Bias of selection on human copy-number variants

Understanding genetic variability: exploring large-scale copy number variants through non-invasive prenatal testing in European populations

Large-scale copy number variants (CNVs) are structural alterations in the genome that involve the duplication or deletion of DNA segments, contributing to genetic diversity and playing a crucial role in the evolution and development of various diseases and disorders, as they can lead to the dosage imbalance of one or more genes. Massively parallel sequencing (MPS) has revolutionized the field of genetic analysis and contributed significantly to routine clinical diagnosis and screening. It offers a precise method for detecting CNVs with exceptional accuracy. In this context, a non-invasive prenatal test (NIPT) based on the sequencing of cell-free DNA (cfDNA) from pregnant women's plasma using a low-coverage whole genome MPS (WGS) approach represents a valuable source for population studies. Here, we analyzed genomic data of 12,732 pregnant women from the Slovak (9,230), Czech (1,583), and Hungarian (1,919) populations. We identified 5,062 CNVs ranging from 200 kbp and described their basic characteristics and differences between the subject populations. Our results suggest that re-analysis of sequencing data from routine WGS assays has the potential to obtain large-scale CNV population frequencies, which are not well known and may provide valuable information to support the classification and interpretation of this type of genetic variation. Furthermore, this could contribute to expanding knowledge about the central European genome without investing in additional laboratory work, as NIPTs are a relatively widely used screening method.

Copy Number Variations in Pancreatic Cancer: From Biological Significance to Clinical Utility

Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer, characterized by high tumor heterogeneity and a poor prognosis. Inter- and intra-tumoral heterogeneity in PDAC is a major obstacle to effective PDAC treatment; therefore, it is highly desirable to explore the tumor heterogeneity and underlying mechanisms for the improvement of PDAC prognosis. Gene copy number variations (CNVs) are increasingly recognized as a common and heritable source of inter-individual variation in genomic sequence. In this review, we outline the origin, main characteristics, and pathological aspects of CNVs. We then describe the occurrence of CNVs in PDAC, including those that have been clearly shown to have a pathogenic role, and further highlight some key examples of their involvement in tumor development and progression. The ability to efficiently identify and analyze CNVs in tumor samples is important to support translational research and foster precision oncology, as copy number variants can be utilized to guide clinical decisions. We provide insights into understanding the CNV landscapes and the role of both somatic and germline CNVs in PDAC, which could lead to significant advances in diagnosis, prognosis, and treatment. Although there has been significant progress in this field, understanding the full contribution of CNVs to the genetic basis of PDAC will require further research, with more accurate CNV assays such as single-cell techniques and larger cohorts than have been performed to date.

ggcoverage: an R package to visualize and annotate genome coverage for various NGS data

BACKGROUND

Visualizing genome coverage is of vital importance to inspect and interpret various next-generation sequencing (NGS) data. Besides genome coverage, genome annotations are also crucial in the visualization. While different NGS data require different annotations, how to visualize genome coverage and add the annotations appropriately and conveniently is challenging. Many tools have been developed to address this issue. However, existing tools are often inflexible, complicated, lack necessary preprocessing steps and annotations, and the figures generated support limited customization.

RESULTS

Here, we introduce ggcoverage, an R package to visualize and annotate genome coverage of multi-groups and multi-omics. The input files for ggcoverage can be in BAM, BigWig, BedGraph and TSV formats. For better usability, ggcoverage provides reliable and efficient ways to perform read normalization, consensus peaks generation and track data loading with state-of-the-art tools. ggcoverage provides various available annotations to adapt to different NGS data (e.g. WGS/WES, RNA-seq, ChIP-seq) and all the available annotations can be easily superimposed with ' + '. ggcoverage can generate publication-quality plots and users can customize the plots with ggplot2. In addition, ggcoverage supports the visualization and annotation of protein coverage.

CONCLUSIONS

ggcoverage provides a flexible, programmable, efficient and user-friendly way to visualize and annotate genome coverage of multi-groups and multi-omics. The ggcoverage package is available at https://github.com/showteeth/ggcoverage under the MIT license, and the vignettes are available at https://showteeth.github.io/ggcoverage/ .

Genomic Landscape of Copy Number Variations and Their Associations with Climatic Variables in the World's Sheep

Sheep show characteristics of phenotypic diversity and adaptation to diverse climatic regions. Previous studies indicated associations between copy number variations (CNVs) and climate-driven adaptive evolution in humans and other domestic animals. Here, we constructed a genomic landscape of CNVs (n = 39,145) in 47 old autochthonous populations genotyped at a set of high-density (600 K) SNPs to detect environment-driven signatures of CNVs using a multivariate regression model. We found 136 deletions and 52 duplications that were significantly (Padj. < 0.05) associated with climatic variables. These climate-mediated selective CNVs are involved in functional candidate genes for heat stress and cold climate adaptation (e.g., B3GNTL1, UBE2L3, and TRAF2), coat and wool-related traits (e.g., TMEM9, STRA6, RASGRP2, and PLA2G3), repairing damaged DNA (e.g., HTT), GTPase activity (e.g., COPG), fast metabolism (e.g., LMF2 and LPIN3), fertility and reproduction (e.g., SLC19A1 and CCDC155), growth-related traits (e.g., ADRM1 and IGFALS), and immune response (e.g., BEGAIN and RNF121) in sheep. In particular, we identified significant (Padj. < 0.05) associations between probes in deleted/duplicated CNVs and solar radiation. Enrichment analysis of the gene sets among all the CNVs revealed significant (Padj. < 0.05) enriched gene ontology terms and pathways related to functions such as nucleotide, protein complex, and GTPase activity. Additionally, we observed overlapping between the CNVs and 140 known sheep QTLs. Our findings imply that CNVs can serve as genomic markers for the selection of sheep adapted to specific climatic conditions.

Accumulation of gene copy number variations during the early phase of free-spawning abalone speciation

The genetic basis of speciation in free-spawning marine invertebrates is poorly understood. Although gene copy number variations (GCNVs) and nucleotide variations possibly trigger the speciation of these organisms, empirical evidence for such a hypothesis is limited. In this study, we searched for genomic signatures of GCNVs that may contribute to the speciation of Western Pacific abalone species. Whole-genome sequencing data suggested the existence of significant amounts of GCNVs in closely related abalones, Haliotis discus and H. madaka, in the early phase of speciation. In addition, the degree of interspecies genetic differentiation in the genes where GCNVs were estimated was higher than that in other genes, suggesting that nucleotide divergence also accumulates in the genes with GCNVs. GCNVs in some genes were also detected in other related abalone species, suggesting that these GCNVs are derived from both ancestral and de novo mutations. Our findings suggest that GCNVs have been accumulated in the early phase of free-spawning abalone speciation.

Identification of cellular heterogeneity and immunogenicity of chondrocytes via single-cell RNA sequencing technique in human osteoarthritis

Background: Osteoarthritis (OA) has placed a heavy burden to the economy and humanistics. To explore the biological functions and markers of chondrocytes contributes significantly to the accurate diagnosis and targeted treatment of OA.

Methods: We systematically analyzed the immunogenicity and biological function of varied chondrocytes at single cell resolution, and identified the chondrocyte subtypes and biomarkers involved in the development of OA, which are verified in the bulk sequencing cohort.

Results: Based on previous study, we defined eight subtypes of chondrocytes with different biological functions, finding out that effector chondrocytes (ECs) and fibrocartilage chondrocytes (FCs) may promote the development of OA. Compared with other chondrocytes, ECs and FCs show stronger immunogenicity. FCs mainly affects the degeneration of cartilage caused by fibrous degeneration, while ECs mainly exerts immune function and causes tissues inflammation. In addition, the canonical gene markers of EC and FC assist with the prediction of OA, which has been verified in Bulk RNA sequencing data from two GEO datasets.

