High-resolution haplotype structure in the human genome

Capitalizing on genebank core collections for rare and novel disease resistance loci to enhance barley resilience

In the realm of agricultural sustainability, the utilization of plant genetic resources for enhanced disease resistance is paramount. Preservation efforts in genebanks are justified by their potential contributions to future crop improvement. To capitalize on the potential of plant genetic resources, we focused on a barley core collection from the German ex situ genebank and contrasted it with a European elite collection. The phenotypic assessment included 812 plant genetic resources and 298 elites, with a particular emphasis on four disease traits (Puccinia hordei, Blumeria graminis hordei, Ramularia collo-cygni, and Rhynchosporium commune). An integrated genome-wide association study, employing both Bayesian-information and linkage-disequilibrium iteratively nested keyway (BLINK) and a linear mixed model, was performed to unravel the genetic underpinnings of disease resistance. A total of 932 marker-trait associations were identified and assigned to 49 quantitative trait loci. The accumulation of novel and rare resistance alleles significantly bolstered the overall resistance level in plant genetic resources. Three plant genetic resources donors with high counts of novel/rare alleles and exhibiting exceptional resistance to leaf rust and powdery mildew were identified, offering promise for targeted pre-breeding goals and enhanced resilience in future varieties. Our findings underscore the critical contribution of plant genetic resources to strengthening crop resilience and advancing sustainable agricultural practices.

Haplotype-based breeding: A new insight in crop improvement

Haplotype-based breeding (HBB) is one of the cutting-edge technologies in the realm of crop improvement due to the increasing availability of Single Nucleotide Polymorphisms identified by Next Generation Sequencing technologies. The complexity of the data can be decreased with fewer statistical tests and a lower probability of spurious associations by combining thousands of SNPs into a few hundred haplotype blocks. The presence of strong genomic regions in breeding lines of most crop species facilitates the use of haplotypes to improve the efficiency of genomic and marker-assisted selection. Haplotype-based breeding as a Genomic Assisted Breeding (GAB) approach harnesses the genome sequence data to pinpoint the allelic variation used to hasten the breeding cycle and circumvent the challenges associated with linkage drag. This review article demonstrates ways to identify candidate genes, superior haplotype identification, haplo-pheno analysis, and haplotype-based marker-assisted selection. The crop improvement strategies that utilize superior haplotypes will hasten the breeding progress to safeguard global food security.

A fine-scale genetic map of the Japanese population

Genetic maps are fundamental resources for linkage and association studies. A fine-scale genetic map can be constructed by inferring historical recombination events from the genome-wide structure of linkage disequilibrium-a non-random association of alleles among loci-by using population-scale sequencing data. We constructed a fine-scale genetic map and identified recombination hotspots from 10 092 551 bi-allelic high-quality autosomal markers segregating among 150 unrelated Japanese individuals whose genotypes were determined by high-coverage (30×) whole-genome sequencing, and the genotype quality was carefully controlled by using their parents' and offspring's genotypes. The pedigree information was also utilized for haplotype phasing. The resulting genome-wide recombination rate profiles were concordant with those of the worldwide population on a broad scale, and the resolution was much improved. We identified 9487 recombination hotspots and confirmed the enrichment of previously known motifs in the hotspots. Moreover, we demonstrated that the Japanese genetic map improved the haplotype phasing and genotype imputation accuracy for the Japanese population. The construction of a population-specific genetic map will help make genetics research more accurate.

Estimating Haplotype Structure and Frequencies: A Bayesian Approach to Unknown Design in Pooled Genomic Data

The estimation of haplotype structure and frequencies provides crucial information about the composition of genomes. Techniques, such as single-individual haplotyping, aim to reconstruct individual haplotypes from diploid genome sequencing data. However, our focus is distinct. We address the challenge of reconstructing haplotype structure and frequencies from pooled sequencing samples where multiple individuals are sequenced simultaneously. A frequentist method to address this issue has recently been proposed. In contrast to this and other methods that compute point estimates, our proposed Bayesian hierarchical model delivers a posterior that permits us to also quantify uncertainty. Since matching permutations in both haplotype structure and corresponding frequency matrix lead to the same reconstruction of their product, we introduce an order-preserving shrinkage prior that ensures identifiability with respect to permutations. For inference, we introduce a blocked Gibbs sampler that enforces the required constraints. In a simulation study, we assessed the performance of our method. Furthermore, by using our approach on two distinct sets of real data, we demonstrate that our Bayesian approach can reconstruct the dominant haplotypes in a challenging, high-dimensional set-up.

Disparities in ABO blood type determination across diverse ancestries: a systematic review and validation in the All of Us Research Program

OBJECTIVES

ABO blood types have widespread clinical use and robust associations with disease. The purpose of this study is to evaluate the portability and suitability of tag single-nucleotide polymorphisms (tSNPs) used to determine ABO alleles and blood types across diverse populations in published literature.

MATERIALS AND METHODS

Bibliographic databases were searched for studies using tSNPs to determine ABO alleles. We calculated linkage between tSNPs and functional variants across inferred continental ancestry groups from 1000 Genomes. We compared r2 across ancestry and assessed real-world consequences by comparing tSNP-derived blood types to serology in a diverse population from the All of Us Research Program.

RESULTS

Linkage between functional variants and O allele tSNPs was significantly lower in African (median r2 = 0.443) compared to East Asian (r2 = 0.946, P = 1.1 × 10-5) and European (r2 = 0.869, P = .023) populations. In All of Us, discordance between tSNP-derived blood types and serology was high across all SNPs in African ancestry individuals and linkage was strongly correlated with discordance across all ancestries (ρ = -0.90, P = 3.08 × 10-23).

DISCUSSION

Many studies determine ABO blood types using tSNPs. However, tSNPs with low linkage disequilibrium promote misinference of ABO blood types, particularly in diverse populations. We observe common use of inappropriate tSNPs to determine ABO blood type, particularly for O alleles and with some tSNPs mistyping up to 58% of individuals.

CONCLUSION

Our results highlight the lack of transferability of tSNPs across ancestries and potential exacerbation of disparities in genomic research for underrepresented populations. This is especially relevant as more diverse cohorts are made publicly available.

Haplotype blocks for genomic prediction: a comparative evaluation in multiple crop datasets

In modern plant breeding, genomic selection is becoming the gold standard for selection of superior genotypes. The basis for genomic prediction models is a set of phenotyped lines along with their genotypic profile. With high marker density and linkage disequilibrium (LD) between markers, genotype data in breeding populations tends to exhibit considerable redundancy. Therefore, interest is growing in the use of haplotype blocks to overcome redundancy by summarizing co-inherited features. Moreover, haplotype blocks can help to capture local epistasis caused by interacting loci. Here, we compared genomic prediction methods that either used single SNPs or haplotype blocks with regards to their prediction accuracy for important traits in crop datasets. We used four published datasets from canola, maize, wheat and soybean. Different approaches to construct haplotype blocks were compared, including blocks based on LD, physical distance, number of adjacent markers and the algorithms implemented in the software "Haploview" and "HaploBlocker". The tested prediction methods included Genomic Best Linear Unbiased Prediction (GBLUP), Extended GBLUP to account for additive by additive epistasis (EGBLUP), Bayesian LASSO and Reproducing Kernel Hilbert Space (RKHS) regression. We found improved prediction accuracy in some traits when using haplotype blocks compared to SNP-based predictions, however the magnitude of improvement was very trait- and model-specific. Especially in settings with low marker density, haplotype blocks can improve genomic prediction accuracy. In most cases, physically large haplotype blocks yielded a strong decrease in prediction accuracy. Especially when prediction accuracy varies greatly across different prediction models, prediction based on haplotype blocks can improve prediction accuracy of underperforming models. However, there is no "best" method to build haplotype blocks, since prediction accuracy varied considerably across methods and traits. Hence, criteria used to define haplotype blocks should not be viewed as fixed biological parameters, but rather as hyperparameters that need to be adjusted for every dataset.

