Common deletions and SNPs are in linkage disequilibrium in the human genome

Fusion of brain imaging genetic data for alzheimer's disease diagnosis and causal factors identification using multi-stream attention mechanisms and graph convolutional networks

Correctly diagnosing Alzheimer's disease (AD) and identifying pathogenic brain regions and genes play a vital role in understanding the AD and developing effective prevention and treatment strategies. Recent works combine imaging and genetic data, and leverage the strengths of both modalities to achieve better classification results. In this work, we propose MCA-GCN, a Multi-stream Cross-Attention and Graph Convolutional Network-based classification method for AD patients. It first constructs a brain region-gene association network based on brain region fMRI time series and gene SNP data. Then it integrates the absolute and relative positions of the brain region time series to obtain a new brain region time series containing temporal information. Then long-range and local association features between brain regions and genes are sequentially aggregated by multi-stream cross-attention and graph convolutional networks. Finally, the learned brain region and gene features are input to the fully connected network to predict AD types. Experimental results on the ADNI dataset show that our model outperforms other methods in AD classification tasks. Moreover, MCA-GCN designed a multi-stage feature scoring process to extract high-risk genes and brain regions related to disease classification.

Validation of selection signatures for coat color in the Podolica Italiana gray cattle breed

Taurine and indicine gray cattle represent relevant livestock resources in many countries of the world. A gray coat color and pigmented skin, which are common in most of the gray cattle breeds, have been demonstrated to confer better adaptation to solar radiation and thermal stresses. In a previous study adopting the FST-outlier approach with BayeScan v2.0, we identified differentially selected genomic regions in a set of gray cattle breeds, including the Podolica Italiana, and contrasted these findings with four non-gray cattle breeds. More supported signals were detected on bovine chromosomes (BTAs) 2, 4, 14, and 26 that encompassed more than fifty genes known to be directly or indirectly related to one or more steps in pigment biology. In the present study, we aimed to validate the previously observed signals using the same methodological approach on three new Podolica Italiana sample sets (N = 30 animals each). These animals were selected from the ANABIC genetic station during performance tests as being representative of the Podolica Italiana population at three different timeframes separated by approximately 10 years each. We typed these samples to the loci of 23,027 quality-controlled single-nucleotide polymorphisms. We also analyzed the dataset using the haplotype-based approach available in hapFLK v1.4 software. Both the FST-outlier and hapFLK approaches validated the abovementioned signals on BTAs 2, 4, 14, and 26. Moreover, both methods detected additional supported regions on BTAs 7 and 18 that included a total of 42 genes, of which most were already known from literature to be implicated in pigmentation traits.

Exome-wide comparative analyses revealed differentiating genomic regions for performance traits in Indian native buffaloes

In India, 20 breeds of buffalo have been identified and registered, yet limited studies have been conducted to explore the performance potential of these breeds, especially in the Indian native breeds. This study is a maiden attempt to delineate the important variants and unique genes through exome sequencing for milk yield, milk composition, fertility, and adaptation traits in Indian local breeds of buffalo. In the present study, whole exome sequencing was performed on Chhattisgarhi (n = 3), Chilika (n = 4), Gojri (n = 3), and Murrah (n = 4) buffalo breeds and after stringent quality control, 4333, 6829, 4130, and 4854 InDels were revealed, respectively. Exome-wide FST along 100-kb sliding windows detected 27, 98, 38, and 35 outlier windows in Chhattisgarhi, Chilika, Gojri, and Murrah, respectively. The comparative exome analysis of InDels and subsequent gene ontology revealed unique breed specific genes for milk yield (CAMSAP3), milk composition (CLCN1, NUDT3), fertility (PTGER3) and adaptation (KCNA3, TH) traits. Study provides insight into mechanism of how these breeds have evolved under natural selection, the impact of these events on their respective genomes, and their importance in maintaining purity of these breeds for the traits under study. Additionally, this result will underwrite to the genetic acquaintance of these breeds for breeding application, and in understanding of evolution of these Indian local breeds.

Genomic variation across distribution of Micro-Tom, a model cultivar of tomato (Solanum lycopersicum)

Micro-Tom is a cultivar of tomato (Solanum lycopersicum), which is known as a major crop and model plant in Solanaceae. Micro-Tom has phenotypic traits such as dwarfism, and substantial EMS-mutagenized lines have been reported. After Micro-Tom was generated in Florida, USA, it was distributed to research institutes worldwide and used as a genetic resource. In Japan, the Micro-Tom lines have been genetically fixed; currently, three lines have been re-distributed from three institutes, but many phenotypes among the lines have been observed. We have determined the genome sequence de novo of the Micro-Tom KDRI line, one of the Micro-Tom lines distributed from Kazusa DNA Research Institute (KDRI) in Japan, and have built chromosome-scale pseudomolecules. Genotypes among six Micro-Tom lines, including three in Japan, one in the United States, one in France, and one in Brazil showed phenotypic alternation. Here, we unveiled the swift emergence of genetic diversity in both phenotypes and genotypes within the Micro-Tom genome sequence during its propagation. These findings offer valuable insights crucial for the management of bioresources.

Accurate prediction of quantitative traits with failed SNP calls in canola and maize

In modern plant breeding, genomic selection is becoming the gold standard to select superior genotypes in large breeding populations that are only partially phenotyped. Many breeding programs commonly rely on single-nucleotide polymorphism (SNP) markers to capture genome-wide data for selection candidates. For this purpose, SNP arrays with moderate to high marker density represent a robust and cost-effective tool to generate reproducible, easy-to-handle, high-throughput genotype data from large-scale breeding populations. However, SNP arrays are prone to technical errors that lead to failed allele calls. To overcome this problem, failed calls are often imputed, based on the assumption that failed SNP calls are purely technical. However, this ignores the biological causes for failed calls-for example: deletions-and there is increasing evidence that gene presence-absence and other kinds of genome structural variants can play a role in phenotypic expression. Because deletions are frequently not in linkage disequilibrium with their flanking SNPs, permutation of missing SNP calls can potentially obscure valuable marker-trait associations. In this study, we analyze published datasets for canola and maize using four parametric and two machine learning models and demonstrate that failed allele calls in genomic prediction are highly predictive for important agronomic traits. We present two statistical pipelines, based on population structure and linkage disequilibrium, that enable the filtering of failed SNP calls that are likely caused by biological reasons. For the population and trait examined, prediction accuracy based on these filtered failed allele calls was competitive to standard SNP-based prediction, underlying the potential value of missing data in genomic prediction approaches. The combination of SNPs with all failed allele calls or the filtered allele calls did not outperform predictions with only SNP-based prediction due to redundancy in genomic relationship estimates.

Genomic structural variation: A complex but important driver of human evolution

Structural variants (SVs)-including duplications, deletions, and inversions of DNA-can have significant genomic and functional impacts but are technically difficult to identify and assay compared with single-nucleotide variants. With the aid of new genomic technologies, it has become clear that SVs account for significant differences across and within species. This phenomenon is particularly well-documented for humans and other primates due to the wealth of sequence data available. In great apes, SVs affect a larger number of nucleotides than single-nucleotide variants, with many identified SVs exhibiting population and species specificity. In this review, we highlight the importance of SVs in human evolution by (1) how they have shaped great ape genomes resulting in sensitized regions associated with traits and diseases, (2) their impact on gene functions and regulation, which subsequently has played a role in natural selection, and (3) the role of gene duplications in human brain evolution. We further discuss how to incorporate SVs in research, including the strengths and limitations of various genomic approaches. Finally, we propose future considerations in integrating existing data and biospecimens with the ever-expanding SV compendium propelled by biotechnology advancements.

