Reducing GWAS Complexity

Rethinking GWAS: how lessons from genetic screens and artificial intelligence could reveal biological mechanisms

MOTIVATION

Modern single-cell omics data are key to unraveling the complex mechanisms underlying risk for complex diseases revealed by genome-wide association studies (GWAS). Phenotypic screens in model organisms have several important parallels to GWAS which the author explores in this essay.

RESULTS

The author provides the historical context of such screens, comparing and contrasting similarities to association studies, and how these screens in model organisms can teach us what to look for. Then the author considers how the results of GWAS might be exhaustively interrogated to interpret the biological mechanisms underpinning disease processes. Finally, the author proposes a general framework for tackling this problem computationally, and explore the data, mechanisms, and technology (both existing and yet to be invented) that are necessary to complete the task.

AVAILABILITY AND IMPLEMENTATION

There are no data or code associated with this article.

Identifying New Susceptibility Genes of Non-Syndromic Orofacial Cleft Based on Syndromes Accompanied With Craniosynostosis

OBJECTIVES

Orofacial cleft (OC) can be classified into syndromic orofacial cleft (SOC) and non-syndromic orofacial cleft (NSOC), depending on whether there are other congenital deformities. Craniosynostosis, the premature closure of cranial sutures, is a common phenotype of SOC resulting in abnormal ossification of skull and brain development disorders. Its correlation with OC offers a promising approach to identify susceptibility genes for NSOC by examining causative genes of SOCs with craniosynostosis.

MATERIALS AND METHODS

This study included 2556 patients with NSOC and 2255 normal controls from western Han Chinese with their genomic DNA samples. We selected 31 causative genes of 34 syndromes with both craniosynostosis and OC as candidate genes and performed quality control. Allelic and genotypic association analyses and haplotype analysis were performed to identify statistically significant single nucleotide polymorphisms (SNPs).

RESULTS

In allelic association analysis performed with 1265 qualified SNPs in 20 genes, only rs2239936, located in MYH3 gene, was statistically associated with non-syndromic cleft lip only (NSCLO) (P = 1.70×10-07, OR = 1.33, 95%CI: 1.17-1.52) and non-syndromic cleft palate only (NSCPO) (P = 6.43×10-05, OR = 1.33, 95%CI: 1.16-1.52). The higher frequency of allele G in NSCPO suggesting that minor allele G at rs2239936 will result in an elevated risk of NSCPO. However, rs2239936 only exhibited a statistical association with NSCPO in genotypic association analysis (P = 8.06×10-06) and haplotype analysis (P = 1.43×10-05).

CONCLUSION

This study identified that allele G at rs2239936 in MYH3 gene was significantly associated with NSCPO as a risk factor and MYH3 was a new susceptibility gene for NSCPO in western Han Chinese population.

Genome-wide association studies are enriched for interacting genes

BACKGROUND

With recent advances in single cell technology, high-throughput methods provide unique insight into disease mechanisms and more importantly, cell type origin. Here, we used multi-omics data to understand how genetic variants from genome-wide association studies influence development of disease. We show in principle how to use genetic algorithms with normal, matching pairs of single-nucleus RNA- and ATAC-seq, genome annotations, and protein-protein interaction data to describe the genes and cell types collectively and their contribution to increased risk.

RESULTS

We used genetic algorithms to measure fitness of gene-cell set proposals against a series of objective functions that capture data and annotations. The highest information objective function captured protein-protein interactions. We observed significantly greater fitness scores and subgraph sizes in foreground vs. matching sets of control variants. Furthermore, our model reliably identified known targets and ligand-receptor pairs, consistent with prior studies.

CONCLUSIONS

Our findings suggested that application of genetic algorithms to association studies can generate a coherent cellular model of risk from a set of susceptibility variants. Further, we showed, using breast cancer as an example, that such variants have a greater number of physical interactions than expected due to chance.

Genome wide association studies are enriched for interacting genes

Background

With recent advances in single cell technology, high-throughput methods provide unique insight into disease mechanisms and more importantly, cell type origin. Here, we used multi-omics data to understand how genetic variants from genome-wide association studies influence development of disease. We show in principle how to use genetic algorithms with normal, matching pairs of single-nucleus RNA- and ATAC-seq, genome annotations, and protein-protein interaction data to describe the genes and cell types collectively and their contribution to increased risk.