MIR31HG, a potential lncRNA in human cancers and non-cancers

Long non-coding RNAs have recently attracted considerable attention due to their aberrant expression in human diseases. LncMIR31HG is a novel lncRNA that is abnormally expressed in multiple diseases and implicated in various stages of disease progression. A large proportion of recent studies have indicated that MIR31HG has biological functions by triggering various signalling pathways in the pathogenesis of human diseases, especially cancers. More importantly, the abnormal expression of MIR31HG makes it a potential biomarker in diagnosis and prognosis, as well as a promising target for treatments. This review aims to systematically summarize the gene polymorphism, expression profiles, biological roles, underlying mechanisms, and clinical applications of MIR31HG in human diseases.

Pairwise comparative analysis of six haplotype assembly methods based on users' experience

BACKGROUND

A haplotype is a set of DNA variants inherited together from one parent or chromosome. Haplotype information is useful for studying genetic variation and disease association. Haplotype assembly (HA) is a process of obtaining haplotypes using DNA sequencing data. Currently, there are many HA methods with their own strengths and weaknesses. This study focused on comparing six HA methods or algorithms: HapCUT2, MixSIH, PEATH, WhatsHap, SDhaP, and MAtCHap using two NA12878 datasets named hg19 and hg38. The 6 HA algorithms were run on chromosome 10 of these two datasets, each with 3 filtering levels based on sequencing depth (DP1, DP15, and DP30). Their outputs were then compared.

RESULT

Run time (CPU time) was compared to assess the efficiency of 6 HA methods. HapCUT2 was the fastest HA for 6 datasets, with run time consistently under 2 min. In addition, WhatsHap was relatively fast, and its run time was 21 min or less for all 6 datasets. The other 4 HA algorithms' run time varied across different datasets and coverage levels. To assess their accuracy, pairwise comparisons were conducted for each pair of the six packages by generating their disagreement rates for both haplotype blocks and Single Nucleotide Variants (SNVs). The authors also compared them using switch distance (error), i.e., the number of positions where two chromosomes of a certain phase must be switched to match with the known haplotype. HapCUT2, PEATH, MixSIH, and MAtCHap generated output files with similar numbers of blocks and SNVs, and they had relatively similar performance. WhatsHap generated a much larger number of SNVs in the hg19 DP1 output, which caused it to have high disagreement percentages with other methods. However, for the hg38 data, WhatsHap had similar performance as the other 4 algorithms, except SDhaP. The comparison analysis showed that SDhaP had a much larger disagreement rate when it was compared with the other algorithms in all 6 datasets.

CONCLUSION

The comparative analysis is important because each algorithm is different. The findings of this study provide a deeper understanding of the performance of currently available HA algorithms and useful input for other users.

Translating non-coding genetic associations into a better understanding of immune-mediated disease

Genome-wide association studies have identified hundreds of genetic loci that are associated with immune-mediated diseases. Most disease-associated variants are non-coding, and a large proportion of these variants lie within enhancers. As a result, there is a pressing need to understand how common genetic variation might affect enhancer function and thereby contribute to immune-mediated (and other) diseases. In this Review, we first describe statistical and experimental methods to identify causal genetic variants that modulate gene expression, including statistical fine-mapping and massively parallel reporter assays. We then discuss approaches to characterise the mechanisms by which these variants modulate immune function, such as clustered regularly interspaced short palindromic repeats (CRISPR)-based screens. We highlight examples of studies that, by elucidating the effects of disease variants within enhancers, have provided important insights into immune function and uncovered key pathways of disease.

Genomic prediction of carcass traits using different haplotype block partitioning methods in beef cattle

Genomic prediction (GP) based on haplotype alleles can capture quantitative trait loci (QTL) effects and increase predictive ability because the haplotypes are expected to be in linkage disequilibrium (LD) with QTL. In this study, we constructed haploblocks using LD-based and the fixed number of single nucleotide polymorphisms (fixed-SNP) methods with Illumina BovineHD chip in beef cattle. To evaluate the performance of different haplotype block partitioning methods, we constructed haploblocks based on LD thresholds (from r 2 > 0.2 to r 2 > 0.8) and the number of fixed-SNPs (5, 10, 20). The performance of predictive methods for three carcass traits including liveweight (LW), dressing percentage (DP), and longissimus dorsi muscle weight (LDMW) was evaluated using three approaches (GBLUP and BayesB model based on the SNP, GHBLUP, and BayesBH models based on the haploblock, and GHBLUP+GBLUP and BayesBH+BayesB models based on the combined haploblock and the nonblocked SNPs, which were located between blocks). In this study, we found the accuracies of LD-based and fixed-SNP haplotype Bayesian methods outperformed the Bayesian models (up to 8.54 ± 7.44% and 5.74 ± 2.95%, respectively). GHBLUP showed a high improvement (up to 11.29 ± 9.87%) compared with GBLUP. The Bayesian models have higher accuracies than BLUP models in most scenarios. The average computing time of the BayesBH+BayesB model can reduce by 29.3% compared with the BayesB model. The prediction accuracies using the LD-based haplotype method showed higher improvements than the fixed-SNP haplotype method. In addition, to avoid the influence of rare haplotypes generated from haplotype construction, we compared the performance of GP by filtering four types of minor haplotype allele frequency (MHAF) (0.01, 0.025, 0.05, and 0.1) under different conditions (LD levels were set at r 2 > 0.3, and the fixed number of SNPs was 5). We found the optimal MHAF threshold for LW was 0.01, and the optimal MHAF threshold for DP and LDMW was 0.025.

Failing the four-gamete test enables exact phasing: the Corners’ Algorithm

Background

Failing the four-gamete test for two polymorphic DNA markers is an indication that two or three rather than four haplotypes segregate in the population. The objective of this paper is to show that when just three haplotypes are segregating, all three haplotypes can be fully and unambiguously phase-resolved.

Theory and methods

The Corners’ Algorithm tests the four corners in a 3 × 3 table of two-locus genotypes. If one of the four corners is filled with zeroes, then the missing haplotype is identified and the phases of all three haplotypes can be unambiguously resolved for all individuals. Three applications of this method are proposed when the four-gamete test fails: (1) direct estimation of linkage disequilibrium (LD), (2) haplotype-based genome-wide association studies (GWAS) of three haplotypes (single-marker GWAS tests for two out of three haplotypes only), and (3) haplotyping of chromosomal regions that are comprised of pairs of single nucleotide polymorphisms (SNPs) that consist of just three haplotypes. An example based on 435 sows with performance records for total number of piglets born is used to illustrate the methods.

Results

Of 20,339 SNPs, approximately 50% of the pairs of flanking SNPs failed the four-gamete test. For those, the expectation maximization (EM) algorithm gave the same results. The average of the absolute value of the difference in r2 between flanking SNPs across the genome between the two methods was 0.00082. Single-marker GWAS (using two of three haplotypes) detected significant associations for total number of piglets born on chromosomes 1, 2, 6, 9, 10, 12, 13, 14, 15, and 18. Haplotype-based GWAS using the third haplotype resolved with the Corners’ Algorithm detected additional significant associations for total number of piglets born on chromosomes 2, 5, 10, 13, 14, 15, and 18. Estimated substitution effects ranged from 0.40 to 1.35 piglets. Haplotyping of chromosomal regions that failed the four-gamete test for any pair of SNPs covered 961 Mb out of the 2249 Mb by the SNP array.

Conclusions

The Corner’s Algorithm allows to fully phase haplotypes when the four-gamete test fails. Longer haplotypes in chromosomal regions in which the four-gamete test fails for any pair of SNPs can be used as a multi-allelic marker with increased polymorphism information content.

Genetic regulation of newborn telomere length is mediated and modified by DNA methylation

Telomere length at birth determines later life telomere length and potentially predicts ageing-related diseases. However, the genetic and epigenetic settings of telomere length in newborns have not been analyzed. In addition, no study yet has reported how the interplay between genetic variants and genome-wide cytosine methylation explains the variation in early-life telomere length. In this study based on 281 mother-newborn pairs from the ENVIRONAGE birth cohort, telomere length and whole-genome DNA methylation were assessed in cord blood and 26 candidate single nucleotide polymorphism related to ageing or telomere length were genotyped. We identified three genetic variants associated with cord blood telomere length and 57 cis methylation quantitative trait loci (cis-mQTLs) of which 22 mQTLs confirmed previous findings and 35 were newly identified. Five SNPs were found to have significant indirect effects on cord blood telomere length via the mediating CpGs. The association between rs911874 (SOD2) and newborn telomere length was modified by nearby DNA methylation indicated by a significant statistical interaction. Our results suggest that DNA methylation in cis might have a mediation or modification effect on the genetic difference in newborn telomere length. This novel approach warrants future follow-up studies that are needed to further confirm and extend these findings.