Multilevel Annotation of Germline MEN1 Variants of Synonymous, Nonsynonymous, and Uncertain Significance in Indian Patients With Sporadic Primary Hyperparathyroidism

Primary hyperparathyroidism (PHPT) is third most common endocrine disorder characterized by hypercalcemia with elevated or nonsuppressed parathyroid hormone levels by parathyroid tumors. Familial PHPT, as part of multiple endocrine type-1, occurs due to the germline mutation in the MEN1 gene. The involvement and the role of germline MEN1 variations in sporadic PHPT of Indian PHPT patients are unknown. Precise classifications of different types of MEN1 variations are fundamental for determining clinical relevance and diagnostic role. This prospective cohort study was performed on 82 patients with PHPT (with no clinical or history of MEN1) who underwent screening for MEN1 variations through Sanger sequencing. Multilevel computational analysis was performed to determine the structure-function relationship of synonymous, nonsynonymous, and variants of uncertain significance (VUS). Of the 82 PHPT patients, 42 (51%) had 26 germline MEN1 variants, including eight nonsynonymous, seven synonymous, nine VUS, one splice site, and one regulatory variation. Five most common germline variations (c.1838A>G, c.1817C>T, c.1525C>A, c.-35A>T, and c.250T>C) were observed in this study. c.-35A>T (5' untranslated region [UTR]) was associated with recurrence of PHPT (odds ratio [OR] = 5.4; p = 0.04) and subsequent detection of other endocrine tumors (OR = 13.6, p = 0.035). c.1525C>A was associated with multi glandular parathyroid tumor (OR = 13.6, p = 0.035). Align-Grantham variation and Grantham deviation (Align-GVGD), functional analysis through hidden Markov MODEL (FATHMM), and MutationTaster analysis reported the disease-specific potential of VUS and synonymous variations. Significant linkage disequilibrium was observed in c.1785G>A and c.1817C>T (r²  = 0.3859, p = 0.0001), c.1475C>G and c.1525C>A (r²  = 0.385, p = 0.0004), and c.1569T>C and c.1838A>G (r²  = 0.488, p = 0.0001). The detection of MEN1 variations, especially those with disease-specific potential, can prompt early screening for other MEN1-related tumors and disease recurrence. © 2022 American Society for Bone and Mineral Research (ASBMR).

Assessment of linkage disequilibrium patterns between structural variants and single nucleotide polymorphisms in three commercial chicken populations

BACKGROUND

Structural variants (SV) are causative for some prominent phenotypic traits of livestock as different comb types in chickens or color patterns in pigs. Their effects on production traits are also increasingly studied. Nevertheless, accurately calling SV remains challenging. It is therefore of interest, whether close-by single nucleotide polymorphisms (SNPs) are in strong linkage disequilibrium (LD) with SVs and can serve as markers. Literature comes to different conclusions on whether SVs are in LD to SNPs on the same level as SNPs to other SNPs. The present study aimed to generate a precise SV callset from whole-genome short-read sequencing (WGS) data for three commercial chicken populations and to evaluate LD patterns between the called SVs and surrounding SNPs. It is thereby the first study that assessed LD between SVs and SNPs in chickens.

RESULTS

The final callset consisted of 12,294,329 bivariate SNPs, 4,301 deletions (DEL), 224 duplications (DUP), 218 inversions (INV) and 117 translocation breakpoints (BND). While average LD between DELs and SNPs was at the same level as between SNPs and SNPs, LD between other SVs and SNPs was strongly reduced (DUP: 40%, INV: 27%, BND: 19% of between-SNP LD). A main factor for the reduced LD was the presence of local minor allele frequency differences, which accounted for 50% of the difference between SNP - SNP and DUP - SNP LD. This was potentially accompanied by lower genotyping accuracies for DUP, INV and BND compared with SNPs and DELs. An evaluation of the presence of tag SNPs (SNP in highest LD to the variant of interest) further revealed DELs to be slightly less tagged by WGS SNPs than WGS SNPs by other SNPs. This difference, however, was no longer present when reducing the pool of potential tag SNPs to SNPs located on four different chicken genotyping arrays.

CONCLUSIONS

The results implied that genomic variance due to DELs in the chicken populations studied can be captured by different SNP marker sets as good as variance from WGS SNPs, whereas separate SV calling might be advisable for DUP, INV, and BND effects.

Ultrasensitive Quantitation of Genomic Chimerism by Single-Molecule Molecular Inversion Probe Capture and High-Throughput Sequencing of Copy Number Deletion Polymorphisms

Genomic chimerism represents co-existing cells with different genotypes and has diagnostic significance in transplant engraftment monitoring, residual cancer detection, and other contexts. We previously described an approach to chimerism detection by interrogating variably present or absent genomic loci using single-molecule molecular inversion probes (smMIPs) and next-generation sequencing, which provided ultrasensitive limits of detection (<1 in 10,000 cells) but was not reliably quantitative. Herein, smMIP testing was modified to accurately quantitate chimeric cells by incorporating copy number neutral control loci for data normalization and computationally modeling cell mixtures from individual-specific genotypes. Data demonstrate precision and accuracy over three orders of magnitude (0.01% to 50% chimerism). Seventy hematopoietic stem cell transplant specimens from single (n = 42) or double (n = 28) donors were evaluated, benchmarking smMIP against conventional variable number tandem repeat (VNTR) analysis and an unrelated, ultrasensitive polymorphism-specific quantitative PCR (PS-qPCR) assay. Quantitative concordance of all three assays was high (P < 0.0005, Pearson correlation coefficient), although smMIP correlated better with VNTR testing than PS-qPCR. smMIP and PS-qPCR collectively identified low-level chimerism in all specimens testing negative by VNTR (n = 41 and n = 45 of 48 specimens, respectively). This work demonstrates the feasibility of smMIP-based chimerism testing for quantitative and ultrasensitive measurement of genomic chimerism at practical levels approaching one in one million cells, and cross-validates the approach.

A chromosome-level genome assembly of an alpine plant Crucihimalaya lasiocarpa provides insights into high-altitude adaptation

It remains largely unknown how plants adapt to high-altitude habitats. Crucihimalaya (Brassicaceae) is an alpine genus occurring in the Qinghai-Tibet Plateau characterized by cold temperatures and strong ultraviolet radiation. Here, we generated a chromosome-level genome for C. lasiocarpa with a total size of 255.8 Mb and a scaffold N50 size of 31.9 Mb. We first examined the karyotype origin of this species and found that the karyotype of five chromosomes resembled the ancestral karyotype of the Brassicaceae family, while the other three showed strong chromosomal structural variations. In combination with the rough genome sequence of another congener (C. himalaica), we found that the significantly expanded gene families and positively selected genes involved in alpine adaptation have occurred since the origin of this genus. Our new findings provide valuable information for the chromosomal karyotype evolution of Brassicaceae and investigations of high-altitude environment adaptation of the genus.

Distinct sequence features underlie microdeletions and gross deletions in the human genome

Microdeletions and gross deletions are important causes (~20%) of human inherited disease and their genomic locations are strongly influenced by the local DNA sequence environment. This notwithstanding, no study has systematically examined their underlying generative mechanisms. Here, we obtained 42,098 pathogenic microdeletions and gross deletions from the Human Gene Mutation Database (HGMD) that together form a continuum of germline deletions ranging in size from 1 to 28,394,429 bp. We analyzed the DNA sequence within 1 kb of the breakpoint junctions and found that the frequencies of non‐B DNA‐forming repeats, GC‐content, and the presence of seven of 78 specific sequence motifs in the vicinity of pathogenic deletions correlated with deletion length for deletions of length ≤30 bp. Further, we found that the presence of DR, GQ, and STR repeats is important for the formation of longer deletions (>30 bp) but not for the formation of shorter deletions (≤30 bp) while significantly (χ², p < 2E−16) more microhomologies were identified flanking short deletions than long deletions (length >30 bp). We provide evidence to support a functional distinction between microdeletions and gross deletions. Finally, we propose that a deletion length cut‐off of 25–30 bp may serve as an objective means to functionally distinguish microdeletions from gross deletions.