Conclusion: In summary, this study provides a new perspective for the exploration of cellular heterogeneity and pathophysiology in OA and will make contribution to the accurate diagnosis and targeted treatment of OA.

DNA sequence features underlying large-scale duplications and deletions in human

Copy number variants (CNVs) may cover up to 12% of the whole genome and have substantial impact on phenotypes. We used 5867 duplications and 33,181 deletions available from the 1000 Genomes Project to characterise genomic regions vulnerable to CNV formation and to identify sequence features characteristic for those regions. The GC content for deletions was lower and for duplications was higher than for randomly selected regions. In regions flanking deletions and downstream of duplications, content was higher than in the random sequences, but upstream of duplication content was lower. In duplications and downstream of deletion regions, the percentage of low-complexity sequences was not different from the randomised data. In deletions and upstream of CNVs, it was higher, while for downstream of duplications, it was lower as compared to random sequences. The majority of CNVs intersected with genic regions — mainly with introns. GC content may be associated with CNV formation and CNVs, especially duplications are initiated in low-complexity regions. Moreover, CNVs located or overlapped with introns indicate their role in shaping intron variability. Genic CNV regions were enriched in many essential biological processes such as cell adhesion, synaptic transmission, transport, cytoskeleton organization, immune response and metabolic mechanisms, which indicates that these large-scaled variants play important biological roles.

Large-scale discovery of novel neurodevelopmental disorder-related genes through a unified analysis of single-nucleotide and copy number variants

Background

Previous large-scale studies of de novo variants identified a number of genes associated with neurodevelopmental disorders (NDDs); however, it was also predicted that many NDD-associated genes await discovery. Such genes can be discovered by integrating copy number variants (CNVs), which have not been fully considered in previous studies, and increasing the sample size.

Methods

We first constructed a model estimating the rates of de novo CNVs per gene from several factors such as gene length and number of exons. Second, we compiled a comprehensive list of de novo single-nucleotide variants (SNVs) in 41,165 individuals and de novo CNVs in 3675 individuals with NDDs by aggregating our own and publicly available datasets, including denovo-db and the Deciphering Developmental Disorders study data. Third, summing up the de novo CNV rates that we estimated and SNV rates previously established, gene-based enrichment of de novo deleterious SNVs and CNVs were assessed in the 41,165 cases. Significantly enriched genes were further prioritized according to their similarity to known NDD genes using a deep learning model that considers functional characteristics (e.g., gene ontology and expression patterns).

Results

We identified a total of 380 genes achieving statistical significance (5% false discovery rate), including 31 genes affected by de novo CNVs. Of the 380 genes, 52 have not previously been reported as NDD genes, and the data of de novo CNVs contributed to the significance of three genes (GLTSCR1, MARK2, and UBR3). Among the 52 genes, we reasonably excluded 18 genes [a number almost identical to the theoretically expected false positives (i.e., 380 × 0.05 = 19)] given their constraints against deleterious variants and extracted 34 “plausible” candidate genes. Their validity as NDD genes was consistently supported by their similarity in function and gene expression patterns to known NDD genes. Quantifying the overall similarity using deep learning, we identified 11 high-confidence (> 90% true-positive probabilities) candidate genes: HDAC2, SUPT16H, HECTD4, CHD5, XPO1, GSK3B, NLGN2, ADGRB1, CTR9, BRD3, and MARK2.

Conclusions

We identified dozens of new candidates for NDD genes. Both the methods and the resources developed here will contribute to the further identification of novel NDD-associated genes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-022-01042-w.

Interpreting Functional Impact of Genetic Variations by Network QTL for Genotype–Phenotype Association Study

An enormous challenge in the post-genome era is to annotate and resolve the consequences of genetic variation on diverse phenotypes. The genome-wide association study (GWAS) is a well-known method to identify potential genetic loci for complex traits from huge genetic variations, following which it is crucial to identify expression quantitative trait loci (eQTL). However, the conventional eQTL methods usually disregard the systematical role of single-nucleotide polymorphisms (SNPs) or genes, thereby overlooking many network-associated phenotypic determinates. Such a problem motivates us to recognize the network-based quantitative trait loci (QTL), i.e., network QTL (nQTL), which is to detect the cascade association as genotype → network → phenotype rather than conventional genotype → expression → phenotype in eQTL. Specifically, we develop the nQTL framework on the theory and approach of single-sample networks, which can identify not only network traits (e.g., the gene subnetwork associated with genotype) for analyzing complex biological processes but also network signatures (e.g., the interactive gene biomarker candidates screened from network traits) for characterizing targeted phenotype and corresponding subtypes. Our results show that the nQTL framework can efficiently capture associations between SNPs and network traits (i.e., edge traits) in various simulated data scenarios, compared with traditional eQTL methods. Furthermore, we have carried out nQTL analysis on diverse biological and biomedical datasets. Our analysis is effective in detecting network traits for various biological problems and can discover many network signatures for discriminating phenotypes, which can help interpret the influence of nQTL on disease subtyping, disease prognosis, drug response, and pathogen factor association. Particularly, in contrast to the conventional approaches, the nQTL framework could also identify many network traits from human bulk expression data, validated by matched single-cell RNA-seq data in an independent or unsupervised manner. All these results strongly support that nQTL and its detection framework can simultaneously explore the global genotype–network–phenotype associations and the underlying network traits or network signatures with functional impact and importance.

Copy number variants in genomes of local sheep breeds from Russia

Copy number variants (CNVs) are genomic structural variations that contribute to many adaptive and economically important traits in livestock. In this study, we detected CNVs in 354 animals from 16 Russian indigenous sheep breeds and analysed their possible functional roles. Our analysis of the entire sample set resulted in 4527 CNVs forming 1450 CNV regions (CNVRs). When constructing CNVRs for individual breeds, a total of 2715 regions ranging from 88 in Groznensk to 337 in Osetin breeds were identified. To make interbreed CNVR frequency comparison possible, we also identified core CNVRs using CNVs with overlapping chromosomal locations found in different breeds. This resulted in 137 interbreed CNVRs with frequency >15% in at least one breed. Functional enrichment analysis of genes affected by CNVRs in individual breeds revealed 12 breeds with significant enrichments in olfactory perception, PRAME family proteins, and immune response. Function of genes affected by interbreed and breed-specific CNVRs revealed candidates related to domestication, adaptation to high altitudes and cold climates, reproduction, parasite resistance, milk and meat qualities, wool traits, fat storage, and fat metabolism. Our work is the first attempt to uncover and characterise the CNV makeup of Russian indigenous sheep breeds. Further experimental and functional validation of CNVRs would help in developing new and improving existing sheep breeds.