Updated Genome-Wide Association Study of Intracranial Aneurysms by Genotype Correction and Imputation in Koreans

OBJECTIVE

Compared to European, Japanese, and Chinese populations, genetic studies on intracranial aneurysms (IAs) in Koreans are lacking. We conducted an updated genome-wide association study (GWAS) to more accurately identify candidate variations predicting IA by genotype correction and imputation than in the first Korean GWAS.

METHODS

We performed a high-throughput imputation of single-nucleotide polymorphisms (SNPs) and genotype missing values for 250 IA and 296 controls. Out of a total of 7,333,746 sites with an imputation R² score of ≥0.5, 6,105,212 SNPs were analyzed. A high-throughput GWAS was performed after adjusting for clinical variables and 4 principal component analysis values.

RESULTS

A total of 39 SNPs reached a significant genome-wide threshold (P < 5 × 10^-8). After pruning by pairwise linkage disequilibrium (r² < 0.8), 11 SNPs were consistently associated with IA. Six tagging SNPs, including rs3120004, rs1851347, rs1522095, rs7779989, rs12935558, rs3826442, and rs2440154, showed strong linkage disequilibrium tower tagging haplotype structures. Among them, rs3120004 tagged a large and strong haplotype structure between LOC440704 and RGS18 genes in 1q31.2 (odds ratio, 2.34; 95% confidence interval, 1.74-3.14; P = 1.4 × 10^-8). The rs2440154 (SLC47A1, 17p11.2) SNP increased the risk of IA most significantly (odds ratio, 2.90; 95% confidence interval, 2.07-4.08; P = 8.2 × 10^-10). The region encompassing rs3826442 (MYH13, 17p13.1) showed a high recombination rate of approximately 70 cM/Mbp.

CONCLUSIONS

Our updated GWAS using high-throughput imputation approaches can be an informative milestone in understanding IA formation via susceptibility loci in this stage before large-scale genome-wide association meta-analysis.

Analysis of protein kinase C (HcPKC) gene expression and single-nucleotide polymorphisms related to inner shell color traits in Hyriopsis cumingii

Background

Protein kinase C (PKC) is a multifunctional serine and PKC can phosphorylate serine residues in the cytoplasmic domain of tyrosinase, thereby regulating the activity of tyrosinase. Activated PKC is bound to the melanosome membrane, and unactivated PKC is free in the cytoplasm of melanocytes. In this study, we study the role of PKC gene in the melanin synthesis pathway and its effect on the color of the nacre of H. cumingii.

Results

In this study, a HcPKC gene in H. cumingii was cloned and its effects on melanin synthesis and nacre color were studied. HcPKC was expressed in both purple and white mussels, and the level of mRNA expression was higher in the purple mussels than in white mussels. Strong and specific mRNA signals were detected in the dorsal epithelial cells of the mantle pallial layer, indicating that HcPKC may be involved in nacre formation. After SNP association with inner shell color related traits, according to the principle that 0.25 < PIC < 0.5 is medium polymorphism and PIC < 0.25 is low polymorphism, the A + 332G site on the HcPKC gene was a site of moderate polymorphism, and the other four sites were low polymorphism sex sites. There was strong linkage disequilibrium among the five loci. A haplotype was constructed and it was found that the frequency of T1 (AGGAA)in the white population was significantly higher than that in the purple population (P < 0.05).

Conclusion

The study found that HcPKC of H. cumingii can be used as a candidate gene related to inner shell color, and some of the SNP sites can be used for molecular-assisted breeding in the spinnaker mussel, providing a reference for cultivating high-quality freshwater pearls.

Informative SNP Selection Based on a Fuzzy Clustering and Improved Binary Particle Swarm Optimization Algorithm

Single-nucleotide polymorphism (SNP) involves the replacement of a single nucleotide in a deoxyribonucleic acid (DNA) sequence and is often linked to the development of specific diseases. Although current genotyping methods can tag SNP loci within biological samples to provide accurate genetic information for a disease associated, they have limited prediction accuracy. Furthermore, they are complex to perform and may result in the prediction of an excessive number of tag SNP loci, which may not always be associated with the disease. Therefore in this manuscript, we aimed to evaluate the impact of a newly optimized fuzzy clustering and binary particle swarm optimization algorithm (FCBPSO) on the accuracy and running time of informative SNP selection. Fuzzy clustering and FCBPSO were first applied to identify the equivalence relation and the candidate tag SNP set to reduce the redundancy between loci. The FCBPSO algorithm was then optimized and used to obtain the final tag SNP set. The prediction performance and running time of the newly developed model were compared with other traditional methods, including NMC, SPSO, and MCMR. The prediction accuracy of the FCBPSO algorithm was always higher than that of the other algorithms especially as the number of tag SNPs increased. However, when the number of tag SNPs was low, the prediction accuracy of FCBPSO was slightly lower than that of MCMR (add prediction accuracy values for each algorithm). However, the running time of the FCBPSO algorithm was always lower than that of MCMR. FCBPSO not only reduced the size and dimension of the optimization problem but also simplified the training of the prediction model. This improved the prediction accuracy of the model and reduced the running time when compared with other traditional methods.

Association between MIR31HG polymorphisms and the risk of Lumbar disc herniation in Chinese Han population

Lumbar disc herniation (LDH) is a common spinal disease that endangers human health. Genetic factors play a vital role in the progression of LDH. This study aimed to explore the relationship of the MIR31HG polymorphism with LDH risk in the Chinese population. Seven candidate SNPs on MIR31HG in 504 patients with LDH and 503 healthy people were genotyped by Agena MassARRAY platform. Logistic regression was used to calculate the relationship between MIR31HG polymorphism and LDH risk under different genetic models. Multi-factor dimensionality reduction (MDR) analysis was performed to evaluate the SNP-SNP interaction. We found that rs10965059 was significantly associated with a decreased risk of LDH under the dominant (OR = 0.46, 95% CI: 0.34-0.62, P < 0.001), log-additive (OR = 0.59, 95%CI: 0.45-0.76, P < 0.001), and codominant (OR = 0.40, 95%CI: 0.29-0.55, P < 0.001) models in the overall analysis. In the subgroup analyses of age, male, and complications, we found that rs10965059 was associated with a reduced risk of LDH. However, there was no significant correlation between MiR-31HG polymorphisms and risk of LDH in females. In addition, the three SNPs (rs72703442-rs2025327-rs55683539) was mapped to a 26kb LD block with D' >0.96, suggesting a significant linkage disequilibrium presence among each pair SNPs. MDR analysis showed that the best single-locus and multi-locus models for the prediction of LDH risk were rs10965059 and seven-locus models, respectively, and both of them increased LDH risk. Our results shown that in the Chinese Han population, the MIR31HG polymorphism rs10965059 was involved in a risk to symptomatic LDH, which provides a scientific basis for early screening, prevention, diagnosis and treatment of local LDH high-risk populations.

Recombination in Positive-Strand RNA Viruses

RNA recombination is a major driver of genetic shifts tightly linked to the evolution of RNA viruses. Genomic recombination contributes substantially to the emergence of new viral lineages, expansion in host tropism, adaptations to new environments, and virulence and pathogenesis. Here, we review some of the recent progress that has advanced our understanding of recombination in positive-strand RNA viruses, including recombination triggers and the mechanisms behind them. The study of RNA recombination aids in predicting the probability and outcome of viral recombination events, and in the design of viruses with reduced recombination frequency as candidates for the development of live attenuated vaccines. Surveillance of viral recombination should remain a priority in the detection of emergent viral strains, a goal that can only be accomplished by expanding our understanding of how these events are triggered and regulated.