Results

We used genetic algorithms to measure fitness of gene-cell set proposals against a series of objective functions that capture data and annotations. The highest information objective function captured protein-protein interactions. We observed significantly greater fitness scores and subgraph sizes in foreground vs.matching sets of control variants. Furthermore, our model reliably identified known targets and ligand-receptor pairs, consistent with prior studies.

Conclusions

Our findings suggested that application of genetic algorithms to association studies can generate a coherent cellular model of risk from a set of susceptibility variants. Further, we showed, using breast cancer as an example, that such variants have a greater number of physical interactions than expected due to chance.

MotifbreakR v2: extended capability and database integration

MotifbreakR is a software tool that scans genetic variants against position weight matrices of transcription factors (TF) to determine the potential for the disruption of TF binding at the site of the variant. It leverages the Bioconductor suite of software packages and annotations to operate across a diverse array of genomes and motif databases. Initially developed to interrogate the effect of single nucleotide variants (common and rare SNVs) on potential TF binding sites, in motifbreakR v2, we have updated the functionality. New features include the ability to query other types of more complex genetic variants, such as short insertions and deletions (indels). This function allows modeling a more extensive array of variants that may have more significant effects on TF binding. Additionally, while TF binding is based partly on sequence preference, predictions of TF binding based on sequence preference alone can indicate many more potential binding events than observed. Adding information from DNA-binding sequencing datasets lends confidence to motif disruption prediction by demonstrating TF binding in cell lines and tissue types. Therefore, motifbreakR implements querying the ReMap2022 database for evidence that a TF matching the disrupted motif binds over the disrupting variant. Finally, in motifbreakR, in addition to the existing interface, we have implemented an R/Shiny graphical user interface to simplify and enhance access to researchers with different skill sets.

Investigating the genetic determination of duration-of-fertility trait in breeding hens

The duration-of-fertility (DF), which was defined as the number of days when breeding hens lay fertile eggs following copulation or artificial insemination (AI), is an important economic trait in chick production when it has strong effects on fertile egg output and production costs. Little is known about the underlying genes and molecular markers related to DF trait to date. Here, we measured the DF of 701 Chinese Jinghong hens and 408 Jingfen hens. The DF showed high individual variability and potential for genetic improvement. Then, 192 Jinghong breeding hens were provided for a genome-wide association study, 27 SNPs respectively located in three genomic linkage regions (GGA1:41Kb; GGA3:39Kb and GGA8:39Kb) were suggested to be significantly associated with DF. Particularly, 6 of these 27 SNPs were further verified to be associated with DF in the 701 Jinghong and 408 Jingfen hens using PCR-RFLP genotyping method. These 27 SNPs were also mapped to 7 genes according to their genomic position. Furtherly, 5 of these 7 genes were tested using qPCR. Results show that the CYP2D6, WBP2NL, ESR1 and TGFBR3 mRNA expression levels of hens with long DF were significantly higher than the hens with short DF (P < 0.05). Overall, findings in our research provide new insight into the genetic basis of duration-of-fertility in breeding hens while providing new clues for further functional validation on the DF-related genetic regulation mechanism and improvement of DF through chicken breeding.

Reviewing the essential roles of remote phenotyping, GWAS and explainable AI in practical marker-assisted selection for drought-tolerant winter wheat breeding

Marker-assisted selection (MAS) plays a crucial role in crop breeding improving the speed and precision of conventional breeding programmes by quickly and reliably identifying and selecting plants with desired traits. However, the efficacy of MAS depends on several prerequisites, with precise phenotyping being a key aspect of any plant breeding programme. Recent advancements in high-throughput remote phenotyping, facilitated by unmanned aerial vehicles coupled to machine learning, offer a non-destructive and efficient alternative to traditional, time-consuming, and labour-intensive methods. Furthermore, MAS relies on knowledge of marker-trait associations, commonly obtained through genome-wide association studies (GWAS), to understand complex traits such as drought tolerance, including yield components and phenology. However, GWAS has limitations that artificial intelligence (AI) has been shown to partially overcome. Additionally, AI and its explainable variants, which ensure transparency and interpretability, are increasingly being used as recognised problem-solving tools throughout the breeding process. Given these rapid technological advancements, this review provides an overview of state-of-the-art methods and processes underlying each MAS, from phenotyping, genotyping and association analyses to the integration of explainable AI along the entire workflow. In this context, we specifically address the challenges and importance of breeding winter wheat for greater drought tolerance with stable yields, as regional droughts during critical developmental stages pose a threat to winter wheat production. Finally, we explore the transition from scientific progress to practical implementation and discuss ways to bridge the gap between cutting-edge developments and breeders, expediting MAS-based winter wheat breeding for drought tolerance.