LD-CNV: rapid and simple discovery of chromosomal translocations using linkage disequilibrium between copy number variable loci

Large-scale structural variations, such as chromosomal translocations, can have profound effects on fitness and phenotype, but are difficult to identify and characterize. Here, we describe a simple and effective method aimed at identifying translocations using only the dosage of sequence reads mapped on the reference genome. We binned reads on genomic segments sized according to sequencing coverage and identified instances when copy number segregated in populations. For each dosage-polymorphic 1 Mb bin, we tested independence, effectively an apparent linkage disequilibrium (LD), with other variable bins. In nine potato (Solanum tuberosum) dihaploid families translocations affecting pericentromeric regions were common and in two cases were due to genomic misassembly. In two populations, we found evidence for translocation affecting euchromatic arms. In cv. PI 310467, a nonreciprocal translocation between chromosomes (chr.) 7 and 8 resulted in a 5-3 copy number change affecting several Mb at the respective chromosome tips. In cv. "Alca Tarma," the terminal arm of chr. 4 translocated to the tip of chr. 1. Using oligonucleotide-based fluorescent in situ hybridization painting probes (oligo-FISH), we tested and confirmed the predicted arrangement in PI 310467. In 192 natural accessions of Arabidopsis thaliana, dosage haplotypes tended to vary continuously and resulted in higher noise, while apparent LD between pericentromeric regions suggested the effect of repeats. This method, LD-CNV, should be useful in species where translocations are suspected because it tests linkage without the need for genotyping.

Analysis of Genetic Variants Associated with Levels of Immune Modulating Proteins for Impact on Alzheimer's Disease Risk Reveal a Potential Role for SIGLEC14

Genome-wide association studies (GWAS) have identified immune-related genes as risk factors for Alzheimer’s disease (AD), including TREM2 and CD33, frequently passing a stringent false-discovery rate. These genes either encode or signal through immunomodulatory tyrosine-phosphorylated inhibitory motifs (ITIMs) or activation motifs (ITAMs) and govern processes critical to AD pathology, such as inflammation and amyloid phagocytosis. To investigate whether additional ITIM and ITAM-containing family members may contribute to AD risk and be overlooked due to the stringent multiple testing in GWAS, we combined protein quantitative trait loci (pQTL) data from a recent plasma proteomics study with AD associations in a recent GWAS. We found that pQTLs for genes encoding ITIM/ITAM family members were more frequently associated with AD than those for non-ITIM/ITAM genes. Further testing of one family member, SIGLEC14 which encodes an ITAM, uncovered substantial copy number variations, identified an SNP as a proxy for gene deletion, and found that gene expression correlates significantly with gene deletion. We also found that SIGLEC14 deletion increases the expression of SIGLEC5, an ITIM. We conclude that many genes in this ITIM/ITAM family likely impact AD risk, and that complex genetics including copy number variation, opposing function of encoded proteins, and coupled gene expression may mask these AD risk associations at the genome-wide level.

Prioritization of schizophrenia risk genes from GWAS results by integrating multi-omics data

Schizophrenia (SCZ) is a polygenic disease with a heritability approaching 80%. Over 100 SCZ-related loci have so far been identified by genome-wide association studies (GWAS). However, the risk genes associated with these loci often remain unknown. We present a new risk gene predictor, rGAT-omics, that integrates multi-omics data under a Bayesian framework by combining the Hotelling and Box-Cox transformations. The Bayesian framework was constructed using gene ontology, tissue-specific protein-protein networks, and multi-omics data including differentially expressed genes in SCZ and controls, distance from genes to the index single-nucleotide polymorphisms (SNPs), and de novo mutations. The application of rGAT-omics to the 108 loci identified by a recent GWAS study of SCZ predicted 103 high-risk genes (HRGs) that explain a high proportion of SCZ heritability (Enrichment = 43.44 and [Formula: see text]). HRGs were shown to be significantly ([Formula: see text]) enriched in genes associated with neurological activities, and more likely to be expressed in brain tissues and SCZ-associated cell types than background genes. The predicted HRGs included 16 novel genes not present in any existing databases of SCZ-associated genes or previously predicted to be SCZ risk genes by any other method. More importantly, 13 of these 16 genes were not the nearest to the index SNP markers, and them would have been difficult to identify as risk genes by conventional approaches while ten out of the 16 genes are associated with neurological functions that make them prime candidates for pathological involvement in SCZ. Therefore, rGAT-omics has revealed novel insights into the molecular mechanisms underlying SCZ and could provide potential clues to future therapies.

The Copy Number Variation of OsMTD1 Regulates Rice Plant Architecture

Copy number variation (CNV) may have phenotypic effects by altering the expression level of the gene(s) or regulatory element(s) contained. It is believed that CNVs play pivotal roles in controlling plant architecture and other traits in plant. However, the effects of CNV contributing to special traits remain largely unknown. Here we report a CNV involved in rice architecture by modulating tiller number and leaf angle. In the genome of Oryza sativa ssp. japonica cv. Nipponbare, we found a locus Loc_Os08g34249 is derived from a 13,002-bp tandem duplication in the nearby region of OsMTD1, a gene regulating tillering in rice. Further survey of 230 rice cultivars showed that the duplication occurred in only 13 japonica rice cultivars. Phenotypic investigation indicated that this CNV region may contribute to tiller number. Moreover, we revealed that OsMTD1 not only influences rice tiller number and leaf angle, but also represses pri-miR156f transcription in the CNV region. Intriguingly, this CNV performs function through both the dosage and position effects on OsMTD1 and pri-miR156f. Thus, our work identified a CNV and revealed a molecular regulatory basis for its effects on plant architecture, implying this CNV may possess importance and application potential in molecular breeding in rice.

Whole-genome sequence diversity and association analysis of 198 soybean accessions in mini-core collections

We performed whole-genome Illumina resequencing of 198 accessions to examine the genetic diversity and facilitate the use of soybean genetic resources and identified 10 million single nucleotide polymorphisms and 2.8 million small indels. Furthermore, PacBio resequencing of 10 accessions was performed, and a total of 2,033 structure variants were identified. Genetic diversity and structure analysis congregated the 198 accessions into three subgroups (Primitive, World, and Japan) and showed the possibility of a long and relatively isolated history of cultivated soybean in Japan. Additionally, the skewed regional distribution of variants in the genome, such as higher structural variations on the R gene clusters in the Japan group, suggested the possibility of selective sweeps during domestication or breeding. A genome-wide association study identified both known and novel causal variants on the genes controlling the flowering period. Novel candidate causal variants were also found on genes related to the seed coat colour by aligning together with Illumina and PacBio reads. The genomic sequences and variants obtained in this study have immense potential to provide information for soybean breeding and genetic studies that may uncover novel alleles or genes involved in agronomically important traits.

