CNV Regions Research Articles

Integration of genetic, transcriptomic, and clinical data provides insight into 16p11.2 and 22q11.2 CNV genes

BackgroundDeletions and duplications of the multigenic 16p11.2 and 22q11.2 copy number variant (CNV) regions are associated with brain-related disorders including schizophrenia, intellectual disability, obesity, bipolar disorder, and autism spectrum disorder (ASD). The contribution of individual CNV genes to each of these identified phenotypes is unknown, as well as the contribution of these CNV genes to other potentially subtler health implications for carriers. Hypothesizing that DNA copy number exerts most effects via impacts on RNA expression, we attempted a novel in silico fine-mapping approach in non-CNV carriers using both GWAS and biobank data.MethodsWe first asked whether gene expression level in any individual gene in the CNV region alters risk for a known CNV-associated behavioral phenotype(s). Using transcriptomic imputation, we performed association testing for CNV genes within large genotyped cohorts for schizophrenia, IQ, BMI, bipolar disorder, and ASD. Second, we used a biobank containing electronic health data to compare the medical phenome of CNV carriers to controls within 700,000 individuals in order to investigate the full spectrum of health effects of the CNVs. Third, we used genotypes for over 48,000 individuals within the biobank to perform phenome-wide association studies between imputed expressions of individual 16p11.2 and 22q11.2 genes and over 1500 health traits.ResultsUsing large genotyped cohorts, we found individual genes within 16p11.2 associated with schizophrenia (TMEM219, INO80E, YPEL3), BMI (TMEM219, SPN, TAOK2, INO80E), and IQ (SPN), using conditional analysis to identify upregulation of INO80E as the driver of schizophrenia, and downregulation of SPN and INO80E as increasing BMI. We identified both novel and previously observed over-represented traits within the electronic health records of 16p11.2 and 22q11.2 CNV carriers. In the phenome-wide association study, we found seventeen significant gene-trait pairs, including psychosis (NPIPB11, SLX1B) and mood disorders (SCARF2), and overall enrichment of mental traits.ConclusionsOur results demonstrate how integration of genetic and clinical data aids in understanding CNV gene function and implicates pleiotropy and multigenicity in CNV biology.

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.

Genome-wide structural variations in Brazilian Senepol cattle, a tropically adapted taurine breed

This study aimed to identify structural variations in the form of runs of homozygosity (ROH) and copy number variants (CNVs) in the genome of the Brazilian Senepol cattle and to better explore the potential biological functions of the genes located within such regions. A total of 140 animals were genotyped with the GeneSeek® Genomic Profiler™ Bovine 50 K. Autosomal ROH and CNVs were detected after appropriated quality control. A total of 5,531 ROH were identified, with an average number of 40.37 per animal and an average length of 5.09 Mb. BTA1 had the greatest number of ROH per chromosome (n = 458), while BTA20 displayed the greatest fraction of the chromosome covered with ROH (22.06%). A total of 181 CNVs were identified, with an average length size of 184.67 kb, with values ranging from 26.61 to 334.48 kb. A total of 16 CNV regions (CNVRs) were seen distributed among eleven autosomes, and the largest number of CNVRs (n = 4) was described on BTA12. Autozygosity islands were identified using an outlier approach, and none of them overlapped with CNVRs. Our study revealed that the limited genetic basis together with the narrow number of imported animals to disseminate the breed might have strongly contributed to the low effective population size and the high genomic autozygosity proportion described in this population. The functional enrichment analysis revealed several significant terms (p<0.05) within the autozygosity islands and CNVRs closely linked to molecular and immune response mechanisms. The average FROH of different lengths were low to in the studied population, however, the autozygotic proportion in the genome indicates moderate to high inbreeding levels. The results exposed the need of implementing mating programs to control the increase of inbreeding and coancestry in Brazilian Senepol cattle.In these sense, Senepol breeders should apply selection and mating strategies to minimize the occurrence of long ROH in the offspring, as well as import of new genetic material to avoid the loss of genetic diversity. This study revealed the existence of overlapped regions between CNVRs and ROH throughout the genome of the Senepol cattle, that contributes to a better understanding of the functional role of genomic structural variations in taurine cattle adapted to tropical regions.