Genome-Wide Assessment Characteristics of Genes Overlapping Copy Number Variation Regions in Duroc Purebred Population

Copy number variations (CNVs) are important structural variations that can cause significant phenotypic diversity. Reliable CNVs mapping can be achieved by identification of CNVs from different genetic backgrounds. Investigations on the characteristics of overlapping between CNV regions (CNVRs) and protein-coding genes (CNV genes) or miRNAs (CNV-miRNAs) can reveal the potential mechanisms of their regulation. In this study, we used 50 K SNP arrays to detect CNVs in Duroc purebred pig. A total number of 211 CNVRs were detected with a total length of 118.48 Mb, accounting for 5.23% of the autosomal genome sequence. Of these CNVRs, 32 were gains, 175 losses, and four contained both types (loss and gain within the same region). The CNVRs we detected were non-randomly distributed in the swine genome and were significantly enriched in the segmental duplication and gene density region. Additionally, these CNVRs were overlapping with 1,096 protein-coding genes (CNV-genes), and 39 miRNAs (CNV-miRNAs), respectively. The CNV-genes were enriched in terms of dosage-sensitive gene list. The expression of the CNV genes was significantly higher than that of the non-CNV genes in the adult Duroc prostate. Of all detected CNV genes, 22.99% genes were tissue-specific (TSI > 0.9). Strong negative selection had been underway in the CNV-genes as the ones that were located entirely within the loss CNVRs appeared to be evolving rapidly as determined by the median dN plus dS values. Non-CNV genes tended to be miRNA target than CNV-genes. Furthermore, CNV-miRNAs tended to target more genes compared to non-CNV-miRNAs, and a combination of two CNV-miRNAs preferentially synergistically regulated the same target genes. We also focused our efforts on examining CNV genes and CNV-miRNAs functions, which were also involved in the lipid metabolism, including DGAT1, DGAT2, MOGAT2, miR143, miR335, and miRLET7. Further molecular experiments and independent large studies are needed to confirm our findings.

Androgen-Binding Protein (Abp) Evolutionary History: Has Positive Selection Caused Fixation of Different Paralogs in Different Taxa of the Genus Mus?

Comparison of the androgen-binding protein (Abp) gene regions of six Mus genomes provides insights into the evolutionary history of this large murid rodent gene family. We identified 206 unique Abp sequences and mapped their physical relationships. At least 48 are duplicated and thus present in more than two identical copies. All six taxa have substantially elevated LINE1 densities in Abp regions compared with flanking regions, similar to levels in mouse and rat genomes, although nonallelic homologous recombination seems to have only occurred in Mus musculus domesticus. Phylogenetic and structural relationships support the hypothesis that the extensive Abp expansion began in an ancestor of the genus Mus. We also found duplicated Abpa27's in two taxa, suggesting that previously reported selection on a27 alleles may have actually detected selection on haplotypes wherein different paralogs were lost in each. Other studies reported that a27 gene and species trees were incongruent, likely because of homoplasy. However, L1MC3 phylogenies, supposed to be homoplasy-free compared with coding regions, support our paralog hypothesis because the L1MC3 phylogeny was congruent with the a27 topology. This paralog hypothesis provides an alternative explanation for the origin of the a27 gene that is suggested to be fixed in the three different subspecies of Mus musculus and to mediate sexual selection and incipient reinforcement between at least two of them. Finally, we ask why there are so many Abp genes, especially given the high frequency of pseudogenes and suggest that relaxed selection operates over a large part of the gene clusters.

Genome-wide detection of CNV regions and their potential association with growth and fatness traits in Duroc pigs

Background

In the process of pig breeding, the average daily gain (ADG), days to 100 kg (AGE), and backfat thickness (BFT) are directly related to growth rate and fatness. However, the genetic mechanisms involved are not well understood. Copy number variation (CNV), an important source of genetic diversity, can affect a variety of complex traits and diseases and has gradually been thrust into the limelight. In this study, we reported the genome-wide CNVs of Duroc pigs using SNP genotyping data from 6627 animals. We also performed a copy number variation region (CNVR)-based genome-wide association studies (GWAS) for growth and fatness traits in two Duroc populations.

Results

Our study identified 953 nonredundant CNVRs in U.S. and Canadian Duroc pigs, covering 246.89 Mb (~ 10.90%) of the pig autosomal genome. Of these, 802 CNVRs were in U.S. Duroc pigs with 499 CNVRs were in Canadian Duroc pigs, indicating 348 CNVRs were shared by the two populations. Experimentally, 77.8% of nine randomly selected CNVRs were validated through quantitative PCR (qPCR). We also identified 35 CNVRs with significant association with growth and fatness traits using CNVR-based GWAS. Ten of these CNVRs were associated with both ADG and AGE traits in U.S. Duroc pigs. Notably, four CNVRs showed significant associations with ADG, AGE, and BFT, indicating that these CNVRs may play a pleiotropic role in regulating pig growth and fat deposition. In Canadian Duroc pigs, nine CNVRs were significantly associated with both ADG and AGE traits. Further bioinformatic analysis identified a subset of potential candidate genes, including PDGFA, GPER1, PNPLA2 and BSCL2.

Conclusions

The present study provides a necessary supplement to the CNV map of the Duroc genome through large-scale population genotyping. In addition, the CNVR-based GWAS results provide a meaningful way to elucidate the genetic mechanisms underlying complex traits. The identified CNVRs can be used as molecular markers for genetic improvement in the molecular-guided breeding of modern commercial pigs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07654-7.

Extensive genome-wide duplications in the eastern oyster (Crassostrea virginica)

Genomic structural variation is an important source of genetic and phenotypic diversity, playing a critical role in evolution. The recent availability of a high-quality reference genome for the eastern oyster, Crassostrea virginica, and whole-genome sequence data of samples from across the species range in the USA, provides an opportunity to explore structural variation across the genome of this species. Our analysis shows significantly greater individual-level duplications of regions across the genome than that of most model vertebrate species. Duplications are widespread across all ten chromosomes with variation in frequency per chromosome. The eastern oyster shows a large interindividual variation in duplications as well as particular chromosomal regions with a higher density of duplications. A high percentage of duplications seen in C. virginica lie completely within genes and exons, suggesting the potential for impacts on gene function. These results support the hypothesis that structural changes may play a significant role in standing genetic variation in C. virginica, and potentially have a role in their adaptive and evolutionary success. Altogether, these results suggest that copy number variation plays an important role in the genomic variation of C. virginica. This article is part of the Theo Murphy meeting issue 'Molluscan genomics: broad insights and future directions for a neglected phylum'.

Genome-Wide Analyses Provide Insights into the Scavenging Lifestyle of the Striped Hyena (Hyaena hyaena)

Hyenas (family Hyaenidae) occupy a variety of different niches, of which the striped hyena (Hyaena hyaena) scavenges mainly on the carcasses of animals. We compared its genome with the genomes of nine other mammals, focusing on similarities and differences in chemoreception, detoxification, digestive, and immune systems. The results showed that the striped hyena's immune and digestive system-related gene families have significantly expanded, which was likely to be an adaptive response to its scavenging lifestyle. In addition, 88 and 26 positive selected genes (PSGs) were identified in the immune system and digestive system, respectively, which may be the molecular basis for immune defense system to effectively resist pathogen invasion. Functional enrichment analysis of PSGs revealed that most of them were involved in the immune regulation process. Among them, eight specific missense mutations were found in two PSGs (MHC class II antigen DOA and MHC class II antigen DOB), suggesting important reorganization of the immune system in the striped hyena. Moreover, we identified one cathelicidin gene and four defensin genes in the striped hyenas by genome mining, which have high-efficiency and broad-spectrum antimicrobial activity. Of particular interest, a striped hyena-specific missense mutation was found in the cathelicidin gene. PolyPhen-2 classified the missense mutation as a harmful mutation, which may have aided in immune adaptation to carrion feeding. Our genomic analyses on the striped hyena provided insights into its success in the adaptation to the scavenging lifestyle.