A map of copy number variations in the Tunisian population: a valuable tool for medical genomics in North Africa

Copy number variation (CNV) is considered as the most frequent type of structural variation in the human genome. Some CNVs can act on human phenotype diversity, encompassing rare Mendelian diseases and genomic disorders. The North African populations remain underrepresented in public genetic databases in terms of single-nucleotide variants as well as for larger genomic mutations. In this study, we present the first CNV map for a North African population using the Affymetrix Genome-Wide SNP (single-nucleotide polymorphism) array 6.0 array genotyping intensity data to call CNVs in 102 Tunisian healthy individuals. Two softwares, PennCNV and Birdsuite, were used to call CNVs in order to provide reliable data. Subsequent bioinformatic analyses were performed to explore their features and patterns. The CNV map of the Tunisian population includes 1083 CNVs spanning 61.443 Mb of the genome. The CNV length ranged from 1.017 kb to 2.074 Mb with an average of 56.734 kb. Deletions represent 57.43% of the identified CNVs, while duplications and the mixed loci are less represented. One hundred and three genes disrupted by CNVs are reported to cause 155 Mendelian diseases/phenotypes. Drug response genes were also reported to be affected by CNVs. Data on genes overlapped by deletions and duplications segments and the sequence properties in and around them also provided insights into the functional and health impacts of CNVs. These findings represent valuable clues to genetic diversity and personalized medicine in the Tunisian population as well as in the ethnically similar populations from North Africa.

Transposable elements have contributed human regulatory regions that are activated upon bacterial infection

Transposable elements (TEs) are increasingly recognized as important contributors to mammalian regulatory systems. For instance, they have been shown to play a role in the human interferon response, but their involvement in other mechanisms of immune cell activation remains poorly understood. Here, we investigated the profile of accessible chromatin enhanced in stimulated human macrophages using ATAC-seq to assess the role of different TE subfamilies in regulating gene expression following an immune response. We found that both previously identified and new repeats belonging to the MER44, THE1, Tigger3 and MLT1 families provide 14 subfamilies that are enriched in differentially accessible chromatin and found near differentially expressed genes. These TEs also harbour binding motifs for several candidate transcription factors, including important immune regulators AP-1 and NF-κB, present in 96% of accessible MER44B and 83% of THE1C instances, respectively. To more directly assess their regulatory potential, we evaluated the presence of these TEs in regions putatively affecting gene expression, as defined by quantitative trait locus (QTL) analysis, and found that repeats are also contributing to accessible elements near QTLs. Together, these results suggest that a number of TE families have contributed to the regulation of gene expression in the context of the immune response to infection in humans. This article is part of a discussion meeting issue 'Crossroads between transposons and gene regulation'.

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.

Rare copy number variants in over 100,000 European ancestry subjects reveal multiple disease associations

Copy number variants (CNVs) are suggested to have a widespread impact on the human genome and phenotypes. To understand the role of CNVs across human diseases, we examine the CNV genomic landscape of 100,028 unrelated individuals of European ancestry, using SNP and CGH array datasets. We observe an average CNV burden of ~650 kb, identifying a total of 11,314 deletion, 5625 duplication, and 2746 homozygous deletion CNV regions (CNVRs). In all, 13.7% are unreported, 58.6% overlap with at least one gene, and 32.8% interrupt coding exons. These CNVRs are significantly more likely to overlap OMIM genes (2.94-fold), GWAS loci (1.52-fold), and non-coding RNAs (1.44-fold), compared with random distribution (P < 1 × 10⁻³). We uncover CNV associations with four major disease categories, including autoimmune, cardio-metabolic, oncologic, and neurological/psychiatric diseases, and identify several drug-repurposing opportunities. Our results demonstrate robust frequency definition for large-scale rare variant association studies, identify CNVs associated with major disease categories, and illustrate the pleiotropic impact of CNVs in human disease.

Associations of copy number variations (CNVs) with complex traits are challenging to study because of their low frequency. Here, the authors analyse SNP array and array comparative genomic hybridization data of 100,028 individuals and report their associations with immune-related, cardiometabolic and neuropsychiatric diseases as well as cancer.

Combinatorial Detection Algorithm for Copy Number Variations Using High-throughput Sequencing Reads

Copy number variation (CNV) is a prevalent kind of genetic structural variation which leads to an abnormal number of copies of large genomic regions, such as gain or loss of DNA segments larger than 1[Formula: see text]kb. CNV exists not only in human genome but also in plant genome. Current researches have testified that CNV is associated with many complex diseases. In this paper, guanine-cytosine (GC) bias, mappability and their effect on read depth signals in sequencing data are discussed first. Subsequently, a new correction method for GC bias and an improved combinatorial detection algorithm for CNV using high-throughput sequencing reads based on hidden Markov model (CNV-HMM) are proposed. The corrected read depth signals have lower correlation with GC content, mappability of reads and the width of analysis window. Then we create a hidden Markov model which maps the reads onto the reference genome and records the unmapped reads. The unmapped reads are counted and normalized. The CNV-HMM detects the abnormal signal of read count and gains the candidate CNVs using the expectation maximization (EM) algorithm. Finally, we filter the candidate CNVs using split reads to promote the performance of our algorithm. The experiment result indicates that the CNV-HMM algorithm has higher accuracy and sensitivity for CNVs detection than most current detection algorithms.

Copy number variation is highly correlated with differential gene expression: a pan-cancer study

BACKGROUND

Cancer is a heterogeneous disease with many genetic variations. Lines of evidence have shown copy number variations (CNVs) of certain genes are involved in development and progression of many cancers through the alterations of their gene expression levels on individual or several cancer types. However, it is not quite clear whether the correlation will be a general phenomenon across multiple cancer types.

METHODS

In this study we applied a bioinformatics approach integrating CNV and differential gene expression mathematically across 1025 cell lines and 9159 patient samples to detect their potential relationship.

RESULTS

Our results showed there is a close correlation between CNV and differential gene expression and the copy number displayed a positive linear influence on gene expression for the majority of genes, indicating that genetic variation generated a direct effect on gene transcriptional level. Another independent dataset is utilized to revalidate the relationship between copy number and expression level. Further analysis show genes with general positive linear influence on gene expression are clustered in certain disease-related pathways, which suggests the involvement of CNV in pathophysiology of diseases.

CONCLUSIONS

This study shows the close correlation between CNV and differential gene expression revealing the qualitative relationship between genetic variation and its downstream effect, especially for oncogenes and tumor suppressor genes. It is of a critical importance to elucidate the relationship between copy number variation and gene expression for prevention, diagnosis and treatment of cancer.

Established and emerging strategies to crack the genetic code of obesity

Tremendous progress has been made in the genetic elucidation of obesity over the past two decades, driven largely by technological, methodological and organizational innovations. Current strategies for identifying obesity-predisposing loci/genes, including cytogenetics, linkage analysis, homozygosity mapping, admixture mapping, candidate gene studies, genome-wide association studies, custom genotyping arrays, whole-exome sequencing and targeted exome sequencing, have achieved differing levels of success, and the identified loci in aggregate explain only a modest fraction of the estimated heritability of obesity. This review outlines the successes and limitations of these approaches and proposes novel strategies, including the use of exceptionally large sample sizes, the study of diverse ethnic groups and deep phenotypes and the application of innovative methods and study designs, to identify the remaining obesity-predisposing genes. The use of both established and emerging strategies has the potential to crack the genetic code of obesity in the not-too-distant future. The resulting knowledge is likely to yield improvements in obesity prediction, prevention and care.