HandyCNV: Standardized Summary, Annotation, Comparison, and Visualization of Copy Number Variant, Copy Number Variation Region, and Runs of Homozygosity.

Detection of CNVs (copy number variants) and ROH (runs of homozygosity) from SNP (single nucleotide polymorphism) genotyping data is often required in genomic studies. The post-analysis of CNV and ROH generally involves many steps, potentially across multiple computing platforms, which requires the researchers to be familiar with many different tools. In order to get around this problem and improve research efficiency, we present an R package that integrates the summarization, annotation, map conversion, comparison and visualization functions involved in studies of CNV and ROH. This one-stop post-analysis system is standardized, comprehensive, reproducible, timesaving, and user-friendly for researchers in humans and most diploid livestock species.

Comparative analysis reveals within-population genome size variation in a rotifer is driven by large genomic elements with highly abundant satellite DNA repeat elements

BackgroundEukaryotic genomes are known to display an enormous variation in size, but the evolutionary causes of this phenomenon are still poorly understood. To obtain mechanistic insights into such variation, previous studies have often employed comparative genomics approaches involving closely related species or geographically isolated populations within a species. Genome comparisons among individuals of the same population remained so far understudied—despite their great potential in providing a microevolutionary perspective to genome size evolution. The rotifer Brachionus asplanchnoidis represents one of the most extreme cases of within-population genome size variation among eukaryotes, displaying almost twofold variation within a geographic population.ResultsHere, we used a whole-genome sequencing approach to identify the underlying DNA sequence differences by assembling a high-quality reference genome draft for one individual of the population and aligning short reads of 15 individuals from the same geographic population including the reference individual. We identified several large, contiguous copy number variable regions (CNVs), up to megabases in size, which exhibited striking coverage differences among individuals, and whose coverage overall scaled with genome size. CNVs were of remarkably low complexity, being mainly composed of tandemly repeated satellite DNA with only a few interspersed genes or other sequences, and were characterized by a significantly elevated GC-content. CNV patterns in offspring of two parents with divergent genome size and CNV patterns in several individuals from an inbred line differing in genome size demonstrated inheritance and accumulation of CNVs across generations.ConclusionsBy identifying the exact genomic elements that cause within-population genome size variation, our study paves the way for studying genome size evolution in contemporary populations rather than inferring patterns and processes a posteriori from species comparisons.

Genome-wide CNV investigation suggests a role for cadherin, Wnt, and p53 pathways in primary open-angle glaucoma

BackgroundTo investigate whether copy number variations (CNVs) are implicated in molecular mechanisms underlying primary open-angle glaucoma (POAG), we used genotype data of POAG individuals and healthy controls from two case-control studies, AGS (n = 278) and GLGS-UGLI (n = 1292). PennCNV, QuantiSNP, and cnvPartition programs were used to detect CNV. Stringent quality controls at both sample and marker levels were applied. The identified CNVs were intersected in CNV region (CNVR). After, we performed burden analysis, CNV-genome-wide association analysis, gene set overrepresentation and pathway analysis. In addition, in human eye tissues we assessed the expression of the genes lying within significant CNVRs.ResultsWe reported a statistically significant greater burden of CNVs in POAG cases compared to controls (p-value = 0,007). In common between the two cohorts, CNV-association analysis identified statistically significant CNVRs associated with POAG that span 11 genes (APC, BRCA2, COL3A1, HLA-DRB1, HLA-DRB5, HLA-DRB6, MFSD8, NIPBL, SCN1A, SDHB, and ZDHHC11). Functional annotation and pathway analysis suggested the involvement of cadherin, Wnt signalling, and p53 pathways.ConclusionsOur data suggest that CNVs may have a role in the susceptibility of POAG and they can reveal more information on the mechanism behind this disease. Additional genetic and functional studies are warranted to ascertain the contribution of CNVs in POAG.

Increased copy number of gibberellin 2-oxidase 8 genes reduced trailing growth and shoot length during soybean domestication.