Systematic identification of genetic systems associated with phenotypes in patients with rare genomic copy number variations

Copy number variation (CNV) related disorders tend to show complex phenotypic profiles that do not match known diseases. This makes it difficult to ascertain their underlying molecular basis. A potential solution is to compare the affected genomic regions for multiple patients that share a pathological phenotype, looking for commonalities. Here, we present a novel approach to associate phenotypes with functional systems, in terms of GO categories and KEGG and Reactome pathways, based on patient data. The approach uses genomic and phenomic data from the same patients, finding shared genomic regions between patients with similar phenotypes. These regions are mapped to genes to find associated functional systems. We applied the approach to analyse patients in the DECIPHER database with de novo CNVs, finding functional systems associated with most phenotypes, often due to mutations affecting related genes in the same genomic region. Manual inspection of the ten top-scoring phenotypes found multiple FunSys connections supported by the previous studies for seven of them. The workflow also produces reports focussed on the genes and FunSys connected to the different phenotypes, alongside patient-specific reports, which give details of the associated genes and FunSys for each individual in the cohort. These can be run in "confidential" mode, preserving patient confidentiality. The workflow presented here can be used to associate phenotypes with functional systems using data at the level of a whole cohort of patients, identifying important connections that could not be found when considering them individually. The full workflow is available for download, enabling it to be run on any patient cohort for which phenotypic and CNV data are available.

The Role of Cell Growth-Related Gene Copy Number Variation in Autoimmune Thyroid Disease

Autoimmune thyroid disease (AITD) is a recurrent and refractory clinical endocrine disease. Some studies have shown that the incidence of AITD is not only related to iodine, a kind of environmental factor, but that susceptibility genes also play a crucial role in its pathogenesis. Since research on susceptibility genes is still underway, the aims of this study were to assess the association between copy number variations (CNVs) and AITD, to identify genes related to susceptibility to AITD, and to explore the risk factors in the occurrence of AITD. Blood samples from five AITD patients and five controls from each area were assessed by chromosome microarray to identify candidate genes. The copy number (CN) of the candidate genes and urinary iodine levels were determined in adults, including 158 AITD patients and 181 controls, from areas having different iodine statuses. The cell growth-related genes, glypican 5 (GPC5), B9 domain containing 2 (B9D2), and ankyrin repeat and suppressor of cytokine signaling [SOCS] box-containing protein family 11 (ASB11), were selected as the candidate genes. The distribution of GPC5, B9D2, and ASB11 CNVs in AITD patients and controls was significantly different, and high urinary iodine levels and GPC5 CNVs are risk factors for AITD. There was no significant association between urinary iodine level and CNVs of the candidate genes. High urinary iodine levels and GPC5 CNVs are risk factors for AITD, but an association with the occurrence of AITD was not found.

Copy number variation in human genomes from three major ethno-linguistic groups in Africa

Background

Copy number variation is an important class of genomic variation that has been reported in 75% of the human genome. However, it is underreported in African populations. Copy number variants (CNVs) could have important impacts on disease susceptibility and environmental adaptation. To describe CNVs and their possible impacts in Africans, we sequenced genomes of 232 individuals from three major African ethno-linguistic groups: (1) Niger Congo A from Guinea and Côte d’Ivoire, (2) Niger Congo B from Uganda and the Democratic Republic of Congo and (3) Nilo-Saharans from Uganda. We used GenomeSTRiP and cn.MOPS to identify copy number variant regions (CNVRs).

Results

We detected 7608 CNVRs, of which 2172 were only deletions, 2384 were only insertions and 3052 had both. We detected 224 previously un-described CNVRs. The majority of novel CNVRs were present at low frequency and were not shared between populations. We tested for evidence of selection associated with CNVs and also for population structure. Signatures of selection identified previously, using SNPs from the same populations, were overrepresented in CNVRs. When CNVs were tagged with SNP haplotypes to identify SNPs that could predict the presence of CNVs, we identified haplotypes tagging 3096 CNVRs, 372 CNVRs had SNPs with evidence of selection (iHS > 3) and 222 CNVRs had both. This was more than expected (p < 0.0001) and included loci where CNVs have previously been associated with HIV, Rhesus D and preeclampsia. When integrated with 1000 Genomes CNV data, we replicated their observation of population stratification by continent but no clustering by populations within Africa, despite inclusion of Nilo-Saharans and Niger-Congo populations within our dataset.

Conclusions

Novel CNVRs in the current study increase representation of African diversity in the database of genomic variants. Over-representation of CNVRs in SNP signatures of selection and an excess of SNPs that both tag CNVs and are subject to selection show that CNVs may be the actual targets of selection at some loci. However, unlike SNPs, CNVs alone do not resolve African ethno-linguistic groups. Tag haplotypes for CNVs identified may be useful in predicting African CNVs in future studies where only SNP data is available.

Population-Specific Genetic and Expression Differentiation in Europeans

Much of the enormous phenotypic variation observed across human populations is thought to have arisen from events experienced as our ancestors peopled different regions of the world. However, little is known about the genes involved in these population-specific adaptations. Here, we explore this problem by simultaneously examining population-specific genetic and expression differentiation in four human populations. In particular, we derive a branch-based estimator of population-specific differentiation in four populations, and apply this statistic to single-nucleotide polymorphism and RNA-seq data from Italian, British, Finish, and Yoruban populations. As expected, genome-wide estimates of genetic and expression differentiation each independently recapitulate the known relationships among these four human populations, highlighting the utility of our statistic for identifying putative targets of population-specific adaptations. Moreover, genes with large copy number variations display elevated levels of population-specific genetic and expression differentiation, consistent with the hypothesis that gene duplication and deletion events are key reservoirs of adaptive variation. Further, many top-scoring genes are well-known targets of adaptation in Europeans, including those involved in lactase persistence and vitamin D absorption, and a handful of novel candidates represent promising avenues for future research. Together, these analyses reveal that our statistic can aid in uncovering genes involved in population-specific genetic and expression differentiation, and that such genes often play important roles in a diversity of adaptive and disease-related phenotypes in humans.

Genome-Wide Genotype-Expression Relationships Reveal Both Copy Number and Single Nucleotide Differentiation Contribute to Differential Gene Expression between Stickleback Ecotypes

Repeated and independent emergence of trait divergence that matches habitat differences is a sign of parallel evolution by natural selection. Yet, the molecular underpinnings that are targeted by adaptive evolution often remain elusive. We investigate this question by combining genome-wide analyses of copy number variants (CNVs), single nucleotide polymorphisms (SNPs), and gene expression across four pairs of lake and river populations of the three-spined stickleback (Gasterosteus aculeatus). We tested whether CNVs that span entire genes and SNPs occurring in putative cis-regulatory regions contribute to gene expression differences between sticklebacks from lake and river origins. We found 135 gene CNVs that showed a significant positive association between gene copy number and gene expression, suggesting that CNVs result in dosage effects that can fuel phenotypic variation and serve as substrates for habitat-specific selection. Copy number differentiation between lake and river sticklebacks also contributed to expression differences of two immune-related genes in immune tissues, cathepsin A and GIMAP7. In addition, we identified SNPs in cis-regulatory regions (eSNPs) associated with the expression of 1,865 genes, including one eSNP upstream of a carboxypeptidase gene where both the SNP alleles differentiated and the gene was differentially expressed between lake and river populations. Our study highlights two types of mutations as important sources of genetic variation involved in the evolution of gene expression and in potentially facilitating repeated adaptation to novel environments.

Genomic evidence sheds light on the genetic mechanisms of musk secretion in muskrats

Adult male muskrat (Ondatra zibethicus) has a pair of scent glands which secret musk to attract females during the breeding stage. The goal of the present study was to investigate the genetic mechanisms of musk secretion of muskrats at the whole genome level. Comparative genomics illustrated obvious expansion in 809 gene families, of which nine gene families played pivotal roles in steroid biosynthesis, possibly related to muskrat musk secretion. We identified 1112 positively selected genes (PSGs) in the muskrat, including estrogen receptor 1 (ER1), an important influencing factor to the weight and size of the scented glands of muskrats. HSD17B3, HSD17B4, CYP7B1 and CYP17B1, crucial to steroid hormone biosynthesis, were under strong positive selection in the muskrat, and phylogenetic analysis of HSD and CYP450 classes revealed high gene diversity. Functional enrichment revealed many pathways associated with musk secretion and/or growth and degeneration of scented gland significantly, such as peroxisome, PI3K-Akt signaling pathway, apoptosis, and prostate cancer. Two muskrat-specific missense mutations (Pro237Thr and Ser297Ile) were detected in LIPC, which were reported to be involved cholesterol metabolic process. More importantly, the missense mutations discovered in LIPC were classified as deleterious by PolyPhen-2, possibly affecting the musk secretion of muskrats.