Polymorphism in the 5' regulatory region of CTNNB1 gene and association with age at first lay and egg production

1. The Wnt signalling pathway is centred on the fact that catenin beta-1(CTNNB1) participates in the regulation of ovarian follicle development. The aim of the following study was to identify the polymorphism in the 5' regulatory region of the chicken CTNNB1 gene and evaluate the association between SNPs and egg production traits.2. The study demonstrated that the 5' regulatory region of the CTNNB1 gene has ten SNPs in the chicken flock. After Bonferroni correction for multiple testing, five SNPs (rs315692306, 2:g43385123, rs735854102, 2:g43385457 and rs737907370) were significantly correlated with egg laying traits.3. An association study of the haplotypes with egg laying traits revealed that both haplotypes in block 1 (consisting of rs735052881, rs740662190, rs315692306, and 2:43385123) and block 2 (consisting of rs735854102 and 2:g43385457) were associated with point of lay age and the number of eggs laid at 18-23 weeks. Prediction of transcription factor binding sites showed that transcription factors changed after mutation in block 2. The luciferase assay revealed that the priming activity of the CA haplotype in block2 was the highest.4. Taken together, the rs315692306, 2:g43385123, rs735854102, 2:g43385457 and rs737907370 in the 5' regulatory region of the CTNNB1 gene have significant impacts on egg production.

A Single-Step Genome Wide Association Study on Body Size Traits Using Imputation-Based Whole-Genome Sequence Data in Yorkshire Pigs

The body shape of a pig is the most direct production index, which can fully reflect the pig’s growth status and is closely related to important economic traits. In this study, a genome-wide association study on seven body size traits, the body length (BL), height (BH), chest circumference (CC), abdominal circumference (AC), cannon bone circumference (CBC), rump width (RW), and chest width (CW), were conducted in Yorkshire pigs. Illumina Porcine 80K SNP chips were used to genotype 589 of 5,572 Yorkshire pigs with body size records, and then the chip data was imputed to sequencing data. After quality control of imputed sequencing data, 784,267 SNPs were obtained, and the averaged linkage disequilibrium (r²) was 0.191. We used the single-trait model and the two-trait model to conduct single-step genome wide association study (ssGWAS) on seven body size traits; a total of 198 significant SNPS were finally identified according to the P-value and the contribution to the genetic variance of individual SNP. 11 candidate genes (CDH13, SIL1, CDC14A, TMRPSS15, TRAPPC9, CTNND2, KDM6B, CHD3, MUC13, MAPK4, and HMGA1) were found to be associated with body size traits in pigs; KDM6B and CHD3 jointly affect AC and CC, and MUC13 jointly affect RW and CW. These genes are involved in the regulation of bone growth and development as well as the absorption of nutrients and are associated with obesity. HMGA1 is proposed as a strong candidate gene for body size traits because of its important function and high consistency with other studies regarding the regulation of body size traits. Our results could provide valuable information for pig breeding based on molecular breeding.

Novel Biomarkers in the Diagnosis of Benign and Malignant Gastrointestinal Diseases

BACKGROUND

Various noninvasive biomarkers have been used in the diagnosis, prognosis, and treatment of different gastrointestinal (GI) diseases for years. Novel technological developments and profound perception of molecular processes related to GI diseases over the last decade have allowed researchers to evaluate genetic, epigenetic, and many other potential molecular biomarkers in different diseases and clinical settings. Here, we present a review of recent and most relevant articles in order to summarize major findings on novel biomarkers in the diagnosis of benign and malignant GI diseases.

SUMMARY

Genetic variations, noncoding RNAs (ncRNAs), cell-free DNA (cfDNA), and microbiome-based biomarkers have been extensively analyzed as potential biomarkers in benign and malignant GI diseases. Multiple single-nucleotide polymorphisms have been linked with a number of GI diseases, and these observations are further being used to build up disease-specific genetic risk scores. Micro-RNAs and long ncRNAs have a large potential as noninvasive biomarkers in the management of inflammatory bowel diseases and GI tumors. Altered microbiome profiles were observed in multiple GI diseases, but most of the findings still lack translational clinical application. As of today, cfDNA appears to be the most potent biomarker for early detection and screening of GI cancers. Key Messages: Novel noninvasive molecular biomarkers show huge potential as useful tools in the diagnostics and management of different GI diseases. However, the use of these biomarkers in real-life clinical practice still remains limited, and further large studies are needed to elucidate the ultimate role of these potential noninvasive clinical tools.