Development and Utilization of Functional Kompetitive Allele-Specific PCR Markers for Key Genes Underpinning Fiber Length and Strength in Gossypium hirsutum L

Fiber length (FL) and fiber strength (FS) are the important indicators of fiber quality in cotton. Longer and stronger fibers are preferred for manufacturing finer yarns in the textile industry. Functional markers (FMs) designed from polymorphic sites within gene sequences attributing to phenotypic variation are highly efficient when used for marker-assisted selection (MAS) in breeding superior varieties with longer FL and higher FS. The aims of this study were to develop FMs via kompetitive allele-specific PCR (KASP) assays and to validate the efficacy of the FMs for allele discrimination and the potential value in practice application. We used four single-nucleotide polymorphism markers and 360 cotton accessions and found that two FMs, namely, D11_24030087 and A07_72204443, could effectively differentiate accessions of different genotypes with higher consistency to phenotype. The appeared frequencies of varieties harbored Hap2 (elite alleles G and T) with longer FL (> the mean of accessions with non-elite allele, 28.50 mm) and higher FS (> the mean of accessions with non-elite allele, 29.06 cN•tex-1) were 100 and 72.7%, respectively, which was higher than that of varieties harbored only on a single elite allele (G or T, 77.9 or 61.9%), suggesting a favorable haplotype for selecting varieties with superior FL and FS. These FMs could be valuable for the high-throughput selection of superior materials by providing genotypic information in cotton breeding programs.

Tools in Pharmacogenomics Biomarker Identification for Cancer Patients

The understanding of the biological differences which underlie the inter-individual variability in drug response improved the efficacy of cancer therapy in the era of precision medicine. In fact molecularly targeted drugs and immunotherapy represent a revolution in cancer treatment. The identification of genetic predictive and/or prognostic biomarkers linked to drug pharmacokinetics (PK) and pharmacodynamics (PD) is allowed by the development of high-throughput omics tools for detecting and understanding biological differences among individuals, in order to improve drug efficacy and minimize risk of toxicity. Personalized medicine in cancer treatment reduces costs of the healthcare system. Unfortunately, pharmacogenomics biomarkers discovery is influenced by complexity, need of high-quality evidence, and a validation process for regulatory purposes. This chapter is focused on the critic analysis of presently available pharmacogenomics tools for discovering or testing genetic polymorphic variants in drug metabolizing enzyme to be introduced in clinical practice for the prospective stratification of cancer patients.

Genetic diversity in the stress regulatory gene LUMAN/CREB3 of Yorkshire and Meishan pigs

A candidate-gene high-density single-nucleotide polymorphism (SNP) scanning approach was used to investigate the swine LUMAN/CREB3 locus for polymorphisms in 232 Ontario Yorkshire and 29 Chinese Meishan pigs. Inter- and intra-breed differences in genetic diversity were characterized. In the Yorkshire breed, eight variations (three coding and five non-coding) were identified. Two linkage disequilibrium (LD) blocks (550 bp and ∼4 kb in length) featuring two and three haplotypes, respectively, were reconstructed. In the Meishan breed, six variations (two coding and four non-coding) and one LD block (∼3 kb in length) with three haplotypes were detected. This investigation may provide insight into variable stress responsiveness among pigs.

Paving the path toward genomic privacy with secure imputation

Ensuring the privacy of participants in genomic studies is a critical responsibility of the biomedical community. Accurate and efficient implementations of secure genotype imputation highlight practical approaches to safeguard sensitive genomic data that can be adapted for numerous bioinformatics applications.

PATRIOT: A Pipeline for Tracing Identity-by-Descent for Chromosome Segments to Improve Genomic Prediction in Self-Pollinating Crop Species

The lowering genotyping cost is ushering in a wider interest and adoption of genomic prediction and selection in plant breeding programs worldwide. However, improper conflation of historical and recent linkage disequilibrium between markers and genes restricts high accuracy of genomic prediction (GP). Multiple ancestors may share a common haplotype surrounding a gene, without sharing the same allele of that gene. This prevents parsing out genetic effects associated with the underlying allele of that gene among the set of ancestral haplotypes. We present "Parental Allele Tracing, Recombination Identification, and Optimal predicTion" (i.e., PATRIOT) approach that utilizes marker data to allow for a rapid identification of lines carrying specific alleles, increases the accuracy of genomic relatedness and diversity estimates, and improves genomic prediction. Leveraging identity-by-descent relationships, PATRIOT showed an improvement in GP accuracy by 16.6% relative to the traditional rrBLUP method. This approach will help to increase the rate of genetic gain and allow available information to be more effectively utilized within breeding programs.

A Functional Variant of CXCL16 Is Associated With Predisposition to Sepsis and MODS in Trauma Patients: Genetic Association Studies

PURPOSE

CXC chemokines are mediators which mediate immune cells migration to sites of inflammation and injury. Chemokine C-X-C motif ligand 16 (CXCL16) plays an important role in the occurrence and development of sepsis through leukocyte chemotaxis, leukocyte adhesion and endotoxin clearance. In this study, we selected a set of tagging single nucleotide polymorphisms (tag SNPs) in the CXCL16 gene and investigated their clinical relevance to the development of sepsis and multiple organ dysfunction syndrome (MODS) in patients with major trauma in three independent Chinese Han populations.

METHODS

A total of 1,620 major trauma patients were enrolled in this study. Among these patients, 920 came from Chongqing in western China, 350 came from Zhejiang Province in eastern China, and 350 came from Guizhou Province in southwestern China. The improved multiplex ligation detection reaction (iMLDR) method was employed in the genotyping and genetic association analyses to determine the associations between CXCL16 haplotypes and sepsis morbidity rate and higher MOD scores in three cohorts.

RESULTS

Only CXCL16 T123V181 haplotype was associated with an increased risk for sepsis morbidity and higher MOD scores in the three cohorts (OR = 1.89, P = 0.001 for the Chongqing cohort; OR = 1.76, P = 0.004 for the Zhejiang cohort; OR = 1.55, P = 0.012 for the Guizhou cohort). The effect of T123V181 haplotype on the chemotaxis, migration and endotoxin clearance of immune cells were further observed. Protein modeling analysis showed that T123 and V181 might alter the structure of the CXCL16 active center. Thus it enhanced the chemotaxis and adhesion ability of immunocytes.

CONCLUSION

We demonstrate the mechanism of CXCL16 T123V181 haplotype which regulates the sepsis morbidity rate and thus provide a new biomarker for early diagnosis of sepsis and MODS.

CLINICAL TRIAL REGISTRATION

www.ClinicalTrials.gov, identifier NCT01713205 (https://www.clinicaltrials.gov/ct2/results?cond=&term=+NCT01713205&cntry=&state=&city=&dist=).

PIP-SNP: a pipeline for processing SNP data featured as linkage disequilibrium bin mapping, genotype imputing and marker synthesizing

Genome-wide association study data analyses often face two significant challenges: (i) high dimensionality of single-nucleotide polymorphism (SNP) genotypes and (ii) imputation of missing values. SNPs are not independent due to physical linkage and natural selection. The correlation of nearby SNPs is known as linkage disequilibrium (LD), which can be used for LD conceptual SNP bin mapping, missing genotype inferencing and SNP dimension reduction. We used a stochastic process to describe the SNP signals and proposed two types of autocorrelations to measure nearby SNPs' information redundancy. Based on the calculated autocorrelation coefficients, we constructed LD bins. We adopted a k-nearest neighbors algorithm (kNN) to impute the missing genotypes. We proposed several novel methods to find the optimal synthetic marker to represent the SNP bin. We also proposed methods to evaluate the information loss or information conservation between using the original genome-wide markers and using dimension-reduced synthetic markers. Our performance assessments on the real-life SNP data from a rice recombinant inbred line (RIL) population and a rice HapMap project show that the new methods produce satisfactory results. We implemented these functional modules in C/C++ and streamlined them into a web-based pipeline named PIP-SNP (https://bioinfo.noble.org/PIP_SNP/) for processing SNP data.