Functional and population genetic features of copy number variations in two dairy cattle populations

BACKGROUND

Copy Number Variations (CNVs) are gain or loss of DNA segments that are known to play a role in shaping a wide range of phenotypes. In this study, we used two dairy cattle populations, Holstein Friesian and Jersey, to discover CNVs using the Illumina BovineHD Genotyping BeadChip aligned to the ARS-UCD1.2 assembly. The discovered CNVs were investigated for their functional impact and their population genetics features.

RESULTS

We discovered 14,272 autosomal CNVs, which were aggregated into 1755 CNV regions (CNVR) from 451 animals. These CNVRs together cover 2.8% of the bovine autosomes. The assessment of the functional impact of CNVRs showed that rare CNVRs (MAF < 0.01) are more likely to overlap with genes, than common CNVRs (MAF ≥ 0.05). The Population differentiation index (Fst) based on CNVRs revealed multiple highly diverged CNVRs between the two breeds. Some of these CNVRs overlapped with candidate genes such as MGAM and ADAMTS17 genes, which are related to starch digestion and body size, respectively. Lastly, linkage disequilibrium (LD) between CNVRs and BovineHD BeadChip SNPs was generally low, close to 0, although common deletions (MAF ≥ 0.05) showed slightly higher LD (r2 = ~ 0.1 at 10 kb distance) than the rest. Nevertheless, this LD is still lower than SNP-SNP LD (r2 = ~ 0.5 at 10 kb distance).

CONCLUSIONS

Our analyses showed that CNVRs detected using BovineHD BeadChip arrays are likely to be functional. This finding indicates that CNVs can potentially disrupt the function of genes and thus might alter phenotypes. Also, the population differentiation index revealed two candidate genes, MGAM and ADAMTS17, which hint at adaptive evolution between the two populations. Lastly, low CNVR-SNP LD implies that genetic variation from CNVs might not be fully captured in routine animal genetic evaluation, which relies solely on SNP markers.

A snapshot neural ensemble method for cancer-type prediction based on copy number variations

An accurate diagnosis and prognosis for cancer are specific to patients with particular cancer types and molecular traits, which needs to address carefully. The discovery of important biomarkers is becoming an important step toward understanding the molecular mechanisms of carcinogenesis in which genomics data and clinical outcomes need to be analyzed before making any clinical decision. Copy number variations (CNVs) are found to be associated with the risk of individual cancers and hence can be used to reveal genetic predispositions before cancer develops. In this paper, we collect the CNVs data about 8000 cancer patients covering 14 different cancer types from The Cancer Genome Atlas. Then, two different sparse representations of CNVs based on 578 oncogenes and 20,308 protein-coding genes, including genomic deletions and duplication across the samples, are prepared. Then, we train Conv-LSTM and convolutional autoencoder (CAE) networks using both representations and create snapshot models. While the Conv-LSTM can capture locally and globally important features, CAE can utilize unsupervised pretraining to initialize the weights in the subsequent convolutional layers against the sparsity. Model averaging ensemble (MAE) is then applied to combine the snapshot models in order to make a single prediction. Finally, we identify most significant CNVs biomarkers using guided-gradient class activation map plus (GradCAM++) and rank top genes for different cancer types. Results covering several experiments show fairly high prediction accuracies for the majority of cancer types. In particular, using protein-coding genes, Conv-LSTM and CAE networks can predict cancer types correctly at least 72.96% and 76.77% of the cases, respectively. Contrarily, using oncogenes gives moderately higher accuracies of 74.25% and 78.32%, whereas the snapshot model based on MAE shows overall 2.5% of accuracy improvement.

Cancer Is Associated with Alterations in the Three-Dimensional Organization of the Genome

The human genome is organized into topologically associating domains (TADs), which represent contiguous regions with a higher frequency of intra-interactions as opposed to inter-interactions. TADs contribute to gene expression regulation by restricting the interactions between their regulatory elements, and TAD disruption has been associated with cancer. Here, we provide a proof of principle that mutations within TADs can be used to predict the survival of cancer patients. Specifically, we constructed a set of 1467 consensus TADs representing the three-dimensional organization of the human genome and used Cox regression analysis to identify a total of 35 prognostic TADs in different cancer types. Interestingly, only 46% of the 35 prognostic TADs comprised genes with known clinical relevance. Moreover, in the vast majority of such cases, the prognostic value of the TAD was not directly related to the presence/absence of mutations in the gene(s), emphasizing the importance of regulatory mutations. In addition, we found that 34% of the prognostic TADs show strong structural perturbations in the cancer genome, consistent with the widespread, global epigenetic dysregulation often observed in cancer patients. In summary, this study elucidates the mechanisms through which non-coding variants may influence cancer progression and opens new avenues for personalized medicine.

An Evolutionary Perspective on the Impact of Genomic Copy Number Variation on Human Health

Copy number variants (CNVs), deletions and duplications of segments of DNA, account for at least five times more variable base pairs in humans than single-nucleotide variants. Several common CNVs were shown to change coding and regulatory sequences and thus dramatically affect adaptive phenotypes involving immunity, perception, metabolism, skin structure, among others. Some of these CNVs were also associated with susceptibility to cancer, infection, and metabolic disorders. These observations raise the possibility that CNVs are a primary contributor to human phenotypic variation and consequently evolve under selective pressures. Indeed, locus-specific haplotype-level analyses revealed signatures of natural selection on several CNVs. However, more traditional tests of selection which are often applied to single-nucleotide variation often have diminished statistical power when applied to CNVs because they often do not show strong linkage disequilibrium with nearby variants. Recombination-based formation mechanisms of CNVs lead to frequent recurrence and gene conversion events, breaking the linkage disequilibrium involving CNVs. Similar methodological challenges also prevent routine genome-wide association studies to adequately investigate the impact of CNVs on heritable human disease. Thus, we argue that the full relevance of CNVs to human health and evolution is yet to be elucidated. We further argue that a holistic investigation of formation mechanisms within an evolutionary framework would provide a powerful framework to understand the functional and biomedical impact of CNVs. In this paper, we review several cases where studies reveal diverse evolutionary histories and unexpected functional consequences of CNVs. We hope that this review will encourage further work on CNVs by both evolutionary and medical geneticists.

Mosaicism of XX and XXY cells accounts for high copy number of Toll like Receptor 7 and 8 genes in peripheral blood of men with Rheumatoid Arthritis

The X chromosome, hemizygous in males, contains numerous genes important to immunological and hormonal function. Alterations in X-linked gene dosage are suspected to contribute to female predominance in autoimmunity. A powerful example of X-linked dosage involvement comes from the BXSB murine lupus model, where the duplication of the X-linked Toll-Like Receptor 7 (Tlr7) gene aggravates autoimmunity in male mice. Such alterations are possible in men with autoimmune diseases. Here we showed that a quarter to a third of men with rheumatoid arthritis (RA) had significantly increased copy numbers (CN) of TLR7 gene and its paralog TLR8. Patients with high CN had an upregulated pro-inflammatory JNK/p38 signaling pathway. By fluorescence in situ hybridization, we further demonstrated that the increase in X-linked genes CN was due to the presence of an extra X chromosome in some cells. Men with RA had a significant cellular mosaicism of female (46,XX) and/or Klinefelter (47,XXY) cells among male (46,XY) cells, reaching up to 1.4% in peripheral blood. Our results present a new potential trigger for RA in men and opens a new field of investigation particularly relevant for gender-biased autoimmune diseases.

