACKGROUND

Chlamydia trachomatis (Ct) is the most common infectious cause of blindness and bacterial sexually transmitted infection worldwide. Ct strain-specific differences in clinical trachoma suggest that genetic polymorphisms in Ct may contribute to the observed variability in severity of clinical disease.

METHODS

Using Ct whole genome sequences obtained directly from conjunctival swabs, we studied Ct genomic diversity and associations between Ct genetic polymorphisms with ocular localization and disease severity in a treatment-naïve trachoma-endemic population in Guinea-Bissau, West Africa.

RESULTS

All Ct sequences fall within the T2 ocular clade phylogenetically. This is consistent with the presence of the characteristic deletion in trpA resulting in a truncated non-functional protein and the ocular tyrosine repeat regions present in tarP associated with ocular tissue localization. We have identified 21 Ct non-synonymous single nucleotide polymorphisms (SNPs) associated with ocular localization, including SNPs within pmpD (odds ratio, OR = 4.07, p* = 0.001) and tarP (OR = 0.34, p* = 0.009). Eight synonymous SNPs associated with disease severity were found in yjfH (rlmB) (OR = 0.13, p* = 0.037), CTA0273 (OR = 0.12, p* = 0.027), trmD (OR = 0.12, p* = 0.032), CTA0744 (OR = 0.12, p* = 0.041), glgA (OR = 0.10, p* = 0.026), alaS (OR = 0.10, p* = 0.032), pmpE (OR = 0.08, p* = 0.001) and the intergenic region CTA0744-CTA0745 (OR = 0.13, p* = 0.043).

CONCLUSIONS

This study demonstrates the extent of genomic diversity within a naturally circulating population of ocular Ct and is the first to describe novel genomic associations with disease severity. These findings direct investigation of host-pathogen interactions that may be important in ocular Ct pathogenesis and disease transmission.

Increased genomic burden of germline copy number variants is associated with early onset breast cancer: Australian breast cancer family registry

BACKGROUND

Women with breast cancer who have multiple affected relatives are more likely to have inherited genetic risk factors for the disease. All the currently known genetic risk factors for breast cancer account for less than half of the average familial risk. Furthermore, the genetic factor(s) underlying an increased cancer risk for many women from multiple-case families remain unknown. Rare genomic duplications and deletions, known as copy number variants (CNVs), cover more than 10% of a human genome, are often not assessed in studies of genetic predisposition, and could account for some of the so-called "missing heritability".

METHODS

We carried out a hypothesis-generating case-control study of breast cancer diagnosed before age 40 years (200 cases, 293 controls) using population-based cases from the Australian Breast Cancer Family Study. Genome-wide scanning for CNVs was performed using the Human610-Quad BeadChip and fine-mapping was conducted using PennCNV.

RESULTS

We identified deletions overlapping two known cancer susceptibility genes, (BRCA1 and BLM), and a duplication overlapping SMARCB1, associated with risk. The number of deletions across the genome was 1.5-fold higher for cases than controls (P = 10^-16), and 2-fold higher when only rare deletions overlapping genes (frequency <1%) were assessed (P = 5 × 10^-4). Association tests of CNVs, followed by experimental validation of CNV calls, found deletions overlapping the OR4C11 and OR4P4 genes were associated with breast cancer (P = 0.02 and P = 0.03, respectively).

CONCLUSION

These results suggest rare CNVs might have a role in breast cancer susceptibility, at least for disease at a young age.

Genome-wide meta-analysis identifies novel loci of plaque burden in carotid artery

BACKGROUND AND AIMS

Carotid artery plaque is an established marker of subclinical atherosclerosis and common patho-mechanisms with coronary artery disease (CAD) are hypothesized. We aimed to identify genetic variants associated with carotid plaque and to examine the potential shared genetic basis with CAD.

METHODS

After investigating the reliability of plaque detection, we performed a genome-wide meta-association study in two independent cohorts (LIFE-Adult, n = 4037 and LIFE-Heart, n = 3152) for carotid plaque score (PS), defined as the sum of the plaque load of common carotid artery and carotid bulb. Further, we analyzed whether previously reported CAD and stroke loci were also associated with PS.

RESULTS

We identified two loci with genome-wide significance for PS. One locus is the known CAD-locus at chromosome 9p21 (lead SNP rs9644862, p = 8.73 × 10^-12). We also describe a novel locus on chromosome 10q24 within the SFXN2 gene as the most probable candidate (lead SNP rs2902548, p = 1.97 × 10^-8). In addition, 17 out of 58 known CAD loci and six of 17 known stroke loci were associated with PS at a nominal level of significance.