Copy number variations (CNVs) play important roles in crop domestication. However, there is only very limited information on the involvement of CNVs in soybean domestication. Trailing growth and long shoots are soybean adaptations for natural habitats but cause lodging that hampers yield in cultivation. Previous studies have focused on Dt1/2 affecting the indeterminate/determinate growth habit, whereas the possible role of the gibberellin pathway remained unclear. In the present study, quantitative trait locus (QTL) mapping of a recombinant inbred population of 460 lines revealed a trailing-growth-and-shoot-length QTL. A CNV region within this QTL was identified, featuring the apical bud-expressed gibberellin 2-oxidase 8A/B, the copy numbers of which were positively correlated with expression levels and negatively with trailing growth and shoot length, and their effects were demonstrated by transgenic soybean and Arabidopsis thaliana. Based on the fixation index, this CNV region underwent intense selection during the initial domestication process.

Population differentiated copy number variation of Bos taurus, Bos indicus and their African hybrids

BackgroundCNV comprises a large proportion in cattle genome and is associated with various traits. However, there were few population-scale comparison studies on cattle CNV.ResultsHere, autosome-wide CNVs were called by read depth of NGS alignment result and copy number variation regions (CNVRs) defined from 102 Eurasian taurine (EAT) of 14 breeds, 28 Asian indicine (ASI) of 6 breeds, 22 African taurine (AFT) of 2 breeds, and 184 African humped cattle (AFH) of 17 breeds. The copy number of every CNVRs were compared between populations and CNVRs with population differentiated copy numbers were sorted out using the pairwise statistics VST and Kruskal-Wallis test. Three hundred sixty-two of CNVRs were significantly differentiated in both statistics and 313 genes were located on the population differentiated CNVRs.ConclusionFor some of these genes, the averages of copy numbers were also different between populations and these may be candidate genes under selection. These include olfactory receptors, pathogen-resistance, parasite-resistance, heat tolerance and productivity related genes. Furthermore, breed- and individual-level comparison was performed using the presence or copy number of the autosomal CNVRs. Our findings were based on identification of CNVs from short Illumina reads of 336 individuals and 39 breeds, which to our knowledge is the largest dataset for this type of analysis and revealed important CNVs that may play a role in cattle adaption to various environments.

Deep learning prediction of attention-deficit hyperactivity disorder in African Americans by copy number variation.

Current understanding of the underlying molecular network and mechanism for attention-deficit hyperactivity disorder (ADHD) is lacking and incomplete. Previous studies suggest that genomic structural variations play an important role in the pathogenesis of ADHD. For effective modeling, deep learning approaches have become a method of choice, with ability to predict the impact of genetic variations involving complicated mechanisms. In this study, we examined copy number variation in whole genome sequencing from 116 African Americans ADHD children and 408 African American controls. We divided the human genome into 150 regions, and the variation intensity in each region was applied as feature vectors for deep learning modeling to classify ADHD patients. The accuracy of deep learning for predicting ADHD diagnosis is consistently around 78% in a two-fold shuffle test, compared with ∼50% by traditional k-mean clustering methods. Additional whole genome sequencing data from 351 European Americans children, including 89 ADHD cases and 262 controls, were applied as independent validation using feature vectors obtained from the African American ethnicity analysis. The accuracy of ADHD labeling was lower in this setting (∼70-75%) but still above the results from traditional methods. The regions with highest weight overlapped with the previously reported ADHD-associated copy number variation regions, including genes such as GRM1 and GRM8, key drivers of metabotropic glutamate receptor signaling. A notable discovery is that structural variations in non-coding genomic (intronic/intergenic) regions show prediction weights that can be as high as prediction weight from variations in coding regions, results that were unexpected.

Copy number variation in triple negative breast cancer samples associated with lymph node metastasis