TreeMap: a structured approach to fine mapping of eQTL variants

Motivation

Expression quantitative trait loci (eQTL) harbor genetic variants modulating gene transcription. Fine mapping of regulatory variants at these loci is a daunting task due to the juxtaposition of causal and linked variants at a locus as well as the likelihood of interactions among multiple variants. This problem is exacerbated in genes with multiple cis-acting eQTL, where superimposed effects of adjacent loci further distort the association signals.

Results

We developed a novel algorithm, TreeMap, that identifies putative causal variants in cis-eQTL accounting for multisite effects and genetic linkage at a locus. Guided by the hierarchical structure of linkage disequilibrium, TreeMap performs an organized search for individual and multiple causal variants. Via extensive simulations, we show that TreeMap detects co-regulating variants more accurately than current methods. Furthermore, its high computational efficiency enables genome-wide analysis of long-range eQTL. We applied TreeMap to GTEx data of brain hippocampus samples and transverse colon samples to search for eQTL in gene bodies and in 4 Mbps gene-flanking regions, discovering numerous distal eQTL. Furthermore, we found concordant distal eQTL that were present in both brain and colon samples, implying long-range regulation of gene expression.

Availability and implementation

TreeMap is available as an R package enabled for parallel processing at https://github.com/liliulab/treemap.

Supplementary information

Supplementary data are available at Bioinformatics online.

Recombination frequencies of human leukocyte antigen loci in hematological malignancies among Turkish population

INTRODUCTION

Allogeneic hematopoietic stem cell transplantation (HSCT) is a treatment option with growing performance for leukaemia, aplastic anaemia and genetic disorders. The frequency of MHC (Major Histocompatibility Complex) gene locus recombination is increased at loci close to the telomeres and in the female gender. The aim of the present study is to document the recombination events by pedigree diagrams with the primary goal to determine the frequency of recombination in a different ethnic population from mostly reported studies.

METHODS

Altogether 9545 allogeneic HSCT recipients and their family-based potential donors (n:36231) were included in this retrospective study.

RESULTS

Recombinations were determined in 118 (F/M:50/68) out of 9545 families enrolled on the study. These were present in 40 of the patients and 78 of healthy donors. The frequency of recombinations was 0.42% and 0.22%, in patients and donors, respectively. Of the 118 recombinations, 60 were detected in A locus (13 inpatients), 14 in B locus (3 inpatients) and 42 in DR locus (22 inpatients). In our study, due to recombinations in HLA (Human Leukocyte Antigen)-A,-B,-DR loci, we found that some patient-donor pairs became 6/5 matched instead of 6/6 (n:45), eliminating the allogeneic HSCT possibility for the patients from the full-matched siblings.

CONCLUSION

To our knowledge, this is the first study reporting the recombination frequencies in HLA loci among Turkish population and thus, providing informative data to the clinicians regarding the cross-over possibilities in Turkish patients with haematological malignancies.

Dissecting polygenic signals from genome-wide association studies on human behaviour

Genome-wide association studies on human behavioural traits are producing large amounts of polygenic signals with significant predictive power and potentially useful biological clues. Behavioural traits are more distal and are less directly under biological control compared with physical characteristics, which makes the associated genetic effects harder to interpret. The results of genome-wide association studies for human behaviour are likely made up of a composite of signals from different sources. While sample sizes continue to increase, we outline additional steps that need to be taken to better delineate the origin of the increasingly stronger polygenic signals. In addition to genetic effects on the traits themselves, the major sources of polygenic signals are those that are associated with correlated traits, environmental effects and ascertainment bias. Advances in statistical approaches that disentangle polygenic effects from different traits as well as extending data collection to families and social circles with better geographical coverage will probably contribute to filling the gap of knowledge between genetic effects and behavioural outcomes.

Haplotype Shuffling and Dimorphic Transposable Elements in the Human Extended Major Histocompatibility Complex Class II Region

The major histocompatibility complex (MHC) on chromosome 6p21 is one of the most single-nucleotide polymorphism (SNP)-dense regions of the human genome and a prime model for the study and understanding of conserved sequence polymorphisms and structural diversity of ancestral haplotypes/conserved extended haplotypes. This study aimed to follow up on a previous analysis of the MHC class I region by using the same set of 95 MHC haplotype sequences downloaded from a publicly available BioProject database at the National Center for Biotechnology Information to identify and characterize the polymorphic human leukocyte antigen (HLA)-class II genes, the MTCO3P1 pseudogene alleles, the indels of transposable elements as haplotypic lineage markers, and SNP-density crossover (XO) loci at haplotype junctions in DNA sequence alignments of different haplotypes across the extended class II region (∼1 Mb) from the telomeric PRRT1 gene in class III to the COL11A2 gene at the centromeric end of class II. We identified 42 haplotypic indels (20 Alu, 7 SVA, 13 LTR or MERs, and 2 indels composed of a mosaic of different transposable elements) linked to particular HLA-class II alleles. Comparative sequence analyses of 136 haplotype pairs revealed 98 unique XO sites between SNP-poor and SNP-rich genomic segments with considerable haplotype shuffling located in the proximity of putative recombination hotspots. The majority of XO sites occurred across various regions including in the vicinity of MTCO3P1 between HLA-DQB1 and HLA-DQB3, between HLA-DQB2 and HLA-DOB, between DOB and TAP2, and between HLA-DOA and HLA-DPA1, where most XOs were within a HERVK22 sequence. We also determined the genomic positions of the PRDM9-recombination suppression sequence motif ATCCATG/CATGGAT and the PRDM9 recombination activation partial binding motif CCTCCCCT/AGGGGAG in the class II region of the human reference genome (NC_ 000006) relative to published meiotic recombination positions. Both the recombination and anti-recombination PRDM9 binding motifs were widely distributed throughout the class II genomic regions with 50% or more found within repeat elements; the anti-recombination motifs were found mostly in L1 fragmented repeats. This study shows substantial haplotype shuffling between different polymorphic blocks and confirms the presence of numerous putative ancestral recombination sites across the class II region between various HLA class II genes.

Determination of complete chromosomal haplotypes by bulk DNA sequencing

Haplotype phase represents the collective genetic variation between homologous chromosomes and is an essential feature of non-haploid genomes. Here we describe a computational strategy to reliably determine complete whole-chromosome haplotypes using a combination of bulk long-range sequencing and Hi-C sequencing. We demonstrate that this strategy can resolve the haplotypes of parental chromosomes in diploid human genomes with high precision (>99%) and completeness (>98%) and assemble the syntenic structure of rearranged chromosomes in aneuploid cancer genomes at base pair level resolution. Our work enables direct interrogation of chromosome-specific alterations and chromatin reorganization using bulk DNA sequencing.

Analysis of Brugada syndrome loci reveals that fine-mapping clustered GWAS hits enhances the annotation of disease-relevant variants

Genome-wide association studies (GWASs) are instrumental in identifying loci harboring common single-nucleotide variants (SNVs) that affect human traits and diseases. GWAS hits emerge in clusters, but the focus is often on the most significant hit in each trait- or disease-associated locus. The remaining hits represent SNVs in linkage disequilibrium (LD) and are considered redundant and thus frequently marginally reported or exploited. Here, we interrogate the value of integrating the full set of GWAS hits in a locus repeatedly associated with cardiac conduction traits and arrhythmia, SCN5A-SCN10A. Our analysis reveals 5 common 7-SNV haplotypes (Hap1-5) with 2 combinations associated with life-threatening arrhythmia-Brugada syndrome (the risk Hap1/1 and protective Hap2/3 genotypes). Hap1 and Hap2 share 3 SNVs; thus, this analysis suggests that assuming redundancy among clustered GWAS hits can lead to confounding disease-risk associations and supports the need to deconstruct GWAS data in the context of haplotype composition.

Functional genomics and epigenomics of atrial fibrillation

Atrial fibrillation is a progressive cardiac arrhythmia that increases the risk of hospitalization and adverse cardiovascular events. Despite years of study, we still do not have a full comprehension of the molecular mechanism responsible for the disease. The recent implementation of large-scale approaches in both patient samples, population studies and animal models has helped us to broaden our knowledge on the molecular drivers responsible for AF and on the mechanisms behind disease progression. Understanding genomic and epigenomic changes that take place during chronification of AF will prove essential to design novel treatments leading to improved patient care.