CONCLUSIONS

We showed that PS is a reliable trait to analyze genetics of atherosclerosis. Two new loci of genome-wide significant association with PS were found. The observed non-random overlap of CAD and PS associations strengthens the hypothesis of a shared genetic basis for these atherosclerotic manifestations.

Diversity analysis of cotton (Gossypium hirsutum L.) germplasm using the CottonSNP63K Array

BACKGROUND

Cotton germplasm resources contain beneficial alleles that can be exploited to develop germplasm adapted to emerging environmental and climate conditions. Accessions and lines have traditionally been characterized based on phenotypes, but phenotypic profiles are limited by the cost, time, and space required to make visual observations and measurements. With advances in molecular genetic methods, genotypic profiles are increasingly able to identify differences among accessions due to the larger number of genetic markers that can be measured. A combination of both methods would greatly enhance our ability to characterize germplasm resources. Recent efforts have culminated in the identification of sufficient SNP markers to establish high-throughput genotyping systems, such as the CottonSNP63K array, which enables a researcher to efficiently analyze large numbers of SNP markers and obtain highly repeatable results. In the current investigation, we have utilized the SNP array for analyzing genetic diversity primarily among cotton cultivars, making comparisons to SSR-based phylogenetic analyses, and identifying loci associated with seed nutritional traits.

RESULTS

The SNP markers distinctly separated G. hirsutum from other Gossypium species and distinguished the wild from cultivated types of G. hirsutum. The markers also efficiently discerned differences among cultivars, which was the primary goal when designing the CottonSNP63K array. Population structure within the genus compared favorably with previous results obtained using SSR markers, and an association study identified loci linked to factors that affect cottonseed protein content.

CONCLUSIONS

Our results provide a large genome-wide variation data set for primarily cultivated cotton. Thousands of SNPs in representative cotton genotypes provide an opportunity to finely discriminate among cultivated cotton from around the world. The SNPs will be relevant as dense markers of genome variation for association mapping approaches aimed at correlating molecular polymorphisms with variation in phenotypic traits, as well as for molecular breeding approaches in cotton.

Genome-wide association analysis of secondary imaging phenotypes from the Alzheimer's disease neuroimaging initiative study

The aim of this paper is to systematically evaluate a biased sampling issue associated with genome-wide association analysis (GWAS) of imaging phenotypes for most imaging genetic studies, including the Alzheimer's Disease Neuroimaging Initiative (ADNI). Specifically, the original sampling scheme of these imaging genetic studies is primarily the retrospective case-control design, whereas most existing statistical analyses of these studies ignore such sampling scheme by directly correlating imaging phenotypes (called the secondary traits) with genotype. Although it has been well documented in genetic epidemiology that ignoring the case-control sampling scheme can produce highly biased estimates, and subsequently lead to misleading results and suspicious associations, such findings are not well documented in imaging genetics. We use extensive simulations and a large-scale imaging genetic data analysis of the Alzheimer's Disease Neuroimaging Initiative (ADNI) data to evaluate the effects of the case-control sampling scheme on GWAS results based on some standard statistical methods, such as linear regression methods, while comparing it with several advanced statistical methods that appropriately adjust for the case-control sampling scheme.

Genome-wide association for milk production and female fertility traits in Canadian dairy Holstein cattle

BACKGROUND

Genome-wide association studies (GWAS) are a powerful tool for detecting genomic regions explaining variation in phenotype. The objectives of the present study were to identify or refine the positions of genomic regions affecting milk production, milk components and fertility traits in Canadian Holstein cattle, and to use these positions to identify genes and pathways that may influence these traits.

RESULT

Several QTL regions were detected for milk production (MILK), fat production (FAT), protein production (PROT) and fat and protein deviation (FATD, PROTD respectively). The identified QTL regions for production traits (including milk production) support previous findings and some overlap with genes with known relevant biological functions identified in earlier studies such as DGAT1 and CPSF1. A significant region on chromosome 21 overlapping with the gene FAM181A and not previous linked to fertility in dairy cattle was identified for the calving to first service interval and days open. A functional enrichment analysis of the GWAS results yielded GO terms consistent with the specific phenotypes tested, for example GO terms GO:0007595 (lactation) and GO:0043627 (response to estrogen) for milk production (MILK), GO:0051057 (positive regulation of small GTPase mediated signal transduction) for fat production (FAT), GO:0040019 (positive regulation of embryonic development) for first service to calving interval (CTFS) and GO:0043268 (positive regulation of potassium ion transport) for days open (DO). In other cases the connection between the enriched GO terms and the traits were less clear, for example GO:0003279 (cardiac septum development) for FAT and GO:0030903 (notochord development) for DO trait.

CONCLUSION

The chromosomal regions and enriched pathways identified in this study confirm several previous findings and highlight new regions and pathways that may contribute to variation in production or fertility traits in dairy cattle.