Simultaneous detection of target CNVs and SNVs of thalassemia by multiplex PCR and next‑generation sequencing

Thalassemia is caused by complex mechanisms, including copy number variants (CNVs) and single nucleotide variants (SNVs). The CNV types of α‑thalassemia are typically detected by gap‑polymerase chain reaction (PCR). The SNV types are detected by Sanger sequencing. In the present study, a novel method was developed that simultaneously detects CNVs and SNVs by multiplex PCR and next‑generation sequencing (NGS). To detect CNVs, 33 normal samples were used as a cluster of control values to build a baseline, and the A, B, C, and D ratios were developed to evaluate‑SEA, ‑α4.2, ‑α3.7, and compound or homozygous CNVs, respectively. To detect other SNVs, sequencing data were analyzed using the system's software and annotated using Annovar software. In a test of performance, 128 patients with thalassemia were detected using the method developed and were confirmed by Sanger sequencing and gap‑PCR. Four different CNV types were clearly distinguished by the developed algorithm, with ‑SEA, ‑α3.7, ‑α4.2, and compound or homozygous deletions. The sensitivities for each CNV type were 96.72% (59/61), 97.37% (37/38), 83.33% (10/12) and 95% (19/20), and the specificities were 93.94% (32/33), 93.94% (32/33), 100% (33/33) and 100% (33/33), respectively. The SNVs detected were consistent with those of the Sanger sequencing.

The non-random patterns of genetic variation induced by asymmetric somatic hybridization in wheat

BACKGROUND

Asymmetric somatic hybridization is an efficient crop breeding approach by introducing several exogenous chromatin fragments, which leads to genomic shock and therefore induces genome-wide genetic variation. However, the fundamental question concerning the genetic variation such as whether it occurs randomly and suffers from selection pressure remains unknown.

RESULTS

Here, we explored this issue by comparing expressed sequence tags of a common wheat cultivar and its asymmetric somatic hybrid line. Both nucleotide substitutions and indels (insertions and deletions) had lower frequencies in coding sequences than in un-translated regions. The frequencies of nucleotide substitutions and indels were both comparable between chromosomes with and without introgressed fragments. Nucleotide substitutions distributed unevenly and were preferential to indel-flanking sequences, and the frequency of nucleotide substitutions at 5'-flanking sequences of indels was obviously higher in chromosomes with introgressed fragments than in those without exogenous fragment. Nucleotide substitutions and indels both had various frequencies among seven groups of allelic chromosomes, and the frequencies of nucleotide substitutions were strongly negatively correlative to those of indels. Among three sets of genomes, the frequencies of nucleotide substitutions and indels were both heterogeneous, and the frequencies of nucleotide substitutions exhibited drastically positive correlation to those of indels.

CONCLUSIONS

Our work demonstrates that the genetic variation induced by asymmetric somatic hybridization is attributed to both whole genomic shock and local chromosomal shock, which is a predetermined and non-random genetic event being closely associated with selection pressure. Asymmetric somatic hybrids provide a worthwhile model to further investigate the nature of genomic shock induced genetic variation.

The coexistence of copy number variations (CNVs) and single nucleotide polymorphisms (SNPs) at a locus can result in distorted calculations of the significance in associating SNPs to disease

With the recent advance in genome-wide association studies (GWAS), disease-associated single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) have been extensively reported. Accordingly, the issue of incorrect identification of recombination events that can induce the distortion of multi-allelic or hemizygous variants has received more attention. However, the potential distorted calculation bias or significance of a detected association in a GWAS due to the coexistence of CNVs and SNPs in the same genomic region may remain under-recognized. Here we performed the association study within a congenital scoliosis (CS) cohort whose genetic etiology was recently elucidated as a compound inheritance model, including mostly one rare variant deletion CNV null allele and one common variant non-coding hypomorphic haplotype of the TBX6 gene. We demonstrated that the existence of a deletion in TBX6 led to an overestimation of the contribution of the SNPs on the hypomorphic allele. Furthermore, we generalized a model to explain the calculation bias, or distorted significance calculation for an association study, that can be 'induced' by CNVs at a locus. Meanwhile, overlapping between the disease-associated SNPs from published GWAS and common CNVs (overlap 10%) and pathogenic/likely pathogenic CNVs (overlap 99.69%) was significantly higher than the random distribution (p < 1 × 10^-6 and p = 0.034, respectively), indicating that such co-existence of CNV and SNV alleles might generally influence data interpretation and potential outcomes of a GWAS. We also verified and assessed the influence of colocalizing CNVs to the detection sensitivity of disease-associated SNP variant alleles in another adolescent idiopathic scoliosis (AIS) genome-wide association study. We proposed that detecting co-existent CNVs when evaluating the association signals between SNPs and disease traits could improve genetic model analyses and better integrate GWAS with robust Mendelian principles.

Ultrasensitive Detection of Chimerism by Single-Molecule Molecular Inversion Probe Capture and High-Throughput Sequencing of Copy Number Deletion Polymorphisms

BACKGROUND

Genomic chimerism, the co-occurrence of cells from different genetic origins, provides important diagnostic information in diverse clinical contexts, including graft injury detection and longitudinal surveillance of hematopoietic stem cell transplantation patients, but existing assays are limiting. Here we applied single-molecule molecular inversion probes (smMIPs), a high-throughput sequencing technology combining multiplexed target capture with read quantification mediated by unique molecular identifiers, to detect chimerism based on the presence or absence of polymorphic genomic loci.

METHODS

We designed a 159-smMIP panel targeting 40 autosomal regions of frequent homozygous deletion across human populations and 2 sex-linked loci. We developed methods for detecting and quantitating loci absent from 1 cell population but present in another, which could be used to sensitively identify chimeric cell populations.

RESULTS

Unrelated individuals and first-degree relatives were highly polymorphic across the loci examined. Using synthetic DNA mixtures, limits of detection of at least 1 in 10000 chimeric cells were demonstrated without prior knowledge of genotypes, and mixtures of up to 4 separate donors could be deconvoluted. Quantitative linearity over 4 orders of magnitude and false-positive rates <1 in 85000 events were achieved. Eleven of 11 posttransplant clinical specimens from patients with hematological malignancies testing positive for residual cancer by conventional methods had detectable chimeric populations by smMIP, whereas 11 of 11 specimens testing negative by conventional methods were low-positive for chimerism by smMIP.

CONCLUSIONS

smMIPs are scalable to high sensitivity and large numbers of informative markers, enabling ultrasensitive chimerism detection for many clinical purposes.

Computational Methods for the Analysis of Array Comparative Genomic Hybridization

Array comparative genomic hybridization (array CGH) is a technique for assaying the copy number status of cancer genomes. The widespread use of this technology has lead to a rapid accumulation of high throughput data, which in turn has prompted the development of computational strategies for the analysis of array CGH data. Here we explain the principles behind array image processing, data visualization and genomic profile analysis, review currently available software packages, and raise considerations for future software development.

Computational Prediction of Position Effects of Apparently Balanced Human Chromosomal Rearrangements

Interpretation of variants of uncertain significance, especially chromosomal rearrangements in non-coding regions of the human genome, remains one of the biggest challenges in modern molecular diagnosis. To improve our understanding and interpretation of such variants, we used high-resolution three-dimensional chromosomal structural data and transcriptional regulatory information to predict position effects and their association with pathogenic phenotypes in 17 subjects with apparently balanced chromosomal abnormalities. We found that the rearrangements predict disruption of long-range chromatin interactions between several enhancers and genes whose annotated clinical features are strongly associated with the subjects' phenotypes. We confirm gene-expression changes for a couple of candidate genes to exemplify the utility of our analysis of position effect. These results highlight the important interplay between chromosomal structure and disease and demonstrate the need to utilize chromatin conformational data for the prediction of position effects in the clinical interpretation of non-coding chromosomal rearrangements.