Post-GWAS knowledge gap: the how, where, and when

Genetic risk for complex diseases very rarely reflects only Mendelian-inherited phenotypes where single-gene mutations can be followed in families by linkage analysis. More commonly, a large set of low-penetrance, small effect-size variants combine to confer risk; they are normally revealed in genome-wide association studies (GWAS), which compare large population groups. Whereas Mendelian inheritance points toward disease mechanisms arising from the mutated genes, in the case of GWAS signals, the effector proteins and even general risk mechanism are mostly unknown. Instead, the utility of GWAS currently lies primarily in predictive and diagnostic information. Although an amazing body of GWAS-based knowledge now exists, we advocate for more funding towards the exploration of the fundamental biology in post-GWAS studies; this research will bring us closer to causality and risk gene identification. Using Parkinson's Disease as an example, we ask, how, where, and when do risk loci contribute to disease?

A genome-wide single nucleotide polymorphism scan reveals genetic markers associated with fertility rate in Chinese Jing Hong chicken

The function of the sperm storage tubules is directly correlated with the fertility of laying hens. However, little is known about the molecular mechanisms regulating the fertility traits in chicken. To identify genetic markers associated with reproductive traits, we calculated fertility rate at 61 to 69 wk (51 D) of Jing Hong chickens parent generation as the phenotype and the genotype were detected by the chicken 600K Affymetrix Axiom High Density single nucleotide polymorphisms (SNP)-array. The genome-wide association study using 190 Jing Hong hens showed that the 20 SNP in chromosomes 3 and 13 were significantly associated with fertility rate. To verify these results, a total of 1900 Jing Hong laying hens from 2 populations (P1 and P2) were further genotyped by polymerase chain reaction-restriction fragments length polymorphisms method. The association analysis results revealed that 12 polymorphisms (AX-75769978, AX-76582632, AX-75730546, AX-75730496, AX-75730588, AX-76530282, AX-76530329, AX-76529310, AX-75769906, AX-75755394, AX-80813697 and AX-76582809) out of 20 showed highly significant effects (P < 0.0001) on fertility rate in P1, P2 and P1+P2. Six haplotypes (TTAA, TTGG, TTAG, CTAA, CTGG, and CTAG) were inferred based on significant loci (AX-75730546 and AX-76530282) also showed significant association with fertility rate, where haplotype CTAG was shown to be markedly associated with the significantly highest (P < 0.0001) fertility rate (in P1, 86.42 ± 0.59; P2, 85.98 ± 0.59 and P1+P2, 86.16 ± 0.42) followed by other haplotypes for the irrespective of population studied. Collectively, we report for the first time that 12 SNP in the chromosomes 3 and 13 were significantly associated with fertility rate during the later stage of egg production, which could be used as the potential genetic markers that would be able to facilitate in the selection and improvement of fertility rate through chicken breeding.

Whole genome sequencing of orofacial cleft trios from the Gabriella Miller Kids First Pediatric Research Consortium identifies a new locus on chromosome 21

Orofacial clefts (OFCs) are among the most prevalent craniofacial birth defects worldwide and create a significant public health burden. The majority of OFCs are non-syndromic, and the genetic etiology of non-syndromic OFCs is only partially determined. Here, we analyze whole genome sequence (WGS) data for association with risk of OFCs in European and Colombian families selected from a multicenter family-based OFC study. This is the first large-scale WGS study of OFC in parent-offspring trios, and a part of the Gabriella Miller Kids First Pediatric Research Program created for the study of childhood cancers and structural birth defects. WGS provides deeper and more specific genetic data than using imputation on present-day single nucleotide polymorphic (SNP) marker panels. Genotypes of case-parent trios at single nucleotide variants (SNV) and short insertions and deletions (indels) spanning the entire genome were called from their sequences using human GRCh38 genome assembly, and analyzed for association using the transmission disequilibrium test. Among genome-wide significant associations, we identified a new locus on chromosome 21 in Colombian families, not previously observed in other larger OFC samples of Latin American ancestry. This locus is situated within a region known to be expressed during craniofacial development. Based on deeper investigation of this locus, we concluded that it contributed risk for OFCs exclusively in the Colombians. This study reinforces the ancestry differences seen in the genetic etiology of OFCs, and underscores the need for larger samples when studying for OFCs and other birth defects in populations with diverse ancestry.