Interferon Regulatory Factor 5 (IRF5) Gene Haplotypes Are Associated with Premature Coronary Artery Disease. Association of the IRF5 Polymorphisms with Cardiometabolic Parameters. The Genetics of Atherosclerotic Disease (GEA) Mexican Study

Interferon regulatory factor 5 (IRF5) has an important role in the inflammatory process, a fundamental component of coronary artery disease (CAD). Thus, the objective of this study was to evaluate the association of IRF5 polymorphisms with the development of premature CAD (pCAD) and cardiometabolic parameters. IRF5 polymorphisms (rs1874330, rs3778754, rs3757386, rs3757385, rs3807134, rs3807135, and rs6968563) were determined in 1116 pCAD patients and 1003 controls. Polymorphism distribution was similar in patients and controls; however, the haplotype analysis showed five haplotypes with a different distribution. TGCGTCT (OR (odds ratio) = 1.248, p = 0005) and TCTGCCT (OR = 10.73, p < 0.0001) were associated with a high risk, whereas TCCGTCT (OR = 0.155, p < 0.0001), CGCTTTT (OR = 0.108, p < 0.0001), and TCCGCCT (OR = 0.014, p < 0.0001) were associated with a low risk of pCAD. Associations with aspartate aminotransferase, hypertriglyceridemia, magnesium deficiency, triglycerides/HDL-C index, LDL-C, and adiponectin levels were observed in pCAD patients. In controls, associations with hypoalphalipoproteinemia, non-HDL-C, apolipoprotein B, hyperuricemia, TNF-α, IL-6, IL-15, valvular calcification, and subclinical hypothyroidism were observed. In summary, five haplotypes were associated with pCAD, two with high risk and three with low risk. Some IRF5 polymorphisms were associated with cardiometabolic parameters in pCAD patients and control.

The anti-Müllerian hormone gene's second exon is associated with the reproductive performance of Jinghai Yellow chickens

Anti-Müllerian hormone (AMH), a member of the transforming growth factor-β superfamily, plays important regulatory roles in follicular development and sex differentiation. Although much has been learned about the impact of polymorphisms of AMH on reproduction in animals, the effect on chicken reproduction is not well explored. In this study, the polymorphism of five exons of AMH gene and its effect on the reproductive performance of Jinghai Yellow chickens were studied. Primers for the amplification of AMH exons were designed, and Sanger sequencing was performed. Finally, only the polymorphism in the second exon of the AMH gene was found in the present population. Polymorphisms in the second exon of the AMH gene in 246 Jinghai Yellow hens and their associations with reproductive traits were analyzed. In total, four single nucleotide polymorphism (SNP) mutations were detected in the second exon of the AMH gene: g.1868A>C (AA, aa and Aa); g.1883G>A (BB, bb and Bb); g.1987G>A (CC, cc and Cc); and g.1996A>G (DD, dd and Dd). Only the mutation of g.1996A>G affected the reproductive traits: the age of laying first egg (AFE) of dd genotype was significantly (p<0.01) earlier than that in the DD and Dd hens. Moreover, the egg number by 300 d old (EN300) of dd individuals was significantly higher than that of DD and Dd individuals (p<0.01). Thus, we inferred that the dd genotype is the beneficial genotype. Additionally, AFE and EN300 showed significantly better performance in both the H2H2 and H7H7 diplotypes compared with other diplotype individuals (p<0.01). Thus, the H2H2 and H7H7 genotype had the best combination of AFE and EN300. Our study may allow for molecular marker section in poultry breeding.

SNP-Density Crossover Maps of Polymorphic Transposable Elements and HLA Genes Within MHC Class I Haplotype Blocks and Junction

The genomic region (~4 Mb) of the human major histocompatibility complex (MHC) on chromosome 6p21 is a prime model for the study and understanding of conserved polymorphic sequences (CPSs) and structural diversity of ancestral haplotypes (AHs)/conserved extended haplotypes (CEHs). The aim of this study was to use a set of 95 MHC genomic sequences downloaded from a publicly available BioProject database at NCBI to identify and characterise polymorphic human leukocyte antigen (HLA) class I genes and pseudogenes, MICA and MICB, and retroelement indels as haplotypic lineage markers, and single-nucleotide polymorphism (SNP) crossover loci in DNA sequence alignments of different haplotypes across the Olfactory Receptor (OR) gene region (~1.2 Mb) and the MHC class I region (~1.8 Mb) from the GPX5 to the MICB gene. Our comparative sequence analyses confirmed the identity of 12 haplotypic retroelement markers and revealed that they partitioned the HLA-A/B/C haplotypes into distinct evolutionary lineages. Crossovers between SNP-poor and SNP-rich regions defined the sequence range of haplotype blocks, and many of these crossover junctions occurred within particular transposable elements, lncRNA, OR12D2, MUC21, MUC22, PSORS1A3, HLA-C, HLA-B, and MICA. In a comparison of more than 250 paired sequence alignments, at least 38 SNP-density crossover sites were mapped across various regions from GPX5 to MICB. In a homology comparison of 16 different haplotypes, seven CEH/AH (7.1, 8.1, 18.2, 51.x, 57.1, 62.x, and 62.1) had no detectable SNP-density crossover junctions and were SNP poor across the entire ~2.8 Mb of sequence alignments. Of the analyses between different recombinant haplotypes, more than half of them had SNP crossovers within 10 kb of LTR16B/ERV3-16A3_I, MLT1, Charlie, and/or THE1 sequences and were in close vicinity to structurally polymorphic Alu and SVA insertion sites. These studies demonstrate that (1) SNP-density crossovers are associated with putative ancestral recombination sites that are widely spread across the MHC class I genomic region from at least the telomeric OR12D2 gene to the centromeric MICB gene and (2) the genomic sequences of MHC homozygous cell lines are useful for analysing haplotype blocks, ancestral haplotypic landscapes and markers, CPSs, and SNP-density crossover junctions.

High-resolution population-specific recombination rates and their effect on phasing and genotype imputation

Previous research has shown that using population-specific reference panels has a significant effect on downstream population genomic analyses like haplotype phasing, genotype imputation, and association, especially in the context of population isolates. Here, we developed a high-resolution recombination rate mapping at 10 and 50 kb scale using high-coverage (20–30×) whole-genome sequenced data of 55 family trios from Finland and compared it to recombination rates of non-Finnish Europeans (NFE). We tested the downstream effects of the population-specific recombination rates in statistical phasing and genotype imputation in Finns as compared to the same analyses performed by using the NFE-based recombination rates. We found that Finnish recombination rates have a moderately high correlation (Spearman’s ρ = 0.67–0.79) with NFE, although on average (across all autosomal chromosomes), Finnish rates (2.268 ± 0.4209 cM/Mb) are 12–14% lower than NFE (2.641 ± 0.5032 cM/Mb). Finnish recombination map was found to have no significant effect in haplotype phasing accuracy (switch error rates ~2%) and average imputation concordance rates (97–98% for common, 92–96% for low frequency and 78–90% for rare variants). Our results suggest that haplotype phasing and genotype imputation mostly depend on population-specific contexts like appropriate reference panels and their sample size, but not on population-specific recombination maps. Even though recombination rate estimates had some differences between the Finnish and NFE populations, haplotyping and imputation had not been noticeably affected by the recombination map used. Therefore, the currently available HapMap recombination maps seem robust for population-specific phasing and imputation pipelines, even in the context of relatively isolated populations like Finland.