MTUS1, a gene encoding angiotensin-II type 2 (AT2) receptor-interacting proteins, in health and disease, with special emphasis on its role in carcinogenesis

Loss of tumor suppressor activity is a frequent event in the formation and progression of tumors and has been listed as an important hallmark of cancers. Microtubule-Associated Scaffold Protein 1 (MTUS1) is a candidate tumor suppressor gene which is reported to be frequently down-regulated in a variety of human cancers including pancreas, colon, bladder, head-and-neck, ovarian, breast cancers, gastric, lung cancers. It is also reported to be implicated in several types of pathologies such as cardiac hypertrophy, atherosclerosis, and SLE-like lymphoproliferative diseases. Moreover, MTUS1-encoded proteins are shown to be involved in the regulation of vital cellular processes such as proliferation, differentiation, DNA repair, inflammation, vascular remodeling and senescence. However, the current knowledge is very limited about the role of this gene in human cancers as well as other type diseases. Besides, there is no literature report which summarizes and criticizes the importance of MTUS1 in the cellular processes, especially in the processes of carcinogenesis. Accordingly, in this comprehensive review, we tried to shed light on the role of tumor suppressor MTUS1/ATIP in health and disease, putting special emphasis on its role in the development and progression of human cancers as well as associated molecular mechanisms and the reasons behind MTUS1/ATIP deficiency, which have been not well documented previously.

A copy number variation in PKD1L2 is associated with colorectal cancer predisposition in korean population

Recently reported genome-wide association studies have identified more than 20 common low-penetrance colorectal cancer (CRC) susceptibility loci. Recent studies have reported that copy number variations (CNVs) are considered important human genomic variants related to cancer, while the contribution of CNVs remains unclear. We performed array comparative genomic hybridization (aCGH) in 36 CRC patients and 47 controls. Using breakpoint PCR, we confirmed the breakpoint of the PKD1L2 deletion region. High frequency of PKD1L2 CNV was observed in CRC cases. We validated the association between PKD1L2 variation and CRC risk in 1,874 cases and 2,088 controls (OR = 1.44, 95% CI = 1.04-1.98, p = 0.028). Additionally, PKD1L2 CNV is associated with increased CRC risk in patients younger than 50 years (OR = 2.14, 95% CI 1.39-3.30, p = 5.8 × 10^-4 ). In subgroup analysis according to body mass index (BMI), we found that the CN loss of PKD1L2 with BMI above or equal to 25 exhibited a significant increase in CRC risk (OR = 2.29, 95% CI 1.29-4.05, p = 0.005). PKD1L2 CNV with BMI above or equal to 25 and age below 50 is associated with a remarkably increased risk of colorectal cancer (OR = 5.24, 95% CI 2.36-11.64, p= 4.8 × 10^-5 ). Moreover, we found that PKD1L2 variation in obese patients (BMI ≥ 25) was associated with poor survival rate (p = 0.026). Our results suggest that the common PKD1L2 CNV is associated with CRC, and PKD1L2 CNV with high BMI and/or age below 50 exhibited a significant increased risk of CRC. In obese patients, PKD1L2 variation was associated with poor survival.

Differential frequency of NKG2C/KLRC2 deletion in distinct African populations and susceptibility to Trachoma: a new method for imputation of KLRC2 genotypes from SNP genotyping data

NKG2C is an activating receptor that is preferentially expressed on natural killer (NK) cells. The gene encoding NKG2C (killer cell lectin-like receptor C2, KLRC2) is present at different copy numbers in the genomes of different individuals. Deletion at the NKG2C locus was investigated in a case-control study of 1522 individuals indigenous to East- and West-Africa and the association with the ocular Chlamydia trachomatis infection and its sequelae was explored. The frequency of homozygous KLRC2 deletion was 13.7 % in Gambians and 4.7 % in Tanzanians. A significantly higher frequency of the deletion allele was found in West-Africans from the Gambia and Guinea-Bissau (36.2 % p = 2.105 × 10(-8), 26.8 % p = 0.050; respectively) in comparison to East-African Tanzanians where the frequency of the deletion is comparable to other human populations (20.9 %). We found no evidence for an association between the numbers of KLRC2 gene copies and the clinical manifestations of trachoma (follicular trachoma or conjunctival scarring). A new method for imputation of KLRC2 genotypes from single nucleotide polymorphism (SNP) data in 2621 individuals from the Gambia further confirmed these results. Our data suggest that NKG2C does not play a major role in trachomatous disease. We found that the deletion allele is present at different frequencies in different populations but the reason behind these differences is currently not understood. The new method offers the potential to use SNP arrays from genome wide association studies to study the frequency of KLRC2 deletion in other populations and its association with other diseases.

How far from the SNP may the causative genes be?

While GWAS identify many disease-associated SNPs, using them to decipher disease mechanisms is hindered by the difficulty in mapping SNPs to genes. Most SNPs are in non-coding regions and it is often hard to identify the genes they implicate. To explore how far the SNP may be from the affected genes we used a pathway-based approach. We found that affected genes are often up to 2 Mbps away from the associated SNP, and are not necessarily the closest genes to the SNP. Existing approaches for mapping SNPs to genes leave many SNPs unmapped to genes and reveal only 86 significant phenotype-pathway associations for all known GWAS hits combined. Using the pathway-based approach we propose here allows mapping of virtually all SNPs to genes and reveals 435 statistically significant phenotype-pathway associations. In search for mechanisms that may explain the relationships between SNPs and distant genes, we found that SNPs that are mapped to distant genes have significantly more large insertions/deletions around them than other SNPs, suggesting that these SNPs may sometimes be markers for large insertions/deletions that may affect large genomic regions.

A genome-wide assessment of rare copy number variants in colorectal cancer

Colorectal cancer (CRC) is a complex disease with an estimated heritability of approximately 35%. However, known CRC-related common single nucleotide polymorphisms (SNPs) can only explain ~0.65% of the heritability. This “missing heritability” may be explained partially by rare copy number variants (CNVs). In this study, we performed a genome-wide scan using Illumina Human-Omni Express BeadChip, 694 sporadic CRC cases and 1641 controls were eventually included in our analysis after quality control. The global burden analysis revealed a 1.53-fold excess of rare CNVs in CRC cases compared with controls (P < 1 × 10⁻⁶), and the difference being more pronounced for genic rare CNVs and CNVs overlapped with coding regions (1.65-fold and 1.84-fold, respectively, both P < 1 × 10⁻⁶). Interestingly, both the cases in the lowest and middle tertile of age carried a higher burden of rare CNVs comparing to the highest tertile. Furthermore, 639 CNV-disrupted genes exclusive to CRC cases were found to be significantly enriched in gene ontology (GO) terms concerning nucleosome assembly and olfactory receptor activity. Our study was the first to evaluate the burden of rare CNVs in sporadic CRC and suggested that rare CNVs contributed to the missing heritability of CRC.

Sensitive Tumorigenic Potential Evaluation of Adult Human Multipotent Neural Cells Immortalized by hTERT Gene Transduction

Stem cells and therapeutic genes are emerging as a new therapeutic approach to treat various neurodegenerative diseases with few effective treatment options. However, potential formation of tumors by stem cells has hampered their clinical application. Moreover, adequate preclinical platforms to precisely test tumorigenic potential of stem cells are controversial. In this study, we compared the sensitivity of various animal models for in vivo stem cell tumorigenicity testing to identify the most sensitive platform. Then, tumorigenic potential of adult human multipotent neural cells (ahMNCs) immortalized by the human telomerase reverse transcriptase (hTERT) gene was examined as a stem cell model with therapeutic genes. When human glioblastoma (GBM) cells were injected into adult (4-6-week-old) Balb/c-nu, adult NOD/SCID, adult NOG, or neonate (1-2-week-old) NOG mice, the neonate NOG mice showed significantly faster tumorigenesis than that of the other groups regardless of intracranial or subcutaneous injection route. Two kinds of ahMNCs (682TL and 779TL) were primary cultured from surgical samples of patients with temporal lobe epilepsy. Although the ahMNCs were immortalized by lentiviral hTERT gene delivery (hTERT-682TL and hTERT-779TL), they did not form any detectable masses, even in the most sensitive neonate NOG mouse platform. Moreover, the hTERT-ahMNCs had no gross chromosomal abnormalities on a karyotype analysis. Taken together, our data suggest that neonate NOG mice could be a sensitive animal platform to test tumorigenic potential of stem cell therapeutics and that ahMNCs could be a genetically stable stem cell source with little tumorigenic activity to develop regenerative treatments for neurodegenerative diseases.