Potential regulatory SNPs in the ATXN7L3B and KRT15 genes are associated with gender-specific colorectal cancer risk

Aim: According to the current data, a major factor for phenotypic variation of complex traits and disease susceptibility is the cis-acting effects of noncoding variants on gene expression. Our purpose was to evaluate the association between colorectal cancer (CRC) and six single nucleotide polymorphisms identified using our original bioinformatics approach as regulatory and putatively related to CRC. Materials: One hundred and sixty CRC patients and 185 healthy controls have been genotyped for rs590352, rs2072580, rs78317230, rs3829202, rs11542583 and rs4796672. Results: Genotypes and alleles distributions of rs590352 of ATXN7L3B gene were significantly different between the male CRC subjects and controls. Significant correlation of genotype with CRC is observable for women only for the rs4796672 of KRT15 gene. Analysis of haplotypes reveals that rs2072580 of the ISCU and SART3 genes can be also associated with CRC. Conclusion: We have identified three SNPs associated with CRC risk and demonstrated a gender specificity of rs590352 and rs4796672.

The Five Dimensions of Parkinson's Disease Genetic Risk

Genome-wide association studies of Parkinson's disease have revealed polymorphic variants associated with closely mapped genes of interest. We propose here that those genes may only represent the tip of an iceberg of regulatory effects and do not necessary reflect disease relevance. To usefully interpret a risk locus, one needs to consider 5 dimensions of information, which represent the three-dimensional structure of chromatin (dimensions #1- 3), which is locally variable across time (dimension #4), and, most importantly, dependent on cell type and context (dimension #5).

Novel Polymorphisms in RAPGEF6 Gene Associated with Egg-Laying Rate in Chinese Jing Hong Chicken using Genome-Wide SNP Scan

The improvement of egg production is of vital importance in the chicken industry to maintain optimum output throughout the laying period. Because of the elongation of the egg-laying cycle, a drop in egg-laying rates in the late laying period has provoked great concern in the poultry industry. In this study, we calculated the egg-laying rate at weeks 61–69 (60 days) of Jing Hong chickens parent generation as the phenotype, and the genotype were detected by the chicken 600K Affymetrix Axiom High Density (HD) Single Nucleotide Polymorphisms (SNP)-array. The Genome-Wide Association Study (GWAS) result showed that the egg production trait is significantly associated with five SNPs (AX-75745366, AX-75745380, AX-75745340, AX-75745388, and AX-75745341), which are in the rap guanine nucleotide exchange factor 6 (RAPGEF6) gene on chicken chromosome 13. A total of 1676 Chinese commercial Jing Hong laying hens—including two populations, P1 population (858 hens) and P2 population (818 hens)—were genotyped using the Polymerase Chain Reaction-Restriction Fragments Length Polymorphisms (PCR-RFLP) method for the association analysis of egg-laying rates for the verification of the GWAS results. Genotypic and allelic frequencies of five SNPs were inconsistent with Hardy–Weinberg equilibrium, and the average population genetics parameters considering all the SNP values; i.e., gene homozygosity (Ho), gene heterozygosity (He), the effective number of alleles (Ne), and the polymorphism information content (PIC) were 0.75, 0.25, 1.40, and 0.20 in P1; 0.71, 0.29, 1.46, and 0.24 in P2; and 0.73, 0.27, 1.43, and 0.22 in P1 + P2 populations, respectively. The association analysis results revealed that out of the five polymorphisms, three of them (AX-75745366, AX-75745340, and AX-75745341; Patent applying No: 201810428916.5) had highly significant effects on egg-laying rates according to the GWAS results. Population-specific association analyses also showed similar significant association effects with this trait. Four haplotypes (AAGG, AAAG, AGGG, and AGAG) were inferred based on significant loci (AX-75745340 and AX-75745341) and also showed significant associations with the egg-laying rate, where haplotype AAGG had the highest egg-laying rate, with the exception of the egg-laying rate in P1 population, followed by other haplotypes. Furthermore, genotypes TT, AA, and GG showed the highest egg-laying rate compared to the corresponding genotypes at AX-75745366, AX-75745340, and AX-75745341 SNP loci in P1+P2, respectively. A similar result was found in the population-specific analysis except for the P1 population, in which TC genotype showed the highest egg-laying rate. No significant association was found in the egg-laying rate during the 60 days laying period for the SNPs (AX-75745380 and AX-75745388) in any group of population (p ≥ 0.05). Collectively, we report for the first time that 3 SNPs in the RAPGEF6 gene were significantly associated with the egg-laying rate during the later stage of egg production, which could be used as the potential candidate molecular genetic markers that would be able to facilitate in the selection and improvement of egg production traits through chicken breeding.