Triple negative breast cancer (TNBC) is a highly metastatic and aggressive subtype of breast cancer and cases presenting with lymph node involvement have worse outcomes. This study aimed to determine the regions of copy number variation (CNV) associated with lymph node metastasis in TNBC patients. CNV analyses were performed in a study cohort of 23 invasive ductal carcinomas (IDCs), 12 lymph node metastases (LNmets), and 7 normal adjacent tissues (NATs); as well as in an independent cohort containing 70 TNBC IDCs and the same 7 NATs. CNV-associated genes were analyzed using GO-enrichment and Pathway analysis. The prognostic role for genes showing CNV-based changes in messenger RNA expression was determined using the Kaplan-Meier plotter database. For the IDCs, there were a number of variations that were common in both the study and independent cohorts in the amplified regions of 1q, 8q, 19 (p and q), 2p, 5p and the deleted regions in 8p followed by 5q, and 19p. The most frequently amplified regions in the LNmets of the study cohort were 4q28.3, 2p, 3q24, 1q21.2, 10p, 12p11.1, 8q, 20p11.22-20p11.21, 21q22.13, 6p22.1 and the most frequently deleted regions were in 1p36.23, 4q21.1 and 5q. A total of 686 (441 amplified and 245 deleted) genes were associated with LNmets. The LNmet-associated genes were highly enriched for “regulation of complement activation,” “regulation of protein activation cascade,” “regulation of humoral immune response,” “oxytocin signalling pathway,” and “TRAIL binding” pathways. Moreover, 6/686 LNmet-associated genes showed CNV-based changes in their mRNA expression of which, high expression of ASPM and KIF14 was significantly associated with worse relapse-free survival. This study has identified several CNV regions in TNBC that could play a major role in metastasis to the lymph node.

Association of Copy Number Variation Signature and Survival in Patients With Serous Ovarian Cancer

Tailoring therapeutic regimens to individual patients with ovarian cancer is informed by severity of disease using a variety of clinicopathologic indicators. Although DNA repair variations are increasingly used for therapy selection in ovarian cancer, molecular features are not widely used for general assessment of patient prognosis and disease severity. To distill a highly dynamic characteristic, signature of copy number variations (CNV), into a risk score that could be easily validated analytically or repurposed for use given existing US Food and Drug Administration (FDA)-approved multigene assays. This genetic association study used the Cancer Genome Atlas Ovarian Cancer database to assess for genome-wide survival associations agnostic to gene function. Regions enriched for significant associations were compared to associations from scrambled data. CNV associations were condensed into a risk score, which was internally validated using bootstrapping. The participants were patients with serous ovarian cancer (stages I-IV) diagnosed from 1992 to 2013. Statistical analysis was performed from April to July 2020. Overall survival (OS). Among 564 patients with serous ovarian cancer, the mean (SD) age was 59.7 (11.5) years; 34 (6%) identified as Black or African American. A total of 13 genome regions, comprising 14 alterations, were identified as significantly risk associated. Composite risk score was independent of total CNV burden, total mutational burden, BRCA status, and open-source genome-wide DNA repair deficiency signatures. Binned terciles yielded high-, standard-, and low-risk groups with respective median OS estimates of 2.9 (95% CI, 2.3-3.2) years, 4.1 (95% CI, 3.7-4.8) years, and 5.7 (95% CI, 4.7-7.4) years, respectively (P < .001). Associated 5-year survival estimates in each tercile were 15% (95% CI, 10%-22%), 36% (95% CI, 29%-46%), and 53% (95% CI, 45%-62%). The risk score had more discriminatory ability to prognosticate OS than age, clinical stage, grade, and race combined, and was strongly additive to significant clinical features (P < .001). Simulated adaptation of FDA-approved assays showed similar performance. Gene ontology analyses of identified regions showed an enrichment for regulatory miRNAs and protein kinase regulators. This study found that a CNV-based risk score is independent to and stronger than current or near-future ovarian cancer genomic biomarkers to prognosticate OS. CNV regions identified were not strongly associated with canonical ovarian cancer biological pathways, identifying candidates for future mechanistic investigations. External validation of the CNV risk score, especially in concert with more extensive clinical features, could be pursued via existing FDA-approved assays.

Copy Number Variants Captured by the Array Comparative Genomic Hybridization in a Cohort of Patients Affected with Hereditary Colorectal Cancer in Sri Lanka: The First CNV Analysis Study of the Hereditary Colorectal Cancer in the Sri Lankan Population