Assessment of PAX6 alleles in 66 families with aniridia

We report on PAX6 alleles associated with a clinical diagnosis of classical aniridia in 81 affected individuals representing 66 families. Allelic variants expected to affect PAX6 function were identified in 61 families (76 individuals). Ten cases of sporadic aniridia (10 families) had complete (8 cases) or partial (2 cases) deletion of the PAX6 gene. Sequence changes that introduced a premature termination codon into the open reading frame of PAX6 occurred in 47 families (62 individuals). Three individuals with sporadic aniridia (three families) had sequence changes (one deletion, two run-on mutations) expected to result in a C-terminal extension. An intronic deletion of unknown functional significance was detected in one case of sporadic aniridia (one family), but not in unaffected relatives. Within these 61 families, single nucleotide substitutions accounted for 30/61 (49%), indels for 23/61 (38%), and complete deletion of the PAX6 locus for 8/61 (13%). In five cases of sporadic aniridia (five families), no disease-causing mutation in the coding region was detected. In total, 23 unique variants were identified that have not been reported in the Leiden Open Variation Database (LOVD) database. Within the group assessed, 92% had sequence changes expected to reduce PAX6 function, confirming the primacy of PAX6 haploinsufficiency as causal for aniridia.

A fast and simple method for detecting and quantifying donor-derived cell-free DNA in sera of solid organ transplant recipients as a biomarker for graft function

Timely detection of graft rejection is an important issue in the follow-up care after solid organ transplantation. Until now, biopsy has been considered the “gold standard” in the diagnosis of graft rejection. However, non-invasive tests such as monitoring the levels of cell-free DNA (cfDNA) as a sensitive biomarker for graft integrity have attracted increasing interest. The rationale of this approach is that a rejected organ will lead to a significant release of donor-derived cfDNA, which can be detected in the serum of the transplant recipient.

We have developed a novel quantitative real-time PCR (qPCR) approach for detecting an increase of donor-derived cfDNA in the recipient’s serum. Common insertion/deletion (InDel) genetic polymorphisms, which differ between donor and recipient, are targeted in our qPCR assay. In contrast to some other strategies, no specific donor/recipient constellations such as certain gender combinations or human leukocyte antigen (HLA) discrepancies are required for the application of our test.

The method was first validated with serial dilutions of serum mixtures obtained from healthy blood donors and then used to determine donor-derived cfDNA levels in patients’ sera within the first 3 days after their kidney transplantation had been performed.

Our method represents a universally applicable, simple and cost-effective tool which can potentially be used to detect graft dysfunction in transplant recipients.

Genome-Wide Study of Structural Variants in Bovine Holstein, Montbéliarde and Normande Dairy Breeds

High-throughput sequencing technologies have offered in recent years new opportunities to study genome variations. These studies have mostly focused on single nucleotide polymorphisms, small insertions or deletions and on copy number variants. Other structural variants, such as large insertions or deletions, tandem duplications, translocations, and inversions are less well-studied, despite that some have an important impact on phenotypes. In the present study, we performed a large-scale survey of structural variants in cattle. We report the identification of 6,426 putative structural variants in cattle extracted from whole-genome sequence data of 62 bulls representing the three major French dairy breeds. These genomic variants affect DNA segments greater than 50 base pairs and correspond to deletions, inversions and tandem duplications. Out of these, we identified a total of 547 deletions and 410 tandem duplications which could potentially code for CNVs. Experimental validation was carried out on 331 structural variants using a novel high-throughput genotyping method. Out of these, 255 structural variants (77%) generated good quality genotypes and 191 (75%) of them were validated. Gene content analyses in structural variant regions revealed 941 large deletions removing completely one or several genes, including 10 single-copy genes. In addition, some of the structural variants are located within quantitative trait loci for dairy traits. This study is a pan-genome assessment of genomic variations in cattle and may provide a new glimpse into the bovine genome architecture. Our results may also help to study the effects of structural variants on gene expression and consequently their effect on certain phenotypes of interest.

The impact of human copy number variation on gene expression

Recent years have witnessed a flurry of important technological and methodological developments in the discovery and analysis of copy number variations (CNVs), which are increasingly enabling the systematic evaluation of their impact on a broad range of phenotypes from molecular-level (intermediate) traits to higher-order clinical phenotypes. Like single nucleotide variants in the human genome, CNVs have been linked to complex traits in humans, including disease and drug response. These recent developments underscore the importance of incorporating complex forms of genetic variation into disease mapping studies and promise to transform our understanding of genome function and the genetic basis of disease. Here we review some of the findings that have emerged from transcriptome studies of CNVs facilitated by the rapid advances in -omics technologies and corresponding methodologies.

A decade of structural variants: description, history and methods to detect structural variation

In the past decade, the view on genomic structural variation (SV) has been changed completely. SVs, previously considered rare events, are now recognized as the largest source of interindividual genetic variation affecting more bases than single nucleotide polymorphisms, variable number of tandem repeats and other small genetic variants. They have also been shown to play a role in phenotypic variation and in disease. In this review, the authors will provide an introduction to SV; a short historical perspective on the research of this source of genomic variation; a description of the types of structural variants, and on how they may have arisen; and an overview on methods of detecting structural variants, focusing on the analysis of high-throughput sequencing data.

Haplotype phasing and inheritance of copy number variants in nuclear families

DNA copy number variants (CNVs) that alter the copy number of a particular DNA segment in the genome play an important role in human phenotypic variability and disease susceptibility. A number of CNVs overlapping with genes have been shown to confer risk to a variety of human diseases thus highlighting the relevance of addressing the variability of CNVs at a higher resolution. So far, it has not been possible to deterministically infer the allelic composition of different haplotypes present within the CNV regions. We have developed a novel computational method, called PiCNV, which enables to resolve the haplotype sequence composition within CNV regions in nuclear families based on SNP genotyping microarray data. The algorithm allows to i) phase normal and CNV-carrying haplotypes in the copy number variable regions, ii) resolve the allelic copies of rearranged DNA sequence within the haplotypes and iii) infer the heritability of identified haplotypes in trios or larger nuclear families. To our knowledge this is the first program available that can deterministically phase null, mono-, di-, tri- and tetraploid genotypes in CNV loci. We applied our method to study the composition and inheritance of haplotypes in CNV regions of 30 HapMap Yoruban trios and 34 Estonian families. For 93.6% of the CNV loci, PiCNV enabled to unambiguously phase normal and CNV-carrying haplotypes and follow their transmission in the corresponding families. Furthermore, allelic composition analysis identified the co-occurrence of alternative allelic copies within 66.7% of haplotypes carrying copy number gains. We also observed less frequent transmission of CNV-carrying haplotypes from parents to children compared to normal haplotypes and identified an emergence of several de novo deletions and duplications in the offspring.

Identification and functional characterization of copy number variations in diverse chicken breeds

Background

The detection and functional characterization of genomic structural variations are important for understanding the landscape of genetic variation in the chicken. A recently recognized aspect of genomic structural variation, called copy number variation (CNV), is gaining interest in chicken genomic studies. The aim of the present study was to investigate the pattern and functional characterization of CNVs in five characteristic chicken breeds, which will be important for future studies associating phenotype with chicken genome architecture.