Single nucleotide polymorphisms in candidate genes are significantly associated with resistance to Haemonchus contortus infection in goats

BACKGROUND

Haemonchosis is a major economic problem in goat production in humid, tropical and subtropical regions. The disease is caused by an abomasal nematode, Haemonchus contortus, which is highly pathogenic in small ruminants. The aim of this study was to identifying single-nucleotide polymorphisms (SNP) that were associated with fecal egg counts (FEC) and could be used as markers to identify resistance to H. contortus in goats.

RESULTS

Ten novel variants in the CIITA, ATP2A3, HSPA8, STAT5B, ESYT1, and SERPING1 genes were associated with FEC in goats with a nominal significance level of P < 0.05. Two missense mutation in the exon region of the caprine CIITA gene resulted in replacement of arginine with cysteine at position 9473550 (R9473550C) and aspartic acid with glutamic acid at position 9473870 (D9473870E). Chinese goat breeds had significantly higher FEC than Bangladeshi goat breeds within their respective genotypes. Polymorphism information content (PIC), effective allele number (Ne), and heterozygosity (He) were greatest for the STAT5B_197_A > G SNP locus in all goat breeds. Pairwise coefficients of linkage disequilibrium (D´, r 2) revealed complete LD (r 2 = 1) between significant SNP polymorphisms in CIITA and SERPING1 and strong LD (r 2 = 0.93 and 0.98) between polymorphisms in HSPA8 and ATP2A3, respectively. Correlation coefficient (r) between FEC and body weight (BW) was significantly positive (r = 0.56***, P < 0.001) but that between FEC and packed cell volume (PCV) was negatively significant (r = - 0.47**, P < 0.01) in the total population of goats. On the other hand, correlation coefficient (r) between BW and PCV was not significant in total population of goats. Association analysis revealed that haplotypes within ATP2A3, HSPA8, and SERPING1 were significantly associated with FEC. Quantitative real-time PCR revealed that the relative expression of mRNA was higher (P < 0.001) for resistant, compared to susceptible, groups of goats for all candidate genes except CIITA.

CONCLUSIONS

This study identified SNP markers that can potentially be used in marker-assisted selection programs to develop goat breeds that are resistant to H. contortus.

CRISPR-mediated deletion of prostate cancer risk-associated CTCF loop anchors identifies repressive chromatin loops

BACKGROUND

Recent genome-wide association studies (GWAS) have identified more than 100 loci associated with increased risk of prostate cancer, most of which are in non-coding regions of the genome. Understanding the function of these non-coding risk loci is critical to elucidate the genetic susceptibility to prostate cancer.

RESULTS

We generate genome-wide regulatory element maps and performed genome-wide chromosome confirmation capture assays (in situ Hi-C) in normal and tumorigenic prostate cells. Using this information, we annotate the regulatory potential of 2,181 fine-mapped prostate cancer risk-associated SNPs and predict a set of target genes that are regulated by prostate cancer risk-related H3K27Ac-mediated loops. We next identify prostate cancer risk-associated CTCF sites involved in long-range chromatin loops. We use CRISPR-mediated deletion to remove prostate cancer risk-associated CTCF anchor regions and the CTCF anchor regions looped to the prostate cancer risk-associated CTCF sites, and we observe up to 100-fold increases in expression of genes within the loops when the prostate cancer risk-associated CTCF anchor regions are deleted.

CONCLUSIONS

We identify GWAS risk loci involved in long-range loops that function to repress gene expression within chromatin loops. Our studies provide new insights into the genetic susceptibility to prostate cancer.