Introduction:Hereditary non-polyposis colorectal cancer (HNPCC), is an autosomal dominant disorder characterized by the development of multiple cancer types. Molecular diagnosis of HNPCC requires the precise identification of pathogenic germline variants in DNA mismatch repair (MMR) genes. Next Generation Sequencing (NGS) is now the gold standard test in practice, to identify these variants. However, large genomic rearrangements (LGR) in cancer predisposing genes (CPGs) are missed by NGS. This may lead to underestimation of the frequency of the variants, misleading the genetic diagnosis and delaying intervention in high risk individuals. Hence this study was aimed at identifying the presence of large genomic alterations that could explain the missing heritable risk of colon cancer in affected patients with family history strongly suggestive of hereditary colorectal cancer in Sri Lanka. Methods:A cohort of six patients affected with hereditary colorectal cancer who tested negative for pathogenic variants in next generation sequencing studies was investigated using Sure Print G3 Human CGH 4x180K microarray platform. Agilent Genomic-Workbench-v7.0.4.0 software was used to identify the Copy Number Variants (CNV). Four healthy individuals (>55years) were used as controls. Annotations of the CNV regions which were observed were done using the database of Genomic Variants. Results:We identified 150 CNVs including regions of both genomic gains and losses in the patient cohort. There was no difference in the average number or the average genomic burden of CNVs identified in the patients versus the controls. CNVs were residing on the positions of 1q21.2, 2q37.3, 2p11.2-p11.1, 5q13.2, 6p12.3, 7q31.33, 7p14.1, 14q32.33, 15q11.1-11.2, 16p11.2, 22q11.22, 22q13.1 that were assessed by the array platform used in the study. CNVs in any of the well-known common CPG s or CNVs that reside on or in close proximity to genes corresponding to MMR pathway were not identified. We found several distinct pathways that have previously been identified as having a direct association with the progression of HNPCC. Conclusion:This study shows that CNVs are likely contributors to the colorectal cancer predisposition in a small but significant proportion of patients affected with hereditary colorectal cancer in this cohort. Further studies have to perform to get a better understanding on the contribution of CNVs to the cancer predisposition in this cohort of patients in the Sri Lankan population.

Comparative analysis of de novo genomes reveals dynamic intra-species divergence of NLRs in pepper

BackgroundPeppers (Capsicum annuum L.) containing distinct capsaicinoids are the most widely cultivated spices in the world. However, extreme genomic diversity among species represents an obstacle to breeding pepper.ResultsHere, we report de novo genome assemblies of Capsicum annuum ‘Early Calwonder (non-pungent, ECW)’ and ‘Small Fruit (pungent, SF)’ along with their annotations. In total, we assembled 2.9 Gb of ECW and SF genome sequences, representing over 91% of the estimated genome sizes. Structural and functional annotation of the two pepper genomes generated about 35,000 protein-coding genes each, of which 93% were assigned putative functions. Comparison between newly and publicly available pepper gene annotations revealed both shared and specific gene content. In addition, a comprehensive analysis of nucleotide-binding and leucine-rich repeat (NLR) genes through whole-genome alignment identified five significant regions of NLR copy number variation (CNV). Detailed comparisons of those regions revealed that these CNVs were generated by intra-specific genomic variations that accelerated diversification of NLRs among peppers.ConclusionsOur analyses unveil an evolutionary mechanism responsible for generating CNVs of NLRs among pepper accessions, and provide novel genomic resources for functional genomics and molecular breeding of disease resistance in Capsicum species.

Detection of copy number variants in African goats using whole genome sequence data

BackgroundCopy number variations (CNV) are a significant source of variation in the genome and are therefore essential to the understanding of genetic characterization. The aim of this study was to develop a fine-scaled copy number variation map for African goats. We used sequence data from multiple breeds and from multiple African countries.ResultsA total of 253,553 CNV (244,876 deletions and 8677 duplications) were identified, corresponding to an overall average of 1393 CNV per animal. The mean CNV length was 3.3 kb, with a median of 1.3 kb. There was substantial differentiation between the populations for some CNV, suggestive of the effect of population-specific selective pressures. A total of 6231 global CNV regions (CNVR) were found across all animals, representing 59.2 Mb (2.4%) of the goat genome. About 1.6% of the CNVR were present in all 34 breeds and 28.7% were present in all 5 geographical areas across Africa, where animals had been sampled. The CNVR had genes that were highly enriched in important biological functions, molecular functions, and cellular components including retrograde endocannabinoid signaling, glutamatergic synapse and circadian entrainment.ConclusionsThis study presents the first fine CNV map of African goat based on WGS data and adds to the growing body of knowledge on the genetic characterization of goats.

Genome-Wide Detection of Copy Number Variations and Their Association With Distinct Phenotypes in the World's Sheep.