Whole-genome sequencing reveals high complexity of copy number variation at insecticide resistance loci in malaria mosquitoes

Polymorphisms in genetic copy number can influence gene expression, coding sequence, and zygosity, making them powerful actors in the evolutionary process. Copy number variants (CNVs) are however understudied, being more difficult to detect than single-nucleotide polymorphisms. We take advantage of the intense selective pressures on the major malaria vector Anopheles gambiae, caused by the widespread use of insecticides for malaria control, to investigate the role of CNVs in the evolution of insecticide resistance. Using the whole-genome sequencing data from 1142 samples in the An. gambiae 1000 genomes project, we identified 250 gene-containing CNVs, encompassing a total of 267 genes of which 28 were in gene families linked to metabolic insecticide resistance, representing significant enrichment of these families. The five major gene clusters for metabolic resistance all contained CNVs, with 44 different CNVs being found across these clusters and multiple CNVs frequently covering the same genes. These 44 CNVs are widespread (45% of individuals carry at least one of them) and have been spreading through positive selection, indicated by their high local frequencies and extended haplotype homozygosity. Our results demonstrate the importance of CNVs in the response to selection, highlighting the urgent need to identify the contribution of each CNV to insecticide resistance and to track their spread as the use of insecticides in malaria endemic countries intensifies and as the operational deployment of next-generation bed nets targeting metabolic resistance gathers pace. Our detailed descriptions of CNVs found across the species range provide the tools to do so.

Copy number variation profiling in pharmacogenetics CYP-450 and GST genes in Colombian population

BACKGROUND

Copy Number variation (CNVs) in genes related to drug absorption, distribution, metabolism and excretion (ADME) are relevant in the interindividual variability of drug response. Studies of the CNVs in ADME genes in Latin America population are lacking. The objective of the study was to identify the genetic variability of CNVs in CYP-450 and GST genes in a subgroup of individuals of Colombian origin.

METHODS

Genomic DNA was isolated from 123 healthy individuals from a Colombian population. Multiplex Ligation-Dependent Probe Amplification (MLPA) was performed for the identification of CNVs in 40 genomic regions of 11 CYP-450 and 3 GST genes. The genetic variability, allelic and genotypic frequencies were analyzed.

RESULTS

We found that 13 out of 14 genes had CNVs: 5 (35.7%) exhibited deletions and duplications, while 8 (57.1%) presented either deletions or duplications.. 33.3% of individuals carried deletions and duplications while 49.6% had a unique type of CNV (deletion or duplication). The allelic frequencies of the CYP and GST genes were 0 to 47.6% (allele null), 0 to 17.5% (duplicated alleles) and 37 to 100% (normal alleles).

CONCLUSIONS

Our results describe, for the first time, the genomic profile of CNVs in a subgroup of Colombian population in GST and CYP-450 genes. GST genes indicated greater genetic variability than CYP-450 genes. The data obtained contributes to the knowledge of genetic profiles in Latin American subgroups. Although the clinical relevance of CNVs has not been fully established, it is a valuable source of pharmacogenetic variability data with potential involvement in the response to medications.

Germline Structural Variations Are Preferential Sites of DNA Replication Timing Plasticity during Development

The DNA replication timing program is modulated throughout development and is also one of the main factors influencing the distribution of mutation rates across the genome. However, the relationship between the mutagenic influence of replication timing and its developmental plasticity remains unexplored. Here, we studied the distribution of copy number variations (CNVs) and single nucleotide polymorphisms across the zebrafish genome in relation to changes in DNA replication timing during embryonic development in this model vertebrate species. We show that CNV sites exhibit strong replication timing plasticity during development, replicating significantly early during early development but significantly late during more advanced developmental stages. Reciprocally, genomic regions that changed their replication timing during development contained a higher proportion of CNVs than developmentally constant regions. Developmentally plastic CNV sites, in particular those that become delayed in their replication timing, were enriched for the clustered protocadherins, a set of genes important for neuronal development that have undergone extensive genetic and epigenetic diversification during zebrafish evolution. In contrast, single nucleotide polymorphism sites replicated consistently early throughout embryonic development, highlighting a unique aspect of the zebrafish genome. Our results uncover a hitherto unrecognized interface between development and evolution.

Chromosome 18 gene dosage map 2.0

In 2009, we described the first generation of the chromosome 18 gene dosage maps. This tool included the annotation of each gene as well as each phenotype associated region. The goal of these annotated genetic maps is to provide clinicians with a tool to appreciate the potential clinical impact of a chromosome 18 deletion or duplication. These maps are continually updated with the most recent and relevant data regarding chromosome 18. Over the course of the past decade, there have also been advances in our understanding of the molecular mechanisms underpinning genetic disease. Therefore, we have updated the maps to more accurately reflect this knowledge. Our Gene Dosage Map 2.0 has expanded from the gene and phenotype maps to also include a pair of maps specific to hemizygosity and suprazygosity. Moreover, we have revamped our classification from mechanistic definitions (e.g., haplosufficient, haploinsufficient) to clinically oriented classifications (e.g., risk factor, conditional, low penetrance, causal). This creates a map with gradient of classifications that more accurately represents the spectrum between the two poles of pathogenic and benign. While the data included in this manuscript are specific to chromosome 18, they may serve as a clinically relevant model that can be applied to the rest of the genome.

NeuroArray, A Custom CGH Microarray to Decipher Copy Number Variants in Alzheimer's Disease

Background:

Copy Number Variants (CNVs) represent a prevailing type of structural variation (deletions or duplications) in the human genome. In the last few years, several studies have demonstrated that CNVs represent significant mutations in Alzheimer’s Disease (AD) hereditability. Currently, innovative high-throughput platforms and bioinformatics algorithms are spreading to screening CNVs involved in different neurological diseases. In particular, the use of custom arrays, based on libraries of probes that can detect significant genomic regions, have greatly improved the resolution of targeted regions and the identification of chromosomal aberrations.

Objective:

In this work, we report the use of NeuroArray, a custom CGH microarray useful to screening and further investigate the role of the recurring genomic aberrations in patients with confirmed or suspected AD.

Methods:

The custom oligonucleotide aCGH design includes 641 genes and 9118 exons, linked to AD. The genomic DNA was isolated from blood samples of AD affected patients. The entire protocol of custom NeuroArray included digestion, labelling and hybridization steps as a standard aCGH assay.

Results:

The NeuroArray analysis revealed the presence of amplifications in several genes associated with AD. In the coding regions of these genes, 14,586 probes were designed with a 348 bp median probe spacing. The majority of targeted AD genes map on chromosomes 1 and 10. A significant aspect of the NeuroArray design is that 95% of the total exon targets is covered by at least one probe, a resolution higher than CGH array platforms commercially available.

Conclusion:

By identifying with a high sensitivity the chromosomal abnormalities in a large panel of AD-related genes and other neurological diseases, the NeuroArray platform is a valid tool for clinical diagnosis.