Association of HLA-DQ and IL13 gene variants with challenge-proven shrimp allergy in West Bengal, India

Little is known about genetic factors and mechanisms underlying shrimp allergy. Genome-wide association studies identified HLA class-II and IL13 genes as highly plausible candidates for shrimp allergy. The present study was designed to investigate potential associations of HLA-DQ rs9275596, IL13 rs20541, and IL13 rs1800925 polymorphisms with challenge-proven shrimp allergy using the data from 532 people of West Bengal, India; selected on basis of positive skin prick test, elevated specific IgE and medical history. Risk genotypes, i.e., HLA-DQ rs9275596 CC, IL13 rs20541 AA, and IL13 rs1800925 TT, were found to be significantly associated with challenge positive shrimp allergy (P = 0.04, 0.01, and 0.03, respectively). Distribution of genotypes for HLA-DQ and IL13 polymorphisms in allergic and control subjects showed significant difference between younger (20-40 years) and older (> 40 years) age group (P = 0.006). Risk genotypes significantly associated with elevated shrimp-specific IgE. IL13 TA haplotype significantly associated with shrimp allergy and elevated specific IgE (P = 0.02). Synergistic effect of IL13 TA haplotype-HLA-DQ rs9275596 CC genotype interaction significantly elevated specific IgE (P = 0.03). The present study suggests that HLA-DQ and IL13 polymorphisms pose major risk for shrimp allergic patients in West Bengal, India and thus could be helpful for early target-specific therapeutic intervention in near future.

Genome-wide association study reveals genes associated with the absence of intermuscular bones in tambaqui (Colossoma macropomum)

The presence of intermuscular bones in fisheries products limits the consumption and commercialization potential of many fish species, including tambaqui (Colossoma macropomum). These bones have caused medical emergencies and are an undesirable characteristic for fish farming because their removal is labor-intensive during fish processing. Despite the difficulty in identifying genes related to the lack of intermuscular bone in diverse species of fish, the discovery of individuals lacking intermuscular bones in a Neotropical freshwater characiform fish has provided a unique opportunity to delve into the genetic mechanisms underlying the pathways of intermuscular bone formation. In this study, we carried out a GWAS among boneless and wt tambaqui populations to identify markers associated with a lack of intermuscular bone. After analyzing 11 416 SNPs in 360 individuals (12 boneless and 348 bony), we report 675 significant (P_adj  < 0.003) associations for this trait. Of those, 13 associations were located near candidate genes related to the reduction of bone mass, promotion of bone formation, inhibition of bone resorption, central control of bone remodeling, bone mineralization and other related functions. To the best of our knowledge, for the first time, we have successfully identified genes related to a lack of intermuscular bones using GWAS in a non-model species.

MinProtMaxVP: Generating a minimized number of protein variant sequences containing all possible variant peptides for proteogenomic analysis

Identifying single-amino-acid variants (SAVs) from mass spectrometry-based experiments is critical for validating single-nucleotide variants (SNVs) at the protein level to facilitate biomedical research. Currently, two approaches are usually applied to convert SNV annotations into SAV-harboring protein sequences. One approach generates one sequence containing exactly one SAV, and the other all SAVs. However, they may neglect the possibility of SAV combinations, e.g., haplotypes, existing in bio-samples. Therefore, it is necessary to consider all SAV combinations of a protein when generating SAV-harboring protein sequences. In this paper, we propose MinProtMaxVP, a novel approach which selects a minimized number of SAV-harboring protein sequences generated from the exhaustive approach, while still accommodating all possible variant peptides, by solving a classic set covering problem. Our study on known haplotype variations of TAS2R38 justifies the necessity for MinProtMaxVP to consider all combinations of SAVs. The performance of MinProtMaxVP is demonstrated by an in silico study on OR2T27 with five SAVs and real experimental data of the HEK293 cell line. Furthermore, assuming simulated somatic and germline variants of OR2T27 in tumor and normal tissues demonstrates that when adopting the appropriate somatic and germline SAV integration strategy, MinProtMaxVP is adaptable to labeling and label-free mass spectrometry-based experiments. SIGNIFICANCE: We present MinProtMaxVP, a novel approach to generate SAV-harboring protein sequences for constructing a customized protein sequence database, which is used in database searching for variant peptide identification. This approach outperforms the existing approaches in generating all possible variant peptides to be included in protein sequences and possibly leading to identification of more variant peptides in proteogenomic analysis.

Impact of NR5A2 and RYR2 3'UTR polymorphisms on the risk of breast cancer in a Chinese Han population

OBJECTIVES

The NR5A2 and RYR2 genes are important players in steroid metabolism and play an important role in cancer research. In this research, we want to evaluate the effect of NR5A2 and RYR2 polymorphisms on breast cancer (BC).

METHODS

Four single nucleotide polymorphisms on NR5A2 and RYR2 were selected to genotype by Agena MassARRAY in 379 BC patients and 407 healthy controls. Using the PLINK software to calculate the Odds ratio (OR) and 95% confidence intervals (CIs) via the logistic regression analysis to evaluate the risk for BC.

RESULTS

We found that NR5A2 rs2246209 significantly decreased the risk of BC with the AA genotype (OR 0.58, 95%CI 0.34-0.99, p = 0.049), and recessive model (OR 0.59, 95%CI 0.35-0.99, p = 0.046); rs12594 in the RYR2 gene significantly decreased the risk of BC in the GG genotype (OR 0.44, 95%CI 0.22-0.88, p = 0.020), and recessive model (OR 0.43, 95%CI 0.21-0.85, p = 0.016). Further stratification analysis showed that NR5A2 rs2246209 was related to a lower incidence of BC affected by age, lymph nodes metastasis, and tumor stage; RYR2 rs12594 was related to a decreased BC risk restricted by age, estrogen receptor (ER), progesterone receptor (PR), menopausal status, tumor size, and tumor stage. Rs12594 in the RyR2 gene remained significant on the genetic susceptibility of PR-positive BC after Bonferroni correction (p < 0.0125).

CONCLUSIONS

This study provides an evidence that NR5A2 rs2246209 and RYR2 rs12594 decreased the risk of breast cancer.

Genome-wide association studies of lactation yields of milk, fat, protein and somatic cell score in New Zealand dairy goats

Background

Identifying associations between genetic markers and traits of economic importance will provide practical benefits for the dairy goat industry, enabling genomic prediction of the breeding value of individuals, and facilitating discovery of the underlying genes and mutations. Genome-wide association studies were implemented to detect genetic regions that are significantly associated with effects on lactation yields of milk (MY), fat (FY), protein (PY) and somatic cell score (SCS) in New Zealand dairy goats.

Methods

A total of 4,840 goats were genotyped with the Caprine 50 K SNP chip (Illumina Inc., San Diego, CA). After quality filtering, 3,732 animals and 41,989 SNPs were analysed assuming an additive linear model. Four GWAS models were performed, a single-SNP additive linear model and three multi-SNP BayesC models. For the single-SNP GWAS, SNPs were fitted individually as fixed covariates, while the BayesC models fit all SNPs simultaneously as random effects. A cluster of significant SNPs were used to define a haplotype block whose alleles were fitted as covariates in a Bayesian model. The corresponding diplotypes of the haplotype block were then fit as class variables in another Bayesian model.

Results

Across all four traits, a total of 43 genome-wide significant SNPs were detected from the SNP GWAS. At a genome-wide significance level, the single-SNP analysis identified a cluster of variants on chromosome 19 associated with MY, FY, PY, and another cluster on chromosome 29 associated with SCS. Significant SNPs mapped in introns of candidate genes (45%), in intergenic regions (36%), were 0-5 kb upstream or downstream of the closest gene (14%) or were synonymous substitutions (5%). The most significant genomic window was located on chromosome 19 explaining up to 9.6% of the phenotypic variation for MY, 8.1% for FY, 9.1% for PY and 1% for SCS.

Conclusions

The quantitative trait loci for yield traits on chromosome 19 confirms reported findings in other dairy goat populations. There is benefit to be gained from using these results for genomic selection to improve milk production in New Zealand dairy goats.