Copy number variations (CNVs) are a major source of structural variation in mammalian genomes. Here, we characterized the genome-wide CNV in 2059 sheep from 67 populations all over the world using the Ovine Infinium HD (600K) SNP BeadChip. We tested their associations with distinct phenotypic traits by conducting multiple independent genome-wide tests. In total, we detected 7547 unique CNVs and 18,152 CNV events in 1217 non-redundant CNV regions (CNVRs), covering 245 Mb (∼10%) of the whole sheep genome. We identified seven CNVRs with frequencies correlating to geographical origins and 107 CNVRs overlapping 53 known quantitative trait loci (QTLs). Gene ontology and pathway enrichment analyses of CNV-overlapping genes revealed their common involvement in energy metabolism, endocrine regulation, nervous system development, cell proliferation, immune, and reproduction. For the phenotypic traits, we detected significantly associated (adjusted P < 0.05) CNVRs harboring functional candidate genes, such as SBNO2 for polycerate; PPP1R11 and GABBR1 for tail weight; AKT1 for supernumerary nipple; CSRP1, WNT7B, HMX1, and FGFR3 for ear size; and NOS3 and FILIP1 in Wadi sheep; SNRPD3, KHDRBS2, and SDCCAG3 in Hu sheep; NOS3, BMP1, and SLC19A1 in Icelandic; CDK2 in Finnsheep; MICA in Romanov; and REEP4 in Texel sheep for litter size. These CNVs and associated genes are important markers for molecular breeding of sheep and other livestock species.

Genome-wide detection of CNVs and their association with performance traits in broilers

BackgroundCopy number variations (CNVs) are a major type of structural genomic variants that underlie genetic architecture and phenotypic variation of complex traits, not only in humans, but also in livestock animals. We identified CNVs along the chicken genome and analyzed their association with performance traits. Genome-wide CNVs were inferred from Affymetrix® high density SNP-chip data for a broiler population. CNVs were concatenated into segments and association analyses were performed with linear mixed models considering a genomic relationship matrix, for birth weight, body weight at 21, 35, 41 and 42 days, feed intake from 35 to 41 days, feed conversion ratio from 35 to 41 days and, body weight gain from 35 to 41 days of age.ResultsWe identified 23,214 autosomal CNVs, merged into 5042 distinct CNV regions (CNVRs), covering 12.84% of the chicken autosomal genome. One significant CNV segment was associated with BWG on GGA3 (q-value = 0.00443); one significant CNV segment was associated with BW35 (q-value = 0.00571), BW41 (q-value = 0.00180) and BW42 (q-value = 0.00130) on GGA3, and one significant CNV segment was associated with BW on GGA5 (q-value = 0.00432). All significant CNV segments were verified by qPCR, and a validation rate of 92.59% was observed. These CNV segments are located nearby genes, such as KCNJ11, MyoD1 and SOX6, known to underlie growth and development. Moreover, gene-set analyses revealed terms linked with muscle physiology, cellular processes regulation and potassium channels.ConclusionsOverall, this CNV-based GWAS study unravels potential candidate genes that may regulate performance traits in chickens. Our findings provide a foundation for future functional studies on the role of specific genes in regulating performance in chickens.

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

BackgroundIn 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.ResultsOur 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.ConclusionsThe 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.

Concurrent mutations associated with trastuzumab-resistance revealed by single cell sequencing.

HER2-positive breast cancer patients benefit from HER2-targeted therapies, among which the most commonly used is trastuzumab. However, acquired resistance typically happens within one year. The cellular heterogeneity of it is less clear. Here we generated trastuzumab-resistant cells in two HER2-positive breast cancer cell lines, SK-BR-3 and BT-474. Cells at different time points during the resistance induction were examined by exome sequencing to study changes of genomic alterations over time. Single cell-targeted sequencing was also used to identify resistance-associated concurrent mutations. We found a rapid increase of copy number variation (CNV) regions and gradual accumulation of single nucleotide variations (SNVs). On the pathway level, non-synonymous SNVs for SK-BR-3 cells were enriched in the MAPK signaling pathway, while for BT-474 cells they were enriched in mTOR and PI3K-Akt signaling pathways. However, all of the three signaling pathways were in the downstream of the HER2 kinase. Putative trastuzumab-resistance-associated SNVs included AIFM1 P548L and ERBB2 M833R in SK-BR-3 cells, and ADAMTS19 V451L,OR5M9 D230N, COL9A1 R627T, andITGA7 H911Q in BT-474 cells. Single-cell-targeted sequencing identified several concurrent mutations. By validation, we found that concurrent mutations (AIFM1 P548L and IL1RAPL2 S546C in SK-BR-3 cells, MFSD11 L242I and ANAPC4 E16K in BT-474 cells) led to a decrease of trastuzumab sensitivity. Taken together, our study revealed a common pathway level trastuzumab-resistance mechanism for HER2-positive breast cancer cells. In addition, our identification of concurrent SNVs associated with trastuzumab-resistance may be indicative of potential targets for the treatment of trastuzumab-resistant breast cancer patients.