Human copy number variants are enriched in regions of low mappability

Copy number variants (CNVs) are known to affect a large portion of the human genome and have been implicated in many diseases. Although whole-genome sequencing (WGS) can help identify CNVs, most analytical methods suffer from limited sensitivity and specificity, especially in regions of low mappability. To address this, we use PopSV, a CNV caller that relies on multiple samples to control for technical variation. We demonstrate that our calls are stable across different types of repeat-rich regions and validate the accuracy of our predictions using orthogonal approaches. Applying PopSV to 640 human genomes, we find that low-mappability regions are approximately 5 times more likely to harbor germline CNVs, in stark contrast to the nearly uniform distribution observed for somatic CNVs in 95 cancer genomes. In addition to known enrichments in segmental duplication and near centromeres and telomeres, we also report that CNVs are enriched in specific types of satellite and in some of the most recent families of transposable elements. Finally, using this comprehensive approach, we identify 3455 regions with recurrent CNVs that were missing from existing catalogs. In particular, we identify 347 genes with a novel exonic CNV in low-mappability regions, including 29 genes previously associated with disease.

Highly similar genomic landscapes in monoclonal B-cell lymphocytosis and ultra-stable chronic lymphocytic leukemia with low frequency of driver mutations

Despite the recent discovery of recurrent driver mutations in chronic lymphocytic leukemia, the genetic factors involved in disease onset remain largely unknown. To address this issue, we performed whole-genome sequencing in 11 individuals with monoclonal B- cell lymphocytosis, both of the low-count and high-count subtypes, and 5 patients with ultra-stable chronic lymphocytic leukemia (>10 years without progression from initial diagnosis). All three entities were indistinguishable at the genomic level exhibiting low genomic complexity and similar types of somatic mutations. Exonic mutations were not frequently identified in putative chronic lymphocytic leukemia driver genes in all settings, including low-count monoclonal B-cell lymphocytosis. To corroborate these findings, we also performed deep sequencing in 11 known frequently mutated genes in an extended cohort of 28 monoclonal B-cell lymphocytosis/chronic lymphocytic leukemia cases. Interestingly, shared mutations were detected between clonal B cells and paired polymorphonuclear cells, strengthening the notion that at least a fraction of somatic mutations may occur before disease onset, likely at the hematopoietic stem cell level. Finally, we identified previously unreported non-coding variants targeting pathways relevant to B-cell and chronic lymphocytic leukemia development, likely associated with the acquisition of the characteristic neoplastic phenotype typical of both monoclonal B-cell lymphocytosis and chronic lymphocytic leukemia.

Selection To Increase Expression, Not Sequence Diversity, Precedes Gene Family Origin and Expansion in Rattlesnake Venom

Gene duplication is the primary mechanism leading to new genes and phenotypic novelty, but the proximate evolutionary processes underlying gene family origin, maintenance, and expansion are poorly understood. Although sub- and neofunctionalization provide clear long-term advantages, selection does not act with foresight, and unless a redundant gene copy provides an immediate fitness advantage, the copy will most likely be lost. Many models for the evolution of genes immediately following duplication have been proposed, but the robustness and applicability of these models is unclear because of the lack of data at the population level. We used qPCR, protein expression data, genome sequencing, and hybrid enrichment to test three competing models that differ in whether selection favoring the spread of duplicates acts primarily on expression level or sequence diversity for specific toxin-encoding loci in the eastern diamondback rattlesnake (Crotalus adamanteus). We sampled 178 individuals and identified significant inter- and intrapopulation variation in copy number, demonstrated that copy number was significantly and positively correlated with protein expression, and found little to no sequence variation across paralogs in all populations. Collectively, these results demonstrate that selection for increased expression, not sequence diversity, was the proximate evolutionary process underlying gene family origin and expansion, providing data needed to resolve the debate over which evolutionary processes govern the fates of gene copies immediately following duplication.

Diversity and regulatory impact of copy number variation in the primate Macaca fascicularis

BACKGROUND

Copy number variations (CNVs) are a significant source of genetic diversity and commonly found in mammalian genomes. We have generated a genome-wide CNV map for Cynomolgus monkeys (Macaca fascicularis). This crab-eating macaque is the closest animal model to humans that is used in biomedical research.

RESULTS

We show that Cynomolgus monkey CNVs are in general much smaller in size than gene loci and are specific to the population of origin. Genome-wide expression data from five vitally important organs demonstrates that CNVs in close proximity to transcription start sites associate strongly with expression changes. Among these eQTL genes we find an overrepresentation of genes involved in metabolism, receptor activity, and transcription.

CONCLUSION

These results provide evidence that CNVs shape tissue transcriptomes in monkey populations, potentially offering an adaptive advantage. We suggest that this genetic diversity should be taken into account when using Cynomolgus macaques as models.

Copy Number Variants in Alzheimer's Disease

Alzheimer's disease (AD) is a devastating disease mainly afflicting elderly people, characterized by decreased cognition, loss of memory, and eventually death. Although risk and deterministic genes are known, major genetics research programs are underway to gain further insights into the inheritance of AD. In the last years, in particular, new developments in genome-wide scanning methodologies have enabled the association of a number of previously uncharacterized copy number variants (CNVs, gain or loss of DNA) in AD. Because of the exceedingly large number of studies performed, it has become difficult for geneticists as well as clinicians to systematically follow, evaluate, and interpret the growing number of (sometime conflicting) CNVs implicated in AD. In this review, after a brief introduction of this type of structural variation, and a description of available databases, computational analyses, and technologies involved, we provide a systematic review of all published data showing statistical and scientific significance of pathogenic CNVs and discuss the role they might play in AD.

Characterization of the Poplar Pan-Genome by Genome-Wide Identification of Structural Variation

Many recent studies have emphasized the important role of structural variation (SV) in determining human genetic and phenotypic variation. In plants, studies aimed at elucidating the extent of SV are still in their infancy. Evidence has indicated a high presence and an active role of SV in driving plant genome evolution in different plant species.

With the aim of characterizing the size and the composition of the poplar pan-genome, we performed a genome-wide analysis of structural variation in three intercrossable poplar species: Populus nigra, Populus deltoides, and Populus trichocarpa. We detected a total of 7,889 deletions and 10,586 insertions relative to the P. trichocarpa reference genome, covering respectively 33.2 Mb and 62.9 Mb of genomic sequence, and 3,230 genes affected by copy number variation (CNV). The majority of the detected variants are inter-specific in agreement with a recent origin following separation of species.

Insertions and deletions (INDELs) were preferentially located in low-gene density regions of the poplar genome and were, for the majority, associated with the activity of transposable elements. Genes affected by SV showed lower-than-average expression levels and higher levels of dN/dS, suggesting that they are subject to relaxed selective pressure or correspond to pseudogenes.

Functional annotation of genes affected by INDELs showed over-representation of categories associated with transposable elements activity, while genes affected by genic CNVs showed enrichment in categories related to resistance to stress and pathogens. This study provides a genome-wide catalogue of SV and the first insight on functional and structural properties of the poplar pan-genome.

Performance Evaluation of NIPT in Detection of Chromosomal Copy Number Variants Using Low-Coverage Whole-Genome Sequencing of Plasma DNA

OBJECTIVES

The aim of this study was to assess the performance of noninvasively prenatal testing (NIPT) for fetal copy number variants (CNVs) in clinical samples, using a whole-genome sequencing method.

METHOD

A total of 919 archived maternal plasma samples with karyotyping/microarray results, including 33 CNVs samples and 886 normal samples from September 1, 2011 to May 31, 2013, were enrolled in this study. The samples were randomly rearranged and blindly sequenced by low-coverage (about 7M reads) whole-genome sequencing of plasma DNA. Fetal CNVs were detected by Fetal Copy-number Analysis through Maternal Plasma Sequencing (FCAPS) to compare to the karyotyping/microarray results. Sensitivity, specificity and were evaluated.

RESULTS

33 samples with deletions/duplications ranging from 1 to 129 Mb were detected with the consistent CNV size and location to karyotyping/microarray results in the study. Ten false positive results and two false negative results were obtained. The sensitivity and specificity of detection deletions/duplications were 84.21% and 98.42%, respectively.