Genomic resources for dissecting the role of non-protein coding variation in gene-environment interactions

The majority of single nucleotide variants (SNVs) identified in Genome Wide Association Studies (GWAS) fall within non-protein coding DNA and have the potential to alter gene expression. Non-protein coding DNA can control gene expression by acting as transcription factor (TF) binding sites or by regulating the organization of DNA into chromatin. SNVs in non-coding DNA sequences can disrupt TF binding and chromatin structure and this can result in pathology. Further, environmental health studies have shown that exposure to xenobiotics can disrupt the ability of TFs to regulate entire gene networks and result in pathology. However, there is a large amount of interindividual variability in exposure-linked health outcomes. One explanation for this heterogeneity is that genetic variation and exposure combine to disrupt gene regulation, and this eventually manifests in disease. Many resources exist that annotate common variants from GWAS and combine them with conservation, functional genomics, and TF binding data. These annotation tools provide clues regarding the biological implications of an SNV, as well as lead to the generation of hypotheses regarding potentially disrupted target genes, epigenetic markers, pathways, and cell types. Collectively this information can be used to predict how SNVs can alter an individual's response to exposure and disease risk. A basic understanding of the regulatory information contained within non-protein coding DNA is needed to predict the biological consequences of SNVs, and to determine how these SNVs impact exposure-related disease. We hope that this review will aid in the characterization of disease-associated genetic variation in the non-protein coding genome.

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.

Salt-Inducible Kinase 3 Haplotypes Associated with Noise-Induced Hearing Loss in Chinese Workers

INTRODUCTION

Noise-induced hearing loss (NIHL) is a common occupational disease that represents an irreversible hearing damage to the auditory system. It has been identified as a complicated disease involving both environmental and genetic factors. More efforts need to be made to explore the genes associated with susceptibility to NIHL. The main aim of this research is to detect the associations between SIK3 polymorphisms and NIHL susceptibility in Han people in China.

METHODS

A case-control study was performed in 586 cases and 639 controls in a textile factory matched for sex, age, smoking, drinking, work time with noise, and intensity of noise exposure. Three single nucleotide polymorphisms (SNPs) (rs493134, rs6589574, and rs7121898) of SIK3 were genotyped in the participants. Then, the main influences of the SNPs on and their interactions with NIHL were assessed.

RESULTS

Under the allelic model, distributions of rs493134 T, rs6589574 G, and rs7121898 A in the NIHL group are statistically different from those of the normal group (p = 0.001, p < 0.001, and p = 0.019, respectively). The following haplotype analysis shows that TAA (rs493134-rs6589574-rs7121898) may have a protective effect, while TGA (rs493134-rs6589574-rs7121898) (OR = 1.49, 95% CI = 1.25-1.79) may be a risk factor for NIHL. Multifactor dimensionality reduction analysis shows that the interaction of the 3 selected SNPs is associated with NIHL susceptibility (OR = 1.88, 95% CI = 1.50-2.36).

CONCLUSION

The results suggest that 3 SNPs (rs493134, rs6589574, and rs7121898) of SIK3 may be an important part of NIHL susceptibility and can be applied in the prevention, early diagnosis, and treatment of NIHL in noise-exposed Chinese workers.

A fast-linear mixed model for genome-wide haplotype association analysis: application to agronomic traits in maize

Background

Haplotypes combine the effects of several single nucleotide polymorphisms (SNPs) with high linkage disequilibrium, which benefit the genome-wide association analysis (GWAS). In the haplotype association analysis, both haplotype alleles and blocks are tested. Haplotype alleles can be inferred with the same statistics as SNPs in the linear mixed model, while blocks require the formulation of unified statistics to fit different genetic units, such as SNPs, haplotypes, and copy number variations.

Results

Based on the FaST-LMM, the fastLmPure function in the R/RcppArmadillo package has been introduced to speed up genome-wide regression scans by a re-weighted least square estimation. When large or highly significant blocks are tested based on EMMAX, the genome-wide haplotype association analysis takes only one to two rounds of genome-wide regression scans. With a genomic dataset of 541,595 SNPs from 513 maize inbred lines, 90,770 haplotype blocks were constructed across the whole genome, and three types of markers (SNPs, haplotype alleles, and haplotype blocks) were genome-widely associated with 17 agronomic traits in maize using the software developed here.

Conclusions

Two SNPs were identified for LNAE, four haplotype alleles for TMAL, LNAE, CD, and DTH, and only three blocks reached the significant level for TMAL, CD, and KNPR. Compared to the R/lm function, the computational time was reduced by ~ 10–15 times.

A Rare Variant Nonparametric Linkage Method for Nuclear and Extended Pedigrees with Application to Late-Onset Alzheimer Disease via WGS Data

To analyze family-based whole-genome sequence (WGS) data for complex traits, we developed a rare variant (RV) non-parametric linkage (NPL) analysis method, which has advantages over association methods. The RV-NPL differs from the NPL in that RVs are analyzed, and allele sharing among affected relative-pairs is estimated only for minor alleles. Analyzing families can increase power because causal variants with familial aggregation usually have larger effect sizes than those underlying sporadic diseases. Differing from association analysis, for NPL only affected individuals are analyzed, which can increase power, since unaffected family members can be susceptibility variant carriers. RV-NPL is robust to population substructure and admixture, inclusion of nonpathogenic variants, as well as allelic and locus heterogeneity and can readily be applied outside of coding regions. In contrast to analyzing common variants using NPL, where loci localize to large genomic regions (e.g., >50 Mb), mapped regions are well defined for RV-NPL. Using simulation studies, we demonstrate that RV-NPL is substantially more powerful than applying traditional NPL methods to analyze RVs. The RV-NPL was applied to analyze 107 late-onset Alzheimer disease (LOAD) pedigrees of Caribbean Hispanic and European ancestry with WGS data, and statistically significant linkage (LOD ≥ 3.8) was found with RVs in PSMF1 and PTPN21 which have been shown to be involved in LOAD etiology. Additionally, nominally significant linkage was observed with RVs in ABCA7, ACE, EPHA1, and SORL1, genes that were previously reported to be associated with LOAD. RV-NPL is an ideal method to elucidate the genetic etiology of complex familial diseases.

Genomic diversity, linkage disequilibrium and selection signatures in European local pig breeds assessed with a high density SNP chip

Genetic characterization of local breeds is essential to preserve their genomic variability, to advance conservation policies and to contribute to their promotion and sustainability. Genomic diversity of twenty European local pig breeds and a small sample of Spanish wild pigs was assessed using high density SNP chips. A total of 992 DNA samples were analyzed with the GeneSeek Genomic Profiler (GGP) 70 K HD porcine genotyping chip. Genotype data was employed to compute genetic diversity, population differentiation and structure, genetic distances, linkage disequilibrium and effective population size. Our results point out several breeds, such as Turopolje, Apulo Calabrese, Casertana, Mora Romagnola and Lithuanian indigenous wattle, having the lowest genetic diversity, supported by low heterozygosity and very small effective population size, demonstrating the need of enhanced conservation strategies. Principal components analysis showed the clustering of the individuals of the same breed, with few breeds being clearly isolated from the rest. Several breeds were partially overlapped, suggesting genetic closeness, which was particularly marked in the case of Iberian and Alentejana breeds. Spanish wild boar was also narrowly related to other western populations, in agreement with recurrent admixture between wild and domestic animals. We also searched across the genome for loci under diversifying selection based on F_ST outlier tests. Candidate genes that may underlie differences in adaptation to specific environments and productive systems and phenotypic traits were detected in potentially selected genomic regions.

Exome sequences and multi-environment field trials elucidate the genetic basis of adaptation in barley

Broadening the genetic base of crops is crucial for developing varieties to respond to global agricultural challenges such as climate change. Here, we analysed a diverse panel of 371 domesticated lines of the model crop barley to explore the genetics of crop adaptation. We first collected exome sequence data and phenotypes of key life history traits from contrasting multi-environment common garden trials. Then we applied refined statistical methods, including some based on exomic haplotype states, for genotype-by-environment (G×E) modelling. Sub-populations defined from exomic profiles were coincident with barley's biology, geography and history, and explained a high proportion of trial phenotypic variance. Clear G×E interactions indicated adaptation profiles that varied for landraces and cultivars. Exploration of circadian clock-related genes, associated with the environmentally adaptive days to heading trait (crucial for the crop's spread from the Fertile Crescent), illustrated complexities in G×E effect directions, and the importance of latitudinally based genic context in the expression of large-effect alleles. Our analysis supports a gene-level scientific understanding of crop adaption and leads to practical opportunities for crop improvement, allowing the prioritisation of genomic regions and particular sets of lines for breeding efforts seeking to cope with climate change and other stresses.