Results

Using a commercial 385 K array-based comparative genomic hybridization (aCGH) genome array, we performed CNV discovery using 10 chicken samples from four local Chinese breeds and the French breed Houdan chicken. The female Anka broiler was used as a reference. A total of 281 copy number variation regions (CNVR) were identified, covering 12.8 Mb of polymorphic sequences or 1.07% of the entire chicken genome. The functional annotation of CNVRs indicated that these regions completely or partially overlapped with 231 genes and 1032 quantitative traits loci, suggesting these CNVs have important functions and might be promising resources for exploring differences among various breeds. In addition, we employed quantitative PCR (qPCR) to further validate several copy number variable genes, such as prolactin receptor, endothelin 3 (EDN3), suppressor of cytokine signaling 2, CD8a molecule, with important functions, and the results suggested that EDN3 might be a molecular marker for the selection of dark skin color in poultry production. Moreover, we also identified a new CNVR (chr24: 3484617–3512275), encoding the sortilin-related receptor gene, with copy number changes in only black-bone chicken.

Conclusions

Here, we report a genome-wide analysis of the CNVs in five chicken breeds using aCGH. The association between EDN3 and melanoblast proliferation was further confirmed using qPCR. These results provide additional information for understanding genomic variation and related phenotypic characteristics.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-934) contains supplementary material, which is available to authorized users.

DNA methylation modifies urine biomarker levels in 1,6-hexamethylene diisocyanate exposed workers: a pilot study

DNA methylation may mediate inter-individual responses to chemical exposure and, thus, modify biomarker levels of exposure and effects. We analyzed inter-individual differences in inhalation and skin exposure to 1,6-hexamethylene diisocyanate (HDI) and urine biomarker 1,6-hexamethylene diamine (HDA) levels in 20 automotive spray-painters. Genome-wide 5-methyl cytosine (CpG) DNA methylation was assessed in each individual's peripheral blood mononuclear cells (PBMC) DNA using the Illumina 450K CpG array. Mediation analysis using linear regression models adjusted for age, ethnicity, and smoking was conducted to identify and assess the association between HDI exposure, CpG methylation, and urine HDA biomarker levels. We did not identify any CpGs common to HDI exposure and biomarker level suggesting that CpG methylation is a mediator that only partially explains the phenotype. Functional significance of genic- and intergenic-CpG methylation status was tested using protein-protein or protein-DNA interactions and gene-ontology enrichment to infer networks. Combined, the results suggest that methylation has the potential to affect HDI mass transport, permeation, and HDI metabolism. We demonstrate the potential use of PBMC methylation along with quantitative exposure and biomarker data to guide further investigation into the mediators of occupational exposure and biomarkers and its role in risk assessment.

Novel hypoxanthine guanine phosphoribosyltransferase gene mutations in Saudi Arabian hyperuricemia patients

Over the past decade, a steady increase in the incidence of HPRT-related hyperuricemia (HRH) has been observed in Saudi Arabia. We examined all the nine exons of HPRT gene for mutations in ten biochemically confirmed hyperuricemia patients, including one female and three normal controls. In all, we identified 13 novel mutations in Saudi Arabian HPRT-related hyperuricemia patients manifesting different levels of uric acid. The Lys103Met alteration was highly recurrent and was observed in 50% of the cases, while Ala160Thr and Lys158Asn substitutions were found in two patients. Moreover, in 70% of the patients ≥2 mutations were detected concurrently in the HPRT gene. Interestingly, one of the patients that harbored Lys103Met substitution along with two frameshift mutations at codons 85 and 160 resulting in shortened protein demonstrated unusually high serum uric acid level of 738 μmol/L. Two of the seven point mutations that resulted in amino acid change (Lys103Met and Val160Gly) were predicted to be damaging by SIFT and Polyphen and were further analyzed for their protein stability and function by molecular dynamics simulation. The identified novel mutations in the HPRT gene may prove useful in the prenatal diagnosis and genetic counseling.

Linkage disequilibrium and signatures of positive selection around LINE-1 retrotransposons in the human genome

Insertions of the human-specific subfamily of LINE-1 (L1) retrotransposon are highly polymorphic across individuals and can critically influence the human transcriptome. We hypothesized that L1 insertions could represent genetic variants determining important human phenotypic traits, and performed an integrated analysis of L1 elements and single nucleotide polymorphisms (SNPs) in several human populations. We found that a large fraction of L1s were in high linkage disequilibrium with their surrounding genomic regions and that they were well tagged by SNPs. However, L1 variants were only partially captured by SNPs on standard SNP arrays, so that their potential phenotypic impact would be frequently missed by SNP array-based genome-wide association studies. We next identified potential phenotypic effects of L1s by looking for signatures of natural selection linked to L1 insertions; significant extended haplotype homozygosity was detected around several L1 insertions. This finding suggests that some of these L1 insertions may have been the target of recent positive selection.

A genome-wide association study on copy-number variation identifies a 11q11 loss as a candidate susceptibility variant for colorectal cancer

Colorectal cancer (CRC) is a complex disease, and therefore its development is determined by the combination of both environmental factors and genetic variants. Although genome-wide association studies (GWAS) of SNP variation have conveniently identified 20 genetic variants so far, a significant proportion of the observed heritability is yet to be explained. Common copy-number variants (CNVs) are one of the most important genomic sources of variability, and hence a potential source to explain part of this missing genetic fraction. Therefore, we have performed a GWAS on CNVs to explore the relationship between common structural variation and CRC development. Phase 1 of the GWAS consisted of 881 cases and 667 controls from a Spanish cohort. Copy-number status was validated by quantitative PCR for each of those common CNVs potentially associated with CRC in phase I. Subsequently, SNPs were chosen as proxies for the validated CNVs for phase II replication (1,342 Spanish cases and 1,874 Spanish controls). Four common CNVs were found to be associated with CRC and were further replicated in Phase II. Finally, we found that SNP rs1944682, tagging a 11q11 CNV, was nominally associated with CRC susceptibility (p value = 0.039; OR = 1.122). This locus has been previously related to extreme obesity phenotypes, which could suggest a relationship between body weight and CRC susceptibility.

Genome-wide copy number variations in Oryza sativa L

Background

Copy number variation (CNV) can lead to intra-specific genome variations. It is not only part of normal genetic variation, but also is the source of phenotypic differences. Rice (Oryza sativa L.) is a model organism with a well-annotated genome, but investigation of CNVs in rice lags behind its mammalian counterparts.

Results

We comprehensively assayed CNVs using high-density array comparative genomic hybridization in a panel of 20 Asian cultivated rice comprising six indica, three aus, two rayada, two aromatic, three tropical japonica, and four temperate japonica varieties. We used a stringent criterion to identify a total of 2886 high-confidence copy number variable regions (CNVRs), which span 10.28 Mb (or 2.69%) of the rice genome, overlapping 1321 genes. These genes were significantly enriched for specific biological functions involved in cell death, protein phosphorylation, and defense response. Transposable elements (TEs) and other repetitive sequences were identified in the majority of CNVRs. Chromosome 11 showed the greatest enrichment for CNVs. Of subspecies-specific CNVRs, 55.75% and 61.96% were observed in only one cultivar of ssp. indica and ssp. japonica, respectively. Some CNVs with high frequency differences among groups resided in genes underlying rice adaptation.

Conclusions

Higher recombination rates and the presence of homologous gene clusters are probably predispositions for generation of the higher number of CNVs on chromosome 11 by non-allelic homologous recombination events. The subspecies-specific variants are enriched for rare alleles, which suggests that CNVs are relatively recent events that have arisen within breeding populations. A number of the CNVs identified in this study are candidates for generation of group-specific phenotypes.