CONCLUSION

Whole-genome sequencing-based NIPT has high performance in detecting genome-wide CNVs, in particular >10Mb CNVs using the current FCAPS algorithm. It is possible to implement the current method in NIPT to prenatally screening for fetal CNVs.

Population-genetic properties of differentiated copy number variations in cattle

While single nucleotide polymorphism (SNP) is typically the variant of choice for population genetics, copy number variation (CNV) which comprises insertion, deletion and duplication of genomic sequence, is an informative type of genetic variation. CNVs have been shown to be both common in mammals and important for understanding the relationship between genotype and phenotype. However, CNV differentiation, selection and its population genetic properties are not well understood across diverse populations. We performed a population genetics survey based on CNVs derived from the BovineHD SNP array data of eight distinct cattle breeds. We generated high resolution results that show geographical patterns of variations and genome-wide admixture proportions within and among breeds. Similar to the previous SNP-based studies, our CNV-based results displayed a strong correlation of population structure and geographical location. By conducting three pairwise comparisons among European taurine, African taurine, and indicine groups, we further identified 78 unique CNV regions that were highly differentiated, some of which might be due to selection. These CNV regions overlapped with genes involved in traits related to parasite resistance, immunity response, body size, fertility, and milk production. Our results characterize CNV diversity among cattle populations and provide a list of lineage-differentiated CNVs.

Gene expression profile analysis of pancreatic cancer based on microarray data

The present study identified differentially-expressed genes (DEGs) between pancreatic cancer (PC) tissues and normal tissues, and assessed genetic factors associated with the pathogenesis of PC. The mRNA expression microarray dataset, GSE16515, containing 52 samples, including 16 paired tumor and normal tissue samples, and 20 tumor samples, was downloaded from Gene Expression Omnibus. Raw data were normalized and DEGs were identified. Subsequently, clustering was performed, protein-protein interaction networks were drawn, and functional and pathway enrichment analyses of the DEGs were performed. Copy number variations of DEGs were also identified. A total of 1,765 DEGs between PC and normal tissues were identified, including 1,312 upregulated and 453 downregulated DEGs. Upregulated DEGs were associated with the regulation of nucleocytoplasmic and intracellular transport, whereas downregulated DEGs were associated with the response to organic substances and hormone stimulus. The pancreatic cancer pathway was connected to three DEGs, namely transforming growth factor β1 (TGFB1), TGFβ receptor 1 (TGFBR1) and epidermal growth factor (EGF), which had 2, 3 and 5 CNVs, respectively. These results indicated the important roles of TGFB1, TGFBR1 and EGF in the pathogenesis of PC. These genes may be potential therapeutic targets for the treatment of PC.

Type 2 diabetes mellitus disease risk genes identified by genome wide copy number variation scan in normal populations

AIMS

To identify the role of copy number variations (CNVs) on disease risk genes and its effect on disease phenotypes in type 2 diabetes mellitus (T2DM) in 12 random populations using high throughput arrays.

METHODS

CNV analysis was carried out on a total of 1715 individuals from 12 populations, from ArrayExpress Archive of the European Bioinformatics Institute along with our subjects using Affymetrix Genome Wide SNP 6.0 array. CNV effect on T2DM genes were analyzed using several bioinformatics tools and a molecular protein interaction network was constructed to identify the disease mechanism altered by the CNVs.

RESULTS

Analysis showed 34.4% of the total population to be under CNV burden for T2DM, with 83 disease causal and associated genes being under CNV influence. Hotspots were identified on chromosomes 22, 12, 6, 19 and 11.Overlap studies with case cohorts revealed significant disease risk genes such as EGFR, E2F1, PPP1R3A, HLA and TSPAN8.

CONCLUSIONS

CNVs play a significant role in predisposing T2DM in normal cohorts and contribute to the phenotypic effects. Thus, CNVs should be considered as one of the major contributors in predisposition of the disease.

Expression Differentiation Is Constrained to Low-Expression Proteins over Ecological Timescales

Protein expression level is one of the strongest predictors of protein sequence evolutionary rate, with high-expression protein sequences evolving at slower rates than low-expression protein sequences largely because of constraints on protein folding and function. Expression evolutionary rates also have been shown to be negatively correlated with expression level across human and mouse orthologs over relatively long divergence times (i.e., ∼100 million years). Long-term evolutionary patterns, however, often cannot be extrapolated to microevolutionary processes (and vice versa), and whether this relationship holds for traits evolving under directional selection within a single species over ecological timescales (i.e., <5000 years) is unknown and not necessarily expected. Expression is a metabolically costly process, and the expression level of a particular protein is predicted to be a tradeoff between the benefit of its function and the costs of its expression. Selection should drive the expression level of all proteins close to values that maximize fitness, particularly for high-expression proteins because of the increased energetic cost of production. Therefore, stabilizing selection may reduce the amount of standing expression variation for high-expression proteins, and in combination with physiological constraints that may place an upper bound on the range of beneficial expression variation, these constraints could severely limit the availability of beneficial expression variants. To determine whether rapid-expression evolution was restricted to low-expression proteins owing to these constraints on highly expressed proteins over ecological timescales, we compared venom protein expression levels across mainland and island populations for three species of pit vipers. We detected significant differentiation in protein expression levels in two of the three species and found that rapid-expression differentiation was restricted to low-expression proteins. Our results suggest that various constraints on high-expression proteins reduce the availability of beneficial expression variants relative to low-expression proteins, enabling low-expression proteins to evolve and potentially lead to more rapid adaptation.

Nomadic genetic elements contribute to oncogenic translocations: Implications in carcinogenesis

Chromosomal translocations as molecular signatures have been reported in various malignancies but, the mechanism behind which is largely unknown. Swapping of chromosomal fragments occurs by induction of double strand breaks (DSBs), most of which were initially assumed de novo. However, decoding of human genome proved that transposable elements (TE) might have profound influence on genome integrity. TEs are highly conserved mobile genetic elements that generate DSBs, subsequently resulting in large chromosomal rearrangements. Previously TE insertions were thought to be harmless, but recently gains attention due to the origin of spectrum of post-insertional genomic alterations and subsequent transcriptional alterations leading to development of deleterious effects mainly carcinogenesis. Though the existing knowledge on the cancer-associated TE dynamics is very primitive, exploration of underlying mechanism promises better therapeutic strategies for cancer. Thus, this review focuses on the prevalence of TE in the genome, associated genomic instability upon transposition activation and impact on tumorigenesis.

Global patterns of large copy number variations in the human genome reveal complexity in chromosome organization

Global patterns of copy number variations (CNVs) in chromosomes are required to understand the dynamics of genome organization and complexity. For this study, analysis was performed using the Affymetrix Genome-Wide Human SNP Array 6.0 chip and CytoScan High-Density arrays. We identified a total of 44 109 CNVs from 1715 genomes with a mean of 25 CNVs in an individual, which established the first drafts of population-specific CNV maps providing a rationale for prioritizing chromosomal regions. About 19 905 ancient CNVs were identified across all chromosomes and populations at varying frequencies. CNV count, and sometimes CNV size, contributed to the bulk CNV size of the chromosome. Population specific lengthening and shortening of chromosomal length was observed. Sex bias for CNV presence was largely dependent on ethnicity. Lower CNV inheritance rate was observed for India, compared to YRI and CEU. A total of 33 candidate CNV hotspots from 5382 copy number (CN) variable region (CNVR) clusters were identified. Population specific CNV distribution patterns in p and q arms disturbed the assumption that CNV counts in the p arm are less common compared to long arms, and the CNV occurrence and distribution in chromosomes is length independent. This study unraveled the force of independent evolutionary dynamics on genome organization and complexity across chromosomes and populations.