Construction of a chromosome-level genome and variation map for the Pacific oyster Crassostrea gigas.

The Pacific oyster (Crassostrea gigas) is a widely distributed marine bivalve of great ecological and economic importance. In this study, we provide a high-quality chromosome-level genome assembled using Pacific Bioscience long reads and Hi-C-based and linkage-map-based scaffolding technologies and a high-resolution variation map constructed using large-scale resequencing analysis. The 586.8Mb genome consists of 10 pseudochromosome sequences ranging from 38.6 to 78.9Mb, containing 301 contigs with an N50 size of 3.1Mb. A total of 30,078 protein-coding genes were predicted, of which 22,757 (75.7%) were high-reliability annotations supported by a homologous match to a curated protein in the SWISS-PROT database or transcript expression. Although a medium level of repeat components (57.2%) was detected, the genomic content of the segmental duplications reached 26.2%, which is the highest among the reported genomes. By whole genome resequencing analysis of 495 Pacific oysters, a comprehensive variation map was built, comprised of 4.78 million single nucleotide polymorphisms, 0.60million short insertions and deletions, and 49,333 copy number variation regions. The structural variations can lead to an average interindividual genomic divergence of 0.21, indicating their crucial role in shaping the Pacific oyster genome diversity. The large amount of mosaic distributed repeat elements, small variations, and copy number variations indicate that the Pacific oyster is a diploid organism with an extremely high genomic complexity at the intra- and interindividual level. The genome and variation maps can improve our understanding of oyster genome diversity and enrich the resources for oyster molecular evolution, comparative genomics, and genetic research.

Identifying potential biomarkers\xa0of\xa0nonalcoholic\xa0fatty\xa0liver\xa0disease via genome-wide analysis of copy number variation

BackgroundThe prevalence of Non-alcoholic fatty liver disease (NAFLD) is increasing and emerging as a global health burden. In addition to environmental factors, numerous studies have shown that genetic factors play an important role in the development of NAFLD. Copy number variation (CNV) as a genetic variation plays an important role in the evaluation of disease susceptibility and genetic differences. The aim of the present study was to assess the contribution of CNV to the evaluation of NAFLD in a Chinese population.MethodsGenome-wide analysis of CNV was performed using high-density comparative genomic hybridisation microarrays (ACGH). To validate the CNV regions, TaqMan real-time quantitative PCR (qPCR) was utilized.ResultsA total of 441 CNVs were identified, including 381 autosomal CNVs and 60 sex chromosome CNVs. By merging overlapping CNVs, a genomic CNV map of NAFLD patients was constructed. A total of 338 autosomal CNVRs were identified, including 275 CNVRs with consistent trends (197 losses and 78 gains) and 63 CNVRs with inconsistent trends. The length of the 338 CNVRs ranged from 5.7 kb to 2.23 Mb, with an average size of 117.44 kb. These CNVRs spanned 39.70 Mb of the genome and accounted for ~ 1.32% of the genome sequence. Through Gene Ontology and genetic pathway analysis, we found evidence that CNVs involving nine genes may be associated with the pathogenesis of NAFLD progression. One of the genes (NLRP4 gene) was selected and verified by quantitative PCR (qPCR) method with large sample size. We found the copy number deletion of NLRP4 was related to the risk of NAFLD.ConclusionsThis study indicate the copy number variation is associated with NAFLD. The copy number deletion of NLRP4 was related to the risk of NAFLD. These results could prove valuable for predicting patients at risk of developing NAFLD.