The genetic component of preeclampsia: A whole-exome sequencing study

Preeclampsia is a major cause of maternal and perinatal deaths. The aetiology of preeclampsia is largely unknown but a polygenetic component is assumed. To explore this hypothesis, we performed an in-depth whole-exome sequencing study in women with (cases, N = 50) and without (controls, N = 50) preeclampsia. The women were identified in an unselected cohort of 2,545 pregnant women based on data from the Danish National Patient Registry and the Medical Birth Registry. Matching DNA was obtained from a biobank containing excess blood from routine antenatal care visits. Novogene performed the whole-exome sequencing blinded to preeclampsia status. Variants for comparison between cases and controls were filtered in the Ingenuity Variant Analysis software. We applied two different strategies; a disease association panel approach, which included variants in single genes associated with established clinical risk factors for preeclampsia, and a gene panel approach, which included biological pathways harbouring genes previously reported to be associated with preeclampsia. Variant variability was compared in cases and controls at the level of biological processes, signalling pathways, and in single genes. Regardless of the applied strategy and the level of variability examined, we consistently found positive correlations between variant numbers in cases and controls (all R²s>0.88). Contrary to what was expected, cases carried fewer variants in biological processes and signalling pathways than controls (all p-values ≤0.02). In conclusion, our findings challenge the hypothesis of a polygenetic aetiology for preeclampsia with a common network of susceptibility genes. The greater genetic diversity among controls may suggest a protective role of genetic diversity against the development of preeclampsia.

Novel approach to functional SNPs discovery from genome-wide data reveals promising variants for colon cancer risk

In the majority of colorectal cancer (CRC) cases, the genetic basis of predisposition remains unexplained. The goal of the study was to assess the regulatory SNPs (rSNPs) in the human genome and to reveal СRC drivers based on the available chromatin immunoprecipitation sequencing (ChIP-Seq, ChIA-PET) and transcriptional profiling (RNA-Seq) data. We combined positional (locations within genome regulatory elements) and functional (associated with allele-specific binding and expression) criteria followed by an analysis using genome-wide association studies (GWAS) and minor allele frequency (MAF) datasets. DeSeq2 analysis through 70 CRC patients reinforced the regulatory potential. rSNPs (1,476) that were associated with significant (P < 0.01) allele-specific events resulting in thirty that exhibited a link with CRC according to the MAF and 27, with a risk of malignancy in general according to GWAS. Selected rSNPs may modify the expression of genes for tumor suppressors and the regulators of signaling pathways, including noncoding RNAs. However, the rSNPs from the most represented group affect the expression of genes related to splicing. Our findings strongly suggest that the identified variants might contribute to CRC susceptibility, which indicates that aberrant splicing is one of the key mechanisms for unraveling disease etiopathogenesis and provides useful inputs for interpreting how genotypic variation corresponds to phenotypic outcome.

Insertion/Deletion Within the KDM6A Gene Is Significantly Associated With Litter Size in Goat

A previous whole-genome association analysis identified lysine demethylase 6A (KDM6A), which encodes a type of histone demethylase, as a candidate gene associated to goat fecundity. KDM6A gene knockout mouse disrupts gametophyte development, suggesting that it has a critical role in reproduction. In this study, goat KDM6A mRNA expression profiles were determined, insertion/deletion (indel) variants in the gene identified, indel variants effect on KDM6A gene expression assessed, and their association with first-born litter size analyzed in 2326 healthy female Shaanbei white cashmere goats. KDM6A mRNA was expressed in all tissues tested (heart, liver, spleen, lung, kidney, muscle, brain, skin and testis); the expression levels in testes at different developmental stages [1-week-old (wk), 2, 3 wk, 1-month-old (mo), 1.5 and 2 mo] indicated a potential association with the mitosis-to-meiosis transition, implying that KDM6A may have an essential role in goat fertility. Meanwhile, two novel intronic indels of 16 bp and 5 bp were identified. Statistical analysis revealed that only the 16 bp indel was associated with first-born litter size (P < 0.01), and the average first-born litter size of individuals with an insertion/insertion genotype higher than that of those with the deletion/deletion genotype (P < 0.05). There was also a significant difference in genotype distributions of the 16 bp indel between mothers of single-lamb and multi-lamb litters in the studied goat population (P = 0.001). Consistently, the 16 bp indel also had a significant effect on KDM6A gene expression. Additionally, there was no significant linkage disequilibrium (LD) between these two indel loci, consistent with the association analysis results. Together, these findings suggest that the 16 bp indel in KDM6A may be useful for marker-assisted selection (MAS) of goats.